Evaluating the Land Degradation trends: A Digital Twin Approach for Enhanced Environmental Monitoring

Climate change significantly impacts land degradation, posing substantial threats to ecosystems and human livelihoods. This paper proposes an outline to create a digital twin aiming to integrate various datasets for monitoring land degradation and supporting stakeholders. The Digital Twin of Land Degradation (DTLD) will integrates satellite and drone imagery, real-time data, IoT, and field collection data to establish a dynamic and real-time simulation of land degradation at the affected regions. This framework implementation can be used by different end-users like scientific community, private sector, NGO, public community, decision-makers and internation organizations for analysis, report, and support the effective of land management practices. By implementing a nested method, the interconnected areas and their associated physical processes contribute to a larger twinning of the entire region. This is achieved by collecting geospatial information from different sources at different scales and modeling this data in real-virtual time. Ultimately, the DTLD approach should proves invaluable in pinpointing vulnerable areas and informing targeted mitigation strategies. This study underscores the critical need for advanced monitoring tools in combating land degradation and highlights the potential of digital twins in environmental research.