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 language | English (US) |
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Pages | 883-886 |
Number of pages | 4 |
DOIs | |
State | Published - 2012 |
Externally published | Yes |
Event | 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany Duration: Jul 22 2012 → Jul 27 2012 |
Other
Other | 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 |
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Country/Territory | Germany |
City | Munich |
Period | 7/22/12 → 7/27/12 |
Keywords
- Drought
- ISDI
- data mining
- remote sensing
ASJC Scopus subject areas
- Computer Science Applications
- Earth and Planetary Sciences(all)