Mapping Invasive Opuntia Stricta in Kenya's Drylands Using Explainable Machine Learning with Time-Series Remote Sensing and Geographic Context

Habitat Suitability Modeling for the Invasive Opuntia stricta Using Remote Sensing and Maxent in Tsavo East National Park, Kenya

International audience Biological invasions represent a major threat to ecosystem ser

Mapping Opuntia stricta in the arid and semi-arid environment of Kenya using sentinel-2 imagery and ensemble machine learning classifiers

Globally, grassland biomes form one of the largest terrestrial covers and present critical social–ec

Landslide Susceptibility Mapping in Nigeria Using Remote Sensing, GIS, and Machine Learning Models

Landslide situations remain a significant concern in Nigeria, as they pose a great risk to human liv

Machine learning and remote sensing based time series analysis for drought risk prediction in Borena Zone, Southwest Ethiopia

USING MACHINE LEARNING COUPLED WITH REMOTE SENSING FOR FOREST FIRE SUSCEPTIBILITY MAPPING. CASE STUDY TETOUAN PROVINCE, NORTHERN MOROCCO

Abstract. Currently there is a public awareness to protect the environment especially forest ecosyst

Predicting Opuntia stricta (Haw.) in arid and semi-arid environment of Kenya using Sentinel imagery and ensemble machine learning classifiers

<p>To ensure effective management of Alien plant species especially the invasive deman