The tidal wetlands of Louisiana comprise about 25% of those found throughout the conterminous United States yet estimates of wetland loss rates in the region between 1932 and 2016 have exceeded 60 km2 yr-1. To mitigate further degradation and wetland loss in the region, a globally unprecedented $50B, 50-year plan for coastal Louisiana is driving restoration efforts, and demand exists from multiple stakeholders for regularly updated, regional-scale, accurate land cover information. We used machine learning (random forests; RF) and cloud computing to develop a new Landsat-based, marsh vegetation community geospatial dataset. The dataset depicts wetland vegetation community types defined in a previous study at annual (1985–2025) time steps at 30-m resolution. An RF algorithm was used to integrate training samples with feature variables derived from Landsat imagery, and the resulting geospatial data product achieved an overall correct classification rate of 78%. The approach for development of the land cover dataset presented here has potential for application in other coastal wetland habitats throughout the world.
Wetlands provide indispensable ecological, hydrological and socio-economic services, yet remain among the most rapidly altered ecosystems worldwide due to encroaching agriculture, urbanisation and hydrological disruption. This study presents a cloud-based, multi-temporal assessment of Koonthankulam, a Ramsar-designated...
A. Varsha, Mahendiran Mylswamy, R. Sakthivel· Asian Journal of Geographica...· 0 citations
The northeastern hilly region of Bangladesh is characterized by subtropical evergreen hilly forests, haors, tea estates, and nationally designated protected areas and is undergoing rapid land-use transformation. This study analyzes spatiotemporal changes in land use and land cover (LULC) in Moulvibazar and Habiganj dis...
M. R. Mim, Tahmina Afroz, Tamanna Tabassum et al.· Land· 0 citations
Vegetation cover is an important indicator of ecosystem condition and environmental sustainability, particularly in semi-arid regions affected by climatic variability and anthropogenic pressures. This study assesses vegetation-cover differences in the Oued Rdat Basin, northwestern Morocco, between 1984 and 2022 using L...
Land use/land cover (LULC) changes in northern Algeria from 2001 to 2021 were investigated in this research. The assessment utilized the MODIS MCD12Q1 dataset combined with Geographic Information System (GIS) techniques. Substantial landscape transformations were highlighted by the findings. Forests (+47.52%), shrublan...
Bilel Zerouali, R. D. da Silva, N. Bailek et al.· Dysona. Applied Science· 0 citations
This study presents the first multi-decadal analysis of Land Use and Land Cover (LULC) dynamics in the Ruhuhu River Basin, Tanzania, over a 34-year period (1990–2023). Multi-temporal satellite imagery from Landsat 5 TM, Landsat 8 OLI, and Sentinel-2 MSI was classified using the Random Forest algorithm within Google Ear...
H. Francis, S. Nakamo, F. Mgumia· Journal of Natural Resources...· 0 citations
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