Canadian prairie drought assessment through MODIS vegetation indices

Xulin Guo, Wei Gao, Pierrot Richard, Yunpei Lu, Youfei Zheng, Elise Pietroniro

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

Consecutive droughts occurred in Canadian prairies have resulted in significant economical losses, ecological degradation, and environmental deterioration. The purpose of this study was to investigate the efficiency of remotely sensed data on drought assessment combined with climate data. The study area was the Canadian prairie ecozone in the provinces of Alberta, Saskatchewan, and Manitoba. The objectives were five-fold: 1) comparing Kriging and inverse distance weighting (IDW) interpolation methods, 2) comparing four spectral variables, the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the red and the mid infrared (MIR), 3) comparing three moisture indices (P-PET, P/PET and (P-PET)TPET), 4) evaluating the relationships between spectral variables and moisture indices, and 5) assessing drought effects on different ecoregions. Results showed that there is no significant difference between Kriging and IDW, the two interpolation methods. MODIS vegetation indices could effectively assess drought conditions, especially EVI. Among the moisture indices compared, P-PET showed a better result. The impacts of droughts vary from year to year and from ecoregion to ecoregion. Aspen Parkland has higher drought resistance because of tree components.

Original languageEnglish
Article number20
Pages (from-to)149-158
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5544
DOIs
StatePublished - 2004
Externally publishedYes
EventRemote Sensing and Modeling of Ecosystems for Sustainability - Denver, CO, United States
Duration: 2 Aug 20044 Aug 2004

Keywords

  • Canadian prairie
  • Drought
  • MODIS
  • Moisture index
  • Vegetation index

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