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A multi-criteria spatial approach for mapping urban ecosystem services demand
Ecological Indicators 112 (2020) 106119
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Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind
A multi-criteria spatial approach for mapping urban ecosystem services demand
T
Fangzheng Lia,1, Shiyi Guoa,b,1, Di Lic, Xiong Lia, , Jing Lid, Shuang Xiea ⁎
a
School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China Graduate School of Frontier Science, The University of Tokyo, Kashiwa 277-8563, Japan c School of Architecture SouthEast University Nanjing 210000 d Beijing Tsinghua Tongheng Urban Planning & Design Institute, Beijing 100085, China b
ARTICLE INFO
ABSTRACT
Keywords: Demand for ecosystem services Landscape ecological security pattern Demand for cultural services Demand for ecological services Urban green space
A growing number of studies have mapped the demand for ecosystem services (ES). Recently, demand for ES has been broadened to include cultural services in addition to ecological services, especially for urbanized areas. In this study, a multi-criteria approach is proposed that synthesizes the available ecological and cultural services to map the demand for ES: including 1) soil erosion sensitivity, 2) geological hazard sensitivity, 3) water management, 4) vegetation coverage, 5) permanent farmland, 6) accessibility, 7) population density, 8) direct use of green spaces, and 9) cultural heritage. The cultural services demand describes the desire or preference, and consumption or direct use of cultural services, e.g. recreation and cultural heritage. Most studies discussed only the desire or preference for cultural services because of the difficulty quantifying the actual consumption of these cultural services. This research gap was filled using the check-in data collected from WeChat (a major social network in China). Each criterion was assigned a weight so that the ecological services demand, the cultural services demand, and the overall ES demand could be quantified. The results suggest that in general, the mountainous areas, farmlands, and suburban areas have high demand for ecological services while public parks in urban areas show high demand for cultural services. However, the ES demand in the availability of some small green spaces in highly urbanized areas may be higher than that for large green spaces in suburban areas. This multi-criteria analysis is necessary to obtain a comprehensive assessment of ES demand, which will contribute to improving the applicability of ES in real-world decision making, e.g. green space planning and conservation.
1. Introduction Ecosystem services (ES) refers to the goods and services of ecosystem structures and functions for human well-being (Costanza et al., 1997; de Groot et al., 2002; Chee, 2004; Burkhard et al., 2012; Crossman et al., 2013; Zulian et al., 2018). Urbanization has placed increasing pressures on ES, especially in highly constructed areas (Forman, 2014). Megacities tend to have various ecological problems because of their large populations and dense development (Peng et al., 2015), such as haze, (Sun et al., 2006; Wang et al., 2016) and heat island effects (Miao et al., 2009; Guo et al., 2015). The growing demand for increasingly degraded ecosystems has seriously threatened the sustainable development (MEA, 2005). Therefore, it is necessary to map the demand for ES, which shows where different kinds of ES are needed, which leads to more efficient land-use plans and policies (Daily and
Matson, 2008; Orenstein and Groner, 2014). While ES are complex and interconnected (Adger, 2000; Bennett et al., 2010). According to Millennium Ecosystem Assessment (2005), ES can be classified into provisioning services, regulating services, supporting services, and cultural services. Provisioning services refer to the products obtained from ecosystems (e.g. food, freshwater); regulating services describe the benefits obtained from regulation of ES (e.g. climate regulation, water regulation); supporting services are services necessary for the production of all other ES (e.g. soil formation, nutrient cycling); cultural services refer to nonmaterial benefits obtained from ES (e.g. recreation, cultural heritage) (Schirpke et al., 2014; Villamagna et al., 2014). Here we sorted provisioning, regulating, and supporting services as ecological services, in comparison with cultural services. In existing research, the assessment of ES from an ecological perspective is relatively well-established (Daily et al., 2000; Fisher
Corresponding author. E-mail addresses: [email protected] (F. Li), [email protected] (S. Guo), [email protected] (D. Li), [email protected] (X. Li), [email protected] (S. Xie). 1 Means the co-first authors. ⁎
https://doi.org/10.1016/j.ecolind.2020.106119 Received 12 November 2018; Received in revised form 22 November 2019; Accepted 17 January 2020 1470-160X/ © 2020 Elsevier Ltd. All rights reserved.
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et al., 2009; Syrbe and Walz, 2012); in contrast, literature on ES indicates that the assessment of cultural services lags behind other service categories. Recently, cultural services have been widely recognized as a critical part in human welfare (Howarth and Farber, 2002; HernándezMorcillo et al., 2013; Ala-Hulkko et al., 2016; Baró et al., 2016; Zhang et al., 2017). A comprehensive mapping of ES demand should include both ecological and cultural services. With regard to the demand of ES, according to the literature review by Wolff et al. (2015), there are three main definitions of demand for ES (Burkhard et al., 2012; Villamagna et al., 2013; Schröter et al., 2014). Burkhard et al. (2012) regard demand for ES as the sum of all actual use or consumption of ES, while the demand is often constrained by the current supply of ES. Because of the influence of preferences or desire on the consumer’s willingness to use a service, Schröter et al. (2014) prefer to use preferences or desire for ES to define the demand for ES. Villamagna et al. (2013) defined demand for ES as the amount of a service required or desired by society, which should be further distinguished according to time and space. All these definitions have been adopted, but each definition has its own emphasis. Wolff et al. (2015) synthesized the existing definitions and elaborated the demand for ES from two aspects: 1) Consumption/direct use, i.e. demand for ES is the sum of all services actually consumed within a certain area over a certain period without regard for where ES originated. Empirical data on the actual consumption, which can be obtained from statistics, interviews, or monitoring, is necessary to assess the demand for ES. 2) Desires and preferences, i.e. the demand for ES is the amount of regulation required for the natural environment or desired by society, including the demand for risk reduction (e.g. flood regulation, erosion control). The former emphasizes actual consumption, while the latter tends to identify the needed services based on given indicators. Most studies have assessed the cultural services demand from the aspect of desires and preferences instead of consumption or direct use, which may be because of the difficulty of measurement. From the aspect of desires and preferences, the demand for cultural services can be quantified by indicators such as accessibility (Paracchini et al., 2014; Meerow and Newell, 2016), population (Zhang et al., 2017), and cultural value, i.e. places with cultural heritage (Plieninger et al., 2013; Casado-Arzuaga et al., 2013). However, from the other aspect, the consumption or direct use of cultural services is usually measured based on empirical data obtained by surveys and questionnaires, which is time and energy consuming (Li et al., 2017). Although public participation GIS (PPGIS) was proposed as an alternative method of collecting the opinion of the public, the sampling and data collection method are mainly surveys, workshop and interviews (Brown, 2013; Brown and Kyttä, 2014; Brown and Fagerholm, 2015), which is limited to the number of samples. Therefore, the consumption or direct use of cultural services is often ignored even though it provides important evidence for ES benefits (Hernández-Morcillo et al., 2013). To address this research gap, we used a multi-criteria approach integrating ecological and cultural services. In particular, we proposed an operational method of measuring the consumption or direct use of cultural services: i.e. we used the check-in data collected from WeChat (one of the major social networks in China). This study aimed to propose an operational and location-based framework for mapping ES demand. First, we evaluated the ecosystem service demand based on multi-criteria: i.e. soil erosion sensitivity, geological hazard sensitivity, water management, vegetation coverage, and permanent farmland for ecological services; and accessibility, population density, direct use of green spaces, and cultural heritage for cultural services. Second, expertdriven weighting of each criterion was conducted to achieve synthesized result of ES demand. Finally, we applied the ES demand to identify the ecological security pattern in landscapes. The research framework is shown in Fig. 1. The results for mapping the demand for ES can provide operational suggestions for policy decision-making, especially in green space planning and management.
Fig. 1. Research framework.
2. Materials and methodology 2.1. Study areas and data Beijing (39°38′–41°05′N), a typical mega-city in Asia, is located in the north of China. Beijing’s administration region occupies an area of 16,410 km2 (Fig. 2). The master plan for Beijing (2016–2035) classified Beijing into central urban, suburban, and outer suburban areas. This study focused on the central urban area (1386 km2), which consists of six districts (Dongcheng, Xicheng, Haidian, Chaoyang, Fengtai, and Shijingshan). Beijing is surrounded by mountains on three sides and there are mountains in the western central urban area. In addition to these mountains, there are some public parks, green belts, long rivers, roads, and waterbodies, which together form an ecosystem. A Landsat 8 OLI satellite remote sensing image (http://www. gscloud.cn) for October 11th, 2016 was fused using the GramSchmidt spectral sharpening method to obtain a higher accuracy of 15 m × 15 m. Land cover information (i.e. farmland, woodland, grassland, wetland, water area, built-up area, unused land) were identified using the support vector machine (SVM) supervised classification. The data was corrected by ERDAS Imagine software, and processed, calculated, tested by ArcGIS platform. The accuracy of the test results reached 84.91%, meeting the accuracy requirements. 2.2. Nine ES demand criteria We selected the following nine criteria for mapping the demand for ES according to a commonly cited reference: MEA (2005), and two reviews (Hernández-Morcillo et al., 2013; Wolff et al., 2015). The selection rationale, data source, and data processing are as following: (Table 1) 2.2.1. Soil erosion sensitivity In sloping fields, debris flow and landslides resulting from soil erosion may occur in rainy seasons. Soil erosion regulation is one of the regulating services. From the perspective of risk reduction (Wolff et al., 2015), the higher the soil erosion sensitivity, the higher the demand for ES. Slope is the critical variable for measuring soil erosion sensitivity. We divided slope into four categories and assigned a value to each category (Table 2). 2
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Fig. 2. The land use map of central Beijing.
