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Research on the influence of site factors on the expansion of construction land in the Pearl River Delta, China: By using GIS and remote sensing
International Journal of Applied Earth Observation and Geoinformation 21 (2013) 366–373
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Research on the influence of site factors on the expansion of construction land in the Pearl River Delta, China: By using GIS and remote sensing Yuyao Ye ∗ , Hongou Zhang, Kai Liu, Qitao Wu Guangzhou Institution of Geography, Guangzhou, China
a r t i c l e
i n f o
Article history: Received 27 December 2010 Accepted 22 October 2011 Keywords: Site factor Construction land The Pearl River Delta, China GIS Remote sensing TM
a b s t r a c t Landsat TM images of the Pearl River Delta taken in 1988, 1998 and 2006 are used to explore the site factors that influence the construction land expansion in this study. Several site factors, including landscape types and the distances to roads, coastlines, or city centers, had significant impacts on the expansion of construction land, influencing the direction, scale and intensity of the expansion. The site factors serve as important natural and spatial indicators of the preferable locales for construction land expansion, describing tendencies to expand to locations in suburbs, plains and areas near roads or coastlines. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Land use and land cover change (hereafter referred to as LUCC) is one of the most important components of current global environmental change and has been a focus of much global change researches (Tuner and Meyer, 1994; Seto and Shepherd, 2009). A general global trend of LUCC has been the expansion of construction land, including land for urban/rural settlements, industry and transportation (e.g., Hart, 1976; Alig and Healy, 1987; Lambin, 1997; Sorensen, 2000; López et al., 2001b; Müller and Zeller, 2002; Adrián and Peter, 2003; Murakami et al., 2005; Tan et al., 2005; Tian et al., 2005; Xiao et al., 2006; Hu et al., 2007; Long et al., 2007; Adrián, 2008; Gong et al., 2009). The resulting conversion of arable land has attracted widespread attention and has been the subjects of numerous studies (Yeh and Li, 1999; Walker, 2001). Researchers typically attribute the dynamics of land use change to five major forces: political, economic, cultural, technological, and natural/spatial ones (e.g., Lambin et al., 2001; Bürgi and Turner, 2002; Lambin et al., 2003; Bürgi et al., 2004; Schneeberger et al., 2007; Hersperger and Matthias, 2009). The natural/spatial factors mainly include site factors, such as landscape types, adjoining land use patterns and distance to roads or city centers (discussed in detail in this paper), and non-site factors, such as soil quality and potential for natural disturbances (i.e., climate changes and disasters). Although these factors play important roles in LUCC, they
∗ Corresponding author. Tel.: +86 20 37656557; fax: +86 20 87685006. E-mail address: [email protected] (Y. Ye). 0303-2434/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jag.2011.10.012
have not received much attention (Bruijn, 1994). Previous research generally, focused on the political, economic, cultural and technological factors, and emphasized the influence of human activities on LUCC (e.g., Haberl et al., 2003; Zhang et al., 2003; Tan et al., 2005; Xie et al., 2005; Quan et al., 2006; Yan et al., 2006; Liu et al., 2008). Fortunately, others have also noted the impact of site factors, especially road networks on LUCC (Patarasuk and Binford, 2011). A common phenomena has been found as that rapid urban growth and conversion of agricultural land to built-up areas preferred to occur closer to road networks in as disparate locations as the Kansas City Metropolitan area in the central USA (Underhill, 2004), Puerto Rico (López et al., 2001a), Indian city (Fazal, 2001) and the urban expansion of Beijing (Zhang et al., 2002). Roads influence regional land cover because they enhance accesses to land for human activities. In this study, we presume that accessibility and distance emerge as important determinants of location for many land uses. We hypothesize site factors, including not only road networks but also landscape type and the distance to the city centers or the coastline, have significant influences on construction land expansion, for their direct relationship with accessibility. The object of this study is to examine the hypothesis and how it works. The Pearl River Delta (PRD) is the most important and representative urbanized regions in China and has been witnessing a dramatic land-cover change in the past 30 years. It’s been developed rapidly, following the reformation of economy and open policy in China since 1978. Began in the late 1980s, the land-use reforming in Shenzhen has leaded to a “property boom” since the real estate market opened in the region in the early 1990s. Investments to real estate have grown not only in Shenzhen, Guangzhou
Y. Ye et al. / International Journal of Applied Earth Observation and Geoinformation 21 (2013) 366–373
and Huizhou but the entire PRD region. In addition, the rapid development of industrial and real estate zones – the main targets of construction land expansion at the time – led to large-scale encroachment of farmland, due primarily to land speculation. Land was priced cheaply, so speculators often purchased then hoarded large tracts of land, resulting in widespread areas of lower-density plants and buildings and large-scale destruction of farmland (Li, 2004). Since 1998, economic growth in the PRD had slowed. The national government introduced several new policies for price regulation, land exploitation and foreign investment. These policies brought subsequent economic adjustment throughout the entire region. The slowdown of economic growth and the introduction of more rigorous national policies protecting cultivated land somewhat slowed the speed of expansion of construction land, but the speed remained difficult to control. Currently, throughout the region, construction land covers near 20% of the land on average and up to 40% in cities like Dongguan and Shenzhen (Guangdong Province State Land and Resources Department, 2007). As a result, the scale of arable land in the region has declined dramatically. According to the official statistics, the total area of cultivated land in the PRD was 8460.99 km2 in 1996; decreased to 5899.55 km2 by the end of 2007, with a decline of 30.27% with 12 years (Guangdong Province State Land and Resources Department, 2007). It has revealed a rapid spread of construction land encroached upon farmland, destroyed natural habitat, and diminished biodiversity. It’s been a serious challenge for the PRD and served as a model of what can be expected for land use changes in rapidly developing regions of China. Remote sensing provides spatially consistent datasets that cover large areas of land with both high spatial resolution and high temporal frequency. It has been described as a “unique view” of the spatial and temporal dynamics of the processes during land use change (Herold et al., 2003). Satellite remote sensing techniques have been widely used to detect and monitor land cover changes at various scales (e.g., Lucas et al., 1989; Li and Yeh, 1998; Stefanov et al., 2001; Wilson et al., 2003; Seto and Kaufmann, 2003). Recently, remote sensing has been used in combination with Geographical Information Systems (GIS) and Global Positioning Systems (GPS) to provide more comprehensive assessments of land cover change than using itself alone (Sui and Zeng, 2001; Weng, 2002; Li and Yeh, 2004). In this study, we made an exploration on the influence of the site factors on construction land expansion in the PRD by using GIS and remote sensing. Firstly, Landsat Thematic Mapper (TM) images from 1988, 1998, and 2006 were employed to detect the expansion of construction land in the PRD. Subsequently, spatial analysis capabilities of GIS were used to quantify the influences of various site factors on the expansion, focusing on the regional landscape and the distances to city centers, roads or coastlines. The objectives of the study are as follows: (1) to explore the temporal and spatial characteristics of PRD construction land expansion over the last 20 years; (2) to detect and evaluate the influences of site factors and the interactions between them; and (3) to identify the internal drivers of the expansion and derive advices for decision-makers.
