| Abstract | Globally, land degradation threatens environmental sustainability and livelihoods yet, multi indicator assessment with systematic evaluation of restoration interventions have been integrated by few studies, especially in developing countries. Hence, in line with the global commitment to achieve Land Degradation Neutrality (LDN) by 2030, this research aimed to assess spatial patterns of land degradation between 2000-2015 and 2015-2024, evaluate the effectiveness of intervention measures and predict 2030 scenarios in Nepal. Secondary data for spatial indicators of land use/land cover (LULC), Normalized Difference Vegetation Index (NDVI), and Soil Organic Carbon (SOC) were analyzed using Google Earth Engine to generate national land condition maps. A five-class was used to assess land condition for both periods, while a three-class classification was applied to evaluate trends during 2015–2024. During 2000-2015 to 2015-2024, degraded land increased (7.97% to 26.42%) respectively while improved (34.83% to 28.47%) and stable land (57.20% to 45.11%) decreased. Overall, as compared to lowland areas fragile mountain ecosystems recorded more land degradation. Based on reduced degradation and increased improvement in Chure landscape, restoration interventions were ranked as revetment/spurs, check dams, plantations, gabion wall embankments and recharge ponds. Moreover, higher improved land (35.02%) was recorded in intervention areas during 2015-2024 than non-intervention areas (29.72%). Although intervention effects were non-uniform (DiD -0.66 to 1.02), Circular and Green Economy for Environmental Restoration under Project 2 recorded the best outcome at district level projects. Terai districts Jhapa (67.63%), Dhanusha (58.87%) and Sarlahi (58.15%) under Project 2 recorded the highest land improvements while Hills and Himalayan districts under Project 4, 1 and 3 had the highest degradation Parbat (75.25%), Dolakha (71.07%), and Sindhupalchok (65.80%) respectively. Pre-treatment comparability was confirmed (p=0.59) and moderate but non-uniform spatial variability was recorded by SD results. Furthermore, under BAU 2030 scenarios, generated by using simple arithmetic extrapolation, degraded land is projected to increase (22.12%) while improved (3.62%) may remain low. Although projections show the forest cover target to be met, achieving the national and the renaming specific LDN targets in Nepal will require scaling up targeted and site-specific land restoration interventions. |