land use change and impacts on environment in South Asia

Journal of Environmental Management 148 (2015) 1e3

Contents lists available at ScienceDirect

Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman

Editorial

Land cover/land use change and impacts on environment in South Asia South Asia spans an area of about 4.5 million sq km and has a population of 1.62 billion, which represents almost 22% of the world population on 3.31% of the world's land mass (SAARC country profiles, 2014). The cumulative population of South Asia is expected to overtake China by 2050 and this population growth will increase current pressure to convert land from natural and agricultural areas to residential and urban uses with significant impact on ecosystem services. Increased land cover/land use changes (LCLUC) can also impact agricultural production efficiency including environmental impacts on urban, suburban, rural communities and natural areas. Further, most of the countries in this region have high population densities and relatively low rates of economic growth. Low rates of economic growth indicate low adaptive capacities and therefore, high vulnerability to climate change and human induced pressures on ecosystems (Shukla et al., 2008; Lobell et al., 2008). LCLUC in the region is disrupting and perturbing biodiversity, regional climate, biogeochemical cycles, water resources and other ecosystem services (Turner and Annamalai, 2012; Madson, 2013). Understanding LCLUC requires addressing spatial scale issues, technological innovations, policy and institutional changes (IGBP, 2001). Also, spatially explicit data are needed to assess how land cover has changed over past decades. Most importantly, addressing LCLUC research in South Asia requires developing strong partnerships with regional scientists who are most able to identify the research gaps and priorities in the region. To achieve this, the NASA LCLUC program organized a regional science meeting and field visits during January 19the23rd, 2013 at Karunya University in Coimbatore, India (http://lcluc.umd.edu). Prof. E.J.James, Water Institute, Karunya University served as a local host. The meeting provided an international forum to bring scientists together to discuss LCLUC and its impacts, with a regional focus. This science meeting was sponsored by NASA's LCLUC Program, the International System for Analysis Research and Training (START) Program and our Indian counterpart the Karunya University (Coimbatore, Tamil Nadu). Nearly 120 participants from India attended the meeting. In addition, there were 18 researchers from the U.S., 3 from Nepal, 2 from Sri Lanka, and 1 each from Myanmar, Afghanistan, and Bangladesh. Selected papers presented at the above regional science meeting were invited to contribute full length articles to this special issue. All articles have undergone a peer review following the journal protocols. The special issue covers a spectrum of LCLUC topics and includes new contemporary LCLUC issues in South Asia and environmental impacts. The papers highlight a series of LCLUC case studies which use remote sensing datasets. A brief summary of the articles is provided below. http://dx.doi.org/10.1016/j.jenvman.2014.12.005 0301-4797/© 2014 Published by Elsevier Ltd.

In the introductory article, Justice et al., provide a brief overview of the LCLUC program, its focus areas, and the importance of satellite remote sensing observations including future directions. The LCLUC program is global in scope and it aims to develop and use remote sensing technologies to improve understanding of human interactions with the environment. The program has supported a wide variety of projects since 1997 on topics such as urban and suburban expansion, land abandonment, wetland loss, agricultural land use change and land use in mountain systems. Further, the program has contributed to diverse regional science programs. The program promotes use of remote sensing datasets and the strength of the program lies in the integration of physical and social sciences to address regional to global scale issues of LCLUC for the benefit of society. The first four articles of this issue focus on an agricultural theme. In the article entitled “Fire regimes and Bioenergy Loss from Agricultural Lands in the Indo-Ganges Region”, the authors use MODIS satellite datasets in conjunction with IRS-AWiFS classified data and crop statistical data for area, production and yield for 31 different crops to map the potential of agricultural residues for bioenergy generation in the Indo-Gangetic Plain (IGP). They report 88.13% fires occurring in agricultural areas, with more fires during the winter than the summer. They also show MODIS NPP data explaining 60% of variation in field-level crop yield estimates. The authors estimate that ~73.28 Tg of crop residue biomass is available for recycling in the IGP with the energy equivalent of 1110.77 PJ. The authors also provide estimates on biogas, electric power, and the total bioethanol production potentials from the agricultural residues. Their results also highlight geographic locations of bioenergy resources in the IGP and areas of optimum location for bioenergy plants useful for energy planning. Mondal et al., used 16-day MODIS Enhanced Vegetation Index (EVI) data over monsoon and winter seasons from 2000 to 2012 and Tropical Rainfall Measuring Mission (TRMM) dataset to understand the sensitivity of crop cover to climate variability in two different agro-ecoregions. Their results suggest relatively higher sensitivity of crop phenology to precipitation variability at the Central Indian site compared to the Western India site. The authors suggest the need for better access to weather data for farmers and the use of climate-resilient crop types for maintaining future agricultural productivity. In the paper entitled “Remote sensing based change analysis of rice environments in Odisha”, Gumma et al., use 250 m MODIS 8day time series data from 2000 to 2010 to identify stress-prone areas due to submergence (flooding) and water shortage, using a spectral matching technique. Accuracy was determined by

