A remotely sensed global terrestrial drought severity index

Qiaozhen Mu, Maosheng Zhao, John S. Kimball, Nathan G. McDowell, Steven W. Running

Research output: Contribution to journalArticlepeer-review

353 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)83-98
Number of pages16
JournalBulletin of the American Meteorological Society
Volume94
Issue number1
DOIs
StatePublished - Jan 2013

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