2. Study area Located on the southern coast of mainland China (112◦ –115.5◦ E, 21.5◦ –24◦ N, see Fig. 1), PRD is the largest alluvial plain in the subtropical monsoon climate zone of continental China and is adjacent to the South China Sea from the north. The region is surrounded by mountains to the east, west and north with widespread plateaus. Located in the subtropical monsoon climate zone, the region is warm and humid with long summers and short winters, proved as suitable for the growth of a variety of types of crops.
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Table 1 Landsat TM images used in this paper. Number
Orbit number
Imaging day
Imaging day
Imaging day
1 2 3 4 5
121-044 121-045 122-044 122-045 123-044
1988-12-14 1988-12-10 1988-07-30 1988-07-30 1988-12-17
1998-12-26 1998-08-25 1998-12-22 1998-12-22 1998-12-29
2006-12-05 2006-12-21 2006-12-28 2006-11-10 2006-12-19
Ranging a total area of 40,041 km2 with a population of 40.80 million people (Guangdong Province Office, 2009), the PRD covers nine municipalities in the Guangdong province: Dongguan, Foshan, Guangzhou, Huizhou, Shenzhen, Zhongshan, Zhuhai and part of Jiangmen, Zhaoqing. Since the establishment of Chinese Opening Policies in 1978, it has been rapidly transforming from an agricultural area to one of the most important urban industrial regions of China. In 2008, the gross domestic product (GDP) in the PRD reached 434.28 billion U.S. dollars, over 10% of the Chinese total and more than 80% of the Guangdong province GDP (Guangdong Statistical Yearbook, 2009). The rapid industrialization and urbanization of the PRD has brought with it dramatic land cover change. 3. Data and methods 3.1. Data sources The land-use data were derived from historical Landsat TM images with spatial resolution of 30 m × 30 m. Five Landsat scenes were needed to cover the entire study area and each was obtained from versions of 1988, 1998 and 2006 (a total of fifteen Landsat scenes). For the monsoonal climate in the region, it’s difficult to obtain simultaneous cloud-free images for any five PRD scenes within a year. Therefore, for each year, multiple images were collected at different times within a six-month interval. Table 1 shows the orbit number and imaging time for the Landsat TM images used in this study. The specific images were all selected because they were available and cloud-free. 3.2. Data processing The first stage of data processing involved applying a geometrical image correction and a geo-reference correction. The latter correction consisted of two steps: (1) a topographic correction based on a topographic map and field survey points that were used to correct the 2006 images; and (2) an image-to-image registration based on the 2006 image that was used to ensure all images had the same projection. We subsequently derived land cover maps from the TM images using the artificial visual interpretation method (AVIM), which has proven to be one of the most effective methods for TM image interpretation because it takes full advantage of the experience and knowledge of the image interpreters (Zhu and Zhang, 2002). In this study, we use ERDAS IMAGINE 9.1, a software program developed by ERDAS, to process the remote sensing images. To interpret the images, we use ArcGIS9.1, developed by Environment System Research Institute (ESRI). Fig. 2 shows the results, which reflect the expansion of construction land. Finally, we made 1000 sample points (patches) for each year, some derived from higher spatial resolution remote sensing images (acquired for 1988, 1998) and others from field survey (acquired for 2006), to test the classification results: 500 each for construction land and farmland. The Kappa coefficient and overall accuracy were used to quantify the classification precision of the images. The overall accuracies were 91.1% (1988), 93.4% (1998), and 94.7% (2006), and the Kappa coefficients were 0.889 (1988), 0.917 (1998) and
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Fig. 1. Location of the study area.
0.926 (2006). Accuracies near 100% and Kappa coefficients near 1 indicate precise classification by the AVIM (see Table 2). 3.3. Study methods To understand the impacts of site factors on the expansion of construction land, we overlaid maps of construction land with topographic maps. Then, patterns of construction land expansion in the buffer zones around urban centers and along major roads, coastlines, and other geographic features were analyzed.
Table 2 Classification accuracy for the three periods. CLF 1988 CLM FLM 1998 CLM FLM 2006 CLM FLM
FLF
Overall accuracy (%)
Kappa coefficient
0.889
448 37
52 463
91.1
465 31
35 469
93.4
0.917
475 28
25 472
94.7
0.926
The effects were quantified with indices those reflect the degree of construction land expansion in each buffer zone. Namely (1) the construction land expansion rate (UL1 ); (2) the structure coefficient (UL2 ), which represents the change in the fraction of land used for construction purposes; (3) the scale coefficient (UL3 ), which represents the ratio of construction land expansion in a given region to that in the entire study area; (4) the expansion intensity (UL4 ), which represents the ratio of construction land expansion in a given region to the region’s total land area; (5) a composite called the comprehensive expansion index (ULc ), which is composed of the latter four indices; and (6) the construction land density (Du ). The indices are defined as follows: ULc =
ULi
(i = 1, 2, 3, 4);
i=1
UL1 =
Note: CLM – construction land on maps; CLF – construction land in the field; FLM – farmland on maps; FLF – farmland in the field.
