The decline in mangrove forests has reduced their capacity to mitigate climate change, making monitoring and mapping essential for their sustainability. This study examined mangrove area changes in the Segara Anakan Cilacap (SAC) mangrove cluster (2019–2022), analyzed local driving factors, and proposed mitigation strategies. Using geographically weighted logistic regression (GWLR) and geospatial machine learning (GML), validated by field surveys, the study identified significant mangrove conversion into ponds, open land, and cultivated areas. The results show that spatial heterogeneity of driving factors was effectively modeled, with a fixed bi‐square kernel type increasing accuracy by 3%. Mangrove area changes are influenced by local conditions within a 19,052‐m radius. In the western region, mangrove area degradation is caused by population density and salinity (regression coefficient > 0.98); in the central region, it is determined by the distance to aquaculture (coefficient 0.88); and in the eastern region, it is due to the distance to settlements (coefficient ∼0.97). Tailored interventions, such as managing community activities, land use changes, and settlements, are essential for conserving mangrove forests in this area.
Purwanto et al. (Wed,) studied this question.
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