This research was motivated by changes in mangrove forest areas in Central Sulawesi Province, Donggala Regency, especially South Banawa District. The objective of the research is to analyze the change of mangrove forests in the district of South Banawa years 2002-2018 and to determine the dominant factors influencing the change of mangrove forests. This study uses a quantitative approach combining geographic information systems and remote sensing, using overlay and descriptive analysis. Results from research this showing that the mangrove forest in the district South Banawa years 2002-2018 decline area amounting to 47.59 hectares, which was originally large mangrove forest 261.32 hectares to 213.73 hectares on in 2018. The Changing of mangrove forests to fishponds is a dominant factor in the change of mangrove forests when compared to other changes.

Land conversion is a change in the function of a part or whole land area of its original function (as planned) into another function that becomes a negative impact (problem) on the environment and potential land itself. The study aims to analyze changes in land cover over five years with the image of Landsats 8 of 2016 and 2021 as well as analyze the factors of the cause of changes in land cover in the Limited Production Forest Area in Kulawi Subdistrict. The study used guided image analysis (supervised) and binary logistics regression analysis. The formation of spatial models of forest cover changes in the Kulawi Subdistrict Limited Production Forest Area using 5 modifier factors consisting of accessibility aspects i.e., settlement, population density, river, slope, road. Logit (p)=-0.24087+0.04249(x1)+0.2815(x2)-0.42492(x3)-0,.0480(x4)+0.04010(x5). The results of binary logistic regression analysis showed goodness of fit value of 5471996.86 chi-square values of 60287.17 and pseudo r2 of 0.30 greater than 0.2, indicating the model is worth using. Based on the results of binary logistics regression analysis, it is known that distance from roads, distance from settlement and population density are influential to changes in forest land cover.