Monitoring of the mangrove ecosystem on the coastal of Ecuador during the period 2018-2022
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SERVIR AMAZONIA is part of SERVIR Global, a joint development initiative between the National Aeronautics and Space Administration (NASA) and the United States Agency for International Development (USAID). As part of the SERVIR-Amazonia program, the EcoCiencia Foundation, as a local partner in Ecuador, signed a memorandum of understanding with the International Research Center for El Niño Phenomenon (CIIFEN) to generate various tools and services for comprehensive land management. To contribute to coastal management and facilitate mangrove monitoring, the EcoCiencia Foundation developed MANGLEE, an open, multi-user tool based on Synthetic Aperture Radar data, optical satellite images, cloud computing (Google Earth Engine), and machine learning. MANGLEE includes data preprocessing for Sentinel-1 and Sentinel-2, Random Forest classification (mangrove - non-mangrove), distributed change detection in three modules, and a visualization app. MANGLEE's performance was tested in the Ecuadorian mangroves during the period 2018-2022, resulting in 10-meter coverage maps. The maps generated in this service are also available on the APP MANGLEE The methodology and the diffusion workshops can be found at: https://sites.google.com/view/mangleetrain/inicio
SERVIR亚马逊（SERVIR AMAZONIA）是SERVIR全球计划的组成部分，该计划由美国国家航空航天局（National Aeronautics and Space Administration, NASA）与美国国际开发署（United States Agency for International Development, USAID）联合发起。作为SERVIR-亚马逊项目的一环，厄瓜多尔本地合作伙伴生态科学基金会（EcoCiencia Foundation）与厄尔尼诺现象国际研究中心（International Research Center for El Niño Phenomenon, CIIFEN）签署了谅解备忘录，旨在开发各类工具与服务以支撑土地综合管理工作。 为助力海岸带管理并推进红树林监测工作，生态科学基金会开发了MANGLEE——一款基于合成孔径雷达（Synthetic Aperture Radar）数据、光学卫星影像、谷歌地球引擎（Google Earth Engine）云计算平台与机器学习技术的开源多用户工具。 MANGLEE涵盖Sentinel-1与Sentinel-2的数据预处理、随机森林（Random Forest）分类（红树林-非红树林）、三个模块的分布式变化检测功能，以及可视化应用程序。该工具的性能已于2018-2022年期间在厄瓜多尔红树林区域完成测试，最终生成了分辨率为10米的红树林覆盖范围地图。 本服务生成的地图也可通过MANGLEE应用程序获取。相关方法论与推广研讨会的信息可通过以下链接查阅：https://sites.google.com/view/mangleetrain/inicio
