Integrating Time Series Remote Sensing Information in Suitability Analysis for Land Use Planning

The goal of this study was to inform land use planning decisions by incorporating remote sensing time series data and land cover classifications into a suitability analysis. Trends extracted from land cover classifications between the years 2000 and 2020 informed on general land cover trends occurring in the study area, the THLD District of Ghana. Remotely sensed environmental and anthropogenic variables were combined with road and soil data to form the foundations of a suitability analysis. These classifications were then integrated along with time-series remote sensing variables and road and soil data into the suitability analysis, which analyses the validity of land areas for predetermined uses. The preliminary results of the classification show that urban areas have largely expanded throughout the THLD District, while there have been losses in forested areas. The baseline results from the suitability analysis effectively determined transportation accessibility and soil quality for areas across the THLD District. These results provide a strong foundation for the impacts of land use decisions on land cover and environmental trends.