湿地
变更检测
土地覆盖
遥感
生态系统
地理
环境资源管理
自然地理学
环境科学
土地利用
生态学
生物
作者
Masoud Mahdianpari,Hamid Jafarzadeh,Jean Granger,Fariba Mohammadimanesh,Brian Brisco,Bahram Salehi,Saeid Homayouni,Qihao Weng
标识
DOI:10.1109/igarss47720.2021.9553053
摘要
Wetlands are highly sensitive ecosystems that have experienced largely undocumented loss across Canada. Accurate statistics of historic loss of wetlands across many provinces is vague at best or non-existent at worst, as exemplified in Newfoundland and Labrador (NL). Thus, NL represents a perfect candidate for implementing historical remote sensing data sets and change detection methods. Given recent advancements in earth observation technology, it is now feasible to implement remote sensing-based change detection methods at scales never previously possible. As such, the goal of this work is to develop a methodology to assess wetland class change across the island of Newfoundland between 1985 and 2015 using historic and current Landsat imagery, Random Forest classification, and the Google Earth Engine (GEE) platform. The resulting accuracies ranged from 84.37% to 88.96%. The analysis reveals that wetland classes over the last 30 years have been unstable, and the biggest loss of wetlands to anthropogenic land cover occurred between the 1980's and the 1990's. Index Terms - Wetlands, Change Detection, Landsat, Geo big data
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