4
t
UL2 = Pt − P0 ; UL3 =
St −1 S0
St − S0 ; At − A0
× 100;
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Fig. 2. Expansion of construction land in the Pearl River Delta.
UL4 =
Du =
St − S0 ; H×t
S × 100 H
where Pt and P0 are the ratios of construction land in a given target region to total land area in the region at times t and 0; St and S0 are the areas of construction land in the target region at times t and 0; t is the number of years over which the changes are calculated; At and A0 are the areas of construction land in the entire study area at times t and 0; and H is the total land area in the study region. The computations were preformed for each target region, i.e., the buffer zones described earlier. 4. Results 4.1. The processes and characteristics of construction land expansion in PRD 4.1.1. From 1988 to 1998 Throughout this period, the region witnessed vigorous expansion of construction land. The area occupied by construction land increased to 4345.70 km2 in 1998, nearly 1.5 times its size in 1988. In 1998, UL1 , UL2 , and UL4 were 9.43%, 6.44%, 6.44‰, respectively, and Du increased from 4.41% to 10.85%. The eastern coastal region of the PRD revealed the most prominent construction expansion, especially around the GuangzhouShenzhen Railway and the Guangzhou-Shenzhen section of National Highway 107, forming the main axis of the expansion. The so-called “road economy,” accompanied by the spread of construction land along major roads, was prevalent in the PRD during
this period, resulting in a waste of land resources. In Dongguan, for example, the length of arterial roads had increased to 150 km by 1992. These roads were associated with construction land expansion, which led to the development of a landscape known as the “100-kilometer-long Street,” reflecting the abnormal growth and exploitation along the roads. 4.1.2. From 1998 to 2006 In this period, a decrease in the rate of construction land expansion in the region was accompanied by the slowdown of economic growth and the introduction of more rigorous national policies protecting cultivated land; nonetheless, the intensity of expansion remained high. In 2006, the total area occupied by construction land reached 6816.04 km2 , nearly 1.5 times its area in 1998. By 2006, UL1 , UL2 , UL4 and Du were 5.79%, 6.17%, 7.71‰ and 17.02%, respectively. In some cities, such as Shenzhen and Dongguan, Du reached values of up to 40%. Urban sprawl and overlapping regions of development characterized the entire region. This pattern was particularly evident in the eastern coastal region, where a highdensity urban corridor developed, linking the cities of Guangzhou, Shengzhen, Dongguan, and Huizhou (see Fig. 2). 4.2. Influence of site factors on the expansion of construction land 4.2.1. Influence of the distance to the city center We used development in Guangzhou as a case study to examine the impacts of distance to the city center on the expansion of construction land. We performed a radiation buffer analysis centered on the Guangzhou city center, which is defined as the location of the municipal government. 24 circular radiation zones were defined, with the innermost zone extending 5 km from the city center and all subsequent zones extending 5 km from the previous zone.
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2-km-wide buffer zones. We then overlaid the buffer zones on the maps of construction land for the three periods and analyzed the patterns of expansion within the zones (see Fig. 4). The results of this analysis (Table 3) show that construction land along the roads increased by 1552.96 km2 between 1988 and 1998. During this period, UL1 , UL3 , and UL4 were 9.95%, 60.18%, and 13.32‰, respectively, indicating that construction land tended to spread along major roads. The so-called “road economy” was prevalent during this period, leading to extensive construction along the main roads. From 1988 to 2006, UL1 , UL3 and UL4 decreased to 4.82%, 46.98% and 12.44‰, respectively. Nevertheless, construction along the roads was still evident in 2006, with Du at 31.69% inside the zones, twice the average for the region. The distance to a major road thus has a marked impact on the expansion of construction land. Locations near roads are often preferred for construction due to their accessibility and the associated low costs of transporting materials. The result is a “webbed” pattern of construction that sprawls along the main roads. This pattern is especially evident in the high-density urban corridors that have formed along the Guangzhou-Shenzhen section of 107 National Road, the Guangzhou-Zhuhai section of 105 National Road, and the Guangzhou-Shenzhen Railway.
Fig. 3. Relationship between the expansion of construction land and the distance to the city center.
