The Fate of Wetlands

Strauch, Adrian; Bunting, Peter; Campbell, Jillian; Cornish, Natalie; Eberle, Jonas; Fatoyinbo, Temilola; Franke, Jonas; Hentze, Konrad; Lagomasino, David; Lucas, Richard; Paganini, Marc; Rebelo, Lisa‐Maria; Riffler, Michael; Rosenqvist, Åke; Steinbach, Stefanie; Thonfeld, Frank; Tøttrup, Christian

doi:10.1002/9781119536789.ch5

Cited by 2 publications

(1 citation statement)

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“…However, wetlands are difficult to identify and characterize due to their dispersal [6], their fine-grained pattern [7], and the high spatio-temporal dynamics of the water and vegetation that shape them [8]. Thus, monitoring wetlands requires intra-annual observations of the Earth at high spatial resolutions for several decades and observations that cover large areas [9]. Moreover, while there have been global mapping initiatives such as the global wetland map developed by the Center for International Forestry Research (https://www2.cifor.org/global-wetlands/, accessed on 1 November 2022), the global map of saltmarshes [10], or the global map of peatlands [11], there is a gap with respect to long-term monitoring efforts.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Wetland Monitoring Using the Landsat Archive: A Review

et al. 2023

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Wetlands, which provide multiple functions and ecosystem services, have decreased and been degraded worldwide for several decades due to human activities and climate change. Managers and scientists need tools to characterize and monitor wetland areas, structure, and functions in the long term and at regional and global scales and assess the effects of planning policies on their conservation status. The Landsat earth observation program has collected satellite images since 1972, which makes it the longest global earth observation record with respect to remote sensing. In this review, we describe how Landsat data have been used for long-term (≥20 years) wetland monitoring. A total of 351 articles were analyzed based on 5 topics and 22 attributes that address long-term wetland monitoring and Landsat data analysis issues. Results showed that (1) the open access Landsat archive successfully highlights changes in wetland areas, structure, and functions worldwide; (2) recent progress in artificial intelligence (AI) and machine learning opens new prospects for analyzing the Landsat archive; (3) most unexplored wetlands can be investigated using the Landsat archive; (4) new cloud-computing tools enable dense Landsat times-series to be processed over large areas. We recommend that future studies focus on changes in wetland functions using AI methods along with cloud computing. This review did not include reports and articles that do not mention the use of Landsat imagery.

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