2

Editorial / Journal of Environmental Management 148 (2015) 1e3

correlating the MODIS-derived rice areas with field-plot data and sub-national statistics obtained from Odisha's Ministry of Agriculture. The authors report 90% accuracy from the MODIS derived rice maps, correlating well with district level rice area statistics. Also, authors report individual class accuracy based on field-plot data at 84.8%. In the paper entitled “LCLUC as an entry point for trans disciplinary research: reflections from an agriculture land use change study in South Asia”, Nagabhatla et al., stress the need for multitiered geospatial analysis for the assessment of agro ecosystem resources and management. The authors analyze land cover/land use in Wayanad, Kerala at three different levels, i.e., district level mapping using Landsat TM-30 m, sub-district level using ASTER-15 m and village level using GeoEye-0.5 m. Two scientists, a natural scientist and a sociologist joined efforts in assessing the LCLUC results. Authors report significant improvement in results through integration of knowledge from different disciplines. Based on the results derived from the remote sensing data, they report that Wayanad is undergoing rapid LCLUC due to economic, climatic, and political changes. Authors stress the need for the participatory mapping exercises and trans-disciplinary approaches for better management of natural resources. Two different papers focus on urbanization. Pandey et al., examine the impacts of urbanization on agricultural land loss in India from 2001 to 2010 in the study titled “Urbanization and agricultural land loss in India: comparing satellite estimates with census data”. Authors use the MODIS time series dataset in conjunction with TIMESAT algorithm and DMSP-OLS data to quantify the agricultural land loss to urban areas. Authors report less than 1% agricultural land loss to urban areas for each state from 2001 to 2010, with the total amount of agricultural land loss in India of 0.7 million hectares for the same period. Authors also report spatial variability in agricultural land loss to urban areas and suggest that due to increased population growth and economic activities, the region might face much increased urbanization at the cost of agricultural land loss in the near future. In the paper entitled “Monitoring urbanization and its implications in a mega city from space: spatiotemporal patterns with indicators”, Ramachandra et al., use Landsat data from 1973 to 2010 to address urbanization in Delhi. They use the normalized difference vegetation index to quantify vegetation changes and a maximum likelihood classification algorithm for quantifying LCLUC. Their results suggest that during the last four decades, Delhi has witnessed a massive 83.5% growth in built-up area with the decline of vegetated areas by 25% and water bodies by 31%. Using the Shannon entropy and fragmentation metrics, authors show agriculture and other green spaces as highly fragmented due to increased urban areas. Authors call for conservative urban planning to ensure the sustenance of water, natural resources, and people's livelihoods. Two papers present land cover and land use changes at a national scale, one focusing on Nepal and other on Bhutan. In the study entitled “Development of 2010 national land cover database for the Nepal’, Kabiruddin et al., use Landsat TM data integrated with object-based classification for land cover mapping. They report 39.1% of Nepal as being covered by forests and 29.83% by agriculture. Authors also perform landscape fragmentation analysis and report that hills constitute the largest portion of Nepal covering 29.5% of the geographical area, natural and semi natural vegetation (22,621 km2), a large area of cultivated or managed lands (19,783 km2) and artificial surfaces (200 km2). The patch and edge forests constitute 23.4% of national forest and are highly impacted due to anthropogenic factors. Authors also note that the Tarai and Siwalik regions have a high-level of population and agricultural areas and less forested area, with potential land use

