首页> 外文会议>Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International >Environmental change detection in prairie landscapes with simulated Radarsat 2 imagery
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Environmental change detection in prairie landscapes with simulated Radarsat 2 imagery

机译:利用Radarsat 2影像模拟草原景观中的环境变化

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For the past decade, we have been using Landsat TM imagery to monitor changes in the area and distribution of ecosystems in a relatively undisturbed natural region in southwestern Manitoba, Canada. The 40,000 hectares of Canadian Forces Base Shilo are protected from urbanisation, commercialisation and agriculture, and are disturbed only by modest and controlled amounts of military training. A significant problem with the use of TM imagery for this study is that some of the more sensitive indicators of environmental change, such as the infestation of disturbed grassland by leafy spurge, are very difficult to identify and delineate in the visible and near-IR bands. A fully polarized SAR that is sensitive to vegetation morphology may not have the same difficulty. C band radars, such as that being constructed for Radarsat 2, are known to have difficulty differentiating vegetation types in regions of dense foliage, but, in a prairie ecosystem such as the one under study here, even the densest foliage should be sparse enough to yield a unique polarisation signature. In order to test this hypothesis we have simulated Radarsat 2 HH, HV and VV images, using several TM images of the area, polarisation ratios extracted from the literature for vegetation types similar to those found in the area, and a Radarsat 1 HH image of the area collected almost simultaneously with one of the TM images. Comparison of synthesized imagery from different years shows sufficient differences to imply that Radarsat 2 imagery will likely be a useful tool for continuing our prairie ecosystem monitoring and assessment.
机译:在过去的十年中,我们一直使用Landsat TM影像来监视加拿大曼尼托巴西南部一个相对未受干扰的自然区域中生态系统的面积和分布的变化。加拿大军队希洛的40,000公顷受到保护,免受城市化,商业化和农业发展的影响,并且仅受到适度和受控数量的军事训练的干扰。使用TM影像进行这项研究的一个重要问题是,在可见光和近红外波段很难识别和描绘出一些更敏感的环境变化指标,例如多叶大面积侵扰扰乱的草原。 。对植被形态敏感的全极化SAR可能没有同样的困难。众所周知,C波段雷达(例如为Radarsat 2建造的雷达)很难区分茂密的树叶区域的植被类型,但是,在诸如此处研究的草原生态系统中,即使最茂密的树叶也应足够稀疏,以至于产生独特的极化特征。为了检验该假设,我们使用该区域的若干TM图像,从文献中提取的类似于该区域发现的植被类型的文献中提取的极化率以及该地区的Radarsat 1 HH图像对Radarsat 2 HH,HV和VV图像进行了模拟。该区域几乎与TM图像之一同时收集。来自不同年份的合成影像的比较显示出足够的差异,这表明Radarsat 2影像将可能是继续进行草原生态系统监测和评估的有用工具。

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