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Mapping of Agriculture Drought Using Remote Sensing and GIS
Agriculture drought occurs when moisture level in soils is insufficient to maintain average crop yields. Initial consequences are in the reduced seasonal output of crops & other related production. An extreme agricultural drought can lead to a famine, which is a prolonged shortage of food in a restricted region causing widespread diseases and deaths from starvation. Agriculture drought is mainly dependent on low rainfall which results in agricultural production.
This study demonstrates the use of Remote Sensing and GIS in the mapping of drought. In the present work, an effort has been made to assess drought condition using temporal images from Landsat TM, ETM+ in Jodhpur District, particularly where the occurrence of drought is high. The Landsat-7 ETM+ and Landsat-5 TM satellite sensor data were used for calculating Brightness Temperature (BT), Land Surface Temperature (LST). Correlation and regression analysis was performed between Normalized Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Food Grain Anomaly.
BT was converted to the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), which are useful indices for the estimation of vegetation health and agriculture drought. The yield and production analysis of crops analysis was carried out for a period of 21 years (1991-2011). On the basis of the satellite-based indices, the study area was divided into several drought categories;moderate, mild, no drought using GIS software. It was found that in years 2000, 2002 and 2010, the entire study area was affected by moderate drought with greater intensity.
This study demonstrates the use of Remote Sensing and GIS in the mapping of drought. In the present work, an effort has been made to assess drought condition using temporal images from Landsat TM, ETM+ in Jodhpur District, particularly where the occurrence of drought is high. The Landsat-7 ETM+ and Landsat-5 TM satellite sensor data were used for calculating Brightness Temperature (BT), Land Surface Temperature (LST). Correlation and regression analysis was performed between Normalized Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Food Grain Anomaly.
BT was converted to the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), which are useful indices for the estimation of vegetation health and agriculture drought. The yield and production analysis of crops analysis was carried out for a period of 21 years (1991-2011). On the basis of the satellite-based indices, the study area was divided into several drought categories;moderate, mild, no drought using GIS software. It was found that in years 2000, 2002 and 2010, the entire study area was affected by moderate drought with greater intensity.
Keywords
Drought Indices, Remote Sensing and GIS, Crop Yield and Production.
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