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Land Use Land Cover (LULC) change is a complex phenomenon driven by various natural and anthropogenic factors, significantly impacting carbon storage potential. By applying integrated models of ANN-CA Markov, GeoDetector, and InVEST model, this study aimed to analyze LULC change, their driving factors, and implications on carbon storage in the Forest Management Unit (FMU) of Ampang Plampang in West Nusa Tenggara, Indonesia. Several data sources were utilized in the modelling approach, including DEM (Digital Elevation Model), topographical map, Landsat imageries (2011, 2016, 2021), measured carbon density (above ground, below ground, soil, dead organic), and socio-economic data (number of populations, farmer, and agricultural land). The dryland forest in the study area constitutes the most extensive LULC that has experienced significant declines due to deforestation, predominantly transforming into agricultural land, and these are predicted to continue until 2031 with different magnitudes. The significant driving factors of LULC change were elevation, population pressure on land, and distance from settlement. The LULC change also greatly influenced the decline of carbon storage historically (2011–2016) and in projected LULC (2026–2031). The conversion of forested areas to non-forest LULCs has released carbon emissions of about 1.89 Mt CO 2 -eq. The study findings implied that the integration of ANN-CA Markov, GeoDetector, and InVEST models has been helpful for comprehending complicated interactions among LULC change, driving factors, and carbon dynamics. The results also contribute to the scientific knowledge base for land management decision-making and policy formulation. Effective management of LULC changes through low carbon development is suggested to mitigate the loss of carbon storage capacities, foster sustainable development goals (SDGs), support Nationally Determined Contribution (NDC), and improve ecosystem resilience. [ABSTRACT FROM AUTHOR]

Comprehending the characteristics of infiltration is essential for conserving spring recharge areas, particularly on hillslopes of a Quaternary volcanic landscape. Quantitative investigations were carried out to identify soil physical properties and morphological features related to infiltration behavior. We used 15 transects with 70 sampling points in total to collect soil samples, observed morphological characteristics, and measured the infiltration. Data analysis employed statistical methods, including principal component analysis (PCA) and K-means cluster analysis. PCA revealed that infiltration was strongly correlated with slope, slope length, surface curvature, and slope position and that it was a function of soil physical properties, i.e., soil moisture, particle size distribution, and bulk density. The K-means cluster analysis classified the sampling points into four clusters that corresponded to three slope positions, namely upper slope, middle slope, and footslope. The high infiltration rate in the middle slope was caused by the relatively steep slope, sandy soil texture, low soil moisture, and low bulk density. On the contrary, the relatively flat slope, high clay content, high soil moisture, and high bulk density of the footslope created a low infiltration rate. According to these infiltration parameters, the preferred area for spring water catchment conservation was the middle slope. [ABSTRACT FROM AUTHOR]