ESTIMATION OF CROPPED AREA AND IRRIGATION WATER REQUIREMENT USING REMOTE SENSING AND GIS

Pub Date : 2020-01-01 DOI:10.36899/japs.2020.4.0103
R. Ahsen, Z. Khan, H. Farid, A. Shakoor, I. Ali
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引用次数: 4

Abstract

Land use-land cover (LULC) mapping has immerged as a useful and important Remote Sensing (RS) and Geographic Information System (GIS) technique for improving the management of natural resources for the progress of a country like Pakistan. Therefore, a research study was conducted to develop LULC maps for the District of Multan, Pakistan. For this purpose, economically available multi temporal (time series) images with acceptable resolution from satellite (LANDSAT 7 ETM+) were obtained for Rabi and Kharif season of 2011-12 to perform supervised classification and identification of crops in the study area. Image Processing was performed in ERDAS Imagine 2011 version for obtaining the high-class time series normalized difference vegetation indices (NDVI) for each LANDSAT 7 imagery. Four classes were targeted for crops out of the seven clusters created using target crop signatures with 95% maximum likely-hood. The resulting crop types were validated by 86 ground truthing points. Over all 74 % efficiency was found using error matrix technique. The regional irrigation water requirements of specific crops were estimated using the generated LULC maps of exerted crop area. The calculated cropped areas through ArcGIS 9.3 version were of 0.226 Mha for cotton, 0.207 Mha for wheat, 0.014 Mha for rice and 0.007 Mha for sugarcane. The total regional crop water requirement of the study area was of 1653.62 Mm3 for cotton, 911.25 Mm3 for wheat, 97.93 Mm3 for rice and 112.25 Mm3 for sugarcane. The LULC mapping technique should be used to develop a decision support system for water, land and other natural resources management at regional scale for efficient resource utilization and sustainable development.
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基于遥感和gis的作物种植面积和灌溉需水量估算
土地利用-土地覆被(LULC)制图已经成为一种有用和重要的遥感(RS)和地理信息系统(GIS)技术,用于改善巴基斯坦等国家的自然资源管理。因此,进行了一项研究,以制定巴基斯坦木尔坦地区的土地利用资源地图。为此,我们获取了2011-12年Rabi和Kharif季节经济可行且分辨率可接受的卫星(LANDSAT 7 ETM+)多时相(时间序列)图像,对研究区作物进行监督分类和识别。在ERDAS Imagine 2011版本中进行图像处理,获得LANDSAT 7各影像的高阶时间序列归一化植被指数(NDVI)。使用目标作物签名以95%最大似然创建的七个集群中的四个类别针对作物。所得到的作物类型通过86个地面测点进行验证。总体而言,使用误差矩阵技术发现74%的效率。利用生成的作物面积LULC图估算了特定作物的区域灌溉需水量。通过ArcGIS 9.3版计算的种植面积分别为棉花0.226 Mha、小麦0.207 Mha、水稻0.014 Mha、甘蔗0.007 Mha。研究区作物总需水量为棉花1653.62 Mm3、小麦911.25 Mm3、水稻97.93 Mm3、甘蔗112.25 Mm3。应利用土地利用和土地利用资源制图技术开发区域尺度的水、土地和其他自然资源管理决策支持系统,以实现资源的有效利用和可持续发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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