A very high spatial resolution Land Use and Land Cover map was produced for the greater Marino watershed (Peru) using the MORINGA processing chain. The methods involved multisource satellite imagery and a random forest model, as well as manual post-treatment. The final map provides important information for environmental management and monitoring and contributes to developing standardized methodologies for accurate LULC mapping. 3 levels are available with the training dataset

A very high spatial resolution Land Use and Land Cover map was produced for the greater Marino watershed (Peru) using the MORINGA processing chain. The methods involved multisource satellite imagery and a random forest model, as well as manual post-treatment. The final map provides important information for environmental management and monitoring and contributes to developing standardized methodologies for accurate LULC mapping. Classification 2019 – Level 3

A very high spatial resolution Land Use and Land Cover map was produced for the greater Marino watershed (Peru) using the MORINGA processing chain. The methods involved multisource satellite imagery and a random forest model, as well as manual post-treatment. The final map provides important information for environmental management and monitoring and contributes to developing standardized methodologies for accurate LULC mapping. Training Dataset

A very high spatial resolution Land Use and Land Cover map was produced for the greater Marino watershed (Peru) using the MORINGA processing chain. The methods involved multisource satellite imagery and a random forest model, as well as manual post-treatment. The final map provides important information for environmental management and monitoring and contributes to developing standardized methodologies for accurate LULC mapping. Classification 2019 – Level 2

A very high spatial resolution Land Use and Land Cover map was produced for the greater Marino watershed (Peru) using the MORINGA processing chain. The methods involved multisource satellite imagery and a random forest model, as well as manual post-treatment. The final map provides important information for environmental management and monitoring and contributes to developing standardized methodologies for accurate LULC mapping. Classification 2019 – Level 1