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Indonesia has a karst region abundant in high-quality marble mining products but is also prone to disasters. Over the years, this area has experienced numerous natural disasters, thereby leading to the need for a land suitability assessment. This is a descriptive qualitative and quantitative research with data collected from field observations, laboratory tests, interviews, and documents. Four places in the center and adjacent areas of marble producers were selected for the research sample. The data collected were analyzed using the spatial and ecological approach, fishbone, tabulation, percentage, and SWOT analysis. The result showed that numerous land mismatches contribute to the occurrence of natural catastrophes, such as improper vegetation kinds, population settlement patterns, excessive exploitation, and unfriendly human activities. This study recommends a variety of measures to improve the mining area.

Disaster mitigation activities require the availability of a potentially flooded area (PFA) map. One of the causes of flooding is the criticality of water catchment areas; the higher the criticality level, the higher the flooding potential. This study aims to determine the accuracy of the model for determining the PFA around Bengkulu City, which was derived from the Level of Critical Water Catchment Area (LCWCA) model developed by the Ministry of Forestry. After obtaining the LCWCA Map, another analysis was performed in order to obtain the PFA Map. Furthermore, the overlaying was carried out with the Existing Flood Map in such a way that the level of accuracy is known. The threshold values from Justice are used to justify the level of accuracy in three categories, namely Good (> 85%), Moderate (70 - 85%), and Poor ( 85%), which means that there was > 85% overlap between areas on the Potentially Flooded Area Map as a result of the analysis of The LCWCA with the area on the Existing Flood Map. There are three sub-watersheds with Moderate accuracy (70 - 85%) and three sub-watersheds with Poor accuracy (

Mapping of potential flood hazards is an important element in ensuring proper planning of development and implementing flood disaster mitigation efforts for flooded areas. Therefore, this study was conducted to assess the regional-scale flood hazard areas in Gorontalo District using an AHP-GIS integration technique with the focus on factors such as annual rainfall, elevation, slope, soil type, distance to the water bodies, and land-use. The flood hazard was divided into five classes, ranging from very low to very high, and 13.61% of the total area in Gorontalo Regency is classified as either high or very high. Moreover, the distribution of the hazard was verified and 65 events were recorded to have a level of 90.7% and this indicates the model is reliable to assess flood hazard. The results showed GIS-AHP integration is a promising method to accurately predict flood-hazard areas, especially in those with limited data.