2.2.2. Geological hazard sensitivity Various geological hazards, such as collapse, debris flow, ground fissures, and landslides, threaten urban ecological security. Geologically sensitive areas are also ecologically fragile areas with high demand for ES. The seismic information includes the unexpected, chronic, and dangerous geological hazard areas.
effect and poor drainage can lead to waterlogging. We conducted a buffer analysis on water areas within the study area and obtained buffer zones of 50 m, 100 m, and 150 m. The weight of each category decreased from each waterbody to the 150-m buffer zone. 2.2.4. Vegetation coverage Vegetation is the main component of green spaces. On the one side, especially in urban areas, places with high vegetation coverage usually provide more ES, for example, urban microclimates regulation, erosion regulation, and biodiversity conservation (Burkhard et al., 2012). On the other side, under the trend of urbanization, people in places with high vegetation coverage have a stronger demand of ES and a higher willingness to pay, because demand is influenced by the awareness, desires, and the willingness to conserve services (Schröter et al., 2014). In this case, vegetation coverage was classified into four categories
2.2.3. Water systems Urban water systems are the foundation of ecosystems, playing an important role in flood regulation and climate regulation services. For example, demand for flood regulation can be regarded as a necessity for disaster prevention or safety assurance. Due to urbanization, water and surrounding areas are affected by human activities; therefore, these areas have a higher demand for ecological services. The large amounts of impervious surfaces in urban areas is responsible for the heat island Table 1 Experts for weighting ES demand. Name of organization
Major
Type
Beijing Forestry University Tsinghua University Beijing University of Civil Engineering and Architecture North China University of Technology Beijing Tsinghua Tongheng Urban Planning & Design Institute Beijing Beilin Landscape Planning and Design Institute Co., Ltd.
landscape planning, environmental science urban planning, landscape planning urban planning, landscape planning landscape planning urban planning, landscape planning urban planning, landscape planning, environmental science landscape planning urban planning, landscape planning, environmental science environmental science
university university university university planning and design organization planning and design organization
planning and design organization
landscape planning
government agency
Beijing Landscape and Garden Design Co., Ltd. Landscape Architecture Planning and Design Institute of Beijing Forestry University Planning and Design Institute of Forest Products Industry, State Forestry and Grass Bureau Beijing Municipal Landscape and Greening Bureau
3
planning and design organization planning and design organization
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Table 2 Criteria of mapping the demand for ES. Class
Single-criterion
Weight
Justification
Assigned value
Data
Ecological service
Soil erosion sensitivity
0.25
0.20
Vegetation coverage
0.25
Farmland
0.20
Geological hazard sensitivity
0.10
Accessibility
0.25
Population density
0.25
Use frequency of green spaces
0.25
reclassified by Jenks’s natural breaks method
cultural heritage
0.25
Culture relic protection site Within 300 m buffer zone Within 500 m buffer zone
9 7 3 1 9 7 5 1 9 7 5 1 9 5 9 5 1 9 7 5 3 1 9 7 5 3 1 9 7 5 3 1 9 5 1
Digital Elevation Model (DEM) data
Water buffer
slope above25° slope between 15° and 25°, elevation higher than 100 m slope between 6° and 15°, elevation higher than 100 m slope below 6°, elevation higher than 100 m Waterbody itself within50m buffer zone within 50–100 m buffer zone within 100–150 m buffer zone higher than60% 45%–60% 35%–45% 20%–35% Permanent farmland Ordinary farmland Unexpected geological hazard areas Chronic geological Burst geological hazard areas below300m 300–500 m 500–800 800–1000 m above1000m reclassified by Jenks’s natural breaks method
Cultural service
Land cover information (2016)
NDVI (2016) and Land cover information (2016) Land cover information (2016) and the distribution of permanent farmland Seismic data Point of interest (POI) regarding public parks, distribution of residential areas, and the land cover information (2016) Point of interest (POI) regarding public parks and the density of population
Point of interest (POI) regarding public parks and the check-in data
Beijing cultural heritage application
buffer zone) refers to the desire for recreation service. The higher the population density, the higher the demand for recreation services. Green spaces include not only existing urban parks, but also potential green parks. The population data (resolution = 250 m) used for population density analysis was provided by the Global Human Settlement Project (http://ghslsys.jrc.ec.europa.eu/datasets.php).
according to the Normalized Differential Vegetation Index (NDVI): i.e. 20%–35%, 35%–45%, 45%–60%, and > 60%. 2.2.5. Permanent basic farmland Although there is always human disturbance, farmland is an important component of urban ecosystems, especially permanent basic farmland. In China, permanent basic farmland refers to farmland that has been protected to ensure food security. Farmland not only provides food for human beings, but also provides a habitat for animals and plants. We identified permanent and ordinary farmland based on the land cover interpreted from remote-sensing images and maps obtained from the Beijing Municipal Planning Commission.
2.2.8. Use frequency of green spaces The use frequency of green spaces was obtained using the location information from check-in spots. The check-in data (resolution = 27 m) from July 29th to August 2nd, 2015 (including three weekdays) were processed through the Tencent EasyGo project, which was supported by WeChat (WeChat ID: easygo-qq), one of the three major social network services in China. The total number of visitors within this period was 6,104,811. The higher check-in data for a green space indicated that there were more visitors, which means a larger consumption of ecological services.
2.2.6. Accessibility The concept of accessibility, which can be defined as how easily a location can be reached from another location or the possibility to reach spatially distributed opportunities, is a well-developed concept and a common research framework within the field of transport geography (Rodrigue et al., 2016). In this study, the accessibility of green spaces was characterized by calculating the Euclidean distances between green spaces and the nearest neighborhood. The higher the accessibility to green spaces, the better the function of green spaces recreation services and the higher the demand for recreation. We used point of interest (POI) data captured by Baidu Maps (https://map.baidu.com/, 2016) to obtain location information for the community.
2.2.9. Cultural heritage Cultural heritage refers to historically or culturally important landscapes (MEA, 2005). The point data for the distribution of all cultural relics in the study area were obtained from the Beijing Tsinghua Tongheng Urban Planning & Design Institute, and each point was allocated 300-m and 500-m buffer zones. 2.3. Weight identification: expert scoring
2.2.7. Population density Population density is related with multiple services, for example, flooding regulation service (Nedkov and Burkhard, 2012). In this study, since the flooding regulation service is assessed by water systems in the Section 2.2.3., population density (population in the 500-m green space
Expert scoring approach is widely used in the assessment of ES for the complex correlation among variables (Jacobs et al., 2015). In our case, 25 experts from majors of urban planning, landscape planning, and environmental science representing government agencies, 4
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Table 3 A summary of data sources. Data
Data sources
DEM data Land cover information (2016) NDVI (2016) Distribution of permanent farmland Seismic data Point of interest (POI) regarding public parks Distribution of residential areas Density of population Check-in data Beijing cultural heritage application
Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences (http://www.gscloud.cn) Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences (http://www.gscloud.cn) Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences (http://www.gscloud.cn) Beijing municipal commission for city planning and land resources management Beijing Earthquake Agency (http://www.bjdzj.gov.cn/) Baidu map (http://map.baidu.com/) Baidu map (http://map.baidu.com/) Global Human Settlement Project (http://ghslsys.jrc.ec.europa.eu/datasets.php) Tecent easygo: a project that collect street-level IP location data. Beijing Tsinghua Tongheng Urban Planning & Design Institute
universities and planning and design organizations were surveyed. Experts were selected on the basis of their expertise and leadership in ecosystem services and urban greenspaces. They asked to define: 1) the weight of ecological service demand (0.55) and cultural service demand (0.45); 2) the weight of every single criterion (Table 2) by completing the importance of each criterion using methods of rating, ranking and pair-wise comparisons (Meerow and Newell, 2016). For example, the weight of accessibility, population density, and use frequency were defined according to the averaged weight distribution. In this way, we obtained comprehensive and multi-criteria mapping capabilities for ecological service demand. Each ES demand type is assigned a value indicating the demand level (“9”: the highest demand; “1”: the lowest demand), using Jenks’s natural breaks method by raster calculator function in Arcgis (Chen et al., 2013). A detailed weight assignment is shown for every single criterion in Table 2. Data sources are shown in Table 3.
where f represents the positive correlation coefficient between ecological process and minimum resistance, Dij is the spatial distance from source j to destination i, and Ri is the resistance coefficient of destination i to species migration. 3. Results 3.1. Demand for ecological services The demand for ecological services was assessed according to multiple ecological variables (Fig. 3). The study area is almost a plain, with only some mountains encroaching into the plain in the west, where there is a high sensitivity to soil erosion. The foot of the mountain is defined as a sensitive area for unexpected geological hazards; therefore, there is a high demand for ecological services in the western mountainous areas. Considering the vegetation coverage, areas with more than 45% vegetation coverage were mainly located in the western mountainous and northern parts of the study area, e.g. the Olympic Forest Park. Water bodies i.e. urban rivers and lakes were distributed evenly. Farmland was scattered throughout the suburbs, but permanent basic farmlands (i.e. areas designated for permanent protection) were mainly distributed in the eastern and northern suburbs. In summary, the western mountainous areas, public parks, water bodies, and permanent basic farmlands were areas with high demand for ES (Fig. 4).
2.4. Mapping multiple ES demand To generate a map of demand for both ecological services and cultural services, we overlaid the mapping result of every single ES demand according to Table 2. Although no comprehensive and available data of all ES demand for the central Beijing exists yet, the selected nine criteria are typical and informative to represent the overall situation of the demand for ES. We then reclassified the multi-criteria map of ES demand into three levels: low demand (1 < value 5) , medium demand (5 < value 9) , high demand (value = 9).
3.2. Demand for cultural services
2.5. Application of ES demand mapping
The mapping of the demand for cultural services was based on accessibility and population density within the 500-m buffer zone as well as the use frequency of green spaces and cultural heritage. In terms of accessibility, Fig. 5(a) shows that the distances between green spaces and residential areas were within 500 m in most cases. This was especially true for areas between the fourth and fifth ring roads in north Beijing, which include the Yuanmingyuan Park, the Summer Palace, and the Olympic Forest Park. In terms of population density (Fig. 5(b)), the population density in the whole study area generally decreased. Green spaces in Dongcheng, Xicheng, and southern Haidian districts have a large potential for cultural services, which also means a high demand for cultural services in these areas. In contrast, the suburban demand for cultural services was lower because of the low population in the suburbs. In terms of green space use frequency (Fig. 5(c)), the use frequency of large urban parks was higher, as was the case for the Olympic Forest Park, Summer Palace, Yuanmingyuan Park, and Zizhuyuan Park. Considering cultural heritage (Fig. 5(d)), these were mostly located in Dongcheng and Xicheng districts at the center of the city. These areas were very important because of their cultural service functions. In summary, areas with a high demand for cultural services are mainly located in public parks (Fig. 6).
Yu (1996) proposed a methodology of identifying ecological security patterns in landscapes, including: 1) assessing the ecosystem; 2) identifying the landscape elements that are most critical to maintaining the health, integrity, and security of the ecosystem; 3) constructing spatial links between these landscape elements. In this respect, we applied the mapping results of the demand for ES to the identification of ecological security patterns in landscapes. First, we integrated the evaluation of demand for ES with the construction of an ecological security pattern by identifying key landscape elements according to the related demand for ES. Second, green spaces with high and medium demand for ecological services were defined as key ecological sources. Finally, we identified key ecological corridors that depend on the least-cost path analysis (Kong et al., 2010), which can be used to calculate the shortest path between two ecological sources by determining the resistance values of different land cover types. These resistance values were assigned according to previous studies (Zhang et al., 2017): i.e. woodland, 1; grassland, 10; farmland, 30; unused land, 300; water area, 50; and built-up area, 500. i=m
MCR = fmin
Dij × Ri j=n
5
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Fig. 3. Analysis of ecological criteria. The numbers in the legend refers to the assigned value (see Table 2).