conflicts. In addition, these regions are also impacted by snow/glaciers. Thus, understanding land use change transitions and climate impacts in these regions gains significance. In South Asia, Bhutan is a landlocked country located at the eastern end of the Himalayas. The country is bordered to the north by China and to the south, east and west by India. In the paper entitled “Decadal land cover change dynamics in Bhutan”, authors studied land cover change from 1990 to 2000e2010 using Landsat data. They used object-based image analysis technique to assess the land cover changes and performed an accuracy assessment using 300 systematic points from Google Earth Pro and 119 points located on the ground. They conclude that in Bhutan, forest area increased over 20 years by 1174 km2 with almost no loss, attributing the increase to annual plantations by the government, social forestry, slow population growth rate, high literacy rate, and use of alternative energy resources and better forest management plans (Gilani et al., this issue). Further, they show almost no change in built-up areas (0.18%) between 1990 and 2010 and attribute that to the low population growth rate of 1.2% per annum in Bhutan. Wetlands and coastal areas are some of the most productive ecosystems in the world with rich biodiversity. In several regions of the world, they are rapidly undergoing anthropogenic pressure resulting from encroachment, siltation, aquaculture development and pollution. In addition, sea-level rise is a major indicator of climate change (Cazenave et al., 2014) that is occurring rapidly and impacting some of the coastal areas. In the special issue, four different papers highlight LCLUC changes in wetlands and coastal areas. Giri et al., discuss the current extent of mangrove forests in South Asia in the paper entitled “Distribution and dynamics of mangrove forests of South Asia”, using Landsat satellite data from 2000 to 2012 and classification and regression tree algorithms. Authors also report on mangrove extent and their changes in Indus Delta (Pakistan), Goa (India), and Sundarbans. The authors report an areal extent of 1,187,476 ha of mangrove forests accounting for ~6% of the global mangrove forests in South Asia. They report 92,135 ha of mangroves being deforested and 80,461 ha as reforested with a net loss of 11,673 ha from 2000 to 2012. In all three case studies, the authors report mangrove areas remaining the same or having increased slightly in areal extent. In the paper, Giri et al., also discusses the major causes of mangrove forest loss. In the paper entitled “Wetland assessment, monitoring and management in India using Geospatial techniques”, Garg et al., describes the nationwide wetland mapping between 1993 and 98 carried out by the Space Applications Center, Department of Space Government of India, at the behest of the Ministry of Environment and Forests, Government of India. As a part of the inventory, a new classification system of wetlands was adopted based on the Ramsar convention, which takes into account all wetlands whether inland or coastal, natural or man-made. From the satellite remote sensing analysis, Garg et al., show that during the 1992e1993 to 2007e08, among inland wetlands, man-made wetlands have shown an increase of 1,756,942 ha (85%). Mangroves (39%) and coral reefs (69%) have also shown significant increase of 39% and 69% respectively. Garg et al., also estimate 3 Tg of methane release from water and waterlogged areas in India. Authors Mani Murali and Dinesh Kumar presents the “Implications of Sea Level Rise Scenarios on Land use/Land cover classes of the Coastal Zones of Cochin, India”. The authors used IRS P6 LISS III data for deriving land use/cover classes in conjunction with the Shuttle Radar Topographic Mission digital elevation data to extract the different elevation areas. For the sea level rise scenarios of 1 m and 2 m, authors estimate the total inundation zones to be 169.11 km2 and 598.83 km2 respectively. The potential loss of urban areas was estimated at 43 km2 and 187 km2 for 1 m and 2 m sea level rise respectively for the coastal areas of Cochin. These