Differences in the construction land expansion between the 24 radiation zones were overlaid on the construction land distributions for each of the three analysis periods. Fig. 3 shows the resulting impacts of distance to the city center on changes in Du and ULc . Fig. 3a shows that Du decreased with increasing distance to the city center for all three years included in the analysis. The changes in ULc from the city center to the periphery were more complex, as shown in Fig. 3b. During the 1988–1998 period, ULc peaked in the third zone at a distance of 10–15 miles from the city center. This region was a suburb of Guangzhou at the time, and the ULc maximum here indicates rapid development of the suburb with construction spilling outwards from the city center. ULc also showed a secondary peak in the sixth zone, at 25–30 miles from the city center, due to the development of industrial zones and the construction of satellite cities in the outer suburbs. In the 1998–2006, ULc had a broad peak that extended from the fourth zone to the eighth zone. The peak construction in this period occurred farther from the city center than in the previous period, suggesting that the city boundary had expanded outward as land in the central part of the city was used up. During this period, the development of construction land slowed significantly. Most construction occurred 15–40 km from the city center, indicating expansion of the city center and peripheral satellite cities as well as development between them. Distance to the city center thus has a clear impact on the expansion of construction land. Initially, construction tends to occur in two locations, the nearby suburbs and the outer suburbs. Later, construction moves to the area between the suburbs, resulting in a land-use distribution characterized by a decline in construction land from the city center to the periphery. 4.2.2. Influence of the distance to major roads We also examined buffer zones along major national and provincial-level roads in the study area. The zones were defined to extend 1 km from the centerline of each road, resulting in
4.2.3. Influence of distance to the coastlines To test the influence of distance to the coastline on the expansion of construction land, we defined a buffer zone that extended 10 km to the coastline, which had previously been smoothed. We then overlaid it on the construction land distribution for the three periods and analyzed the pattern of the expansion within the buffer zone (see Fig. 5). The results (Table 3) show that from 1988 to 1996, UL1 , UL2 and UL4 were 20.20%, 15.94%, and 15.94‰, respectively. UL3 was 43.6%, indicating that nearly half of the new construction in the PRD was concentrated in the 10-km zone along the coastline. From 1998 to 2006, the expansion of construction land within this zone slowed somewhat, with decreases in UL1 , UL2 , UL3 and UL4 . Nonetheless, new construction land within the zone still made up 16.39% of the total regional construction land during this period. After the near-shore construction peaked in the previous period, coastal development encountered a number of bottlenecks, including land scarcity and constraints of co-environmental capacity. These difficulties caused the expansion of construction land along the coast to slow, although the tendency to concentrate construction along the coastline remained unchanged. Distance to the coastline thus has an obvious impact on the expansion of construction land. The PRD region is characterized by an export-driven economy and limited resources. As a result, the availability of industrial raw materials and sale of manufacturing products are highly dependent on marine transportation and international markets. Since 1978, the coastal region has gradually become a development hot spot. Shenzhen, for example, has rapidly developed from a small fishing village to an international metropolis. Reliant on major ports, many new portside cities and industrial bases have boomed, forming an industrial band along the coast. 4.2.4. Influence of the landscape We used GIS spatial technology to analyze the relationship between the expansion of construction land and topographic factors such as elevation and gradient. We first established a digital elevation mode (DEM) of the topographic map of the region (1:250,000) based on a Triangulated Irregular Network (TIN) mode and overlaid it on the construction land distribution for each of the three analysis periods. We then computed the total area of construction land in the subset of the region where the slope is less than 10% and the altitude is less than 50 m above sea level. Finally,
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Fig. 4. Analysis of buffer zones along the major roads of the Pearl River Delta.
Table 3 Results of the spatial analysis of construction land in the Pearl River Delta. From 1988 to 1998 UL1 (%) 2-km-wide zone centered on major roads 10-km zone along the coastline Zones with slope of less than 10% and altitude of less than 50 m above sea level Entire PRD
9.95 20.20 9.07 9.43
UL2 (%) 13.32 15.94 9.29 6.44
From 1998 to 2006 UL3 (%) 60.18 43.6 84.83 100.00
UL4 (‰) 13.32 15.94 9.29 6.44
Fig. 5. Analysis of the buffer zone along the coastline of the Pearl River Delta.
UL1 (%) 4.82 3.36 5.71 5.79
UL2 (%)
UL3 (%)
UL4 (‰)
9.95 5.72 8.95 6.17
46.98 16.39 85.39 100.00
12.44 7.16 11.19 7.71
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we analyzed the characteristics of construction land expansion in this region. The low-slope, low-elevation region accounts for 58.85% of the total area of the PRD and is primarily composed of plains interspersed with low mountains, hills, mesas and other landscape types. Construction land in this region accounted for 89.66% (1988), 86.79% (1998), and 86.28% (2006) of that in the whole delta. UL1 , UL4 , and UL3 were 9.07%, 9.29%, and 84.83% from 1988 to 1998 and 5.71%, 11.19%, and 85.39% from 1998 to 2006. The majority of new construction land in the delta was therefore in this region. This low-slope, low-elevation region is also the most suitable location for cultivation, resulting in conflicts between the development of construction land and the protection of farmland (Anthony and Li, 1999). The regional landscape thus has an impact on construction land expansion, with low-elevation plains always being preferred construction sites. The portion of construction occurring outside the low-lying areas did increase gradually. This change reflects the decreasing influence of landscape type as construction land became less available and construction technology improved. As a result, the ecological security of the region became threatened.
(3) The landscape of the region also plays an important role in the expansion of construction land. Low-lying plains are preferred for both construction and farming, leading to a competition between construction development and farmland protection. In recent years, the increasing scarcity of land resources and improvement in construction technology has forced the removal of an increasing number of hills and mountains to make room for new construction. The result has been not only a decreasing influence of the landscape on construction land development but also hidden threats to regional ecological security. The site factors described here serve as indicators of the preferable locales for expansion of construction land. Development tends to expand to locations in suburbs, on plains and along major roads and coastlines. As some of the most important natural/spatial factors, site factors play an important role in driving and constraining the expansion of construction land, determining the direction, scale, intensity and speed of expansion. Acknowledgments
5. Discussion and conclusion Previous research has often attributed the growth of construction to socio-economic factors and human behavior and has suggested that rapid industrialization and urbanization were the most important factors in the expansion of construction land. While those factors do play an important role, in this study, we address the influence of natural and spatial factors on construction land expansion. Our results show, as our hypothesis, site factors, such as landscape type and the distance to the city center, major roads and the coastline, also have a significant influence on construction land expansion in the following specific ways.
(1) The expansion of construction land reached relative maxima at two distances to the city center. The inner peak represents the growth of suburbs, indicating spillover from the city center and rapid development of the suburbs. The outer peak indicates the growth of industrial zones and the construction of satellite cities in the outer suburbs, suggesting a leapfrog-like pattern of urban expansion. The suburban region is the preferred location for development, and construction land expands most rapidly in that region. This pattern reflects the interaction between urban and rural areas and the process of suburbanization in large cities. The process in the PRD differs from suburbanization abroad, which led to the decline of central city areas, in that in the PRD it is characterized by the simultaneous development of both the city center and the suburbs. The result is a land-use distribution characterized by a decline in construction land from the city center to the periphery. (2) The distance of a given region from major roads and coastlines impacts the transportation accessibility of the land and therefore its potential for construction. Quantitative analysis shows that locations close to roads or shorelines are preferable for construction activities. Roads and coastlines are thus drivers of construction land expansion, resulting in a distribution pattern with construction land clustered along roads and coastlines. Unfortunately, the overlap between the urban centers and roadways/coastlines makes it difficult to distinguish the individual influence of each factor. We can demonstrate the distribution of construction land along roads and coastlines but cannot analyze the changes in construction land expansion with distance to these features.