3.3. Demand for ecosystem services
mountainous area and the permanent farmland in the east, with a high demand for ecological services and a fine demand for cultural services. These areas are sightseeing and recreational green spaces. For example, some permanent farmland functions as a country park or urban agriculture garden. Second, as green islands in a city, public parks are often considered to have high ecological services demand as well as high cultural services demand. Most public parks are coincident with this hypothesis; however, three parks (Guanyuan Park, Ditan Park, and
In comparing Figs. 4 and 6, we can see that for the same patch of green space, there are trade-offs and synergies in the demand for ecological services and the demand of cultural services. First, mountains and farmlands located in suburbs are usually believed to have a high demand for ecological services, but low demand for cultural services. However, the exceptions in this case are distributed in the western
Fig. 4. The multi-criteria results of the demand for ecological services. 6
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Fig. 5. Indicators of cultural services: a) accessibility, b) population density, c) use frequency of green space, d) cultural heritage.
Fig. 6. The mapping of demand for cultural services based on multi-criteria.
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Fig. 7. Assessment of the demand for ecosystem services using multi-criteria. “0″ represents built up areas.
Tiantan Park) show a high demand for cultural services, but relatively low demand for ecological services. Fig. 7 shows the synthesized results for services demand and cultural services demand. We divided the demand into high-, middle-, and low-demand areas according to their value and further calculated the area of each category (Table 4). The Summer Palace and Olympic Forest Park are the largest areas with high ES demand. Surprisingly, some small green spaces also have high demand for ES, although they are located in densely built-up areas; e.g. some green spaces in Beihai Park, Yuyuantan Park, and Chaoyang Park, as well as some permanent farmlands in the east. In other words, the level of demand for ES is uncorrelated with the location, size, and type of green spaces. Areas with high demand for ES can be regarded as a baseline pattern for green spaces. These areas occupy 1,630.52 hm2 of Beijing, comprising 1.50% of the total area of the central city (Table 4). These areas mainly include the Western Mountain, Summer Palace, Olympic Forest Park, Dongba Country Park, and some small patches on the southeastern edge of Beijing. The areas with high demand for ES are the most important green spaces for ecological-cultural services. The areas with medium demand for ES are distributed evenly, with an area of 20,454.07 hm2 comprising 18.78% of the total urban area. The areas with low demand for ES, with an area of 40,678.02 hm2 comprises 37.34% of the total urban area.
corridors calculated with least-cost path are not always to be green spaces (Table 4). Small green spaces located on corridors can be important as stepping stones, which contribute to the overall landscape connectivity. 4. Discussion 4.1. Multi-criteria assessment of demand for ecosystem services Mapping of the demand for ES from multiple aspects provides various insights (Villamagna et al., 2013). Several studies have argued that assessments regarding ES should include multiple drivers (Daily et al., 2000; Fisher et al., 2009; Maes et al., 2012), therefore, a multi-criteria approach is needed for a more explicit, detailed, and comprehensive assessment of demand for ES. Ecological services and cultural services are inextricably correlated, and their combination and comparison can benefit our understanding of urban ecosystems. The necessity for applying multi-criteria was verified by different assessment results for the demand for ecocultural services. First, compared with other studies that compare the supply and demand of ES (Castro et al., 2014), we carried out explicit spatial comparisons between ecological and cultural demand for ES. For ecological services, places with high demands are mainly distributed in suburban areas. In contrast, for cultural services, places with high demand are mainly located in densely urbanized areas. Second, with regard to the size of green spaces, our findings showed that large green spaces located in suburban or city margins tend to have a higher demand for ecological services than small patches of green spaces in densely built-up areas are coincident with previous studies (Kong et al., 2007; Kong et al., 2010; Zhou et al., 2014; Guo et al., 2018). Actually, higher demand for ecological services isn’t always located in suburban areas, it depends on the
3.4. Application of mapping the demand for ES on optimizing green spaces The ecological security pattern of the landscape (Fig. 8) comprised ecosystem-critical cores and corridors. The ecological cores are mainly distributed in suburban areas, and the cultural cores are mainly located in the center of the city. This pattern can be regarded as an ideal landscape pattern for central Beijing, but the current land covers of the Table 4 Different levels of demand for ecosystem services. Green spatial pattern level
Ideal pattern area of green space (hm2)
Other land area (hm2)
Proportion of ideal pattern area of green space
High (value = 9) Medium (5 ≤ value < 9) Low (1 ≤ value < 5)
1630.52 20454.07 40678.02
107299.48 88475.93 68251.98
1.50% 18.78% 37.34%
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Fig. 8. The cores and potential corridors in the ecological security pattern.
demand for ecological services to achieve more precise results.
ES type included in the assessment. For example, Baró et al. (2016) measured the demand for air purification in Barcelona, and it turned out to be higher in urbanized areas. However, the availability of related data on various ES can limited the mapping of ES demand/ supply (Seppelt et al., 2012). Third, according to the synthesized mapping of ecological and cultural services, the demand for ES of small green spaces in highly urbanized areas can be higher than that for large green spaces (e.g. forestry lands on mountains) in suburban areas. These small green spaces are not only crucial for recreation of human, but also important in risk reduction such as erosion prevention and microclimate regulation. In a sum, the demand for ES in a green space is uncorrelated with its location, size, and type.
4.3. Ecological security pattern and suggestions As showed in Fig. 8, we made the integration of ES demand into landscape assessment. Prior studies (Kong et al., 2010; Zhou et al., 2014; Su et al., 2016) used various approaches to identify cores and corridors, but all of them emphasize spatial connectivity or geological/ ecological sensitivity instead of the demand for ES. We selected the cores and corridors of ecological security patterns in the landscape in terms of areas with high demand for ecological-cultural services. The ecological security patterns offer a useful reference for landscape planning and land-use management. First, considering that some small green spaces in urbanized areas have not only high cultural services demand but also ecological services demand, a good way to improve public parks’ ecological services is to extract some specialized green spaces from the parks for biodiversity conservation. These small green spaces can become stepping stones for species migration. Second, suburban green spaces, such as mountains and permanent basic farmland, have huge potential cultural value. Using the example of country parks in the study area, proper development by ensuring an ecological environment can increase visitors to the surrounding green spaces. Third, river systems, mountains, and parks in urbanized areas should be well protected considering their ecological security.
4.2. Consumption and direct use of cultural services The demands for cultural services were intangible and varied from region to region because of different social characteristics, which makes demand challenging to assess (Daniel et al., 2012). Although PPGIS has been applied on assessing preferences and desires of the public, especially on the cultural and spiritual values of ecosystems (Brown et al., 2012, Brown, 2013, Brown and Kyttä, 2014); as Burkhard et al. (2012) mentioned, studies on demand for ES should not only consider the potential of green spaces to provide ES (e.g. population density and accessibility of green spaces), but also the current consumption/use of ES. Considering that empirical data about the consumption of cultural services is relatively difficult to obtain, we proposed a new approach using the big data on the use frequency of green spaces as empirical data, which is based on the check-in data from social networks. This new indicator helps to broaden the concept of the demand for ES, and it is much more efficient than direct observations. On the premise of available data, the indicator of use frequency can be easily applied to other study areas. From the aspect of the consumption of ecological services, a few studies have analyzed ecological consumption. For example, Burkhard et al. (2012) and Kroll et al. (2012) assessed energy consumption to clarify the demand for ES, while Change et al. (2013) assessed the water demand using water consumption data, including public, municipal irrigation, and industrial water use. In future research, additional information on ES consumption should be included in mapping the
4.4. Methodological limitations Although this model is flexible and useful, methodology limitations still exist. In large-scale cases with less-detailed data, the expert-based weighting method was assumed to be more appropriate (Wolff et al., 2015), but was still subjective. If more empirical data are collected as part of the database, the weighting method may be validated, and assessment results may be more accurate and convincing. For example, Paracchini et al. (2014) assigned weights after conducting surveys to collect information on people’s preferences for recreation. Unfortunately, we did not obtain information on preferences, health, and security considering demand for cultural services. In the future work, more factors and participants should be involved in weighting identification. 9
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5. Conclusion
