Merits and limitations in assessing droughts by using long-term NDVI and 1st time series

A. Karnieli, N. Agam, M. C. Anderson, R. T. Pinker, M. L. Imhoff, G. G. Gutman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A large number of water-and climate-related applications, such as drought monitoring, are based on spaceborne-derived relationships between land surface temperature (LST) and the Normalized Difference Vegetation Index (NDVI). The majority of these applications rely on the existence of a negative slope between the two variables found from site-and time-specific studies. The current paper investigates the generality of the LST-NDVl relationship over a wide range of moisture and climatic/radiation regimes encountered over the North American continent (up to 60° N) during the summer growing season (April-September). Information on LST and NDVI comes from long-term (21-year) datasets obtained by the Advanced Very High Resolution Radiometer (AVHRR). It was found that when water is the limiting factor for vegetation growth (typical situation for low latitudes of the study area and during the mid-season), the LST-NDVI correlation is negative. However, when energy is the limiting factor for vegetation growth, (in higher latitudes and elevations, especially at the beginning of the growing season) a positive correlation exists between LST and NDVI. Forward multiple regression analysis revealed that during the beginning and the end of the growing season, solar radiation is the predominant factor driving the correlation between LST and NDVI, while other biophysical variables play a lesser role. Air temperature is the primary factor in mid summer. It is concluded that there is a need to use the LST-NDVI relationship with caution and to restrict its applications as a drought index to areas and periods where negative correlations are observed.

Original languageEnglish
Title of host publication5th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2009, MultiTemp 2009
EditorsDaniel L. Civco
PublisherMultiTemp 2009
Pages194-204
Number of pages11
ISBN (Electronic)9781618391940
StatePublished - 1 Jan 2009
Event5th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2009, MultiTemp 2009 - Groton, United States
Duration: 28 Jul 200930 Jul 2009

Publication series

Name5th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2009, MultiTemp 2009

Conference

Conference5th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images 2009, MultiTemp 2009
Country/TerritoryUnited States
CityGroton
Period28/07/0930/07/09

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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