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Soil drought monitoring based on Landsat time-series images and nonlinear edges: A case study of the growing season in Inner Mongolia section of the Yellow River from 1986 to 2020
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摘要: 土壤温度植被干旱指数（TVDI）是表征土壤干旱状态的常用指标，土地利用/覆被（LULC）类型、LST-NDVI特征空间的干燥与湿润边界的非线性属性是TVDI遥感反演过程需要考虑的问题，然而前人的研究与应用大多忽视了这些条件，带来了部分误差。选取黄河流域典型资源驱动型河段内蒙古“几”字湾都市圈（呼包巴鄂乌五市）作为研究对象，以1986—2020年8期816景Landsat-5/8时序影像和同期30 m土地利用/覆被栅格数据为数据源，剔除建设用地和水体，采用无缝拼接和生长季均值合成重构LST-NDVI特征空间，在4类LULC下，非线性拟合干燥边界和湿润边界，反演得到8期经验证精度可靠的黄河内蒙古段的土壤表层干旱等级空间分布100 m栅格。研究结果可为区域性的土壤旱情预测提供理论参考和技术借鉴。Abstract: Soil temperature vegetation drought index (TVDI) is a commonly used indicator to characterize soil drought state. Land use/cover (LULC) types and nonlinear properties of dry edge and wet edge in LST-NDVI feature space are issues that need to be considered in TVDI remote sensing inversion process. However, most of the previous studies and applications of TVDI ignored these conditions, thus causing part of the error. In order to improve the inversion accuracy of TVDI with long time and wide space, this study took the Chinese character “Ji” shaped bay of the Yellow River basin, a typical resource-driven region, including five cites of Inner Mongolia Autonomous Region, namely, Hohhot, Ordos, Bayannur, Baotou and Wuhai, as a study area. A long time series Landsat data composed of 816 scences of image, during the local vegetation growing season, in eight periods, during 1986 to 2020, as well as contemporaneous 30 m LULC rasters, were used in this study. After excluding construction land and water body, the LST-NDVI feature spaces were rebuilt by seamless mosaicing and mean value synthesis of NDVI and LST during vegetation growth season under the four LULC types. Then their dry edges and wet edges were fitted through polynomial of higher power. Finally, eight 100 m TVDI grids, proven to be accurate, of soil surface in Inner Mongolia section of the Yellow River were obtained. The results of this work could provide theoretical reference and technical guidance for regional soil drought prediction.
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图 1 研究区地理信息和所用Landsat影像行列号
Figure 1. Geographical information of study area and the path and row numbers of Landsat images
图 2 被指数与地表温度特征空间和非线性干湿边界遥感反演TVDI原理示意
Figure 2. Vegetation index and surface temperature space and schematic diagram of TVDI remote sensing version based on the nonlinear dry and wet edges
图 3 1986—2020年黄河内蒙古段4类土地利用下LST-NDVI特征空间干燥边界与湿润边界非线性拟合结果
Figure 3. Non-linear fitting results of dry edge and wet edge of LST-NDVI space in Inner Mongolia section of the Yellow River under four land use types from 1986 to 2020
图 4 1986—2020年黄河内蒙古段TVDI空间分布和土地利用/覆被面积变化
Figure 4. Spatial distribution of TVDI and changes of land use/cove ratio in Inner Mongolia section of the Yellow River
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