Monitoring of the mangrove ecosystem in the province of Guayas-Ecuador during the period 2018-2022.
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Mangroves are highly productive ecosystems that provide important ecosystem services, are strategic allies in carbon capture and storage, conserve different plant and wildlife species, are producers of aquatic species such as crabs and shrimp, and local communities have developed strong economic, cultural and identity ties. Despite their great ecological, economic, and social importance, mangroves are threatened by natural and anthropogenic factors, hence the importance of their constant monitoring.  Remote sensing technology has demonstrated its ability to map changes in mangroves and technological advances allow faster application of mapping methodologies, optimizing costs and time. To facilitate the sustainable management of mangroves, an open tool based on remote sensing data and machine learning was developed on the Google Earth' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["agroforestry systems","biodiversity","biomass","carbon sequestration","carbon sink","classification","Cloud computing","deforestation","ecology","ecosystem","ecosystem services","ecosystem services","Ecuador","GEE","Google Earth Engine","Guayas","land degradation","Latin America and the Caribbean","Mangrove change map","Mangrove cover","Mangrove ecosystem","mapping","Random Forest","SAR","Sentinel 1","Sentinel 2","SERVIR Amazonia","Shrimp farms","USAID","vegetation index"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Mangroves are highly productive ecosystems that provide important ecosystem services, are strategic allies in carbon capture and storage, conserve different plant and wildlife species, are producers of aquatic species such as crabs and shrimp, and local communities have developed strong economic, cultural and identity ties. Despite their great ecological, economic, and social importance, mangroves are threatened by natural and anthropogenic factors, hence the importance of their constant monitoring.  Remote sensing technology has demonstrated its ability to map changes in mangroves and technological advances allow faster application of mapping methodologies, optimizing costs and time. To facilitate the sustainable management of mangroves, an open tool based on remote sensing data and machine learning was developed on the Google Earth' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Mangroves are highly productive ecosystems that provide important ecosystem services, are strategic allies in carbon capture and storage, conserve different plant and wildlife species, are producers of aquatic species such as crabs and shrimp, and local communities have developed strong economic, cultural and identity ties. Despite their great ecological, economic, and social importance, mangroves are threatened by natural and anthropogenic factors, hence the importance of their constant monitoring.  Remote sensing technology has demonstrated its ability to map changes in mangroves and technological advances allow faster application of mapping methodologies, optimizing costs and time. To facilitate the sustainable management of mangroves, an open tool based on remote sensing data and machine learning was developed on the Google Earth
agroforestry systems; biodiversity; biomass; carbon sequestration; carbon sink; classification; Cloud computing; deforestation; ecology; ecosystem; ecosystem services; ecosystem services; Ecuador; GEE; Google Earth Engine; Guayas; land degradation; Latin America and the Caribbean; Mangrove change map; Mangrove cover; Mangrove ecosystem; mapping; Random Forest; SAR; Sentinel 1; Sentinel 2; SERVIR Amazonia; Shrimp farms; USAID; vegetation index