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首页> 外文期刊>Photogrammetric Engineering & Remote Sensing: Journal of the American Society of Photogrammetry >Mapping Crop Types, Irrigated Areas, and Cropping Intensities in Heterogeneous Landscapes of Southern India Using Multi-Temporal Medium-Resolution Imagery: Implications for Assessing Water Use in Agriculture
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Mapping Crop Types, Irrigated Areas, and Cropping Intensities in Heterogeneous Landscapes of Southern India Using Multi-Temporal Medium-Resolution Imagery: Implications for Assessing Water Use in Agriculture

机译:使用多时相中分辨率图像绘制印度南部异质景观中的作物类型,灌溉面积和耕种强度:对农业用水的评估意义

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摘要

In regions of water scarcity, mapping individual crops, cropping intensities and irrigation can contribute significantly to understanding agricultural water use. But such mapping is challenging in landscapes dominated by small-scale traditional agricultural land holdings with high spatial and temporal heterogeneity. Here, we assessed the benefit of using multi-temporal 24 m resolution LiSS-lli imagery to characterize cropping systems in the Mala-prabha basin of southern India. We used hierarchical stacked supervised classification to create three increasingly detailed maps showing: (a) single rainfed paddy rice versus continuously irrigated sugarcane, (b) irrigated versus rainfed areas, and (c) multiple cropping. Although increasing detail was accompanied by decreasing overall accuracies (89 percent, 74.6 percent and 60.1 percent respectively), using multi-temporal imagery out-performed single imagery alone in all cases. Results also led to higher estimates of total (69.8 percent) and irrigated (34.7 percent) cropland than previous single-imagery studies and census data, revealing the high uncertainty in crop estimates in this region.
机译:在缺水地区,绘制单种作物,耕种强度和灌溉的地图可以极大地有助于了解农业用水。但是,在以传统的小规模农耕土地为主导,具有高时空异质性的景观中,这种制图具有挑战性。在这里,我们评估了使用多时相24 m分辨率LiSS-lli图像来表征印度南部Mala-prabha盆地种植系统的好处。我们使用分层堆叠监督分类来创建三个越来越详细的地图,这些地图显示:(a)单个雨养水稻与连续灌溉的甘蔗,(b)灌溉与雨养区域,以及(c)多种作物。尽管随着细节的增加,总体准确性下降(分别为89%,74.6%和60.1%),但在所有情况下使用多时相影像均胜过单独的影像。结果还导致对总耕地(69.8%)和灌溉耕地(34.7%)的估计高于以前的单图像研究和人口普查数据,这表明该地区收成估计的高度不确定性。

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