Landscape approach for quantifying land use land cover change (1972–2006) and habitat diversity in a mining area in Central India (Bokaro, Jharkhand)

The rate and intensity of land use land cover (LULC) change has increased considerably during the past couple of decades. Mining brings significant alterations in LULC specifically due to its impact on forests. Parts of Central India are well endowed with both forests and minerals. Here, the conflict between human interests and nature has intensified over time. Monitoring and assessment of such conflicts are important for land management and policy making. Remote sensing and Geographical Information System have the potential to serve as accurate tools for environmental monitoring. Understanding the importance of landscape metrics in land use planning is challenging but important. These metrics calculated at landscape, class, and patch level provide an insight into changing spatiotemporal distribution of LULC and ecological connectedness. In the present study, geospatial tools in conjunction with landscape metrics have been used to assess the impact of coal mining on habitat diversity. LULC maps, change detection analysis, and landscape metrics have been computed for the four time periods (1972, 1992, 2001, and 2006). There has been a significant decline in forest cover especially of the Sal-mixed forests, both in area as well as quality, due to flouted mining regulations. Reclamation of mined lands has also been observed in some of the areas since 2001.     

A landscape approach for quantifying land-use and land-cover change (1976–2006) in middle Himalaya

With the growth of socio-economic activities, natural land cover is being modified for various development purposes. This has increased the rate of land-use and land-cover changes (LULCC), and thus, affecting the overall ecosystem health. LULCC mapping is an important tool for land management and monitoring. This paper presents LULCC analysis using remotely sensed data integrated into a Geographic Information System (GIS). LULCC was quantified using Markov analysis, and the associated probability of change for each class was predicted. Landscape metrics were also used to quantify the spatial and temporal changes in the area. The unique combination of these techniques support the conclusion that with increasing human activities, (1) the deforestation rate has increased, (2) forested areas have become increasingly fragmented, and (3) the forested areas have the highest probability of getting converted to some other land-use and land-cover (LULC) class.     

Modeling spatio-temporal change patterns of forest cover: a case study from the Himalayan foothills (India)

The present study used temporal remote sensing data for 1990, 2001 and 2006 to assess spatio-temporal patterns of forest cover changes in Shiwalik range of the Himalaya, Dehradun forest division. Forests are innately associated to human well-being. However, with the increasing anthropogenic activities, deforestation has increased. Quantitative change analysis of the forest cover for the past two decades provides valuable insight into the forest conservation vis-à-vis anthropogenic activities in the region. Spatio-temporal datasets along with biotic and abiotic variables provide opportunities to model the forest cover change further. The present study investigates forest cover change and predicts status of forest cover in the Dehradun forest division. Land Change Modeller (LCM) was used to predict status of forest cover for 2010 and 2015 using current disturbance scenarios. Comparing actual LULC of 2006 with the predicted LULC of 2006 validated change prediction model and agreement was 61.03%. The forested areas are getting degraded due to anthropogenic activities, but deforestation/degradation does not contribute much in expanding urban area. Agricultural areas and fallow lands are the main contributors to increased urban area. The study demonstrates the potential of geospatial tools to understand spatio-temporal forest cover change and generate the future scenarios.