Land allocation optimization based on carbon storage capacity

Optimization of land use allocation is a challenging optimization problem that requires joint decision-making by multiple stakeholders for conflicting objectives. In addition, the solution space of the optimization becomes more complex as the size of the study area increases. With the ACO algorithm developed for this study, a problem solution that can solve complex allocation problems of multiple land use types was tested. The spatial change mechanism of the program was equipped with various strategies that can deal with competition between different varieties of land use allocation. With the developed solution space, an optimization program was obtained that can meet the land use requirements of Adana province in 2050, while at the same time preserving the suitability of land use at the maximum level, the compactness of land use at the optimum level, and the carbon storage capacity of the land at the terrestrial level at the maximum level. This program was tested for this sample area consisting of 15,663,097 cells (30x30m). When the 2020 reference land use layer was compared with the 2050 target land use allocation layer, it was observed that the land use suitability score of the study area increased from 1177993.08 to 1625142.58, the compactness score increased from 292576.05 to 1384057.12, and the carbon storage capacity score decreased from 243879.13 to 165288.71. This experiment proved that the developed program is an effective optimization technique to obtain the optimal land use allocation pattern.