首页> 外文期刊>International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences >GIS BASED ANALYSIS OF SPATIAL DISTRIBUTION OF NDVI FOR AGRICULTURAL APPLICATIONS IN SALEM DISTRICT – TAMIL NADU
【24h】

GIS BASED ANALYSIS OF SPATIAL DISTRIBUTION OF NDVI FOR AGRICULTURAL APPLICATIONS IN SALEM DISTRICT – TAMIL NADU

机译:基于GIS塞勒姆地区农业应用新型农业应用的空间分布分析 - 泰米尔纳德邦

获取原文
       

摘要

Remote sensing satellites in recent years have emerged as a vital tool for generating the biophysical information, which further helps to evolve the optimal land use plan for sustainable development of an area. The natural resources are to be categorized to obtain the area best suitable for crop production so that they could be better utilized in agricultural planning. The Normalized Difference Vegetation Index (NDVI) has been widely used to monitor moisture-related vegetation condition. The 8-day composite and spatial resolution of 250 m for the years 2002–2012 have obtained from the Moderate Resolution Imaging Spectro-radiometer (MODIS) Surface Reflectance (MOD09A) used for grouping biomass. The MOD09A product was selected because it consisted of both visible and infrared bands, which is requisite for deriving NDVI. The NDVI was used to determine the biomass categorization had four classes B1 (NDVI of 0.06–0.10), B2 (0.1 to 0.2), B3 (0.2–0.4) and B4 ( 0.4) which were rated as poor, moderate, good and excellent, respectively. Here, excellent biomass category was found to cover more area compared to other biomass categories. The per cent area covered under excellent category was (88.7 %) in Salem district. This showed that the agriculture area in this district is largely suitable for crop growth. The categorization of biomass as good to excellent in Salem might be due to the good seasonal (both monsoon) rainfall. It could pave way for better agricultural management and transfer of technology.
机译:近年来近年来遥感卫星作为生成生物物理信息的重要工具,这进一步有助于发展最佳的土地利用计划,以实现一个地区的可持续发展。自然资源将被分类以获得最适合作物生产的地区,以便在农业规划中可以更好地利用它们。归一化差异植被指数(NDVI)已被广泛用于监测水分相关的植被状况。 2002-2012年的800米的8天复合和空间分辨率从用于分组生物质的中等分辨率成像光谱辐射计(MOD09a)获得。选择MOD09A产品,因为它包括可见光和红外条带,这是导出NDVI的必要条件。 NDVI用于确定生物量分类的四类B1(NDVI为0.06-0.10),B2(0.1至0.2),B3(0.2-0.4)和B4(> 0.4),其被评为差,中等,良好和优秀分别。在这里,与其他生物量类别相比,发现优秀的生物量类别覆盖更多区域。塞勒姆地区优秀类别下涵盖的百分之九个面积(88.7%)。这表明该地区的农业区主要适合作物生长。生物质的分类为良好的塞勒姆优秀可能是由于季节性良好的季节性(季风)降雨量。它可以为更好的农业管理和技术转移铺平道路。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号