Brown, G., Fagerholm, N., 2015. Empirical PPGIS/PGIS mapping of ecosystem services: a review and evaluation. Ecosyst. Serv. 13, 119–133. Brown, G., Kyttä, M., 2014. Key issues and research priorities for public participation GIS (PPGIS): a synthesis based on empirical research. Appl. Geogr. 46, 122–136. Burkhard, B., Kroll, F., Nedkov, S., Müller, F., 2012. Mapping ecosystem service supply, demand and budgets. Ecol. Indic. 21, 17–29. Casado-Arzuaga, I., Madariaga, I., Onaindia, M., 2013. Perception, demand and user contribution to ecosystem services in the Bilbao Metropolitan Greenbelt. J. Environ. Manage. 129, 33–43. Castro, A.J., Verburg, P.H., Martín-López, B., Garcia-Llorente, M., Cabello, J., Vaughn, C.C., López, E., 2014. Ecosystem service trade-offs from supply to social demand: a landscape-scale spatial analysis. Landscape Urban Plann. 132, 102–110. Chang, H., Jung, I.W., Strecker, A., Wise, D., Lafrenz, M., Shandas, V., Johnson, G., 2013. Water supply, demand, and quality indicators for assessing the spatial distribution of water resource vulnerability in the Columbia River Basin. Atmos. Ocean 51 (4), 339–356. Chee, Y.E., 2004. An ecological perspective on the valuation of ecosystem services. Biol. Conserv. 120 (4), 549–565. Chen, J., Yang, S., Li, H., Zhang, B., Lv, J., 2013. Research on geographical environment unit division based on the method of natural breaks (Jenks). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4 (W3), 47. Costanza, R., d'Arge, R., De Groot, R., Farber, S., Grasso, M., Hannon, B., Raskin, R.G., 1997. The value of the world's ecosystem services and natural capital. Nature 387 (6630), 253. Crossman, N.D., Burkhard, B., Nedkov, S., Willemen, L., Petz, K., Palomo, I., Alkemade, R., 2013. A blueprint for mapping and modelling ecosystem services. Ecosyst. Serv. 4, 4–14. Daily, G.C., Matson, P.A., 2008. Ecosystem services: from theory to implementation. Proc. Natl. Acad. Sci. 105 (28), 9455–9456. Daily, G.C., Söderqvist, T., Aniyar, S., Arrow, K., Dasgupta, P., Ehrlich, P.R., Levin, S., 2000. The value of nature and the nature of value. Science 289 (5478), 395–396. Daniel, T.C., Muhar, A., Arnberger, A., et al., 2012. Contributions of cultural services to the ecosystem services agenda. Proc. Natl. Acad. Sci. U.S.A 109 (23), 8812–8819. De Groot, R.S., Wilson, M.A., Boumans, R.M., 2002. A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol. Econ. 41 (3), 393–408. Fisher, B., Turner, R.K., Morling, P., 2009. Defining and classifying ecosystem services for decision making. Ecol. Econ. 68 (3), 643–653. Forman, R.T., 2014. Land Mosaics: The ecology of landscapes and regions (1995) (p. 217). Island Press. ISBN:978-1-61091-491-8. Guo, S., Saito, K., Yin, W., Su, C., 2018. Landscape connectivity as a tool in green space evaluation and optimization of the haidan district, beijing. Sustainability 10 (6), 1979. Guo, G., Wu, Z., Xiao, R., Chen, Y., Liu, X., Zhang, X., 2015. Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landscape Urban Plann. 135, 1–10. Hernández-Morcillo, M., Plieninger, T., Bieling, C., 2013. An empirical review of cultural ecosystem service indicators. Ecol. Ind. 29, 434–444. Howarth, R.B., Farber, S., 2002. Accounting for the value of ecosystem services. Ecol. Econ. 41 (3), 421–429. Jacobs, S., Burkhard, B., Van Daele, T., Staes, J., Schneiders, A., 2015. ‘The Matrix Reloaded’: a review of expert knowledge use for mapping ecosystem services. Ecol. Model. 295, 21–30. Kong, F., Yin, H., Nakagoshi, N., 2007. Using GIS and landscape metrics in the hedonic price modeling of the amenity value of urban green space: A case study in Jinan City, China. Landscape Urban Plann. 79 (3–4), 240–252. Kong, F., Yin, H., Nakagoshi, N., Zong, Y., 2010. Urban green space network development for biodiversity conservation: identification based on graph theory and gravity modeling. Landscape Urban Plann. 95 (1–2), 16–27. Kroll, F., Müller, F., Haase, D., Fohrer, N., 2012. Rural–urban gradient analysis of ecosystem services supply and demand dynamics. Land Use Policy 29 (3), 521–535. Li, F., Zhang, F., Li, X., Wang, P., Liang, J., Mei, Y., Qian, Y., 2017. Spatiotemporal patterns of the use of urban green spaces and external factors contributing to their use in central Beijing. Int. J. Environ. Res. Public Health 14 (3), 237. Maes, J., Egoh, B., Willemen, L., Liquete, C., Vihervaara, P., Schägner, J.P., Bouraoui, F., 2012. Mapping ecosystem services for policy support and decision making in the European Union. Ecosyst. Serv. 1 (1), 31–39. Meerow, S., Newell, J.P., 2016. Spatial planning for multifunctional green infrastructure: growing resilience in Detroit. Landscape Urban Plann. 159, 62–75. Miao, S., Chen, F., LeMone, M.A., Tewari, M., Li, Q., Wang, Y., 2009. An observational and modeling study of characteristics of urban heat island and boundary layer structures in Beijing. J. Appl. Meteorol. Climatol. 48 (3), 484–501. Millennium Ecosystem Assessment. (2005). Ecosystems and human well-being (Vol. 5). Washington, DC: Island Press. Nedkov, S., Burkhard, B., 2012. Flood regulating ecosystem services—Mapping supply and demand, in the Etropole municipality, Bulgaria. Ecol. Ind. 21, 67–79. Orenstein, D.E., Groner, E., 2014. In the eye of the stakeholder: changes in perceptions of ecosystem services across an international border. Ecosyst. Serv. 8, 185–196. Paracchini, M.L., Zulian, G., Kopperoinen, L., Maes, J., Schägner, J.P., Termansen, M., Bidoglio, G., 2014. Mapping cultural ecosystem services: a framework to assess the potential for outdoor recreation across the EU. Ecol. Ind. 45, 371–385. Peng, J., Liu, Y., Wu, J., Lv, H., Hu, X., 2015. Linking ecosystem services and landscape patterns to assess urban ecosystem health: a case study in shenzhen city, china. Landscape Urban Plann. 143, 56–68. Plieninger, T., Dijks, S., Oteros-Rozas, E., Bieling, C., 2013. Assessing, mapping, and
A multi-criteria approach is needed for urbanized areas, where relationships among various ecosystems services are complex. In this study, we proposed a multi-criteria approach integrating ecological and cultural services demand to obtain a more comprehensive assessment of the demand for ES. Particularly, we innovatively introduced check-in data from WeChat to identify the consumption of cultural services, which is seldom used in existing research. The results show that large natural elements in urban regions, such as mountainous area, parks, and water bodies, tend to have higher demand for ES. However, some small green spaces located in densely built-up areas have a higher demand for ES than that of large green spaces. The consumption of cultural services is closely related to the distribution of green space and the composition of surrounding residents. Therefore, more details of the utilization of green space can be included in the future to obtain a better understanding of the consumption of cultural services. Besides, the study framework is repeatable and can be applied to any other study areas if suitable indicators and weights are adopted. Additional criteria are allowed if necessary, and the weight of every single criterion can be altered according to the study areas. CRediT authorship contribution statement Fangzheng Li: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Supervision, Funding acquisition, Project administration, Writing original draft, Writing - review & editing. Shiyi Guo: Conceptualization, Methodology, Visualization, Formal analysis, Writing - review & editing. Di Li: Writing - review & editing. Xiong Li: Funding acquisition, Supervision, Project administration, Writing - review & editing. Jing Li: Methodology, Software, Resources, Data curation, Visualization. Shuang Xie: Visualization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No. 51908036, 31670704), Beijing Natural Science Foundation (Grant NO. 8194071); Humanities and social sciences fund of the Ministry of Education (NO. 19YJC760042); China Postdoctoral Science Foundation (NO. 2018M641222);the Fundamental Research Funds for the Central Universities (NO. BLX201808), Research and Development Plan of Beijing Municipal Science and Technology Commission (Grant No.D17110900710000). We thank Daniel Schmidt, PhD, and Peter Fogarty, MA, from Liwen Bianji, Edanz Editing China (www.liwenbianji.cn/ac), for editing the English text of drafts of this manuscript. References Adger, W.N., 2000. Social and ecological resilience: are they related? Prog. Hum. Geogr. 24 (3), 347–364. Ala-Hulkko, T., Kotavaara, O., Alahuhta, J., Helle, P., Hjort, J., 2016. Introducing accessibility analysis in mapping cultural ecosystem services. Ecol. Ind. 66, 416–427. Baró, F., Palomo, I., Zulian, G., Vizcaino, P., Haase, D., Gómez-Baggethun, E., 2016. Mapping ecosystem service capacity, flow and demand for landscape and urban planning: a case study in the Barcelona metropolitan region. Land Use Policy 57, 405–417. Bennett, E.M., Peterson, G.D., Gordon, L.J., 2010. Understanding relationships among multiple ecosystem services. Ecol. Lett. 12 (12), 1394–1404. Brown, G., 2013. The relationship between social values for ecosystem services and global land cover: an empirical analysis. Ecosyst. Serv. 5, 58–68.
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F. Li, et al. quantifying cultural ecosystem services at community level. Land Use Policy 33, 118–129. Rodrigue, J.P., Comtois, C., Slack, B., 2016. The Geography of Transport Systems. Routledge. Schirpke, U., Scolozzi, R., Marco, C.D., Tappeiner, U., 2014. Mapping beneficiaries of ecosystem services flows from natura 2000 sites. Ecosyst. Serv. 9, 170–179. Schröter, M., Barton, D.N., Remme, R.P., Hein, L., 2014. Accounting for capacity and flow of ecosystem services: a conceptual model and a case study for Telemark, Norway. Ecol. Ind. 36, 539–551. Seppelt, R., Fath, B., Burkhard, B., Fisher, J.L., Grêt-Regamey, A., Lautenbach, S., Van Oudenhoven, A.P., 2012. Form follows function? Proposing a blueprint for ecosystem service assessments based on reviews and case studies. Ecol. Ind. 21, 145–154. Su, Y., Chen, X., Liao, J., Zhang, H., Wang, C., Ye, Y., Wang, Y., 2016. Modeling the optimal ecological security pattern for guiding the urban constructed land expansions. Urban For. Urban Greening 19, 35–46. Sun, Y., Zhuang, G., Tang, A., Wang, Y., An, Z., 2006. Chemical characteristics of PM2. 5 and PM10 in haze− fog episodes in Beijing. Environ. Sci. Technol. 40 (10), 3148–3155. Syrbe, R.U., Walz, U., 2012. Spatial indicators for the assessment of ecosystem services: providing, benefiting and connecting areas and landscape metrics. Ecol. Ind. 21, 80–88.
Villamagna, A.M., Angermeier, P.L., Bennett, E.M., 2013. Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery. Ecol. Complexity 15, 114–121. Villamagna, A.M., Mogollón, B., Angermeier, P.L., 2014. A multi-indicator framework for mapping cultural ecosystem services: the case of freshwater recreational fishing. Ecol. Ind. 45, 255–265. Wang, G., Zhang, R., Gomez, M.E., Yang, L., Zamora, M.L., Hu, M., Li, J., 2016. Persistent sulfate formation from London Fog to Chinese haze. Proc. Natl. Acad. Sci. 113 (48), 13630–13635. Wolff, S., Schulp, C.J.E., Verburg, P.H., 2015. Mapping ecosystem services demand: A review of current research and future perspectives. Ecol. Indic. 55, 159–171. Yu, K., 1996. Security patterns and surface model in landscape ecological planning. Landscape Urban Plann. 36 (1), 1–17. Zhang, L., Peng, J., Liu, Y., Wu, J., 2017. Coupling ecosystem services supply and human ecological demand to identify landscape ecological security pattern: a case study in Beijing–Tianjin–Hebei region, China. Urban Ecosyst. 20 (3), 701–714. Zhou, K., Liu, Y., Tan, R., Song, Y., 2014. Urban dynamics, landscape ecological security, and policy implications: a case study from the Wuhan area of central China. Cities 41, 141–153. Zulian, G., Stange, E., Woods, H., et al., 2018. Practical application of spatial ecosystem service models to aid decision support. Ecosyst. Serv. 29, 465–480.
