Detecting changes in mangrove forests along the Bintang Bolong Estuary, Gambia using Google Earth Engine, Sentinel-2 imagery and Random Forest classification

Detecting Harvest Events in Plantation Forest Using Sentinel-1 and -2 Data via Google Earth Engine

South Africa is reported to experience timber shortages as a result of growing timber demands and pu

INTEGRATED ANALYSIS OF MANGROVE CHANGES USING THE MANGROVE VEGETATION INDEX AND RANDOM FOREST CLASSIFICATION IN THE GAMBIA

Abstract. The extraction of mangrove forests from satellite imagery is usually accomplished using im

Comparison Between Sentinel-2 and Landsat in Mapping Mangroves in The Gambia Using the Google Earth Engine Mangrove Mapping Methodology (GEM v2)

Mangroves play a vital role in coastal environments by supporting biodiversity, protecting shoreline

Land Use and Land Cover Classification in Google Earth Engine Using Sentinel-2 Based Random Forest: A Case Study of Katsina State, Nigeria

Monitoring Mangrove Recovery in the Bay of Assassins, Madagascar Using Sentinel-2 Imagery and the Google Earth Mangrove Mapping Methodology (GEM)

Mangroves are unique plant species that support livelihoods and provide critical ecosystem services.

Supervised Mangrove Classification in Madagascar Comparing Optical Imagery to Combined Optical and Synthetic Aperture Radar Imagery Using Random Forest on Sentinel-1 and Sentinel 2

Mangrove ecosystems are critical coastal habitats that provide essential services such as shoreline