Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data
Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data
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DOI：
10.1016/j.rse.2004.12.018
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发表时间：
2005-04-15
影响因子：
13.5
通讯作者：
Turral, H
中科院分区：
文献类型：
--
作者：
Thenkabail, PS;Schull, M;Turral, H
本研究的总体目标是利用2001-2002年近连续时间序列（8天）、500米分辨率、7波段MODIS土地数据绘制恒河和印度河流域灌溉区地图。基于一个包含294个波段的大型文件，进行了多时间分析，这些文件由7个波段中的42个MODIS图像组成。从196个地点收集了补充的现场数据。研究开始于MODIS 7波段反射率数据的两种去云算法（CRAs）的开发，命名为：(a)蓝波段最小反射率阈值和(b)可见光波段最小反射率阈值。介绍了一系列分析时间序列MODIS数据的创新方法和途径，包括：(a) 42个日期中每个日期的亮度-绿度-湿度（BGW） RED-NIR二维特征空间（2-d FS）图，(b)使用RED-NIR单日期（RN-SD）图进行端元（光谱角）分析，(c)在单个图中结合多个RN-SD图建立RED-NIR多日期（rnmd）图，以帮助跟踪2-d FS中光谱类别的大小和方向变化。(d)引入独特的时空螺旋曲线（ST-SCs）概念，以连续跟踪时间和空间上的类别动态，并确定季节内和季节间不同时间段的类别可分离性；(e)基于NDVI （CS-NDVI）和/或多波段反射率（CS-MBR）为每个类别建立独特的类别特征，并展示其季节内和季节间以及年内和年际特征。这些技术和方法的结果使我们能够收集到每个灌溉和雨养类别的发病-峰值-衰老持续时间的精确信息。由此产生的土地利用/土地覆盖（LULC）图包括恒河和印度河流域133,021,156公顷研究区域内6个独特的灌区类别。其中，净灌溉面积3308万公顷，运河灌溉面积占26.6%，地下水灌溉面积占73.4万公顷。在33.08 Mha中，98.4%的面积在khariff（6 - 10月西南季风雨季）灌溉，92.5%的面积在Rabi（11 - 2月东北季风雨季）灌溉，只有3.5%的面积全年持续灌溉。定量模糊分类准确度评价（QFCAA）结果表明，29个类别的准确率在56% ~ 100%之间，其中17个类别的准确率在80%以上，23个类别的准确率在70%以上。以1240 nm为中心的MODIS波段5在灌区分类中具有最佳的可分离性，其次是波段2 （859 nm为中心）、波段7 （2130 nm）和波段6 （1640 rim）。(c) 2005爱思唯尔公司版权所有。
The overarching goal of this study was to map irrigated areas in the Ganges and Indus river basins using near-continuous time-series (8-day), 500-m resolution, 7-band MODIS land data for 2001-2002. A multitemporal analysis was conducted, based on a mega file of 294 wavebands, made from 42 MODIS images each of 7 bands. Complementary field data were gathered from 196 locations. The study began with the development of two cloud removal algorithms (CRAs) for MODIS 7-band reflectivity data, named: (a) blue-band minimum reflectivity threshold and (b) visible-band minimum reflectivity threshold.A series of innovative methods and approaches were introduced to analyze time-series MODIS data and consisted of. (a) brightness-greenness-wetness (BGW) RED-NIR 2-dimensional feature space (2-d FS) plots for each of the 42 dates, (b) end-member (spectral angle) analysis using RED-NIR single date (RN-SD) plots, (c) combining several RN-SDs in a single plot to develop RED-NIR multidate (RNMDs) plots in order to help track changes in magnitude and direction of spectral classes in 2-d FS, (d) introduction of a unique concept of space-time spiral curves (ST-SCs) to continuously track class dynamics over time and space and to determine class separability at various time periods within and across seasons, and (e) to establish unique class signatures based on NDVI (CS-NDVI) and/or multiband reflectivity (CS-MBR), for each class, and demonstrate their intra- and inter-seasonal and intra- and inter-year characteristics. The results from these techniques and methods enabled us to gather precise information on onset-peak-senescence-duration of each irrigated and rainfed classes.The resulting 29 land use/land cover (LULC) map consisted of 6 unique irrigated area classes in the total study area of 133,021,156 ha within the Ganges and Indus basins. Of this, the net irrigated area was estimated as 33.08 million hectares-26.6% by canals and 73.4z5 by groundwater. Of the 33.08 Mha, 98.4% of the area was irrigated during khariff (Southwest monsoonal rainy season during June-October), 92.5% irrigated during Rabi (Northeast monsoonal rainy season during November-February), and only 3.5% continuously through the year. Quantitative Fuzzy Classification Accuracy Assessment (QFCAA) showed that the accuracies of the 29 classes varied from 56% to 100%-with 17 classes above 80% accurate and 23 classes above 70% accurate.The MODIS band 5 centered at 1240 nm provided the best separability in mapping irrigated area classes, followed by bands 2 (centered at 859 nm), 7 (2130 nm) and 6 (1640 rim). (c) 2005 Elsevier Inc. All rights reserved.