Continental-scale wetland mapping: A novel algorithm for detailed wetland types classification based on time series Sentinel-1/2 images. (April 2023)

• Record Type: Journal Article
• Authors: Peng, Kaifeng; Jiang, Weiguo; Hou, Peng; Wu, Zhifeng; Ling, Ziyan; Wang, Xiaoya; Niu, Zhenguo; Mao, Dehua
• Is Part Of: Ecological indicators. Volume 148(2023)
• Publication Date: 2023-04
• Subjects: Wetland mapping -- Two-step classification -- K-fold random forest -- Phenology-based features -- Hierarchical decision tree -- Google Earth Engine; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2023.110113
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Integrating phenology and geometry features boosts wetland classification accuracy. Developing a novel algorithm for detailed wetland types classification. Mapping 5 inland wetlands, 6 coastal wetlands, and 3 human-made wetlands. First wetland map at 10-m resolution covering northern, central and southern Asia. Abstract: Wetlands have suffered from considerable degradation due to anthropogenic and natural disturbances in recent decades. Although some advancements have been made, effective methods that can produce large-scale wetland maps with detailed categories are still lacking due to the diversity and complexity of wetland ecosystems. To address this issue, we developed a novel algorithm for detailed wetland types classification integrating k-fold random forest and hierarchical decision tree, and so named two-step classification algorithm. Firstly, the phenology-based features were composited based on time series Sentinel-1/2 images, and the k-fold random forest was used to extract five rough wetland types in Google Earth Engine platform. Secondly, the hierarchical decision tree designed based on geometric features was used to separate the rough wetland types into fourteen detailed types. Application of the two-step classification method in Northern, Central and Southern Asia (NCSA) resulted in a continental-scale wetland map with an overall accuracy of 90.0 ± 0.5%. Wetland types, including inland marsh, lake, river, coastal swamp, estuarine water, lagoon, shallow marine water, reservoir, canal/channel and agricultural pond, had good accuracy with both UA and PA over 77%. The remaining wetland types had moderate accuracy, with both UA and PA over 58%. As we calculated, total wetland areas of NCSA were 1, 375, 489.27 km 2 . Among the fourteen wetland categories, the inland marsh had the largest area (544, 584.38 km 2 ) and was primarily distributed in subarctic and humid continental climates, while the canal/channel had the smallest area (1, 651.57 km 2 ) and was primarily scattered in desert, semiarid and humid subtropical climates. The lake and floodplain shared generally large areas with value of 392, 413.55 km 2 and 173, 255.71 km 2 respectively, which were typically distributed across desert and semiarid climates. This study successfully mapped continental-scale wetlands with detailed categories at a 10-m spatial resolution, which can provide valuable information for the management of wetland ecosystems and facilitate the implementation of wetland-related sustainable development goals.