首页> 外文会议>International Symposium on Remote Sensing of Environment >SPECTRAL DISCRIMINATION AND REFLECTANCE PROPERTDZS OF VARIOUS VINE VARIETIES FROM SATELLITE, UAV AND PROXIMATE SENSORS
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SPECTRAL DISCRIMINATION AND REFLECTANCE PROPERTDZS OF VARIOUS VINE VARIETIES FROM SATELLITE, UAV AND PROXIMATE SENSORS

机译:卫星,无人机和近距传感器对各种葡萄品种的光谱鉴别和反射性能

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An assessment of the spectral discrimination between different vine varieties was undertaken using non-destructive remote sensing observations at the veraison period. During concurrent satellite, aerial and field campaigns, in-situ reflectance data were collected from a spectroradiometer, hyperspectral data were acquired from a UAV and multispectral data from a high-resolution satellite imaging sensor. Data were collected during a three years period (i.e, 2012, 2013 and 2014) over five wine-growing regions, covering more than lOOOha, in Greece. Data for more than twenty different vine varieties were processed and analysed. In particular, reflectance hyperspectral data from a spectroradiometer (GER 1500, Spectra Vista Corporation, 350-1050nm, 512 spectral bands) were calculated from the raw radiance values and then were correlated with the corresponding reflectance observations from the UAV and satellite data. Reflectance satellite data (WorldView-2, 400nm-1040nm, 8 spectral bands, DigitalGlobe), after the radiometric and atmospheric correction of the raw datasets, were classified towards the detection and the discrimination of the different vine varieties. The concurrent observations from in-situ hyperspectral, aerial hyperspectral and satellite multispectral data over the same vines were highly correlated. High correlations were, also, established for the same vine varieties (e.g., Syrah, Sauvignon Blanc) cultivated in different regions. The analysis of in-situ reflectance indicated that certain vine varieties, like Merlot, Sauvignon Blanc, Ksinomavro and Agiorgitiko possess specific spectral properties and detectable behaviour. These observations were, in most cases, in accordance with the classification results from the high resolution satellite data. In particular, Merlot and also Sauvignon Blanc were detected and discriminated with high accuracy rates. Surprisingly different clones from the same variety could be separated (e.g., clones of Syrah), while they were confused with other varieties (e.g., with Riesling).
机译:在检验期间,使用非破坏性遥感观测对不同葡萄品种之间的光谱辨别力进行了评估。在同时进行的卫星,空中和野战活动中,从光谱辐射仪收集原位反射率数据,从无人机获取高光谱数据,并从高分辨率卫星成像传感器获取多光谱数据。在三年期间(即2012年,2013年和2014年)收集了希腊五个葡萄酒产区的数据,覆盖面积超过1000公顷。处理和分析了二十多个不同葡萄品种的数据。特别是,根据原始辐射值计算了来自光谱辐射仪(GER 1500,Spectra Vista Corporation,350-1050nm,512个光谱带)的反射高光谱数据,然后将其与来自无人机和卫星数据的相应反射率观测值相关联。在对原始数据集进行辐射和大气校正之后,将反射卫星数据(WorldView-2、400nm-1040nm,8个光谱带,DigitalGlobe)分类,以检测和区分不同的葡萄树品种。来自同一葡萄树的原位高光谱,空中高光谱和卫星多光谱数据的同时观测值高度相关。还建立了在不同地区种植的相同葡萄品种(例如西拉,长相思)的高度相关性。对原位反射率的分析表明,某些葡萄树品种,如梅洛,长相思,克索诺马沃和阿乔吉蒂科具有特定的光谱特性和可检测的行为。在大多数情况下,这些观察结果均与高分辨率卫星数据的分类结果一致。特别是,以高准确率检测并区分了梅洛和长相思。令人惊讶的是,可以将来自同一品种的不同克隆(例如西拉(Syrah)的克隆)分离,而将它们与其他品种(例如与雷司令(Riesling))混淆。

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