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Long-term agricultural performance and climate variability for drought assessment: a regional study from Telangana and Andhra Pradesh states, India

机译:长期农业绩效和气候变异性以进行干旱评估:来自印度特兰甘纳邦和安得拉邦的区域研究

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ABSTRACT A novel approach is presented to assess the agriculture performance in the states of Telangana and Andhra Pradesh using long-term fortnightly satellite, meteorological and irrigation data-sets. National Oceanic and Atmospheric Administration (NOAA), Global Inventory Modeling and Mapping Studies (GIMMS) and Normalized Difference Vegetation Index (NDVI) data for the period 1982?¢????2000 were used to study the pattern of anomalies in the NDVI anomalies and Standardized Precipitation Index (SPI) in the agriculture areas to capture the drought events. After hierarchical image classification and field observations, the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI product was used to generate the cropped area. The deviation of the NDVI (NDVI Dev ) was used to understand the agricultural growth/stress, variations in the cropped area and per cent fluctuation in space and time. The SPI, derived from the rainfall data pertaining to 2000?¢????2015, was used to determine the distribution of precipitation. The crop area (%) and growth conditions during the different cropping seasons agree well with the prevailing drought conditions. A significant ( p < 0.05) relation was found between the NDVI and precipitation in the summer monsoon each year except during excellent summer monsoon year. The seasonal precipitation, residual soil moisture and source of irrigation were also found to have significant ( p < 0.05) impacts on the winter and summer crops.
机译:摘要提出了一种新颖的方法,该方法使用每两周的长期卫星,气象和灌溉数据集来评估Telangana和安得拉邦的农业表现。国家海洋和大气管理局(NOAA),全球清单建模和制图研究(GIMMS)和归一化植被指数(NDVI)1982年至2000年期间的数据用于研究NDVI异常中的异常模式农业领域的标准化降水指数(SPI)以记录干旱事件。在对图像进行分级分类和现场观察之后,使用中分辨率成像光谱仪(MODIS)NDVI产品生成裁剪区域。 NDVI(NDVI Dev)的偏差用于了解农业的增长/压力,作物面积的变化以及时空的百分比波动。 SPI是从2015年的降水数据中得出的,用于确定降水分布。不同作物季节的作物面积(%)和生长条件与当前干旱条件非常吻合。除极好的夏季风季节外,每年夏季风的NDVI与降水之间都存在显着的(p <0.05)关系。还发现季节性降水,残留土壤水分和灌溉来源对冬季和夏季农作物有显着影响(p <0.05)。

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