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Maya Forest Water Resources I: Using NASA Earth Observations to Map Forested Inundation in the Maya ForestAs climate change increases the severity and frequency of extreme weather events in the tropics, it is vital for the safety of local communities and the health of ecosystems to monitor seasonal inundation. Forested inundation affects the ability of forested wetlands to provide ecosystem services, such as flood mitigation, water filtration, carbon storage, and erosion mitigation. While ground-based monitoring has traditionally been used to map inundation extent, those methods are costly and time-intensive. The NASA DEVELOP team focused on seasonal inundation throughout 2008 in the Maya Forest, when changes in inundation were drastic. To monitor seasonal inundation, our team used in situ field data and Earth observations from Landsat 7 Enhanced Thematic Mapper (ETM+), Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) 1, Shuttle Radar Topography Mission (SRTM), and products from the Ice, Cloud, and Land Elevation Satellite (ICESat). The team applied a Random Forest algorithm to Landsat 7 imagery, generating an object-level land cover classification with an overall accuracy of 72.1% and forest class with 100% recall and 78% precision. The team applied L-band backscatter thresholds from existing literature to forest-masked ALOS imagery and refined the thresholds in an iterative process using field data and hydrology models to delineate seasonal inundation extent. These publicly available data products help end users from Belize’s Land Information Center (LIC) and Forest Department, Guatemala’s Center for Monitoring and Evaluation (CEMEC), and Mexico’s El Colegio de la Frontera Sur (ECOSUR) to inform land management and protect community infrastructure.
Document ID
20210021332
Acquisition Source
Langley Research Center
Document Type
Other - DEVELOP Summer 2021 technical report
Authors
Madelyn Savan
(Science Systems & Applications, Inc. Hampton, VA, USA)
Kathryn Tafoya
(Science Systems & Applications, Inc. Hampton, VA, USA)
Lara O'Brien
(Science Systems & Applications, Inc. Hampton, VA, USA)
Stephanie Jiménez
(Science Systems & Applications, Inc. Hampton, VA, USA)
Tamara Rudic
(Science Systems & Applications, Inc. Hampton, VA, USA)
Date Acquired
September 7, 2021
Publication Date
August 13, 2021
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: NNL16AA05C
WBS: 970315.02.02.01.01
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
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