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Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind
A multi-criteria spatial approach for mapping urban ecosystem services demand
T
Fangzheng Lia,1, Shiyi Guoa,b,1, Di Lic, Xiong Lia, , Jing Lid, Shuang Xiea ⁎
a
School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China Graduate School of Frontier Science, The University of Tokyo, Kashiwa 277-8563, Japan c School of Architecture SouthEast University Nanjing 210000 d Beijing Tsinghua Tongheng Urban Planning & Design Institute, Beijing 100085, China b
ARTICLE INFO
ABSTRACT
Keywords: Demand for ecosystem services Landscape ecological security pattern Demand for cultural services Demand for ecological services Urban green space
A growing number of studies have mapped the demand for ecosystem services (ES). Recently, demand for ES has been broadened to include cultural services in addition to ecological services, especially for urbanized areas. In this study, a multi-criteria approach is proposed that synthesizes the available ecological and cultural services to map the demand for ES: including 1) soil erosion sensitivity, 2) geological hazard sensitivity, 3) water management, 4) vegetation coverage, 5) permanent farmland, 6) accessibility, 7) population density, 8) direct use of green spaces, and 9) cultural heritage. The cultural services demand describes the desire or preference, and consumption or direct use of cultural services, e.g. recreation and cultural heritage. Most studies discussed only the desire or preference for cultural services because of the difficulty quantifying the actual consumption of these cultural services. This research gap was filled using the check-in data collected from WeChat (a major social network in China). Each criterion was assigned a weight so that the ecological services demand, the cultural services demand, and the overall ES demand could be quantified. The results suggest that in general, the mountainous areas, farmlands, and suburban areas have high demand for ecological services while public parks in urban areas show high demand for cultural services. However, the ES demand in the availability of some small green spaces in highly urbanized areas may be higher than that for large green spaces in suburban areas. This multi-criteria analysis is necessary to obtain a comprehensive assessment of ES demand, which will contribute to improving the applicability of ES in real-world decision making, e.g. green space planning and conservation.
1. Introduction Ecosystem services (ES) refers to the goods and services of ecosystem structures and functions for human well-being (Costanza et al., 1997; de Groot et al., 2002; Chee, 2004; Burkhard et al., 2012; Crossman et al., 2013; Zulian et al., 2018). Urbanization has placed increasing pressures on ES, especially in highly constructed areas (Forman, 2014). Megacities tend to have various ecological problems because of their large populations and dense development (Peng et al., 2015), such as haze, (Sun et al., 2006; Wang et al., 2016) and heat island effects (Miao et al., 2009; Guo et al., 2015). The growing demand for increasingly degraded ecosystems has seriously threatened the sustainable development (MEA, 2005). Therefore, it is necessary to map the demand for ES, which shows where different kinds of ES are needed, which leads to more efficient land-use plans and policies (Daily and
Matson, 2008; Orenstein and Groner, 2014). While ES are complex and interconnected (Adger, 2000; Bennett et al., 2010). According to Millennium Ecosystem Assessment (2005), ES can be classified into provisioning services, regulating services, supporting services, and cultural services. Provisioning services refer to the products obtained from ecosystems (e.g. food, freshwater); regulating services describe the benefits obtained from regulation of ES (e.g. climate regulation, water regulation); supporting services are services necessary for the production of all other ES (e.g. soil formation, nutrient cycling); cultural services refer to nonmaterial benefits obtained from ES (e.g. recreation, cultural heritage) (Schirpke et al., 2014; Villamagna et al., 2014). Here we sorted provisioning, regulating, and supporting services as ecological services, in comparison with cultural services. In existing research, the assessment of ES from an ecological perspective is relatively well-established (Daily et al., 2000; Fisher
Corresponding author. E-mail addresses: [email protected] (F. Li), [email protected] (S. Guo), [email protected] (D. Li), [email protected] (X. Li), [email protected] (S. Xie). 1 Means the co-first authors. ⁎
https://doi.org/10.1016/j.ecolind.2020.106119 Received 12 November 2018; Received in revised form 22 November 2019; Accepted 17 January 2020 1470-160X/ © 2020 Elsevier Ltd. All rights reserved.
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et al., 2009; Syrbe and Walz, 2012); in contrast, literature on ES indicates that the assessment of cultural services lags behind other service categories. Recently, cultural services have been widely recognized as a critical part in human welfare (Howarth and Farber, 2002; HernándezMorcillo et al., 2013; Ala-Hulkko et al., 2016; Baró et al., 2016; Zhang et al., 2017). A comprehensive mapping of ES demand should include both ecological and cultural services. With regard to the demand of ES, according to the literature review by Wolff et al. (2015), there are three main definitions of demand for ES (Burkhard et al., 2012; Villamagna et al., 2013; Schröter et al., 2014). Burkhard et al. (2012) regard demand for ES as the sum of all actual use or consumption of ES, while the demand is often constrained by the current supply of ES. Because of the influence of preferences or desire on the consumer’s willingness to use a service, Schröter et al. (2014) prefer to use preferences or desire for ES to define the demand for ES. Villamagna et al. (2013) defined demand for ES as the amount of a service required or desired by society, which should be further distinguished according to time and space. All these definitions have been adopted, but each definition has its own emphasis. Wolff et al. (2015) synthesized the existing definitions and elaborated the demand for ES from two aspects: 1) Consumption/direct use, i.e. demand for ES is the sum of all services actually consumed within a certain area over a certain period without regard for where ES originated. Empirical data on the actual consumption, which can be obtained from statistics, interviews, or monitoring, is necessary to assess the demand for ES. 2) Desires and preferences, i.e. the demand for ES is the amount of regulation required for the natural environment or desired by society, including the demand for risk reduction (e.g. flood regulation, erosion control). The former emphasizes actual consumption, while the latter tends to identify the needed services based on given indicators. Most studies have assessed the cultural services demand from the aspect of desires and preferences instead of consumption or direct use, which may be because of the difficulty of measurement. From the aspect of desires and preferences, the demand for cultural services can be quantified by indicators such as accessibility (Paracchini et al., 2014; Meerow and Newell, 2016), population (Zhang et al., 2017), and cultural value, i.e. places with cultural heritage (Plieninger et al., 2013; Casado-Arzuaga et al., 2013). However, from the other aspect, the consumption or direct use of cultural services is usually measured based on empirical data obtained by surveys and questionnaires, which is time and energy consuming (Li et al., 2017). Although public participation GIS (PPGIS) was proposed as an alternative method of collecting the opinion of the public, the sampling and data collection method are mainly surveys, workshop and interviews (Brown, 2013; Brown and Kyttä, 2014; Brown and Fagerholm, 2015), which is limited to the number of samples. Therefore, the consumption or direct use of cultural services is often ignored even though it provides important evidence for ES benefits (Hernández-Morcillo et al., 2013). To address this research gap, we used a multi-criteria approach integrating ecological and cultural services. In particular, we proposed an operational method of measuring the consumption or direct use of cultural services: i.e. we used the check-in data collected from WeChat (one of the major social networks in China). This study aimed to propose an operational and location-based framework for mapping ES demand. First, we evaluated the ecosystem service demand based on multi-criteria: i.e. soil erosion sensitivity, geological hazard sensitivity, water management, vegetation coverage, and permanent farmland for ecological services; and accessibility, population density, direct use of green spaces, and cultural heritage for cultural services. Second, expertdriven weighting of each criterion was conducted to achieve synthesized result of ES demand. Finally, we applied the ES demand to identify the ecological security pattern in landscapes. The research framework is shown in Fig. 1. The results for mapping the demand for ES can provide operational suggestions for policy decision-making, especially in green space planning and management.
Fig. 1. Research framework.
2. Materials and methodology 2.1. Study areas and data Beijing (39°38′–41°05′N), a typical mega-city in Asia, is located in the north of China. Beijing’s administration region occupies an area of 16,410 km2 (Fig. 2). The master plan for Beijing (2016–2035) classified Beijing into central urban, suburban, and outer suburban areas. This study focused on the central urban area (1386 km2), which consists of six districts (Dongcheng, Xicheng, Haidian, Chaoyang, Fengtai, and Shijingshan). Beijing is surrounded by mountains on three sides and there are mountains in the western central urban area. In addition to these mountains, there are some public parks, green belts, long rivers, roads, and waterbodies, which together form an ecosystem. A Landsat 8 OLI satellite remote sensing image (http://www. gscloud.cn) for October 11th, 2016 was fused using the GramSchmidt spectral sharpening method to obtain a higher accuracy of 15 m × 15 m. Land cover information (i.e. farmland, woodland, grassland, wetland, water area, built-up area, unused land) were identified using the support vector machine (SVM) supervised classification. The data was corrected by ERDAS Imagine software, and processed, calculated, tested by ArcGIS platform. The accuracy of the test results reached 84.91%, meeting the accuracy requirements. 2.2. Nine ES demand criteria We selected the following nine criteria for mapping the demand for ES according to a commonly cited reference: MEA (2005), and two reviews (Hernández-Morcillo et al., 2013; Wolff et al., 2015). The selection rationale, data source, and data processing are as following: (Table 1) 2.2.1. Soil erosion sensitivity In sloping fields, debris flow and landslides resulting from soil erosion may occur in rainy seasons. Soil erosion regulation is one of the regulating services. From the perspective of risk reduction (Wolff et al., 2015), the higher the soil erosion sensitivity, the higher the demand for ES. Slope is the critical variable for measuring soil erosion sensitivity. We divided slope into four categories and assigned a value to each category (Table 2). 2
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Fig. 2. The land use map of central Beijing.
