Temperature Vegetation Precipitation Dryness Index (TVPDI)-based dryness-wetness monitoring in China

被引:66
|
作者
Wei, Wei [1 ]
Pang, Sufei [1 ]
Wang, Xufeng [2 ]
Zhou, Liang [3 ]
Xie, Binbin [4 ]
Zhou, Junju [1 ]
Li, Chuanhua [1 ]
机构
[1] Northwest Normal Univ, Coll Geog & Environm Sci, Lanzhou 730070, Gansu, Peoples R China
[2] Chinese Acad Sci, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China
[3] Lanzhou Jiaotong Univ, Fac Geomat, Lanzhou 730070, Peoples R China
[4] Lanzhou City Univ, Sch Urban Econ & Tourism Culture, Lanzhou 730070, Gansu, Peoples R China
基金
中国国家自然科学基金;
关键词
Dryness indices; Dryness-wetness monitoring; Spatiotemporal variation; Remote sensing; China; SOIL-MOISTURE; RIVER-BASIN; DROUGHT; MODEL; MODIS; VALIDATION; DISTANCE;
D O I
10.1016/j.rse.2020.111957
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil Moisture (SM) is a direct indicator of dryness of the land surface, and the amount of precipitation (P), vegetation status, and Land Surface Temperature (LST) are directly related to SM; thus, these factors indirectly characterize the dryness of the land surface. However, there are limitations and shortcomings of using a single factor to assess dryness because of the interactions among factors. A method that can combine the advantages of the three factors is needed to better monitor dryness. In this study, a new Remote Sensing (RS) dryness index, called the Temperature Vegetation Precipitation Dryness Index (TVPDI), was defined and developed using the Euclidean distance method and three-dimensional (3D) P-Normalized Difference Vegetation Index (NDVI)-LST.The reasonableness of this index was tested and verified using SM data, three variables (P, NDVI, and LST), other recognized dryness indices, crop yield per unit area and Net Primary Productivity (NPP). In addition, the reliability of the TVPDI results was analyzed at different spatial scales and using different data sources. The results demonstrated that the TVPDI was highly correlated with SM (R > 0.64, p < .01) and exhibited better performance than the P, NDVI, and LST results. The time series of the TVPDI and other dryness indices exhibited spatially good consistency. The TVPDI was temporally well-matched to the crop yield per unit area and NPP in most regions of China, and performed better than other dryness indices. Furthermore, in the four sample regions, the TVPDIMODIS results closely matched the TVPDILandsat and Landsat image results, indicating that the TVPDI is a reliable and robust index for dryness monitoring to some extent. Moreover, the application of the TVPDI for dryness-wetness monitoring in China indicated significant spatiotemporal differences in the dryness-wetness status at both monthly and annual scales. The distribution of dryness in China exhibited obvious differences in different agricultural regions. In conclusion, the TVPDI is an RS dryness index that can be applied to dryness assessments.
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页数:18
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