This study used Remote Sensing and Geographic Information System (GIS) tools to produce a predictive model of land use/land cover changes in Makassar City by 2031. The model was based on the classification of SPOT satellite images from 2006, 2011, and 2016 with an assessment of 10 driving factors. The Multi-Layer Perceptron Neural Network (MLPNN) method was run with the Markov Chain model using the Business as Usual scenario. The results predict that built-up areas will cover about 80% of the total area of Makassar City by 2031. This research can inform stakeholder decision-making in Makassar City.

The spatial plan program for Makassar City and the surrounding area called Mamminasata (Makassar, Maros, Sungguminasa, and Takalar) was created by the Indonesian Government. The program regulates the proportion of land cover, but predictions about land cover changes were not considered. Therefore, in this study, we predict what the land cover may be in 2031 using the multi-layer perceptron neural network and the Markov chain methods. For this purpose, image composite, support vector machine classifier, and change detection were applied to a time series of satellite data. Visual validation showed the hot-spots of land cover changes related to population density, and statistical validation scored 0.99 and 0.78 in no information kappa and grid-cell level location kappa, respectively. The model was performed to predict land cover in 2031, and the predicted result was then compared with the spatial plan using an overlapping method. The results showed that built-up area, dryland agriculture, and wetland agriculture occupied two, twenty, and eight percent of the protected zone, respectively. Meanwhile, fifteen percent of the development zone was covered by forest, mainly in the eastern part of Mamminasata. The result can be used to help the Government decide future plans for the Mamminasata area.

Urban watershed is a discrete and complex system where a diverse number of factors govern its quality and health. Soil erosion by water is the most dominant factor that determines a watershed quality, and considered as one of the most significant forms of land degradation that affects sustained productivity of land use. The principal aim of this paper is to utilise spatial-based soil erosion information to assess land suitability at a watershed level. The specific aim is three-fold: (i) to develop techniques based on a GIS in the parameterisation of a soil erosion model, which is designed for use at a large scale assessment; (ii) to assess and map the spatial distribution of average annual rate of soil losses in; (iii) to employ such related concept as soil loss tolerance to determine land suitability at a watershed level. An analytical procedure is used to analyse an urban watershed of Tallo River, in South Sulawesi, Indonesia, with a total area of 43,422 ha. The procedure is executed using RUSLE (Revised Universal Soil Loss Equation), in a GIS environment, utilising available information in the region (including climate, soil, slope, and land use and land conservation practices), and with the assistance of ground surveys. The results indicate that around 56.5% of the area experience annual soil loos of less than 1 ton/ha/year, while erosion rate of more than 25 ton/ha/year covers a total area of 8.9%. Due to a good ground cover in forested land, most of the slopping areas have actual soil losses of 1-5 ton/ha/year. This study reveals that areas categorized as high risk, where only forest cover allowed consist of 9.4%, and those with very low risk cover a total area of 5.4%. Most of the study region (around 84%) experience moderate and low erosion risk, and suitable for cropping with special management practices (CS) + perennial crops (PC) + grass (GR) + and forest (FR). This study suggests that the outputs of this modeling procedure can be used for the identification of land management units based on degradation levels, as well as the most suitable land use to be practiced on individual land units on a sustainable basis.

Several studies have focused on present environmental carrying capacity, but predictions based on future conditions are rarely considered. In this study, land use/land cover (LU/LC) data and ecosystem services valuation (ESV) were used to quantify the future environmental carrying capacity in Makassar City by 2031. The LU/LC data were based on previous research and the ESV coefficients were based on Muta’ali (2015). The results predict that all types of ecosystem services in Makassar City will decrease every year and will be below 0.5 of current values by 2031. These results can be used to inform plans for sustainable development in Makassar City.

One of the major obstacles in increasing the agricultural production yields is the inappropriate management of land use due to the differences in land biophysical characteristics in each region. Therefore, it is necessary to have spatial-based land use management that is appropriate for handling agricultural land. This research aims at structuring geospatial information of agricultural land biophysical characteristics and agricultural land appropriateness (potential and limiter) for food plants development in Pangkep Regency. This research uses the up-to-date approach of multi-scale observation, so the problems becoming the restricting factors of productivity can immediately be overcome. The method used consists of 2 stages, namely stage 1, analysis of agricultural land (biophysical) climate and land characteristics through land survey, laboratory analysis, and land characteristic spatialization; stage 2, analysis of agricultural land appropriateness (potential and limiter) using land appropriateness method offuzzy set/FAO, satellite image information extraction, ground truth, and ground sampling. The results of the research are in the form of geospatial information on agricultural land biophysical characteristics and agricultural land appropriateness (potential and limiter) for food plants development in Pangkep Regency. With the information, decision makers will have more ease and they integrate into making policies for agricultural land use management in Pangkep Regency that will end up aiming to increase food production.