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Regional crop monitoring and discrimination based on simulated ENVISAT ASAR wide swath mode images

机译:基于模拟的ENVISAT ASAR宽幅模式图像的区域作物监测和鉴别

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The current paper investigates the potential contribution of ENVISAT wide swath (WS) images for discrimination and monitoring of crops at a regional scale. The study was based on synthetic aperture radar (SAR) images acquired throughout an entire growing season. Advanced synthetic aperture radar sensor (ASAR) images in both narrow swath (NS) and WS modes were simulated based on 15 European Remote Sensing (ERS) satellite images recorded over Belgium. Unlike 'real' ASAR imagery, this exercise provided a consistent data set (i.e. same incidence angle, same acquisition date, same acquisition hour) to study the impact of spatial resolution on the SAR signal information content. A quantitative approach using 787 parcels of medium field size and various data combinations assessed monitoring and discrimination capabilities for six crop types: wheat, barley, grasses, sugar beet, maize and potato. The spatial resolution impact of the ASAR sensor was discussed with respect to the field size by comparing the results obtained from NS (30m) and WS (150m) mode images. WS temporal profiles were able to discriminate the various crops of interest and were representative of the crop development observed in the region. Furthermore, parcel-based unsupervised classifications successfully discriminated between grass, wheat, barley and other crops of large parcels (success rate of 83%). Dedicated interpretation schemes were developed in order to discriminate between cereal crops.
机译:本文研究了ENVISAT宽幅(WS)图像对区域范围内的作物歧视和监测的潜在贡献。该研究基于在整个生长季节中获得的合成孔径雷达(SAR)图像。基于在比利时记录的15幅欧洲遥感(ERS)卫星图像,模拟了窄幅(NS)和WS模式下的高级合成孔径雷达传感器(ASAR)图像。与``真实''ASAR图像不同,此练习提供了一致的数据集(即相同的入射角,相同的采集日期,相同的采集时间)来研究空间分辨率对SAR信号信息内容的影响。使用787块中等田地大小和各种数据组合的定量方法评估了对六种作物的监测和鉴别能力:小麦,大麦,草,甜菜,玉米和马铃薯。通过比较从NS(30m)和WS(150m)模式图像获得的结果,讨论了ASAR传感器对空间大小的空间分辨率影响。 WS时间剖面能够区分各种感兴趣的作物,并代表了该地区观察到的作物生长。此外,基于包裹的无监督分类成功区分了草,小麦,大麦和其他大包裹作物(成功率为83%)。为了区分谷物作物,制定了专用的解释方案。

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