Geocomputation and Spatial Analysis Applied for Geological Mapping: A Case Study in Palopo, South Sulawesi, Indonesia - Langkoke, Rohaya; Ahmad, Asmita; Thamrin, Meinarni; Husain, Ratna; Iqbal, Muhammad (Universitas Hasanuddin, 2024)
In searching for a track record of earth formation, people tend to interpret field data in a way that limits the potential of history and explanation, which is often less influenced by theory and available facts, this requires valid data gathered intellectually. Geocomputing, which is the digital processing of geographic data, is a relatively recent field that reflects a wide range of research methodologies and their application to help solve problems in machine learning, geostatistics, image processing, and spatial analysis, among other areas. The purpose of this study was to assess the effectiveness of using geocomputational methods with Avenza Map and ArcGIS. This study uses geocomputation and spatial analysis to carry out geological mapping at a scale of 1:25,000 located in the Battang area, West Wara District, Palopo City, South Sulawesi. Two aspects are the main focus in implementing this research method, namely when mapping by relying on Avenza with a base map sourced from the Rupa Bumi Indonesia (RBI) map and on data management using the ArcGIS application to become a 3D map. Lithological of the study area showed basalt, porphyry basalt, and phyllite. The geological structure that develops in the research area is joint and fault. Avenza Map work with spatial analysis in ArcGIS is obtained cognitively, involving the relationship between individual conditions, tools, and terrain conditions. It can be stated that the use of avenza on smartphones in this modernization condition is more effective. This research allows for a review of the practical level of use of computer methods ranging from mapping to data management. Regarding implementing cognitive mapping, Avenza Map and ArcGIS can be recommended tools in geo-computation techniques as more effective support for recording and managing data while still paying attention to noise that may occur as a barrier to data accuracy.