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International Journal of Applied Earth Observation and Geoinformation journal homepage: www.elsevier.com/locate/jag
Research on the influence of site factors on the expansion of construction land in the Pearl River Delta, China: By using GIS and remote sensing Yuyao Ye ∗ , Hongou Zhang, Kai Liu, Qitao Wu Guangzhou Institution of Geography, Guangzhou, China
a r t i c l e
i n f o
Article history: Received 27 December 2010 Accepted 22 October 2011 Keywords: Site factor Construction land The Pearl River Delta, China GIS Remote sensing TM
a b s t r a c t Landsat TM images of the Pearl River Delta taken in 1988, 1998 and 2006 are used to explore the site factors that influence the construction land expansion in this study. Several site factors, including landscape types and the distances to roads, coastlines, or city centers, had significant impacts on the expansion of construction land, influencing the direction, scale and intensity of the expansion. The site factors serve as important natural and spatial indicators of the preferable locales for construction land expansion, describing tendencies to expand to locations in suburbs, plains and areas near roads or coastlines. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Land use and land cover change (hereafter referred to as LUCC) is one of the most important components of current global environmental change and has been a focus of much global change researches (Tuner and Meyer, 1994; Seto and Shepherd, 2009). A general global trend of LUCC has been the expansion of construction land, including land for urban/rural settlements, industry and transportation (e.g., Hart, 1976; Alig and Healy, 1987; Lambin, 1997; Sorensen, 2000; López et al., 2001b; Müller and Zeller, 2002; Adrián and Peter, 2003; Murakami et al., 2005; Tan et al., 2005; Tian et al., 2005; Xiao et al., 2006; Hu et al., 2007; Long et al., 2007; Adrián, 2008; Gong et al., 2009). The resulting conversion of arable land has attracted widespread attention and has been the subjects of numerous studies (Yeh and Li, 1999; Walker, 2001). Researchers typically attribute the dynamics of land use change to five major forces: political, economic, cultural, technological, and natural/spatial ones (e.g., Lambin et al., 2001; Bürgi and Turner, 2002; Lambin et al., 2003; Bürgi et al., 2004; Schneeberger et al., 2007; Hersperger and Matthias, 2009). The natural/spatial factors mainly include site factors, such as landscape types, adjoining land use patterns and distance to roads or city centers (discussed in detail in this paper), and non-site factors, such as soil quality and potential for natural disturbances (i.e., climate changes and disasters). Although these factors play important roles in LUCC, they
∗ Corresponding author. Tel.: +86 20 37656557; fax: +86 20 87685006. E-mail address: [email protected] (Y. Ye). 0303-2434/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.jag.2011.10.012
have not received much attention (Bruijn, 1994). Previous research generally, focused on the political, economic, cultural and technological factors, and emphasized the influence of human activities on LUCC (e.g., Haberl et al., 2003; Zhang et al., 2003; Tan et al., 2005; Xie et al., 2005; Quan et al., 2006; Yan et al., 2006; Liu et al., 2008). Fortunately, others have also noted the impact of site factors, especially road networks on LUCC (Patarasuk and Binford, 2011). A common phenomena has been found as that rapid urban growth and conversion of agricultural land to built-up areas preferred to occur closer to road networks in as disparate locations as the Kansas City Metropolitan area in the central USA (Underhill, 2004), Puerto Rico (López et al., 2001a), Indian city (Fazal, 2001) and the urban expansion of Beijing (Zhang et al., 2002). Roads influence regional land cover because they enhance accesses to land for human activities. In this study, we presume that accessibility and distance emerge as important determinants of location for many land uses. We hypothesize site factors, including not only road networks but also landscape type and the distance to the city centers or the coastline, have significant influences on construction land expansion, for their direct relationship with accessibility. The object of this study is to examine the hypothesis and how it works. The Pearl River Delta (PRD) is the most important and representative urbanized regions in China and has been witnessing a dramatic land-cover change in the past 30 years. It’s been developed rapidly, following the reformation of economy and open policy in China since 1978. Began in the late 1980s, the land-use reforming in Shenzhen has leaded to a “property boom” since the real estate market opened in the region in the early 1990s. Investments to real estate have grown not only in Shenzhen, Guangzhou
Y. Ye et al. / International Journal of Applied Earth Observation and Geoinformation 21 (2013) 366–373
and Huizhou but the entire PRD region. In addition, the rapid development of industrial and real estate zones – the main targets of construction land expansion at the time – led to large-scale encroachment of farmland, due primarily to land speculation. Land was priced cheaply, so speculators often purchased then hoarded large tracts of land, resulting in widespread areas of lower-density plants and buildings and large-scale destruction of farmland (Li, 2004). Since 1998, economic growth in the PRD had slowed. The national government introduced several new policies for price regulation, land exploitation and foreign investment. These policies brought subsequent economic adjustment throughout the entire region. The slowdown of economic growth and the introduction of more rigorous national policies protecting cultivated land somewhat slowed the speed of expansion of construction land, but the speed remained difficult to control. Currently, throughout the region, construction land covers near 20% of the land on average and up to 40% in cities like Dongguan and Shenzhen (Guangdong Province State Land and Resources Department, 2007). As a result, the scale of arable land in the region has declined dramatically. According to the official statistics, the total area of cultivated land in the PRD was 8460.99 km2 in 1996; decreased to 5899.55 km2 by the end of 2007, with a decline of 30.27% with 12 years (Guangdong Province State Land and Resources Department, 2007). It has revealed a rapid spread of construction land encroached upon farmland, destroyed natural habitat, and diminished biodiversity. It’s been a serious challenge for the PRD and served as a model of what can be expected for land use changes in rapidly developing regions of China. Remote sensing provides spatially consistent datasets that cover large areas of land with both high spatial resolution and high temporal frequency. It has been described as a “unique view” of the spatial and temporal dynamics of the processes during land use change (Herold et al., 2003). Satellite remote sensing techniques have been widely used to detect and monitor land cover changes at various scales (e.g., Lucas et al., 1989; Li and Yeh, 1998; Stefanov et al., 2001; Wilson et al., 2003; Seto and Kaufmann, 2003). Recently, remote sensing has been used in combination with Geographical Information Systems (GIS) and Global Positioning Systems (GPS) to provide more comprehensive assessments of land cover change than using itself alone (Sui and Zeng, 2001; Weng, 2002; Li and Yeh, 2004). In this study, we made an exploration on the influence of the site factors on construction land expansion in the PRD by using GIS and remote sensing. Firstly, Landsat Thematic Mapper (TM) images from 1988, 1998, and 2006 were employed to detect the expansion of construction land in the PRD. Subsequently, spatial analysis capabilities of GIS were used to quantify the influences of various site factors on the expansion, focusing on the regional landscape and the distances to city centers, roads or coastlines. The objectives of the study are as follows: (1) to explore the temporal and spatial characteristics of PRD construction land expansion over the last 20 years; (2) to detect and evaluate the influences of site factors and the interactions between them; and (3) to identify the internal drivers of the expansion and derive advices for decision-makers.
