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首页> 外文会议>IEEE International Geoscience and Remote Sensing Symposium >Use of Radarsat-2 and ALOS-PALSAR SAR images for wetland mapping in New Brunswick
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Use of Radarsat-2 and ALOS-PALSAR SAR images for wetland mapping in New Brunswick

机译：在新不伦瑞克省使用Radarsat-2和ALOS-PALSAR SAR影像进行湿地制图

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Our study tests the use of dual-polarized (HH, HV) RADARSAT-2 C-band and ALOS-PALSAR L-band SAR images for mapping wetland areas in New Brunswick. The study also uses LANDSAT-5 TM and DEM data. The resulting maps were compared to GPS field data as well as to two wetland maps currently in use by the Province of New Brunswick. Overall the Random Forests classifier gave better classification accuracies than the maximum likelihood classifier. The comparison with the 146 wetland truth sites shows that 73.3% are correctly identified over the LANDSAT-5 TM classified image. For the SAR-based classified images, the number of correctly identified wetland ground truth sites is higher when the image acquired during the flooding is considered, the difference being higher with the ALOS-PALSAR images than with the RADARSAT-2 images. The number of correctly identified sites is the highest when both the ALOS-PALSAR images and RADARSAT-2 images are used (98.6%). These percentages of correctly identified wetland sites are well above of those computed using the DNR wetland and forested wetland maps (44.5 %).
机译：我们的研究测试了双极化（HH，HV）RADARSAT-2 C波段和ALOS-PALSAR L波段SAR图像在新不伦瑞克省湿地面积制图中的应用。该研究还使用了LANDSAT-5 TM和DEM数据。将生成的地图与GPS实地数据以及新不伦瑞克省目前正在使用的两个湿地地图进行了比较。总体而言，与最大似然分类器相比，随机森林分类器提供了更好的分类准确性。与146个湿地真实地点的比较表明，在LANDSAT-5 TM分类图像中正确识别了73.3％。对于基于SAR的分类图像，当考虑洪水期间获取的图像时，正确识别的湿地真实地点的数量更多，与ADAR-PALSAR图像相比，与RADARSAT-2图像相比，差异更大。当同时使用ALOS-PALSAR图像和RADARSAT-2图像时，正确识别的位置数最多（98.6％）。正确识别的湿地面积的这些百分比远高于使用DNR湿地和森林湿地地图计算的百分比（44.5％）。

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