RT info:eu-repo/semantics/article
T1 MANGLEE: A tool for mapping and monitoring MANgrove ecosystem on google earth engine—A case study in Ecuador
A1 Caiza Morales, Lorena
A1 Gómez Almaraz, Cristina
A1 Torres, Rodrigo
A1 Puzzi Nicolau, Andrea
A1 Olano Mendoza, José Miguel
K1 Google Earth Engine
K1 Guayas
K1 Mangrove
K1 Random Forest
K1 Sentinel-1
K1 Sentinel-2
K1 31 Ciencias Agrarias
AB Mangroves, integral to ecological balance and socioeconomic well-being, are facing a concerning decline worldwide. Remotesensing is essential for monitoring their evolution, yet its effectiveness is hindered in developing countries by economic andtechnical constraints. In addressing this issue, this paper introduces MANGLEE (Mangrove Mapping and Monitoring Toolin Google Earth Engine), an accessible, adaptable, and multipurpose tool designed to address the challenges associated withsustainable mangrove management. Leveraging remote sensing data, machine learning techniques (Random Forest), andchange detection methods, MANGLEE consists of three independent modules. The first module acquires, processes, andcalculates indices of optical and Synthetic Aperture Radar (SAR) data, enhancing tracking capabilities in the presence ofatmospheric interferences. The second module employs Random Forest to classify mangrove and non-mangrove areas, pro-viding accurate binary maps. The third module identifies changes between two-time mangrove maps, categorizing alterationsas losses or gains. To validate MANGLEE’s effectiveness, we conducted a case study in the mangroves of Guayas, Ecuador,a region historically threatened by shrimp farming. Utilizing data from 2018 to 2022, our findings reveal a significant lossof over 2900 hectares, with 46% occurring in legally protected areas. This loss corresponds to the rapid expansion of Ecua-dor’s shrimp industry, confirming the tool’s efficacy in monitoring mangroves despite cloud cover challenges. MANGLEEdemonstrates its potential as a valuable tool for mangrove monitoring, offering insights essential for conservation, manage-ment plans, and decision-making processes. Remarkably, it facilitates equal access and the optimal utilization of resources,contributing significantly to the preservation of coastal ecosystems.
PB Springer
SN 2509-8810
YR 2024
FD 2024
LK https://uvadoc.uva.es/handle/10324/75231
UL https://uvadoc.uva.es/handle/10324/75231
LA eng
NO Journal of Geovisualization and Spatial Analysis, 2024, vol.8, n. 1
NO Producción Científica
DS UVaDOC
RD 02-abr-2025