2. Study area Located on the southern coast of mainland China (112◦ –115.5◦ E, 21.5◦ –24◦ N, see Fig. 1), PRD is the largest alluvial plain in the subtropical monsoon climate zone of continental China and is adjacent to the South China Sea from the north. The region is surrounded by mountains to the east, west and north with widespread plateaus. Located in the subtropical monsoon climate zone, the region is warm and humid with long summers and short winters, proved as suitable for the growth of a variety of types of crops.
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Table 1 Landsat TM images used in this paper. Number
Orbit number
Imaging day
Imaging day
Imaging day
1 2 3 4 5
121-044 121-045 122-044 122-045 123-044
1988-12-14 1988-12-10 1988-07-30 1988-07-30 1988-12-17
1998-12-26 1998-08-25 1998-12-22 1998-12-22 1998-12-29
2006-12-05 2006-12-21 2006-12-28 2006-11-10 2006-12-19
Ranging a total area of 40,041 km2 with a population of 40.80 million people (Guangdong Province Office, 2009), the PRD covers nine municipalities in the Guangdong province: Dongguan, Foshan, Guangzhou, Huizhou, Shenzhen, Zhongshan, Zhuhai and part of Jiangmen, Zhaoqing. Since the establishment of Chinese Opening Policies in 1978, it has been rapidly transforming from an agricultural area to one of the most important urban industrial regions of China. In 2008, the gross domestic product (GDP) in the PRD reached 434.28 billion U.S. dollars, over 10% of the Chinese total and more than 80% of the Guangdong province GDP (Guangdong Statistical Yearbook, 2009). The rapid industrialization and urbanization of the PRD has brought with it dramatic land cover change. 3. Data and methods 3.1. Data sources The land-use data were derived from historical Landsat TM images with spatial resolution of 30 m × 30 m. Five Landsat scenes were needed to cover the entire study area and each was obtained from versions of 1988, 1998 and 2006 (a total of fifteen Landsat scenes). For the monsoonal climate in the region, it’s difficult to obtain simultaneous cloud-free images for any five PRD scenes within a year. Therefore, for each year, multiple images were collected at different times within a six-month interval. Table 1 shows the orbit number and imaging time for the Landsat TM images used in this study. The specific images were all selected because they were available and cloud-free. 3.2. Data processing The first stage of data processing involved applying a geometrical image correction and a geo-reference correction. The latter correction consisted of two steps: (1) a topographic correction based on a topographic map and field survey points that were used to correct the 2006 images; and (2) an image-to-image registration based on the 2006 image that was used to ensure all images had the same projection. We subsequently derived land cover maps from the TM images using the artificial visual interpretation method (AVIM), which has proven to be one of the most effective methods for TM image interpretation because it takes full advantage of the experience and knowledge of the image interpreters (Zhu and Zhang, 2002). In this study, we use ERDAS IMAGINE 9.1, a software program developed by ERDAS, to process the remote sensing images. To interpret the images, we use ArcGIS9.1, developed by Environment System Research Institute (ESRI). Fig. 2 shows the results, which reflect the expansion of construction land. Finally, we made 1000 sample points (patches) for each year, some derived from higher spatial resolution remote sensing images (acquired for 1988, 1998) and others from field survey (acquired for 2006), to test the classification results: 500 each for construction land and farmland. The Kappa coefficient and overall accuracy were used to quantify the classification precision of the images. The overall accuracies were 91.1% (1988), 93.4% (1998), and 94.7% (2006), and the Kappa coefficients were 0.889 (1988), 0.917 (1998) and
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Fig. 1. Location of the study area.
0.926 (2006). Accuracies near 100% and Kappa coefficients near 1 indicate precise classification by the AVIM (see Table 2). 3.3. Study methods To understand the impacts of site factors on the expansion of construction land, we overlaid maps of construction land with topographic maps. Then, patterns of construction land expansion in the buffer zones around urban centers and along major roads, coastlines, and other geographic features were analyzed.
Table 2 Classification accuracy for the three periods. CLF 1988 CLM FLM 1998 CLM FLM 2006 CLM FLM
FLF
Overall accuracy (%)
Kappa coefficient
0.889
448 37
52 463
91.1
465 31
35 469
93.4
0.917
475 28
25 472
94.7
0.926
The effects were quantified with indices those reflect the degree of construction land expansion in each buffer zone. Namely (1) the construction land expansion rate (UL1 ); (2) the structure coefficient (UL2 ), which represents the change in the fraction of land used for construction purposes; (3) the scale coefficient (UL3 ), which represents the ratio of construction land expansion in a given region to that in the entire study area; (4) the expansion intensity (UL4 ), which represents the ratio of construction land expansion in a given region to the region’s total land area; (5) a composite called the comprehensive expansion index (ULc ), which is composed of the latter four indices; and (6) the construction land density (Du ). The indices are defined as follows: ULc =
ULi
(i = 1, 2, 3, 4);
i=1
UL1 =
Note: CLM – construction land on maps; CLF – construction land in the field; FLM – farmland on maps; FLF – farmland in the field.
