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Object-based random forest wetland mapping in Conne River, Newfoundland, Canada
Journal of Applied Remote Sensing ( IF 1.7 ) Pub Date : 2021-08-01 , DOI: 10.1117/1.jrs.15.038506
Jean Elizabeth Granger 1 , Masoud Mahdianpari 1 , Thomas Puestow 2 , Sherry Warren 1 , Fariba Mohammadimanesh 1 , Bahram Salehi 3 , Brian Brisco 4
Affiliation  

The Conne River watershed is dominated by wetlands that provide valuable ecosystem services, including contributing to the survivability and propagation of Atlantic salmon, an important subsistence species that has shown a dramatic decline over the past 30 years. To better understand and improve the management of the watershed, and in turn, the Atlantic salmon, a wetland inventory of the area is developed using advanced remote sensing methods including field-collected data, object-based image analysis of Sentinel-1, Sentinel-2, and digital elevation model Earth observation data. The resulting classification maps consisted of bog, fen, swamp, marsh, and open water wetlands with an overall accuracy of 92% and a kappa coefficient of 0.916. Among wetland classes, user and producer accuracies range between 84% and 100%. Results show the dominance of peatland wetlands such as bog and fen, and the relative rareness of marsh wetlands.

中文翻译:

加拿大纽芬兰康纳河基于对象的随机森林湿地制图

康恩河流域以湿地为主,这些湿地提供有价值的生态系统服务,包括促进大西洋鲑鱼的生存和繁殖,大西洋鲑鱼是一种重要的生存物种,在过去 30 年中急剧下降。为了更好地了解和改善流域的管理,进而改善大西洋鲑鱼的管理,该地区的湿地清单是使用先进的遥感方法开发的,包括现场收集的数据、Sentinel-1 的基于对象的图像分析、Sentinel- 2、数字高程模型地球观测数据。所得分类图由沼泽、沼泽、沼泽和开阔水域湿地组成,总体准确度为 92%,kappa 系数为 0.916。在湿地类别中,用户和生产者的准确率在 84% 到 100% 之间。
更新日期:2021-08-29
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