Forty Years of Wetland Status and Trends Analyses in the Great Lakes Using Landsat Archive Imagery and Google Earth Engine

authored by
Meisam Amani, Mohammad Kakooei, Arsalan Ghorbanian, Rebecca Warren, Sahel Mahdavi, Brian Brisco, Armin Moghimi, Laura Bourgeau-Chavez, Souleymane Toure, Ambika Paudel, Ablajan Sulaiman, Richard Post
Abstract

Wetlands provide many benefits, such as water storage, flood control, transformation and retention of chemicals, and habitat for many species of plants and animals. The ongoing degradation of wetlands in the Great Lakes basin has been caused by a number of factors, including climate change, urbanization, and agriculture. Mapping and monitoring wetlands across such large spatial and temporal scales have proved challenging; however, recent advancements in the accessibility and processing efficiency of remotely sensed imagery have facilitated these applications. In this study, the historical Landsat archive was first employed in Google Earth Engine (GEE) to classify wetlands (i.e., Bog, Fen, Swamp, Marsh) and non-wetlands (i.e., Open Water, Barren, Forest, Grassland/Shrubland, Cropland) throughout the entire Great Lakes basin over the past four decades. To this end, an object-based supervised Random Forest (RF) model was developed. All of the produced wetland maps had overall accuracies exceeding 84%, indicating the high capability of the developed classification model for wetland mapping. Changes in wetlands were subsequently assessed for 17 time intervals. It was observed that approximately 16% of the study area has changed since 1984, with the highest increase occurring in the Cropland class and the highest decrease occurring in the Forest and Marsh classes. Forest mostly transitioned to Fen, but was also observed to transition to Cropland, Marsh, and Swamp. A considerable amount of the Marsh class was also converted into Cropland.

Organisation(s)
Institute of Photogrammetry and GeoInformation (IPI)
External Organisation(s)
Wood Environment & Infrastructure Solutions
Chalmers University of Technology
K.N. Toosi University of Technology
Lund University
Canada Center for Mapping and Earth Observation (CCMEO)
Michigan Technological University
Meteorological Service of Canada (ARQX)
Type
Article
Journal
Remote sensing
Volume
14
ISSN
2072-4292
Publication date
06.08.2022
Publication status
Published
Peer reviewed
Yes
ASJC Scopus subject areas
General Earth and Planetary Sciences
Sustainable Development Goals
SDG 13 - Climate Action
Electronic version(s)
https://doi.org/10.3390/rs14153778 (Access: Open)