4
t
UL2 = Pt − P0 ; UL3 =
St −1 S0
St − S0 ; At − A0
× 100;
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Fig. 2. Expansion of construction land in the Pearl River Delta.
UL4 =
Du =
St − S0 ; H×t
S × 100 H
where Pt and P0 are the ratios of construction land in a given target region to total land area in the region at times t and 0; St and S0 are the areas of construction land in the target region at times t and 0; t is the number of years over which the changes are calculated; At and A0 are the areas of construction land in the entire study area at times t and 0; and H is the total land area in the study region. The computations were preformed for each target region, i.e., the buffer zones described earlier. 4. Results 4.1. The processes and characteristics of construction land expansion in PRD 4.1.1. From 1988 to 1998 Throughout this period, the region witnessed vigorous expansion of construction land. The area occupied by construction land increased to 4345.70 km2 in 1998, nearly 1.5 times its size in 1988. In 1998, UL1 , UL2 , and UL4 were 9.43%, 6.44%, 6.44‰, respectively, and Du increased from 4.41% to 10.85%. The eastern coastal region of the PRD revealed the most prominent construction expansion, especially around the GuangzhouShenzhen Railway and the Guangzhou-Shenzhen section of National Highway 107, forming the main axis of the expansion. The so-called “road economy,” accompanied by the spread of construction land along major roads, was prevalent in the PRD during
this period, resulting in a waste of land resources. In Dongguan, for example, the length of arterial roads had increased to 150 km by 1992. These roads were associated with construction land expansion, which led to the development of a landscape known as the “100-kilometer-long Street,” reflecting the abnormal growth and exploitation along the roads. 4.1.2. From 1998 to 2006 In this period, a decrease in the rate of construction land expansion in the region was accompanied by the slowdown of economic growth and the introduction of more rigorous national policies protecting cultivated land; nonetheless, the intensity of expansion remained high. In 2006, the total area occupied by construction land reached 6816.04 km2 , nearly 1.5 times its area in 1998. By 2006, UL1 , UL2 , UL4 and Du were 5.79%, 6.17%, 7.71‰ and 17.02%, respectively. In some cities, such as Shenzhen and Dongguan, Du reached values of up to 40%. Urban sprawl and overlapping regions of development characterized the entire region. This pattern was particularly evident in the eastern coastal region, where a highdensity urban corridor developed, linking the cities of Guangzhou, Shengzhen, Dongguan, and Huizhou (see Fig. 2). 4.2. Influence of site factors on the expansion of construction land 4.2.1. Influence of the distance to the city center We used development in Guangzhou as a case study to examine the impacts of distance to the city center on the expansion of construction land. We performed a radiation buffer analysis centered on the Guangzhou city center, which is defined as the location of the municipal government. 24 circular radiation zones were defined, with the innermost zone extending 5 km from the city center and all subsequent zones extending 5 km from the previous zone.
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2-km-wide buffer zones. We then overlaid the buffer zones on the maps of construction land for the three periods and analyzed the patterns of expansion within the zones (see Fig. 4). The results of this analysis (Table 3) show that construction land along the roads increased by 1552.96 km2 between 1988 and 1998. During this period, UL1 , UL3 , and UL4 were 9.95%, 60.18%, and 13.32‰, respectively, indicating that construction land tended to spread along major roads. The so-called “road economy” was prevalent during this period, leading to extensive construction along the main roads. From 1988 to 2006, UL1 , UL3 and UL4 decreased to 4.82%, 46.98% and 12.44‰, respectively. Nevertheless, construction along the roads was still evident in 2006, with Du at 31.69% inside the zones, twice the average for the region. The distance to a major road thus has a marked impact on the expansion of construction land. Locations near roads are often preferred for construction due to their accessibility and the associated low costs of transporting materials. The result is a “webbed” pattern of construction that sprawls along the main roads. This pattern is especially evident in the high-density urban corridors that have formed along the Guangzhou-Shenzhen section of 107 National Road, the Guangzhou-Zhuhai section of 105 National Road, and the Guangzhou-Shenzhen Railway.
Fig. 3. Relationship between the expansion of construction land and the distance to the city center.
Differences in the construction land expansion between the 24 radiation zones were overlaid on the construction land distributions for each of the three analysis periods. Fig. 3 shows the resulting impacts of distance to the city center on changes in Du and ULc . Fig. 3a shows that Du decreased with increasing distance to the city center for all three years included in the analysis. The changes in ULc from the city center to the periphery were more complex, as shown in Fig. 3b. During the 1988–1998 period, ULc peaked in the third zone at a distance of 10–15 miles from the city center. This region was a suburb of Guangzhou at the time, and the ULc maximum here indicates rapid development of the suburb with construction spilling outwards from the city center. ULc also showed a secondary peak in the sixth zone, at 25–30 miles from the city center, due to the development of industrial zones and the construction of satellite cities in the outer suburbs. In the 1998–2006, ULc had a broad peak that extended from the fourth zone to the eighth zone. The peak construction in this period occurred farther from the city center than in the previous period, suggesting that the city boundary had expanded outward as land in the central part of the city was used up. During this period, the development of construction land slowed significantly. Most construction occurred 15–40 km from the city center, indicating expansion of the city center and peripheral satellite cities as well as development between them. Distance to the city center thus has a clear impact on the expansion of construction land. Initially, construction tends to occur in two locations, the nearby suburbs and the outer suburbs. Later, construction moves to the area between the suburbs, resulting in a land-use distribution characterized by a decline in construction land from the city center to the periphery. 4.2.2. Influence of the distance to major roads We also examined buffer zones along major national and provincial-level roads in the study area. The zones were defined to extend 1 km from the centerline of each road, resulting in
