The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated ...The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated spatial plan.The study used a quantitative survey using Landsat images in 2016,2019,and 2022.The data analysis techniques used geographic information systems integrated with Artificial Neural Network(ANN)and Cellular Automata(CA)models.This study aims to predict land-use change in 2031,evaluate its alignment with spatial planning,and provide guidance for controlling land-use change.The results showed that there has been an increase in land use.In 2019,built-up land reached 7,069.65 Ha.The model shows its ability to predict land simulation and transformation,where it is predicted that built-up land in 2031 will experience an increase of up to 40.10%,so development and change cannot be avoided every year.This study also suggests that decision-makers and local governments should reconsider spatial planning strategies.This study shows that there have been many land use changes from 2016 to 2022.The model shows its ability to predict simulation and land transformation.When using the model,there are many changes in the land use area in 2031.This is due to wet agricultural land turning into built-up land by almost 70%.This study shows that road network influence land-use change.The cellular automata model managed to capture the complexity with simple rules.Predictions for future research should focus on conserving wetlands and primary forests.展开更多
基金supported by the Ministry of Education,Culture,Research,and Technology Directorate General of Higher Education,Research,and Technology grant number[2147/UN2621/PN/2022].
文摘The simultaneous increase in development in Pesawaran Regency is closely correlated with the intense competi-tion for land use.However,low policy implementation effectiveness has led to construction beyond designated spatial plan.The study used a quantitative survey using Landsat images in 2016,2019,and 2022.The data analysis techniques used geographic information systems integrated with Artificial Neural Network(ANN)and Cellular Automata(CA)models.This study aims to predict land-use change in 2031,evaluate its alignment with spatial planning,and provide guidance for controlling land-use change.The results showed that there has been an increase in land use.In 2019,built-up land reached 7,069.65 Ha.The model shows its ability to predict land simulation and transformation,where it is predicted that built-up land in 2031 will experience an increase of up to 40.10%,so development and change cannot be avoided every year.This study also suggests that decision-makers and local governments should reconsider spatial planning strategies.This study shows that there have been many land use changes from 2016 to 2022.The model shows its ability to predict simulation and land transformation.When using the model,there are many changes in the land use area in 2031.This is due to wet agricultural land turning into built-up land by almost 70%.This study shows that road network influence land-use change.The cellular automata model managed to capture the complexity with simple rules.Predictions for future research should focus on conserving wetlands and primary forests.
