基于热红外遥感的小麦条锈病菌越夏区精准勘界 |
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引用本文:冷伟锋,马占鸿.基于热红外遥感的小麦条锈病菌越夏区精准勘界.植物保护学报,2018,45(1):118-123 |
DOI:10.13802/j.cnki.zwbhxb.2018.2018912 |
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中文摘要:为减少小麦条锈病菌越夏区勘界的人力作业成本和劳动强度,实现大尺度、精准勘界,本研究采用一套基于卫星和地理信息技术的新方法进行小麦条锈病菌越夏区勘界,利用2009年7月的Landsat-5卫星图像,截取甘肃省陇南地区热红外遥感影像,利用辐射传输方程对影像进行地表温度反演,通过反演温度实现对该区域的小麦条锈病菌越夏区精准勘界。结果表明:辐射传输方程Lλ=[ε·B(Ts)+(1-ε)L↓]·f+L↑能较好地反演Landsat-5卫星的热红外遥感影像,建立辐射温度与气温温度的拟合方程t=0.81T-216.52,拟合度较好,R2为0.61。使用ENVI和Google Earth软件能将反演的温度和地理信息实现图层叠加,并能精准定位到小麦条锈病菌越夏区范围内的村庄及田块。这一技术可实现跨省份、跨地区大面积的遥感监测与调查,并且不受时间、空间限制。随着卫星技术和信息技术的发展,这一方法能使与温度相关的勘界调查精度更高。 |
中文关键词:越夏区划 地表温度反演 小麦条锈病 热红外遥感 |
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Precise boundary location of the wheat stripe rust oversummering areas based on thermal infrared remote sensing |
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Abstract:In order to reduce cost and labor intensity of the wheat stripe rust oversummering area demarcation and achieve large and precise area demarcation, a new method based on the satellite and geographic information technology was adopted for precise oversummering area demarcation of the wheat stripe rust pathogen by using Landsat-5 satellite image in July 2009, taking Longnan area of Gansu Province from thermal infrared satellite remote sensing image and the surface temperature inversion imaging of radiative transfer equation. The results showed that the radiative transfer equation Lλ=[ε·B(Ts)+(1-ε)L↓]·f+L↑ could better inverse the Landsat-5 satellite imagery, and the equation of radiation temperature and air temperature(t=0.81T-216.52) had a high degree of fitting(R2=0.61). The use of ENVI and Google Earth software could overlay the temperature and geographic information, and precisely position wheat stripe rust in oversummering villages and farmland areas. This technology can realize remote sensing monitoring and investigation across provinces and regions, and is not restricted by time and space. With the development of satellite and information technology, this method can make the temperature-dependent demarcation survey precise. |
keywords:oversummering area demarcation land surface temperature retrieval wheat stripe rust thermal infrared remote sensing |
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