4.2.3. Influence of distance to the coastlines To test the influence of distance to the coastline on the expansion of construction land, we defined a buffer zone that extended 10 km to the coastline, which had previously been smoothed. We then overlaid it on the construction land distribution for the three periods and analyzed the pattern of the expansion within the buffer zone (see Fig. 5). The results (Table 3) show that from 1988 to 1996, UL1 , UL2 and UL4 were 20.20%, 15.94%, and 15.94‰, respectively. UL3 was 43.6%, indicating that nearly half of the new construction in the PRD was concentrated in the 10-km zone along the coastline. From 1998 to 2006, the expansion of construction land within this zone slowed somewhat, with decreases in UL1 , UL2 , UL3 and UL4 . Nonetheless, new construction land within the zone still made up 16.39% of the total regional construction land during this period. After the near-shore construction peaked in the previous period, coastal development encountered a number of bottlenecks, including land scarcity and constraints of co-environmental capacity. These difficulties caused the expansion of construction land along the coast to slow, although the tendency to concentrate construction along the coastline remained unchanged. Distance to the coastline thus has an obvious impact on the expansion of construction land. The PRD region is characterized by an export-driven economy and limited resources. As a result, the availability of industrial raw materials and sale of manufacturing products are highly dependent on marine transportation and international markets. Since 1978, the coastal region has gradually become a development hot spot. Shenzhen, for example, has rapidly developed from a small fishing village to an international metropolis. Reliant on major ports, many new portside cities and industrial bases have boomed, forming an industrial band along the coast. 4.2.4. Influence of the landscape We used GIS spatial technology to analyze the relationship between the expansion of construction land and topographic factors such as elevation and gradient. We first established a digital elevation mode (DEM) of the topographic map of the region (1:250,000) based on a Triangulated Irregular Network (TIN) mode and overlaid it on the construction land distribution for each of the three analysis periods. We then computed the total area of construction land in the subset of the region where the slope is less than 10% and the altitude is less than 50 m above sea level. Finally,
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Fig. 4. Analysis of buffer zones along the major roads of the Pearl River Delta.
Table 3 Results of the spatial analysis of construction land in the Pearl River Delta. From 1988 to 1998 UL1 (%) 2-km-wide zone centered on major roads 10-km zone along the coastline Zones with slope of less than 10% and altitude of less than 50 m above sea level Entire PRD
9.95 20.20 9.07 9.43
UL2 (%) 13.32 15.94 9.29 6.44
From 1998 to 2006 UL3 (%) 60.18 43.6 84.83 100.00
UL4 (‰) 13.32 15.94 9.29 6.44
Fig. 5. Analysis of the buffer zone along the coastline of the Pearl River Delta.
UL1 (%) 4.82 3.36 5.71 5.79
UL2 (%)
UL3 (%)
UL4 (‰)
9.95 5.72 8.95 6.17
46.98 16.39 85.39 100.00
12.44 7.16 11.19 7.71
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we analyzed the characteristics of construction land expansion in this region. The low-slope, low-elevation region accounts for 58.85% of the total area of the PRD and is primarily composed of plains interspersed with low mountains, hills, mesas and other landscape types. Construction land in this region accounted for 89.66% (1988), 86.79% (1998), and 86.28% (2006) of that in the whole delta. UL1 , UL4 , and UL3 were 9.07%, 9.29%, and 84.83% from 1988 to 1998 and 5.71%, 11.19%, and 85.39% from 1998 to 2006. The majority of new construction land in the delta was therefore in this region. This low-slope, low-elevation region is also the most suitable location for cultivation, resulting in conflicts between the development of construction land and the protection of farmland (Anthony and Li, 1999). The regional landscape thus has an impact on construction land expansion, with low-elevation plains always being preferred construction sites. The portion of construction occurring outside the low-lying areas did increase gradually. This change reflects the decreasing influence of landscape type as construction land became less available and construction technology improved. As a result, the ecological security of the region became threatened.
(3) The landscape of the region also plays an important role in the expansion of construction land. Low-lying plains are preferred for both construction and farming, leading to a competition between construction development and farmland protection. In recent years, the increasing scarcity of land resources and improvement in construction technology has forced the removal of an increasing number of hills and mountains to make room for new construction. The result has been not only a decreasing influence of the landscape on construction land development but also hidden threats to regional ecological security. The site factors described here serve as indicators of the preferable locales for expansion of construction land. Development tends to expand to locations in suburbs, on plains and along major roads and coastlines. As some of the most important natural/spatial factors, site factors play an important role in driving and constraining the expansion of construction land, determining the direction, scale, intensity and speed of expansion. Acknowledgments
5. Discussion and conclusion Previous research has often attributed the growth of construction to socio-economic factors and human behavior and has suggested that rapid industrialization and urbanization were the most important factors in the expansion of construction land. While those factors do play an important role, in this study, we address the influence of natural and spatial factors on construction land expansion. Our results show, as our hypothesis, site factors, such as landscape type and the distance to the city center, major roads and the coastline, also have a significant influence on construction land expansion in the following specific ways.
(1) The expansion of construction land reached relative maxima at two distances to the city center. The inner peak represents the growth of suburbs, indicating spillover from the city center and rapid development of the suburbs. The outer peak indicates the growth of industrial zones and the construction of satellite cities in the outer suburbs, suggesting a leapfrog-like pattern of urban expansion. The suburban region is the preferred location for development, and construction land expands most rapidly in that region. This pattern reflects the interaction between urban and rural areas and the process of suburbanization in large cities. The process in the PRD differs from suburbanization abroad, which led to the decline of central city areas, in that in the PRD it is characterized by the simultaneous development of both the city center and the suburbs. The result is a land-use distribution characterized by a decline in construction land from the city center to the periphery. (2) The distance of a given region from major roads and coastlines impacts the transportation accessibility of the land and therefore its potential for construction. Quantitative analysis shows that locations close to roads or shorelines are preferable for construction activities. Roads and coastlines are thus drivers of construction land expansion, resulting in a distribution pattern with construction land clustered along roads and coastlines. Unfortunately, the overlap between the urban centers and roadways/coastlines makes it difficult to distinguish the individual influence of each factor. We can demonstrate the distribution of construction land along roads and coastlines but cannot analyze the changes in construction land expansion with distance to these features.
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