Habitat monitoring to evaluate crop disease and pest distributions based on multi-source satellite remote sensing imagery
Habitat monitoring to evaluate crop disease and pest distributions based on multi-source satellite remote sensing imagery
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基于多源卫星遥感影像的生境监测评估农作物病虫害分布
DOI：
10.1016/j.ijleo.2017.06.071
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发表时间：
2017-09
期刊：
影响因子：
--
通讯作者：
Xi Liang
中科院分区：
文献类型：
--
作者：
Lin Yuan;Zhiyan Bao;Haibo Zhang;Yuntao Zhang;Xi Liang
生境监测可以用来评价一个地区植物病虫害的潜在发生和分布。本文提出了一种基于worldview2和Landsat 8卫星数据的作物病虫害监测新方法。以河北省锦州市周家庄麦田为例，进行了该方法的应用研究。采用作物生长指数（GNDVI和VARIred-edge）和环境特征（wet、Greenness和LST）描述生境，并采用独立检验方法评价这5个特征对作物病虫害的表征效果。实地测量被用来评估该方法的有效性。与仅基于植被指数的模型相比，结合植被和环境指数的FLDA模型在监测作物病虫害发生方面更为准确（准确率为71%对82%）。未来的工作应包括多种形式的信息（例如，气象数据和网络传感器网络），以进一步改善区域尺度的作物病虫害监测。
Habitat monitoring can be used to evaluate the potential occurrence and distribution of plant diseases and pests in a region. Here, we present a new method for monitoring crop diseases and pests based on Worldview 2 and Landsat 8 satellite data. As a case study, the method was applied to wheat fields in Zhou Jiazhuang, Jinzhou City, Hebei Province. Crop growth indices (GNDVI and VARIred-edge) and environmental features (Wetness, Greenness, and LST) were used describe habitat, and an independentt-test was used to evaluate the performances of these five features in representing crop diseases and pests. Field measurements were used to evaluate the validity of the method. An FLDA model incorporating both vegetation and environmental indices was more accurate for monitoring crop disease and pest occurrence compared with a model based on vegetation indices alone (71% vs. 82% accuracy). Future work should include multiple forms of information (e.g., meteorological data and web sensor networks) to further improve regional-scale monitoring of crop diseases and pests.
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影响因子：
6.2
作者：
Huang, Wenjiang;Lamb, David W.;Wang, Jihua
通讯作者：
Wang, Jihua
DOI：
--
发表时间：
2008
期刊：
--
影响因子：
--
作者：
P. Wolter;P. Townsend;B. Sturtevant;Clayton C. Kingdon
通讯作者：
P. Wolter;P. Townsend;B. Sturtevant;Clayton C. Kingdon
DOI：
10.1109/igarss.2010.5654453
发表时间：
2010-07
期刊：
2010 IEEE International Geoscience and Remote Sensing Symposium
影响因子：
--
作者：
T. Cheng;B. Rivard;A. Sánchez-Azofeifa
通讯作者：
T. Cheng;B. Rivard;A. Sánchez-Azofeifa
DOI：
10.1016/s0303-2434(03)00008-4
发表时间：
2003-11
影响因子：
7.5
作者：
Minghua Zhang;Zhihao Qin;Xue Liu;S. Ustin
通讯作者：
Minghua Zhang;Zhihao Qin;Xue Liu;S. Ustin
影响因子：
13.5
作者：
Cheng, T.;Rivard, B.;Sanchez-Azofeifa, A.
通讯作者：
Sanchez-Azofeifa, A.