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

doi:10.1109/IGARSS.2012.6351417

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 conference › Paper › peer-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 language	English (US)
Pages	883-886
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS.2012.6351417
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
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)

Online availability

10.1109/IGARSS.2012.6351417

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Cite this

Zhou, L., Wu, J. J., Leng, S., Liu, M., Zhang, J., Zhao, L., Diao, C. Y., Zhang, J. H., Luo, H. J., Zhang, F. Y., & Shi, Y. (2012). Using a new integrated drought monitoring index to improve drought detection in mid-eastern China. 883-886. Paper presented at 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, Munich, Germany. https://doi.org/10.1109/IGARSS.2012.6351417

Zhou, L, Wu, JJ, Leng, S, Liu, M, Zhang, J, Zhao, L, Diao, CY, Zhang, JH, Luo, HJ, Zhang, FY & Shi, Y 2012, 'Using a new integrated drought monitoring index to improve drought detection in mid-eastern China', Paper presented at 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, Munich, Germany, 7/22/12 - 7/27/12 pp. 883-886. https://doi.org/10.1109/IGARSS.2012.6351417

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title = "Using a new integrated drought monitoring index to improve drought detection in mid-eastern China",

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.",

keywords = "Drought, ISDI, data mining, remote sensing",

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

year = "2012",

doi = "10.1109/IGARSS.2012.6351417",

language = "English (US)",

pages = "883--886",

note = "2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 ; Conference date: 22-07-2012 Through 27-07-2012",

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T1 - Using a new integrated drought monitoring index to improve drought detection in mid-eastern China

AU - Zhou, Lei

AU - Wu, Jian Jun

AU - Leng, Song

AU - Liu, Ming

AU - Zhang, Jie

AU - Zhao, Lin

AU - Diao, Chun Yuan

AU - Zhang, Jian Hui

AU - Luo, Hai Jiang

AU - Zhang, Feng Ying

AU - Shi, Yu

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

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KW - data mining

KW - remote sensing

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

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