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首页> 外文期刊>ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences >WETLAND MAPPING IN NEW BRUNSWICK, CANADA WITH LANDSAT5-TM, ALOS-PALSAR, AND RADARSAT-2 IMAGERY
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WETLAND MAPPING IN NEW BRUNSWICK, CANADA WITH LANDSAT5-TM, ALOS-PALSAR, AND RADARSAT-2 IMAGERY

机译：加拿大新不伦瑞克的湿地映射，与Landsat5-TM，Alos-Palsar和Radarsat-2图像

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摘要

Several maps of wetland areas in central New Brunswick, Canada, were produced by applying the Random Forests classifier to different combinations of optical Landsat-5 TM images, dual-polarized (HH, HV) Radarsat-2 C-band and Alos-1 PalSAR L-band Synthetic Aperture Radar (SAR) images and digital elevation data. The resulting maps were compared to 199 GPS wetland sites that were visited between 2012 and 2018 as well as to a combination of two wetland maps currently used by the Province of New Brunswick. The number of correctly identified GPS wetland sites was the highest when both the Alos-PalSAR and Radarsat-2 images are used (97.9%). This percentage of correctly identified sites were well above the accuracy of the official New Brunswick wetland maps (44.7 %). With the best-classified image, the misidentifications were due to wetlands not being classified in the right wetland class, and just one case was a wetland site being classified in a non-wetland class. For the NB wetland map, about a quarter of the wetland validation sites were classified in a non-wetland class, and about the same number of sites were classified in the wrong wetland class.
机译：通过将随机森林分类器应用于不同组合的光滑坡-5 TM图像，双极化（HH，HH，HV）雷达拉特-2 C波段和Alos-1 Palsar，通过将随机森林分类器应用于不同组合来制作加拿大新布伦瑞克湿地地区的几张地图。 L波段合成孔径雷达（SAR）图像和数字高度数据。将结果图与2012年至2018年间访问的199 GPS湿地部位进行了比较，以及新不伦瑞克省目前使用的两张湿地地图的组合。当使用Alos-PalsaR和Radarsat-2图像（97.9％）时，正确识别的GPS湿地部位的数量最高。这种正确识别的网站的百分比远高于新的布伦瑞克湿地地图的准确性（44.7％）。通过最佳分类的形象，误识别是由于湿地没有被分类在右湿地班上，只有一个案例是在非湿地班上分类的湿地网站。对于NB湿地地图，大约四分之一的湿地验证地点被分类为非湿地课程，并且在错误的湿地班上归类了相同数量的网站。

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