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首页> 外文期刊>Quaternary International >Object-based identification of vegetation cover decline in irrigated agro-ecosystems in Uzbekistan
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Object-based identification of vegetation cover decline in irrigated agro-ecosystems in Uzbekistan

机译:基于对象的乌兹别克斯坦灌溉农业生态系统植被覆盖率下降

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摘要

The sustainability of irrigated croplands in Central Asia is threatened by degradation of their productive function. To quantify the extent of the cropland degradation, this paper combines object-based change detection and spectral mixture analysis for vegetation cover decline mapping in irrigated agro-ecosystems in Uzbekistan based on multitemporal Landsat TM images from 1998 to 2009. The results of the change detection reveal that the cadastral field parcels, characterized by vegetation cover decrease, occupied 18% (52,938 ha) of the cropland area. Spatial distribution of fields with decreased vegetation cover was mainly associated with abandoned cropland and land with inherently low-fertility soils located on the outreaches of the irrigation system and bordering natural sandy deserts. The comparison with the land degradation map based on trend analyses of 250 m MODIS NDVI time series 2000-2010 yielded an overall agreement of 93%. The proposed approach is a useful supplement to the commonly applied trend analysis for detecting land degradation in cases when plot-specific data are needed but satellite time series of high spatial resolution are not available. The derived parcel-specific, spatial information supports better informed decisions on cropland rehabilitation measures.
机译:中亚灌溉农田的可持续性受到其生产功能下降的威胁。为了量化农田退化的程度,本文基于1998年至2009年的多时相Landsat TM影像,结合了基于对象的变化检测和光谱混合分析,以对乌兹别克斯坦灌溉农业生态系统中的植被覆盖度进行测绘。变化检测的结果揭示了以植被覆盖减少为特征的地籍地块,占耕地面积的18%(52,938公顷)。植被覆盖度降低的田地的空间分布主要与废弃农田和灌溉系统和天然沙质沙漠接壤的土壤肥力低的土地有关。与基于250 m MODIS NDVI时间序列2000-2010趋势分析的土地退化图的比较得出的总体一致性为93%。所提出的方法是对常用趋势分析的有用补充,这种趋势分析用于在需要特定于地块的数据但没有高空间分辨率的卫星时间序列的情况下检测土地退化的情况。所导出的特定于包裹的空间信息支持对农田恢复措施的更明智的决策。

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  • 来源
    《Quaternary International》 |2013年第17期|163-174|共12页
  • 作者单位

    Center for Development Research, University of Bonn, Walter-Flex Str. 3, 53113 Bonn, Germany,Remote Sensing Research Croup, Department of Geography, University of Bonn, Meckenheimer Allee 166, 53115 Bonn, Germany,Centre for the Development Studies (ZEF), University of Bonn, Walter-Flex-Str. 3, D-53113 Bonn, Germany;

    Remote Sensing Research Croup, Department of Geography, University of Bonn, Meckenheimer Allee 166, 53115 Bonn, Germany,Center for Remote Sensing of Land Surfaces, University of Bonn, Walter-Flex Str. 3, 53113 Bonn, Germany;

    Remote Sensing Unit, Institute of Geography and Geology, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany;

    Center for Remote Sensing of Land Surfaces, University of Bonn, Walter-Flex Str. 3, 53113 Bonn, Germany;

    Center for Development Research, University of Bonn, Walter-Flex Str. 3, 53113 Bonn, Germany;

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