Innovative technologies, machine learning and big data have the potential to accelerate progress in improving access to land resource information. The Gums for Adaptation and Mitigation in Sudan (GAMS) project aims to strengthen the adaptive capacity of local communities and restore the carbon sink potential of the Gum Arabic belt (GCP/SUD/083/GCF). As part of this project, GIS and remote sensing improve understanding of land cover change. Sharing knowledge, expertise and information, especially with young people, masters and doctoral students, contributes to the quality of data to support national plans and strategies. With technical guidance from Rashed Jalal, remote sensing expert at the NSL Geospatial Unit, around 50 students from the Faculty of Geography, University of Khartoum exchanged knowledge and opinions on how to improve and prepare more accurate and efficient national land cover information. For this, the national land cover of 2020 was discussed, including the development of the land cover legend, the acquisition and processing of satellite images, the collection of formation data, the machine learning algorithm and accuracy assessment. Technical capacity building, involving the next generation of GIS experts, while using the latest innovations and international standards will contribute to monitoring natural resources and the adaptation of communities and national actors in the context of climate change.