Editorial / Journal of Environmental Management 148 (2015) 1e3

results are significant in the context of climate change scenarios. The results also highlight the need for proactive adaptation and planning to address the LCLUC situation in one of the most densely populated cities in India. Another study that highlights LCLUC in the coastal wetlands is by Dipson et al., entitled “Spatial changes of estuary in Ernakulam district, southern India for last seven decades using multitemporal satellite data.” The authors use Landsat MSS (1973), Landsat ETM (1990) and IRS LISS-III (1998 and 2009) data applying visual interpretation and digitization techniques to quantify changes in estuarine areas. They report a decrease in estuarine area by 12.39% from 1944 to 1973, 3.66% decrease during 1973e1990, a reduction of 1.45% during 1990e1998 and a 1.87% decrease during 1998e2009. They note that most of the decline in estuarine area is due to urban sprawl. In the paper, the authors document decadal changes in LCLUC and identify the causative factors chronologically. The authors stress the need for periodic monitoring of the estuary to help manage estuarine resources in a sustainable way. The final two papers focus on the impacts of LCLUC. In the study entitled “Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data”, Kant et al., use Landsat and MODIS data to analyze surface temperature variations from 2000 to 2010. Over a span of ten years, their analysis revealed that settlement and industrial areas increased from 5.66% to 11.74% and 4.92%e11.87% respectively. During the same period, the authors report a mean surface temperature increase in the range of 2e7
C mainly due to the built-up area expansion in Delhi. In the study entitled “Atmospheric carbonaceous aerosols from Indo-Gangetic Plain and Central Himalaya: impact of anthropogenic sources”, the authors report results from ground-based measurements of carbonaceous aerosols from three urban sites, representing up-wind and down-wind locations. The authors report that due to intense rice residue burning practices, the contribution of total carbonaceous aerosols to the particulate matter is as much as 60% during the post-monsoon and wintertime. They report relatively higher PM10 concentrations during the winter than the summer. Further, the mass concentrations of carbonaceous species of elemental carbon (EC), organic carbon (OC) and water soluble organic carbon (WSOC) from three urban sites is higher than the high altitude sites in the Himalayan region. The Authors also confirm the dominance of carbonaceous species, derived from biomass burning emissions in high OC/EC (~6e8) and low Kþ/ OC (0.02e0.10) ratios at urban and high-altitude sites. In the paper, the authors stress the need for LCLUC-atmospheric interaction

3

studies and the need for conducting long-term ground-based measurements of atmospheric chemical constituents. We hope that the above articles in the special issue will stimulate new ideas, directions and solutions that can lead to both theoretical insights and practical applications of remote sensing data in LCLUC science. We would like to thank all authors for submitting their work to this special issue. We appreciate the scholarly generosity of the reviewers for providing comments and suggestions. Finally, we would like to express our gratitude to Dr. Alison Gill, Editor-in-Chief and Mary Shyla Sivasubramaniyam, Manager, Journal of Environmental Management for their attention and making this effort a success.

References Cazenave, A., Dieng, H.B., Meyssignac, B., von Schuckmann, K., Decharme, B., Berthier, E., 2014. The rate of sea-level rise. Nat. Clim. Change 4 (5), 358e361. Lobell, D.B., Burke, M.B., Tebaldi, C., Mastrandrea, M.D., Falcon, W.P., Naylor, R.L., 2008. Prioritizing climate change adaptation needs for food security in 2030. Science 319 (5863), 607e610. Madsen, S.T., 2013. State, Society and the Environment in South Asia. Routledge. SAARC country profiles, 2014. http://saarc-sec.org/india/. Shukla, P.R., Dhar, S., Mahapatra, D., 2008. Low-carbon society scenarios for India. Clim. Policy 8 (Suppl. 1), S156eS176. Turner, A.G., Annamalai, H., 2012. Climate change and the South Asian summer monsoon. Nat. Clim. Change 2 (8), 587e595.

Krishna Prasad Vadrevu* Department of Geographical Sciences, University of Maryland College Park, USA Chris Justice Department of Geographical Sciences, University of Maryland College Park, USA Thenkabail Prasad United States Geological Survey, Arizona, USA Narasimha Prasad Centre for Water Resources Development and Management, Kozhikode, Kerala, India Garik Gutman NASA Headquarters, Washington DC, USA *

Corresponding author.