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Proceedings Paper

Monitoring the plague of oriental migratory locusts using multi-temporal Landsat TM imagery
Author(s): Zhenbo Liu; Shaoxiang Ni; Yong Zha; Xuezheng Shi
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Paper Abstract

Locust plague is a kind of the world-wide biological calamity to agriculture. In China's history, more than 90% of locust plagues were caused by the oriental migratory locust, Locusta migratoria manilensis (Meyen). At the present time, it is difficult for monitoring and forecasting systems in this country to provide real time information of locust plague outbreak in large area. In order to adopt timely measures for prevention and control of locust outbreak, it is necessary to apply advanced remote sensing technology for monitoring and forecasting locust outbreak This paper introduces a case study on monitoring oriental migratory locust plague with remote sensing technology in 3 pilot sites, namely, Huangzao, Yangguangzhuang, and Tengnan, which were the 3 major locust damaged areas in Huanghua City, Hebei Province, China during the period of large scale oriental migratory locust breakout in 2002. In this study, locust damage intensity, areas with various damage intensities and their distribution in pilot sites are determined by means of comparison between Landsat ETM+ image of locust damaged vegetation on 31st May, 2002 and TM image of healthy vegetation before damage on 23rd May, 2002. Then, information of various locust distribution density in pilot sites is extracted by establishing the Locust Density Index (LDI).

Paper Details

Date Published: 9 June 2006
PDF: 8 pages
Proc. SPIE 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 62000W (9 June 2006); doi: 10.1117/12.682173
Show Author Affiliations
Zhenbo Liu, Institute of Soil Science (China)
Nanjing Normal Univ. (China)
Shaoxiang Ni, Nanjing Normal Univ. (China)
Yong Zha, Nanjing Normal Univ. (China)
Xuezheng Shi, Institute of Soil Science (China)


Published in SPIE Proceedings Vol. 6200:
Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China
Qingxi Tong; Wei Gao; Huadong Guo, Editor(s)

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