Soil erosion is a growing problem especially in areas of agricultural activity where soil erosion not only leads to decreased agricultural productivity but also reduces water availability. Universal Soil Loss Equation (USLE) is the most popular empirically based model used globally for erosion prediction and control. Remote sensing and GIS techniques have become valuable tools specially when assessing erosion at larger scales due to the amount of data needed and the greater area coverage. The present study area is a part of Chotanagpur plateau with undulating topography, with a very high risk of soil erosion. In the present study an attempt has been made to assess the annual soil loss in Upper South Koel basin using Universal Soil Loss Equation (USLE) in GIS framework. Such information can be of immense help in identifying priority areas for implementation of erosion control measures. The soil erosion rate was determined as a function of land topography, soil texture, land use/land cover, rainfall erosivity, and crop management and practice in the watershed using the Universal Soil Loss Equation (for Indian conditions), remote sensing imagery, and GIS techniques. The rainfall erosivity R-factor of USLE was found as 546 MJ mm/ha/hr/yr and the soil erodibility K-factor varied from 0.23 - 0.37. Slopes in the catchment varied between 0% and 42% having LS factor values ranging from 0 - 21. The C factor was computed from NDVI (Normalized Difference Vegetative Index) values derived from Landsat-TM data. The P value was computed from existing cropping patterns in the catchment. The annual soil loss estimated in the watershed using USLE is 12.2 ton/ha/yr. <p> </p>
The quantitative analysis of drainage system is an important aspect of characterization of watersheds. Morphometry is measurement and mathematical analysis of landforms. The present study is an attempt to evaluate the drainage morphometrics of Upper South Koel Basin using Remote Sensing and GIS approach. A morphometric analysis was carried out to describe the topography and drainage characteristics of Upper South Koel watershed. The stream numbers, orders, lengths and other morphometric parameters like bifurcation ratio, drainage density, stream frequency, shape parameters etc. were measured. The drainage area of Upper South Koel watershed is 942.4 sq km and the drainage pattern is dentritic. The watershed was classified as 6<sup>th</sup> order drainage basin. The low values of bifurcation ratio and drainage density suggest that the area has not been much affected by structural disturbances. The study reveals that the different geomorphic units in the study area <i>i.e.</i> Structural hills, Pediments, Valley fills, Pediplains formed under the influence of permeable geology, are moderate to nearly level plains, with medium to low drainage density (<2.0) & low cumulative length of higher order streams . Such studies can be of immense help in planning and management of river basins
Reflectance and emittance spectroscopy in the near-infra red and short-wave infra red offers a rapid, Inexpensive, non-destructive tool for determining the mineralogy of rock and soil samples. Hyperspectral remote sensing has the potential to provide the detailed physico-chemistry (mineralogy, chemistry, morphology) of the earth's surface. This information is useful for mapping potential host rocks, alteration assemblages and mineral characteristics, in contrast to the older generation of low spectral resolution systems. In the present study EO-1, hyperion data has been used for the delineation of AL+OH minerals. The requirements for extracting bauxites from Hyperion images is to first compensate for atmospheric effects using cross track illumination correction & the log residual calibration model. MNF transformation was applied to reduce the data noise and for extracting the extreme pixels. Some pure pixel end member for the target mineral and the backgrounds were used in this study to account for the spectral angle mapping & matched filtering and the results were validated with the respect of field study.
Drought is a recurrent phenomenon in Jharkhand. It affects the livelihoods of the majority of its people, particularly tribals and dalits living in rural areas. Twelve of the 24 districts of the state, covering 43% of the total land area, are covered under the Drought Prone Areas Programme (DPAP). Hunger and starvation deaths are reported almost every year. Vegetation moisture content is one of the key parameters in drought monitoring, agricultural modelling and forest health mapping. In this paper the three different approaches is described using Advanced Spaceborne Thermal Emission & Reflection Radiometer (ASTER) data for measuring the vegetation moisture content in a part of Palamu Commissionaire of Jharkhand state, which is prone to severe drought. ASTER thermal data was used to calculate land surface temperature using Normalized Differential Vegetation Index (NDVI) emissivity correction method. Reflective bands are used to determine NDVI, Modified Soil Adjustment Vegetation Index (MSAVI) & Normalised Differential Water Index (NDWI). The three different vegetation moisture estimation methods namely MSAVI-LST (land surface temperature) feature space identification, NDWI & Vegetation Dryness Index (VDI) is applied to determine the vegetation moisture level. The results of three methods were classified and final moisture content map was produced. The result was validated using rainfall data of study area. This study indicates that by proper pre-processing of ASTER data, it can be used to estimate the land surface temperature and vegetation moisture content and can be used for drought prediction.
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