No abstract

A b s t r a c t A r t i c l e I n f oAgriculture continues to be the backbone of Third World economies. In India, more than two-thirds of population depends on agriculture. Agriculture provides the principal means of livelihood for over 58.4% of India's population. So the promotion of agriculture is an integral part of developmental programmes. The advances through information technology and space technology need to be extended to agriculture as well. Agriculture is always vulnerable, because of unfavorable weather and climatic conditions. So, it needs constant monitoring to improve crop productivity. The linkages among crop varieties, irrigation, soil characteristics, weather, etc., which are the key factors in agricultural productivity can be effectively made with the help of Remote Sensing and GIS tools. Crop Simulation Model (CSM) is a valuable tool to researchers to help them to understand the influence of climatic variables on crop productivity. Simulation models also provide global edge to the farmers and researchers since they are objective, fast and cost effective. The scope of applicability of these simulation models can be extended too much broader scales for regional planning and policy analysis by combining their capabilities with a Geographic Information System (GIS). The principle of this study appeal to review on Remote Sensing (RS), GIS and CSM, and on types of models and its limitations. Overview of CSM models in the current scenario, as well utilization of RS and GIS tools that model the impacts of agricultural interventions.

The presence of fluoride in the groundwater in the Thirukkazhukundram Block in south India is now becoming an increasingly alarming issue. With the semi-arid climatic conditions, charnockite and gneiss rocks form the basement, contributing to the geology of the study area. The pre-monsoon (August 2016) and post-monsoon (February 2017) fluoride concentrations have an average output of 1.3 mg.L-1 and 0.72 mg.L-1 respectively. As of date, only in Neikuppi, the fluoride contamination is found to be 2 mg.L-1 in pre-monsoon which is beyond the accepted limit as per the WHO standards. Other 29 locations taken up for study have fluoride value fluctuation from 1 mg.L-1 to 2 mg.L-1 in the pre-monsoon and from 0 to 1.5 mg.L-1 in the post-monsoon. The main factor responsible for this fluoride contamination lies in the study area’s hydro-geological condition which must be attended to immediately to prevent a public health problem in the future.

No abstract

Change detection is the measure of the distinct data framework and thematic change information that can guide to more tangible insights into underlying process involving land cover and land use changes than the information obtained from continuous change. Land use / Land cover analysis of the semi-urban area was carried out using Landsat TM and ETM+ imageries through Remote sensing software for Vellore district in Tamil Nadu, India. This study attempts to explore the changes along the study areas, two sets of Landsat Thematic Mapper (TM) data were used. TM data are useful for this type of study due to its high spatial resolution, spectral resolution and low repetitive acquisition (16 days).This paper discusses the land use/land cover analysis and change detection techniques using temporal multi-spectral data (1991 and 2001) of the LANDSAT TM images, systematically assessed, and checked in field. Initially 18 major classes were observed for both the images. To minimize similar features, relevant classes were reorganized to end up with 8 classes. The overall accuracy for a 1991 image is 78% and for a 2001 image is 80%. The results demonstrate that the study area experienced a rapid, decrease in forest cover, conversion of wetland vegetation to barren / dry farming, rural to urban conversion in town and municipalities resulting in decreasing ground water table in the 10 year period between 1991 and 2001.