2.2.2. Geological hazard sensitivity Various geological hazards, such as collapse, debris flow, ground fissures, and landslides, threaten urban ecological security. Geologically sensitive areas are also ecologically fragile areas with high demand for ES. The seismic information includes the unexpected, chronic, and dangerous geological hazard areas.
effect and poor drainage can lead to waterlogging. We conducted a buffer analysis on water areas within the study area and obtained buffer zones of 50 m, 100 m, and 150 m. The weight of each category decreased from each waterbody to the 150-m buffer zone. 2.2.4. Vegetation coverage Vegetation is the main component of green spaces. On the one side, especially in urban areas, places with high vegetation coverage usually provide more ES, for example, urban microclimates regulation, erosion regulation, and biodiversity conservation (Burkhard et al., 2012). On the other side, under the trend of urbanization, people in places with high vegetation coverage have a stronger demand of ES and a higher willingness to pay, because demand is influenced by the awareness, desires, and the willingness to conserve services (Schröter et al., 2014). In this case, vegetation coverage was classified into four categories
2.2.3. Water systems Urban water systems are the foundation of ecosystems, playing an important role in flood regulation and climate regulation services. For example, demand for flood regulation can be regarded as a necessity for disaster prevention or safety assurance. Due to urbanization, water and surrounding areas are affected by human activities; therefore, these areas have a higher demand for ecological services. The large amounts of impervious surfaces in urban areas is responsible for the heat island Table 1 Experts for weighting ES demand. Name of organization
Major
Type
Beijing Forestry University Tsinghua University Beijing University of Civil Engineering and Architecture North China University of Technology Beijing Tsinghua Tongheng Urban Planning & Design Institute Beijing Beilin Landscape Planning and Design Institute Co., Ltd.
landscape planning, environmental science urban planning, landscape planning urban planning, landscape planning landscape planning urban planning, landscape planning urban planning, landscape planning, environmental science landscape planning urban planning, landscape planning, environmental science environmental science
university university university university planning and design organization planning and design organization
planning and design organization
landscape planning
government agency
Beijing Landscape and Garden Design Co., Ltd. Landscape Architecture Planning and Design Institute of Beijing Forestry University Planning and Design Institute of Forest Products Industry, State Forestry and Grass Bureau Beijing Municipal Landscape and Greening Bureau
3
planning and design organization planning and design organization
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Table 2 Criteria of mapping the demand for ES. Class
Single-criterion
Weight
Justification
Assigned value
Data
Ecological service
Soil erosion sensitivity
0.25
0.20
Vegetation coverage
0.25
Farmland
0.20
Geological hazard sensitivity
0.10
Accessibility
0.25
Population density
0.25
Use frequency of green spaces
0.25
reclassified by Jenks’s natural breaks method
cultural heritage
0.25
Culture relic protection site Within 300 m buffer zone Within 500 m buffer zone
9 7 3 1 9 7 5 1 9 7 5 1 9 5 9 5 1 9 7 5 3 1 9 7 5 3 1 9 7 5 3 1 9 5 1
Digital Elevation Model (DEM) data
Water buffer
slope above25° slope between 15° and 25°, elevation higher than 100 m slope between 6° and 15°, elevation higher than 100 m slope below 6°, elevation higher than 100 m Waterbody itself within50m buffer zone within 50–100 m buffer zone within 100–150 m buffer zone higher than60% 45%–60% 35%–45% 20%–35% Permanent farmland Ordinary farmland Unexpected geological hazard areas Chronic geological Burst geological hazard areas below300m 300–500 m 500–800 800–1000 m above1000m reclassified by Jenks’s natural breaks method
Cultural service
Land cover information (2016)
NDVI (2016) and Land cover information (2016) Land cover information (2016) and the distribution of permanent farmland Seismic data Point of interest (POI) regarding public parks, distribution of residential areas, and the land cover information (2016) Point of interest (POI) regarding public parks and the density of population
Point of interest (POI) regarding public parks and the check-in data
Beijing cultural heritage application
buffer zone) refers to the desire for recreation service. The higher the population density, the higher the demand for recreation services. Green spaces include not only existing urban parks, but also potential green parks. The population data (resolution = 250 m) used for population density analysis was provided by the Global Human Settlement Project (http://ghslsys.jrc.ec.europa.eu/datasets.php).
according to the Normalized Differential Vegetation Index (NDVI): i.e. 20%–35%, 35%–45%, 45%–60%, and > 60%. 2.2.5. Permanent basic farmland Although there is always human disturbance, farmland is an important component of urban ecosystems, especially permanent basic farmland. In China, permanent basic farmland refers to farmland that has been protected to ensure food security. Farmland not only provides food for human beings, but also provides a habitat for animals and plants. We identified permanent and ordinary farmland based on the land cover interpreted from remote-sensing images and maps obtained from the Beijing Municipal Planning Commission.
2.2.8. Use frequency of green spaces The use frequency of green spaces was obtained using the location information from check-in spots. The check-in data (resolution = 27 m) from July 29th to August 2nd, 2015 (including three weekdays) were processed through the Tencent EasyGo project, which was supported by WeChat (WeChat ID: easygo-qq), one of the three major social network services in China. The total number of visitors within this period was 6,104,811. The higher check-in data for a green space indicated that there were more visitors, which means a larger consumption of ecological services.
2.2.6. Accessibility The concept of accessibility, which can be defined as how easily a location can be reached from another location or the possibility to reach spatially distributed opportunities, is a well-developed concept and a common research framework within the field of transport geography (Rodrigue et al., 2016). In this study, the accessibility of green spaces was characterized by calculating the Euclidean distances between green spaces and the nearest neighborhood. The higher the accessibility to green spaces, the better the function of green spaces recreation services and the higher the demand for recreation. We used point of interest (POI) data captured by Baidu Maps (https://map.baidu.com/, 2016) to obtain location information for the community.
2.2.9. Cultural heritage Cultural heritage refers to historically or culturally important landscapes (MEA, 2005). The point data for the distribution of all cultural relics in the study area were obtained from the Beijing Tsinghua Tongheng Urban Planning & Design Institute, and each point was allocated 300-m and 500-m buffer zones. 2.3. Weight identification: expert scoring
2.2.7. Population density Population density is related with multiple services, for example, flooding regulation service (Nedkov and Burkhard, 2012). In this study, since the flooding regulation service is assessed by water systems in the Section 2.2.3., population density (population in the 500-m green space
Expert scoring approach is widely used in the assessment of ES for the complex correlation among variables (Jacobs et al., 2015). In our case, 25 experts from majors of urban planning, landscape planning, and environmental science representing government agencies, 4
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Table 3 A summary of data sources. Data
Data sources
DEM data Land cover information (2016) NDVI (2016) Distribution of permanent farmland Seismic data Point of interest (POI) regarding public parks Distribution of residential areas Density of population Check-in data Beijing cultural heritage application
Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences (http://www.gscloud.cn) Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences (http://www.gscloud.cn) Geospatial Data Cloud site, Computer Network Information Center, Chinese Academy of Sciences (http://www.gscloud.cn) Beijing municipal commission for city planning and land resources management Beijing Earthquake Agency (http://www.bjdzj.gov.cn/) Baidu map (http://map.baidu.com/) Baidu map (http://map.baidu.com/) Global Human Settlement Project (http://ghslsys.jrc.ec.europa.eu/datasets.php) Tecent easygo: a project that collect street-level IP location data. Beijing Tsinghua Tongheng Urban Planning & Design Institute
universities and planning and design organizations were surveyed. Experts were selected on the basis of their expertise and leadership in ecosystem services and urban greenspaces. They asked to define: 1) the weight of ecological service demand (0.55) and cultural service demand (0.45); 2) the weight of every single criterion (Table 2) by completing the importance of each criterion using methods of rating, ranking and pair-wise comparisons (Meerow and Newell, 2016). For example, the weight of accessibility, population density, and use frequency were defined according to the averaged weight distribution. In this way, we obtained comprehensive and multi-criteria mapping capabilities for ecological service demand. Each ES demand type is assigned a value indicating the demand level (“9”: the highest demand; “1”: the lowest demand), using Jenks’s natural breaks method by raster calculator function in Arcgis (Chen et al., 2013). A detailed weight assignment is shown for every single criterion in Table 2. Data sources are shown in Table 3.
where f represents the positive correlation coefficient between ecological process and minimum resistance, Dij is the spatial distance from source j to destination i, and Ri is the resistance coefficient of destination i to species migration. 3. Results 3.1. Demand for ecological services The demand for ecological services was assessed according to multiple ecological variables (Fig. 3). The study area is almost a plain, with only some mountains encroaching into the plain in the west, where there is a high sensitivity to soil erosion. The foot of the mountain is defined as a sensitive area for unexpected geological hazards; therefore, there is a high demand for ecological services in the western mountainous areas. Considering the vegetation coverage, areas with more than 45% vegetation coverage were mainly located in the western mountainous and northern parts of the study area, e.g. the Olympic Forest Park. Water bodies i.e. urban rivers and lakes were distributed evenly. Farmland was scattered throughout the suburbs, but permanent basic farmlands (i.e. areas designated for permanent protection) were mainly distributed in the eastern and northern suburbs. In summary, the western mountainous areas, public parks, water bodies, and permanent basic farmlands were areas with high demand for ES (Fig. 4).
2.4. Mapping multiple ES demand To generate a map of demand for both ecological services and cultural services, we overlaid the mapping result of every single ES demand according to Table 2. Although no comprehensive and available data of all ES demand for the central Beijing exists yet, the selected nine criteria are typical and informative to represent the overall situation of the demand for ES. We then reclassified the multi-criteria map of ES demand into three levels: low demand (1 < value 5) , medium demand (5 < value 9) , high demand (value = 9).
3.2. Demand for cultural services
2.5. Application of ES demand mapping
The mapping of the demand for cultural services was based on accessibility and population density within the 500-m buffer zone as well as the use frequency of green spaces and cultural heritage. In terms of accessibility, Fig. 5(a) shows that the distances between green spaces and residential areas were within 500 m in most cases. This was especially true for areas between the fourth and fifth ring roads in north Beijing, which include the Yuanmingyuan Park, the Summer Palace, and the Olympic Forest Park. In terms of population density (Fig. 5(b)), the population density in the whole study area generally decreased. Green spaces in Dongcheng, Xicheng, and southern Haidian districts have a large potential for cultural services, which also means a high demand for cultural services in these areas. In contrast, the suburban demand for cultural services was lower because of the low population in the suburbs. In terms of green space use frequency (Fig. 5(c)), the use frequency of large urban parks was higher, as was the case for the Olympic Forest Park, Summer Palace, Yuanmingyuan Park, and Zizhuyuan Park. Considering cultural heritage (Fig. 5(d)), these were mostly located in Dongcheng and Xicheng districts at the center of the city. These areas were very important because of their cultural service functions. In summary, areas with a high demand for cultural services are mainly located in public parks (Fig. 6).
Yu (1996) proposed a methodology of identifying ecological security patterns in landscapes, including: 1) assessing the ecosystem; 2) identifying the landscape elements that are most critical to maintaining the health, integrity, and security of the ecosystem; 3) constructing spatial links between these landscape elements. In this respect, we applied the mapping results of the demand for ES to the identification of ecological security patterns in landscapes. First, we integrated the evaluation of demand for ES with the construction of an ecological security pattern by identifying key landscape elements according to the related demand for ES. Second, green spaces with high and medium demand for ecological services were defined as key ecological sources. Finally, we identified key ecological corridors that depend on the least-cost path analysis (Kong et al., 2010), which can be used to calculate the shortest path between two ecological sources by determining the resistance values of different land cover types. These resistance values were assigned according to previous studies (Zhang et al., 2017): i.e. woodland, 1; grassland, 10; farmland, 30; unused land, 300; water area, 50; and built-up area, 500. i=m
MCR = fmin
Dij × Ri j=n
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Fig. 3. Analysis of ecological criteria. The numbers in the legend refers to the assigned value (see Table 2).
