ArticleRemote sensing of environment2019
Integrating LiDAR data and multi-temporal aerial imagery to map wetland inundation dynamics using Google Earth Engine.
Article in Remote sensing of environment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Wetland-mediated nitrate reductions attenuate downstream: Insights from a modeling study.Journal of environmental management · 2024Article
- Surface water monitoring from 1984 to 2021 based on Landsat time-series images and Google Earth Engine.Heliyon · 2024Article
- Geospatial Science for the Environmental Epidemiology of Cancer in the Exposome Era.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024Article
- Spatiotemporal light exposure modeling for environmental circadian misalignment and solar jetlag.Environmental epidemiology (Philadelphia, Pa.) · 2024Article
- Mapping global non-floodplain wetlands.Earth system science data · 2023Article
- Headwater streams and inland wetlands: Status and advancements of geospatial datasets and maps across the United States.Earth-science reviews · 2022Article
- Seasonality of inundation in geographically isolated wetlands across the United States.Environmental research letters : ERL [Web site] · 2022Article
- Vulnerable Waters are Essential to Watershed Resilience.Ecosystems (New York, N.Y.) · 2022Article
- Impact of wetland fragmentation due to damming on the linkages between water richness and ecosystem services.Environmental science and pollution research international · 2021Article
- Nature-based solutions efficiency evaluation against natural hazards: Modelling methods, advantages and limitations.The Science of the total environment · 2021Review
- Spectro-temporal analysis of the Paraopeba River water after the tailings dam burst of the Córrego do Feijão mine, in Brumadinho, Brazil.Environmental monitoring and assessment · 2021Article
- Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine.Remote sensing · 2021Article
- Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S.Remote sensing · 2020Article
- Land-Cover Changes to Surface-Water Buffers in the Midwestern USA: 25 Years of Landsat Data Analyses (1993-2017).Remote sensing · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The Prairie Pothole Region of North America is characterized by millions of depressional wetlands, which provide critical habitats for globally significant populations of migratory waterfowl and other wildlife species. Due to their relatively small size and shallow depth, these wetlands are highly sensitive to climate variability and anthropogenic changes, exhibiting inter- and intra-annual inundation dynamics. Moderate-resolution satellite imagery (e.g., Landsat, Sentinel) alone cannot be used to effectively delineate these small depressional wetlands. By integrating fine spatial resolution Light Detection and Ranging (LiDAR) data and multi-temporal (2009-2017) aerial images, we developed a fully automated approach to delineate wetland inundation extent at watershed scales using Google Earth Engine. Machine learning algorithms were used to classify aerial imagery with additional spectral indices to extract potential wetland inundation areas, which were further refined using LiDAR-derived landform depressions. The wetland delineation results were then compared to the U.S. Fish and Wildlife Service National Wetlands Inventory (NWI) geospatial dataset and existing global-scale surface water products to evaluate the performance of the proposed method. We tested the workflow on 26 watersheds with a total area of 16,576 km
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Registered trials
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