Mahjoor Ahmad Lone
Articles written in Journal of Earth System Science
Volume 120 Issue 3 June 2011 pp 423-433
Land degradation reduces the ability of the land to perform many biophysical and chemical functions. The main aim of this study was to determine the status of land degradation in the Budgam area of Kashmir Himalaya using remote sensing and geographic information system. The satellite data together with other geospatial datasets were used to quantify different categories of land degradation. The results were validated in the field and an accuracy of 85% was observed. Land use/land cover of the study area was determined in order to know the effect of land use on the rate of land degradation. Normalized differential vegetation index (NDVI) and slope of the area were determined using LANDSAT-enhanced thematic mapper plus (ETM+) data, advanced space-borne thermal emission and reflection radiometer, and digital elevation model along with other secondary data were analysed to create various thematic maps, viz., land use/land cover, geology, NDVI and slopes used in modelling land degradation in the Kashmir Himalayan region. The vegetation condition, elevation and land use/land cover information of the area were integrated to assess the land degradation scenario in the area using the ArcGIS ‘Spatial Analyst Module’. The results reveal that about 13.19% of the study area has undergone moderate to high degradation, whereas about 44.12% of the area has undergone slight degradation.
Volume 121 Issue 4 August 2012 pp 1059-1070
Soil contamination by heavy metals has been a major concern for last few decades due to increase in urbanization and industrialization. The main objective of this research was to identify the heavy metal contaminated zones in the study area. Twenty five soil samples collected throughout the agriculture, residential and industrial areas were analysed by X-ray Fluorescence Spectrometer (XRF) for trace metals and major oxides. These metals can affect the quality of soil and infiltrate through the soil, thereby causing groundwater pollution. Based on the chemical analysis of major oxides (SiO2, Al2O3, Fe2O3, MnO, MgO, CaO, Na2O, K2O, TiO2, and P2O5) and their distribution; it is observed that these soils are predominantly siliceous type with slight enrichment of alumina component in the study area. Correlation matrix (CM) and factor analysis (FA) is employed to the heavy metal variables, viz., Ba, Cr, Cu, Ni, Pb, Rb, Sr, V, Y, Zn and Zr of the soil to determine the dominant factors contributing to the soil contamination in the area. In the analysis, five factors emerged as significant contributors to the soil quality. The total contribution of these five factors is about 90%. The contribution of the first factor is about 45% and has significant positive loadings of Co, Cr, Cu, Ni and Zn. The contribution of second factor is 22% and has significant positive loadings of Rb, Sr and Y. The contribution of third, fourth and fifth factors is 10, 8 and 5% and show positive loadings for lead, molybdenum and barium respectively to the soil contamination. The spatial variation maps deciphering different zones of heavy metal concentration in the soil were generated in a GIS (geographic information system) based environment using ArcGIS 9.3.1. The results reveal that heavy metal contamination in the area is mainly due to anthropogenic activities.
Volume 130, 2021
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