Rapid landuse change in an urban area is inevitable. Jakarta as the capital city of Indonesia is experiencing rapid landuse change. Jakarta is the centre of administration, economic activities, and entertainment pull people coming in to Jakarta. The dynamics of demography in Jakarta influences landuse change strongly. This research use three districts in Jakarta to see how landuse change over period of time. They are Penjaringan, Cengkareng, and Cakungsubdistrict. By combining landuse data, demographic features, and spatial data, such as satellite imagery, landuse change can be monitored and explained. The most significant landuse changes are industrial area and settlements. Both landuses are expanding. Meanwhile open spaces are decresing in size. This happens due to high demand of settlements caused by migrants coming in to work in industrial are. The result of this phenomenon is slum area in the city and lack of opened green spaces that can degrade environmental quality.

This research is conducted to determine and analyze carrying capacity of agricultural land of Sumatra Selatan in 2015 as well as to project it in 2030. The analysis is also carried out to describe the Optimum Population Number and Land Requirement per Hectare of each regency and municipality in 2030. The research method applied using quantitatively descriptive method in which the data is collected from secondary source such as Agricultural Ministry and Central Statistics Agency publication and supported by literature study. The result shows that Sumatra Selatan has high carrying capacity (τ > 1) in 2015 and 2030. It means that the province is capable of food self-sufficiency since the province is underpopulated. The projection indicates that there is decline of carrying capacity in 2030 occurring across the province. For example, Ogan Komering Ulu (OKU) Regency which previously has high carrying capacity, is predicted to have experience low carrying capacity.

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Changes in Land Use/Land Cover (LULC) generate several impacts which affect the energy balance of the Earth and, consequently, modifying the climate of a region. Accordingly, one of the most important indicators of this modification is the Land Surface Temperature (LST). The present work aims to analyze the relationship between LULC and LST, determining the influence of LULC on LST using Geographical Information Systems (GIS) and Remote Sensing (RS) techniques. The selected study area was the San Luis Potosí Basin, México (SLPB). A temporal analysis has been developed for 2007 and 2020. Satellite images from Landsat 5 TM and 8 OLI/TIRS has been used to calculate LST through a single-channel algorithm for winter and spring. LULC has been determined from a supervised classification with neural network algorithm. Finally, change rates for LULC and LST were assessed. The results indicate that an LST increase of 11 °C from 2007 to 2020 has been detected in the region. Also, results showed that covers with spare vegetation or without vegetation have the highest temperatures (29°C to 32°C). In comparison, the covers with dense vegetation and water showed the lowest temperatures (23°C to 25°C). This type of research allows addressing the LULC effects on LST, as well as prove its importance in improving land use planning systems.