Applying remote sensing techniques to changes of water body and aquatic plants in Anzali International Wetland (1985-2018)

Zefrehei, Ahmad Reza Pirali; Fallah, Maryam; Hedayati, Aliakbar

doi:10.25750/1995-4301-2021-1-065-072

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among the marine/coastal wetlands, intertidal swamp forests (8%), intertidal mudflats (6%), tidal salt/brackish/freshwater marshes (6%), and estuarine waters (4%) were studied the most. Conversely, freshwater lagoons and marine aquatic beds were rarely studied, e.g., [31,32]. Among inland wetlands, permanent freshwater marshes (10.5%), seasonal freshwater marshes (8.5%), permanent freshwater rivers (8%), and lakes (7%) were studied the most.…”

Section: Wetland Typesmentioning

confidence: 99%

“…In an arctic archipelago of Canada, climate change and the expansion of a bird species resulted in wetland degradation [46]. In addition, the combination of the expansion of invasive species and LULC changes decreased the area of water bodies [32,124]. Interestingly, many studies highlighted that a combination of drivers of change can both decrease and increase the area of wetlands.…”

Section: Combination Of Drivers Of Changementioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2023

View full text Add to dashboard Cite

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.

show abstract

Section: Wetland Typesmentioning

confidence: 99%