PREDICTING WHEAT APHID USING 2-DIMENSIONAL FEATURE SPACE BASED ON MULTI-TEMPORAL LANDSAT TM
文献类型: 外文期刊
作者: Huang Wenjiang 1 ; Luo Juhua 2 ; Zhao Jinling 1 ; Zhang Jingcheng 1 ; Ma Zhihong 1 ;
作者机构: 1.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
2.Beijing Normal Univ, Coll Geog & Remote Sensing Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China
关键词: Winter wheat;Aphid;land surface temperature (LST);Modified normalized difference water index (MNDWI)
期刊名称:2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)
ISSN: 2153-6996
年卷期: 2011 年
页码:
收录情况: SCI
摘要: Aphid (Hemiptera: Aphididae) outbreaks appear in wheat (Triticum aestivum L.) planting area in China, and had significant economic impacts on wheat. It has severe impact on both winter wheat yield and grain quality. The aim of this study was to monitor and predict of wheat aphid by analyzing the relationship between land surface temperature (LST), modified normalized difference water index (MNDWI) and the occurrence and prevalence of aphid in wheat. The results showed that LST was an important driving factor for occurrence of aphid, and MNDWI was sensitive to aphid damage degree. Meanwhile, a 2-dimensional feature space was established based on LST and MNDWI derived from Landsat TM images, and discrimination model of aphid damage degrees was established according to the distribution of samples in the feature space. It was verified that the overall accuracy of discrimination model is 82.5%, and kappa accuracy is 73.88%.
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