India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for Remote Sens. 2015, 7 2403 comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

The latest tiger census conducted in India during the year 2014 shows that it harbors 57% of the global tiger population in 7% of their historic global range. At the same time, India has 1.25 billion people growing at a rate of 1.7% per year. Protected tiger habitats in India are geographically isolated and collectively holds this tiger population under tremendous anthropogenic pressure. These protected lands are in itself not enough to sustain the growing tiger population, intensifying human-tiger conflict as dispersing individuals enter human occupied areas. These factors-isolation and inadequate size of the protected lands harboring tiger meta-populations, highlight the need to connect tiger habitats and the importance of corridors beyond protected lands. It is imperative to conserve such corridors passing through private lands to safeguard the long-term survival of the tigers in India. The goal of long-term tiger conservation in India lies in smartly integrating tiger conservation concerns in various sectors where tiger conservation is not the priority. To effectively tap into all these resources, we propose a "Triage of Means" strategy. Here we do not prioritize species, populations or sites due to the non-availability of conservation resources. Instead, we aim to channel from available resources (means to achieve conservation) from other sectors where tiger conservation is not the focus. We outline how to prioritize resources available from various sectors into conservation by prioritizing issues hampering tiger conservation beyond protected habitats.

As ecological data and associated analyses become more widely available, synthesizing results for effective communication with stakeholders is essential. In the case of wildlife corridors, managers in human‐dominated landscapes need to identify both the locations of corridors and multiple stakeholders for effective oversight. We synthesized five independent studies of tiger (Panthera tigris) connectivity in central India, a global priority landscape for tiger conservation, to quantify agreement on landscape permeability for tiger movement and potential movement pathways. We used the latter analysis to identify connectivity areas on which studies agreed and stakeholders associated with these areas to determine relevant participants in corridor management. Three or more of the five studies’ resistance layers agreed in 63% of the study area. Areas in which all studies agree on resistance were of primarily low (66%, e.g., forest) and high (24%, e.g., urban) resistance. Agreement was lower in intermediate resistance areas (e.g., agriculture). Despite these differences, the studies largely agreed on areas with high levels of potential movement: >40% of high average (top 20%) current‐flow pixels were also in the top 20% of current‐flow agreement pixels (measured by low variation), indicating consensus connectivity areas (CCAs) as conservation priorities. Roughly 70% of the CCAs fell within village administrative boundaries, and 100% overlapped forest department management boundaries, suggesting that people live and use forests within these priority areas. Over 16% of total CCAs’ area was within 1 km of linear infrastructure (437 road, 170 railway, 179 transmission line, and 339 canal crossings; 105 mines within 1 km of CCAs). In 2019, 78% of forest land diversions for infrastructure and mining in Madhya Pradesh (which comprises most of the study region) took place in districts with CCAs. Acute competition for land in this landscape with globally important wildlife corridors calls for an effective comanagement strategy involving local communities, forest departments, and infrastructure planners.

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ABSTRACT:The Lower Gangetic Basin is one of the most highly populated areas of India, covering an area of 286,899 km 2 with a population density of 720 persons per km 2 . 64% of the area is covered under agriculture which is supported by the highly fertile alluvial soil. Landuse and landcover (LULC) changes due to an ever increasing human population, natural disasters induced by climate change can alter agricultural productivity which in turn can affect the food security of the region. The current study found out the change in LULC over a span of 20 years , and identified the factors driving this change. LULC data was generated from geo-corrected satellite data of LANDSAT-MSS, IRS LISS-I and IRS LISS-III for pre monsoon and post monsoon seasons for the years 1985-86, 1994-95 and 2004-05 respectively, using onscreen visual interpretation at 1:250,000 scale. We used cross-tabulation matrix to investigate landuse and landcover transformation. The most significant transformation has been to built-up category, contributed by agricultural land (515 km 2 ) and scrubland (53 km 2 ). The other notable transformations are from agriculture to plantation (247 km 2 ), fallow to scrubland (838 km 2 ) and from water body to scrubland (407 km 2 ). We generated change no-change matrix and analyzed it using logistic regression to investigate the drivers of LULC change. We identified availability of water for irrigation, literacy, sexratio and the availability of different sources of livelihoods, as the major drivers of LULC change in the Lower Gangetic Basin.