3.3. Demand for ecosystem services
mountainous area and the permanent farmland in the east, with a high demand for ecological services and a fine demand for cultural services. These areas are sightseeing and recreational green spaces. For example, some permanent farmland functions as a country park or urban agriculture garden. Second, as green islands in a city, public parks are often considered to have high ecological services demand as well as high cultural services demand. Most public parks are coincident with this hypothesis; however, three parks (Guanyuan Park, Ditan Park, and
In comparing Figs. 4 and 6, we can see that for the same patch of green space, there are trade-offs and synergies in the demand for ecological services and the demand of cultural services. First, mountains and farmlands located in suburbs are usually believed to have a high demand for ecological services, but low demand for cultural services. However, the exceptions in this case are distributed in the western
Fig. 4. The multi-criteria results of the demand for ecological services. 6
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Fig. 5. Indicators of cultural services: a) accessibility, b) population density, c) use frequency of green space, d) cultural heritage.
Fig. 6. The mapping of demand for cultural services based on multi-criteria.
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Fig. 7. Assessment of the demand for ecosystem services using multi-criteria. “0″ represents built up areas.
Tiantan Park) show a high demand for cultural services, but relatively low demand for ecological services. Fig. 7 shows the synthesized results for services demand and cultural services demand. We divided the demand into high-, middle-, and low-demand areas according to their value and further calculated the area of each category (Table 4). The Summer Palace and Olympic Forest Park are the largest areas with high ES demand. Surprisingly, some small green spaces also have high demand for ES, although they are located in densely built-up areas; e.g. some green spaces in Beihai Park, Yuyuantan Park, and Chaoyang Park, as well as some permanent farmlands in the east. In other words, the level of demand for ES is uncorrelated with the location, size, and type of green spaces. Areas with high demand for ES can be regarded as a baseline pattern for green spaces. These areas occupy 1,630.52 hm2 of Beijing, comprising 1.50% of the total area of the central city (Table 4). These areas mainly include the Western Mountain, Summer Palace, Olympic Forest Park, Dongba Country Park, and some small patches on the southeastern edge of Beijing. The areas with high demand for ES are the most important green spaces for ecological-cultural services. The areas with medium demand for ES are distributed evenly, with an area of 20,454.07 hm2 comprising 18.78% of the total urban area. The areas with low demand for ES, with an area of 40,678.02 hm2 comprises 37.34% of the total urban area.
corridors calculated with least-cost path are not always to be green spaces (Table 4). Small green spaces located on corridors can be important as stepping stones, which contribute to the overall landscape connectivity. 4. Discussion 4.1. Multi-criteria assessment of demand for ecosystem services Mapping of the demand for ES from multiple aspects provides various insights (Villamagna et al., 2013). Several studies have argued that assessments regarding ES should include multiple drivers (Daily et al., 2000; Fisher et al., 2009; Maes et al., 2012), therefore, a multi-criteria approach is needed for a more explicit, detailed, and comprehensive assessment of demand for ES. Ecological services and cultural services are inextricably correlated, and their combination and comparison can benefit our understanding of urban ecosystems. The necessity for applying multi-criteria was verified by different assessment results for the demand for ecocultural services. First, compared with other studies that compare the supply and demand of ES (Castro et al., 2014), we carried out explicit spatial comparisons between ecological and cultural demand for ES. For ecological services, places with high demands are mainly distributed in suburban areas. In contrast, for cultural services, places with high demand are mainly located in densely urbanized areas. Second, with regard to the size of green spaces, our findings showed that large green spaces located in suburban or city margins tend to have a higher demand for ecological services than small patches of green spaces in densely built-up areas are coincident with previous studies (Kong et al., 2007; Kong et al., 2010; Zhou et al., 2014; Guo et al., 2018). Actually, higher demand for ecological services isn’t always located in suburban areas, it depends on the
3.4. Application of mapping the demand for ES on optimizing green spaces The ecological security pattern of the landscape (Fig. 8) comprised ecosystem-critical cores and corridors. The ecological cores are mainly distributed in suburban areas, and the cultural cores are mainly located in the center of the city. This pattern can be regarded as an ideal landscape pattern for central Beijing, but the current land covers of the Table 4 Different levels of demand for ecosystem services. Green spatial pattern level
Ideal pattern area of green space (hm2)
Other land area (hm2)
Proportion of ideal pattern area of green space
High (value = 9) Medium (5 ≤ value < 9) Low (1 ≤ value < 5)
1630.52 20454.07 40678.02
107299.48 88475.93 68251.98
1.50% 18.78% 37.34%
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Fig. 8. The cores and potential corridors in the ecological security pattern.
demand for ecological services to achieve more precise results.
ES type included in the assessment. For example, Baró et al. (2016) measured the demand for air purification in Barcelona, and it turned out to be higher in urbanized areas. However, the availability of related data on various ES can limited the mapping of ES demand/ supply (Seppelt et al., 2012). Third, according to the synthesized mapping of ecological and cultural services, the demand for ES of small green spaces in highly urbanized areas can be higher than that for large green spaces (e.g. forestry lands on mountains) in suburban areas. These small green spaces are not only crucial for recreation of human, but also important in risk reduction such as erosion prevention and microclimate regulation. In a sum, the demand for ES in a green space is uncorrelated with its location, size, and type.
4.3. Ecological security pattern and suggestions As showed in Fig. 8, we made the integration of ES demand into landscape assessment. Prior studies (Kong et al., 2010; Zhou et al., 2014; Su et al., 2016) used various approaches to identify cores and corridors, but all of them emphasize spatial connectivity or geological/ ecological sensitivity instead of the demand for ES. We selected the cores and corridors of ecological security patterns in the landscape in terms of areas with high demand for ecological-cultural services. The ecological security patterns offer a useful reference for landscape planning and land-use management. First, considering that some small green spaces in urbanized areas have not only high cultural services demand but also ecological services demand, a good way to improve public parks’ ecological services is to extract some specialized green spaces from the parks for biodiversity conservation. These small green spaces can become stepping stones for species migration. Second, suburban green spaces, such as mountains and permanent basic farmland, have huge potential cultural value. Using the example of country parks in the study area, proper development by ensuring an ecological environment can increase visitors to the surrounding green spaces. Third, river systems, mountains, and parks in urbanized areas should be well protected considering their ecological security.
4.2. Consumption and direct use of cultural services The demands for cultural services were intangible and varied from region to region because of different social characteristics, which makes demand challenging to assess (Daniel et al., 2012). Although PPGIS has been applied on assessing preferences and desires of the public, especially on the cultural and spiritual values of ecosystems (Brown et al., 2012, Brown, 2013, Brown and Kyttä, 2014); as Burkhard et al. (2012) mentioned, studies on demand for ES should not only consider the potential of green spaces to provide ES (e.g. population density and accessibility of green spaces), but also the current consumption/use of ES. Considering that empirical data about the consumption of cultural services is relatively difficult to obtain, we proposed a new approach using the big data on the use frequency of green spaces as empirical data, which is based on the check-in data from social networks. This new indicator helps to broaden the concept of the demand for ES, and it is much more efficient than direct observations. On the premise of available data, the indicator of use frequency can be easily applied to other study areas. From the aspect of the consumption of ecological services, a few studies have analyzed ecological consumption. For example, Burkhard et al. (2012) and Kroll et al. (2012) assessed energy consumption to clarify the demand for ES, while Change et al. (2013) assessed the water demand using water consumption data, including public, municipal irrigation, and industrial water use. In future research, additional information on ES consumption should be included in mapping the
4.4. Methodological limitations Although this model is flexible and useful, methodology limitations still exist. In large-scale cases with less-detailed data, the expert-based weighting method was assumed to be more appropriate (Wolff et al., 2015), but was still subjective. If more empirical data are collected as part of the database, the weighting method may be validated, and assessment results may be more accurate and convincing. For example, Paracchini et al. (2014) assigned weights after conducting surveys to collect information on people’s preferences for recreation. Unfortunately, we did not obtain information on preferences, health, and security considering demand for cultural services. In the future work, more factors and participants should be involved in weighting identification. 9
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5. Conclusion
