Arnab Kundu

Monitoring the extent of desertification processes in western Rajasthan (India) using geo-information science

Desertification is considered as a major worldwide environmental problem mainly caused by the climate changes and human activities during the last decades. Areas affected by desertification processes are gradually losing their level of biological quality and productivity. Among the different indicators of desertification, degradation of vegetation cover and increasing amount of bare soil have been popularly used by researchers. In India, desertification is one of the major sluggish hazards which is found in northwestern part of this country, mainly in the state of Rajasthan. The infringement of the Thar Desert has become a serious problem in the adjoining districts of Bikaner, Churu, and Nagaur. In this study, a linear spectral unmixing (LSU) method has been used for end-member fraction estimation primarily to differentiate the sand percentage and vegetation cover percentage. This linear spectral unmixing model is a widely used technique in remote sensing to estimate the fractions of several individual surface components present in an image pixel and the pure reflectance spectrum of a component which is called end-member. The LSU technique is able to monitor desertification process in terms of fractional changes in bare soil (sand) and vegetation covers. These two land features are the most crucial indicator of desertification and their long-term changes can produce expected result in identification of desertification process in an area. The long-term multispectral satellite data such as Landsat Thematic Mapper (TM) (1990, 1995, and 1999) and Enhanced Thematic Mapper (ETM+) (2003, 2009) have been used in this study. The time series analysis of fractional images of vegetation cover and bare soil has been employed for monitoring desertification processes over a long period. After analyzing the changes, some distinct patches of vegetation depletion coupled with increasing bare soil fraction were identified within the region that clearly indicates the ongoing process of desertification over there.

Monitoring the vegetation health over India during contrasting monsoon years using satellite remote sensing indices

The detection and monitoring of drought-related vegetation stress over a large spatial area have become possible with the use of satellite-based remote sensing indices, namely, vegetation condition index (VCI) and temperature condition index (TCI). In particular, the water (precipitation)-related moisture stress during drought may be determined using the VCI, while the temperature-related stress using the TCI. An attempt is made here to investigate and demonstrate the importance of these indices over India during the contrasting monsoon years, 2009, 2010, and 2013, termed as meteorological drought, wet, and normal monsoon years, respectively. The overall health of the vegetation during these years is compared using the vegetation health index (VHI). The advantage of VHI over the VCI and TCI is also shown. An assessment of drought over India is then made using the combined information of VCI, TCI, and VHI. The occurrence of vegetative drought over Rajasthan, Gujrat, and Andhra Pradesh is confirmed using drought assessment index, which shows very low value (well below 40) during 2009 over these regions. The area-averaged time series indices as well as spatial maps over the state of Uttar Pradesh show higher thermal stress and poor vegetation health during 2009 as compared to 2010 and 2013. The standardized precipitation index (SPI) and standardized water-level index (SWI) are used to validate the results obtained using the remote sensing indices.

A geo-spatial study on spatio-temporal growth of brackish water aquaculture along the coastal areas of West Bengal (India)

The present study seeks to identify the landuse changes occurring due to haphazard growth of brackish water fisheries along the coastal areas of West Bengal through remote sensing and GIS techniques. High resolution multi-temporal Google Earth images were used for detecting spatio-temporal changes of two blocks of Contai sub-division located in Midnapore district of West Bengal. Also, the area was surveyed with GPS and the digitized maps were verified using the information collected from the aquaculture farm owners. It is evident from change detection analysis that a significant amount of area under agricultural land has been converted into aquaculture farm and also a large number of pre-existing ponds have been converted into brackish water fisheries. Remote sensing derived statistical information on inland fisheries of Contai II and III blocks reveals that area under brackish water fisheries has increased about 2950 acres within the period 2006 to 2011.