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Proceedings Paper

Assessing the sensitivity of two new indicators of vegetation response to water availability for drought monitoring
Author(s): Li Jia; Guangcheng Hu; Jie Zhou; Massimo Menenti
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Paper Abstract

Two new drought indicators based on satellite observations of vegetation index and land surface temperature, i.e. the Normalized Temperature Anomaly Index (NTAI) and the Normalized Vegetation Anomaly Index (NVAI) were applied to monitor drought events in different regions in China and India. We carried out this analysis for drought events with distinct duration, intensity and surface condition in 2006 in Sichuan-Chongqing, in 2009 in Inner-Mongolia (China) and in the Ganga basin (India) using the MODIS LST and NDVI data products and TRMM rainfall data for the period 2001 – 2010. Two newly proposed drought indicators NVAI and NTAI were evaluated against widely accepted indicators such as Precipitation Anomaly Percentage (PAP), Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). The results show that NTAI and NVAI responded consistently to climate forcing. Long lasting rainfall anomalies led to severe drought and anomalies in rainfall, anomalies in NTAI appeared almost simultaneously and followed by negative anomaly in NVAI. The two new drought indicators NTAI and NVAI can distinguish the stages of drought evolution. The sensitivity of the indicators and of their anomalies to drought conditions and severity was also evaluated against drought assessments by operational drought monitoring services, documented how well the indicators meet expectations on the timely and reliable detection of environmental change.

Paper Details

Date Published: 21 November 2012
PDF: 15 pages
Proc. SPIE 8524, Land Surface Remote Sensing, 85241A (21 November 2012); doi: 10.1117/12.977416
Show Author Affiliations
Li Jia, Alterra B (Netherlands)
State Key Lab. of Remote Sensing Science (China)
Guangcheng Hu, State Key Lab. of Remote Sensing Science (China)
Jie Zhou, State Key Lab. of Remote Sensing Science (China)
Massimo Menenti, Technische Univ. Delft (Netherlands)
State Key Lab. of Remote Sensing Science (China)

Published in SPIE Proceedings Vol. 8524:
Land Surface Remote Sensing
Dara Entekhabi; Yoshiaki Honda; Haruo Sawada; Jiancheng Shi; Taikan Oki, Editor(s)

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