Using a new integrated drought monitoring index to improve drought detection in mid-eastern China

Lei Zhou, Jian Jun Wu, Song Leng, Ming Liu, Jie Zhang, Lin Zhao, Chun Yuan Diao, Jian Hui Zhang, Hai Jiang Luo, Feng Ying Zhang, Yu Shi

Research output: Contribution to conferencePaperpeer-review

Abstract

Using data-mining technology, this paper established a new method, named the Integrated Surface Drought Index (ISDI). ISDI integrates traditional meteorological data, remotely sensed indices, and biophysical data, and attempt to describe drought from a more comprehensive perspective. The evaluation results indicated that the construction models for three phases of growth season have very high regression accuracy. The drought condition can be predicted using the independent variables. The practical application of ISDI in mid-eastern china also demonstrated that ISDI has good application accuracy in mid-eastern China. ISDI results were corresponding to the disaster observation records of agro-meteorological sites. It can be potentially extended to nationwide near real time drought monitoring.

Original languageEnglish (US)
Pages883-886
Number of pages4
DOIs
StatePublished - 2012
Externally publishedYes
Event2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany
Duration: Jul 22 2012Jul 27 2012

Other

Other2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
CountryGermany
CityMunich
Period7/22/127/27/12

Keywords

  • Drought
  • ISDI
  • data mining
  • remote sensing

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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