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首页> 外文期刊>Journal of Water and Land Development >High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico
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High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico

机译:用于检测墨西哥中部雨养农业生态系统中农业干旱影响的高精度土地利用土地覆盖(LULC)地图

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Satellite remote sensing provides a synoptic view of the land and a spatial context for measuring drought impacts, which have proved to be a valuable source of spatially continuous data with improved information for monitoring vegetation dynamics. Many studies have focused on detecting drought effects over large areas, given the wide availability of low-resolution images. In this study, however, the objective was to focus on a smaller area (1085 km2) using Landsat ETM+ images (multispectral resolution of 30 m and 15 m panchromatic), and to process very accurate Land Use Land Cover (LULC) classification to determine with great precision the effects of drought in specific classes. The study area was the Tortugas-Tepezata sub watershed (Moctezuma River), located in the state of Hidalgo in central Mexico. The LULC classification was processed using a new method based on available ancillary information plus analysis of three single date satellite images. The newly developed LULC methodology developed produced overall accuracies ranging from 87.88% to 92.42%. Spectral indices for vegetation and soil/vegetation moisture were used to detect anomalies in vegetation development caused by drought; furthermore, the area of water bodies was measured and compared to detect changes in water availability for irrigated crops. The proposed methodology has the potential to be used as a tool to identify, in detail, the effects of drought in rainfed agricultural lands in developing regions, and it can also be used as a mechanism to prevent and provide relief in the event of droughts.
机译:卫星遥感提供了土地的概况视图和用于测量干旱影响的空间背景,事实证明,卫星遥感是空间连续数据的宝贵来源,并具有用于监测植被动态的改进信息。鉴于低分辨率图像的广泛可用性,许多研究都集中在检测大面积的干旱影响上。但是,在这项研究中,目标是使用Landsat ETM +图像(全色分辨率为30 m和15 m的多光谱分辨率)专注于较小的区域(1085 km2),并进行非常准确的土地使用土地覆盖(LULC)分类以确定在特定类别中,干旱的影响非常精确。研究区域是位于墨西哥中部伊达尔戈州的Tortugas-Tepezata子流域(Moctezuma河)。基于可用的辅助信息以及对三个单日卫星图像的分析,使用一种新方法处理了LULC分类。新开发的LULC方法论产生的总体准确度从87.88%到92.42%。利用植被和土壤/植被水分的光谱指数检测干旱引起的植被发育异常;此外,对水体面积进行了测量和比较,以检测灌溉作物的可用水量变化。拟议的方法有可能被用作详细查明发展中地区雨养农业土地上干旱影响的工具,也可以用作预防干旱的方法并提供干旱救济。

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