A REMOTELY SENSED GLOBAL TERRESTRIAL DROUGHT SEVERITY INDEX

被引:345
|
作者
Mu, Qiaozhen [1 ]
Zhao, Maosheng [1 ]
Kimball, John S. [2 ]
McDowell, Nathan G. [3 ]
Running, Steven W. [1 ]
机构
[1] Univ Montana, Numer Terradynam Simulat Grp, Coll Forestry & Conservat, Missoula, MT 59812 USA
[2] Univ Montana, Flathead Lake Biol Stn, Polson, MT 59860 USA
[3] Los Alamos Natl Lab, Atmospher & Environm Dynam Grp, Los Alamos, NM USA
关键词
NET PRIMARY PRODUCTION; INDUCED REDUCTION; VEGETATION INDEX; FLUX MEASUREMENT; SOIL-MOISTURE; HEAT-FLUX; MODIS; WATER; PRODUCTS; IMPACTS;
D O I
10.1175/BAMS-D-11-00213.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
A new global index used operational satellite remote sensing as primary inputs and enhances near real-time drought monitoring and mitigation efforts. A DSI algorithm was developed using satellite-derived ET, PET, and NDVI products to detect and monitor droughts on a global basis. The DSI algorithm was developed to overcome several limitations and to exploit the relative volume of operational satellite records and associated vegetation indicators. The input datasets and the DSI model were introduced and DSI patterns and anomalies in relation to alternative global PDSI information and documented regional drought events. The MODIS operational net primary production (NPP) product was used as an indicator of vegetation productivity changes under documented severe droughts in the Amazon, Europe, and Russia, and to evaluate corresponding DSI- and PDSI-based vegetation drought responses.
引用
收藏
页码:83 / 98
页数:16
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