Brown, G., Fagerholm, N., 2015. Empirical PPGIS/PGIS mapping of ecosystem services: a review and evaluation. Ecosyst. Serv. 13, 119–133. Brown, G., Kyttä, M., 2014. Key issues and research priorities for public participation GIS (PPGIS): a synthesis based on empirical research. Appl. Geogr. 46, 122–136. Burkhard, B., Kroll, F., Nedkov, S., Müller, F., 2012. Mapping ecosystem service supply, demand and budgets. Ecol. Indic. 21, 17–29. Casado-Arzuaga, I., Madariaga, I., Onaindia, M., 2013. Perception, demand and user contribution to ecosystem services in the Bilbao Metropolitan Greenbelt. J. Environ. Manage. 129, 33–43. Castro, A.J., Verburg, P.H., Martín-López, B., Garcia-Llorente, M., Cabello, J., Vaughn, C.C., López, E., 2014. Ecosystem service trade-offs from supply to social demand: a landscape-scale spatial analysis. Landscape Urban Plann. 132, 102–110. Chang, H., Jung, I.W., Strecker, A., Wise, D., Lafrenz, M., Shandas, V., Johnson, G., 2013. Water supply, demand, and quality indicators for assessing the spatial distribution of water resource vulnerability in the Columbia River Basin. Atmos. Ocean 51 (4), 339–356. Chee, Y.E., 2004. An ecological perspective on the valuation of ecosystem services. Biol. Conserv. 120 (4), 549–565. Chen, J., Yang, S., Li, H., Zhang, B., Lv, J., 2013. Research on geographical environment unit division based on the method of natural breaks (Jenks). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-4 (W3), 47. Costanza, R., d'Arge, R., De Groot, R., Farber, S., Grasso, M., Hannon, B., Raskin, R.G., 1997. The value of the world's ecosystem services and natural capital. Nature 387 (6630), 253. Crossman, N.D., Burkhard, B., Nedkov, S., Willemen, L., Petz, K., Palomo, I., Alkemade, R., 2013. A blueprint for mapping and modelling ecosystem services. Ecosyst. Serv. 4, 4–14. Daily, G.C., Matson, P.A., 2008. Ecosystem services: from theory to implementation. Proc. Natl. Acad. Sci. 105 (28), 9455–9456. Daily, G.C., Söderqvist, T., Aniyar, S., Arrow, K., Dasgupta, P., Ehrlich, P.R., Levin, S., 2000. The value of nature and the nature of value. Science 289 (5478), 395–396. Daniel, T.C., Muhar, A., Arnberger, A., et al., 2012. Contributions of cultural services to the ecosystem services agenda. Proc. Natl. Acad. Sci. U.S.A 109 (23), 8812–8819. De Groot, R.S., Wilson, M.A., Boumans, R.M., 2002. A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol. Econ. 41 (3), 393–408. Fisher, B., Turner, R.K., Morling, P., 2009. Defining and classifying ecosystem services for decision making. Ecol. Econ. 68 (3), 643–653. Forman, R.T., 2014. Land Mosaics: The ecology of landscapes and regions (1995) (p. 217). Island Press. ISBN:978-1-61091-491-8. Guo, S., Saito, K., Yin, W., Su, C., 2018. Landscape connectivity as a tool in green space evaluation and optimization of the haidan district, beijing. Sustainability 10 (6), 1979. Guo, G., Wu, Z., Xiao, R., Chen, Y., Liu, X., Zhang, X., 2015. Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landscape Urban Plann. 135, 1–10. Hernández-Morcillo, M., Plieninger, T., Bieling, C., 2013. An empirical review of cultural ecosystem service indicators. Ecol. Ind. 29, 434–444. Howarth, R.B., Farber, S., 2002. Accounting for the value of ecosystem services. Ecol. Econ. 41 (3), 421–429. Jacobs, S., Burkhard, B., Van Daele, T., Staes, J., Schneiders, A., 2015. ‘The Matrix Reloaded’: a review of expert knowledge use for mapping ecosystem services. Ecol. Model. 295, 21–30. Kong, F., Yin, H., Nakagoshi, N., 2007. Using GIS and landscape metrics in the hedonic price modeling of the amenity value of urban green space: A case study in Jinan City, China. Landscape Urban Plann. 79 (3–4), 240–252. Kong, F., Yin, H., Nakagoshi, N., Zong, Y., 2010. Urban green space network development for biodiversity conservation: identification based on graph theory and gravity modeling. Landscape Urban Plann. 95 (1–2), 16–27. Kroll, F., Müller, F., Haase, D., Fohrer, N., 2012. Rural–urban gradient analysis of ecosystem services supply and demand dynamics. Land Use Policy 29 (3), 521–535. Li, F., Zhang, F., Li, X., Wang, P., Liang, J., Mei, Y., Qian, Y., 2017. Spatiotemporal patterns of the use of urban green spaces and external factors contributing to their use in central Beijing. Int. J. Environ. Res. Public Health 14 (3), 237. Maes, J., Egoh, B., Willemen, L., Liquete, C., Vihervaara, P., Schägner, J.P., Bouraoui, F., 2012. Mapping ecosystem services for policy support and decision making in the European Union. Ecosyst. Serv. 1 (1), 31–39. Meerow, S., Newell, J.P., 2016. Spatial planning for multifunctional green infrastructure: growing resilience in Detroit. Landscape Urban Plann. 159, 62–75. Miao, S., Chen, F., LeMone, M.A., Tewari, M., Li, Q., Wang, Y., 2009. An observational and modeling study of characteristics of urban heat island and boundary layer structures in Beijing. J. Appl. Meteorol. Climatol. 48 (3), 484–501. Millennium Ecosystem Assessment. (2005). Ecosystems and human well-being (Vol. 5). Washington, DC: Island Press. Nedkov, S., Burkhard, B., 2012. Flood regulating ecosystem services—Mapping supply and demand, in the Etropole municipality, Bulgaria. Ecol. Ind. 21, 67–79. Orenstein, D.E., Groner, E., 2014. In the eye of the stakeholder: changes in perceptions of ecosystem services across an international border. Ecosyst. Serv. 8, 185–196. Paracchini, M.L., Zulian, G., Kopperoinen, L., Maes, J., Schägner, J.P., Termansen, M., Bidoglio, G., 2014. Mapping cultural ecosystem services: a framework to assess the potential for outdoor recreation across the EU. Ecol. Ind. 45, 371–385. Peng, J., Liu, Y., Wu, J., Lv, H., Hu, X., 2015. Linking ecosystem services and landscape patterns to assess urban ecosystem health: a case study in shenzhen city, china. Landscape Urban Plann. 143, 56–68. Plieninger, T., Dijks, S., Oteros-Rozas, E., Bieling, C., 2013. Assessing, mapping, and
A multi-criteria approach is needed for urbanized areas, where relationships among various ecosystems services are complex. In this study, we proposed a multi-criteria approach integrating ecological and cultural services demand to obtain a more comprehensive assessment of the demand for ES. Particularly, we innovatively introduced check-in data from WeChat to identify the consumption of cultural services, which is seldom used in existing research. The results show that large natural elements in urban regions, such as mountainous area, parks, and water bodies, tend to have higher demand for ES. However, some small green spaces located in densely built-up areas have a higher demand for ES than that of large green spaces. The consumption of cultural services is closely related to the distribution of green space and the composition of surrounding residents. Therefore, more details of the utilization of green space can be included in the future to obtain a better understanding of the consumption of cultural services. Besides, the study framework is repeatable and can be applied to any other study areas if suitable indicators and weights are adopted. Additional criteria are allowed if necessary, and the weight of every single criterion can be altered according to the study areas. CRediT authorship contribution statement Fangzheng Li: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Supervision, Funding acquisition, Project administration, Writing original draft, Writing - review & editing. Shiyi Guo: Conceptualization, Methodology, Visualization, Formal analysis, Writing - review & editing. Di Li: Writing - review & editing. Xiong Li: Funding acquisition, Supervision, Project administration, Writing - review & editing. Jing Li: Methodology, Software, Resources, Data curation, Visualization. Shuang Xie: Visualization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No. 51908036, 31670704), Beijing Natural Science Foundation (Grant NO. 8194071); Humanities and social sciences fund of the Ministry of Education (NO. 19YJC760042); China Postdoctoral Science Foundation (NO. 2018M641222);the Fundamental Research Funds for the Central Universities (NO. BLX201808), Research and Development Plan of Beijing Municipal Science and Technology Commission (Grant No.D17110900710000). We thank Daniel Schmidt, PhD, and Peter Fogarty, MA, from Liwen Bianji, Edanz Editing China (www.liwenbianji.cn/ac), for editing the English text of drafts of this manuscript. References Adger, W.N., 2000. Social and ecological resilience: are they related? Prog. Hum. Geogr. 24 (3), 347–364. Ala-Hulkko, T., Kotavaara, O., Alahuhta, J., Helle, P., Hjort, J., 2016. Introducing accessibility analysis in mapping cultural ecosystem services. Ecol. Ind. 66, 416–427. Baró, F., Palomo, I., Zulian, G., Vizcaino, P., Haase, D., Gómez-Baggethun, E., 2016. Mapping ecosystem service capacity, flow and demand for landscape and urban planning: a case study in the Barcelona metropolitan region. Land Use Policy 57, 405–417. Bennett, E.M., Peterson, G.D., Gordon, L.J., 2010. Understanding relationships among multiple ecosystem services. Ecol. Lett. 12 (12), 1394–1404. Brown, G., 2013. The relationship between social values for ecosystem services and global land cover: an empirical analysis. Ecosyst. Serv. 5, 58–68.
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F. Li, et al. quantifying cultural ecosystem services at community level. Land Use Policy 33, 118–129. Rodrigue, J.P., Comtois, C., Slack, B., 2016. The Geography of Transport Systems. Routledge. Schirpke, U., Scolozzi, R., Marco, C.D., Tappeiner, U., 2014. Mapping beneficiaries of ecosystem services flows from natura 2000 sites. Ecosyst. Serv. 9, 170–179. Schröter, M., Barton, D.N., Remme, R.P., Hein, L., 2014. Accounting for capacity and flow of ecosystem services: a conceptual model and a case study for Telemark, Norway. Ecol. Ind. 36, 539–551. Seppelt, R., Fath, B., Burkhard, B., Fisher, J.L., Grêt-Regamey, A., Lautenbach, S., Van Oudenhoven, A.P., 2012. Form follows function? Proposing a blueprint for ecosystem service assessments based on reviews and case studies. Ecol. Ind. 21, 145–154. Su, Y., Chen, X., Liao, J., Zhang, H., Wang, C., Ye, Y., Wang, Y., 2016. Modeling the optimal ecological security pattern for guiding the urban constructed land expansions. Urban For. Urban Greening 19, 35–46. Sun, Y., Zhuang, G., Tang, A., Wang, Y., An, Z., 2006. Chemical characteristics of PM2. 5 and PM10 in haze− fog episodes in Beijing. Environ. Sci. Technol. 40 (10), 3148–3155. Syrbe, R.U., Walz, U., 2012. Spatial indicators for the assessment of ecosystem services: providing, benefiting and connecting areas and landscape metrics. Ecol. Ind. 21, 80–88.
Villamagna, A.M., Angermeier, P.L., Bennett, E.M., 2013. Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery. Ecol. Complexity 15, 114–121. Villamagna, A.M., Mogollón, B., Angermeier, P.L., 2014. A multi-indicator framework for mapping cultural ecosystem services: the case of freshwater recreational fishing. Ecol. Ind. 45, 255–265. Wang, G., Zhang, R., Gomez, M.E., Yang, L., Zamora, M.L., Hu, M., Li, J., 2016. Persistent sulfate formation from London Fog to Chinese haze. Proc. Natl. Acad. Sci. 113 (48), 13630–13635. Wolff, S., Schulp, C.J.E., Verburg, P.H., 2015. Mapping ecosystem services demand: A review of current research and future perspectives. Ecol. Indic. 55, 159–171. Yu, K., 1996. Security patterns and surface model in landscape ecological planning. Landscape Urban Plann. 36 (1), 1–17. Zhang, L., Peng, J., Liu, Y., Wu, J., 2017. Coupling ecosystem services supply and human ecological demand to identify landscape ecological security pattern: a case study in Beijing–Tianjin–Hebei region, China. Urban Ecosyst. 20 (3), 701–714. Zhou, K., Liu, Y., Tan, R., Song, Y., 2014. Urban dynamics, landscape ecological security, and policy implications: a case study from the Wuhan area of central China. Cities 41, 141–153. Zulian, G., Stange, E., Woods, H., et al., 2018. Practical application of spatial ecosystem service models to aid decision support. Ecosyst. Serv. 29, 465–480.
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