The spatio-temporal analysis of land use changes & above-ground carbon stock in Sumbawa mangrove ecosystem, Indonesia

Abstract Mangrove deforestation in Indonesia amounts to roughly 18,209 ha per year (18.26 MtCO₂e/year −1 ). However, spatial and temporal integrative research in eastern Indonesia's coastal areas remains limited. This study aims to analyse mangrove forests' condition and spatio-temporal changes, compute above-ground carbon (AGC) as a basis for sustainable coastal management in Sumbawa Regency and support the 2030 Nationally Determined Contribution (NDC) target. This research merges UAV-RGB data (July 2024) and multitemporal PlanetScope imagery (2016 and 2024) to develop a Canopy Height Model (CHM) and calculate the AGC. Land use classification was accomplished using Object-Based Image Analysis (OBIA)—Random Forest (RF), while changing trends were assessed using Modules for Land Use Change Evaluation/Simulations (MOLUSCE). AGC at the study site was in the range of 21—168 $${\text{MgC}.\text{ha}}^{-1}$$ MgC . ha - 1 (mean = 72.3 $${\text{MgC}.\text{ha}}^{-1}$$ MgC . ha - 1 , total = 8,999.9 $$\text{MgC}$$ MgC . The investigation found a change of 37.89 ha of mangrove area to barren and shrubland, resulting in an AGC loss of 2,739.5 $$\text{MgC}$$ MgC . However, there has been an increase in land use and changes in aquaculture and agriculture. This study proposes a novel approach by merging UAV data and time-series satellite images to increase the accuracy of AGC prediction in data-sparse locations. A nature-based Solution (NbS) is advocated as an integrated method for adaptive mangrove restoration and conservation, while still supporting the demands of the local community. This research presents a geographical framework that may be duplicated to create inclusive and adaptable coastal resource management plans and directly contribute to reaching the 2030 NDC targets.