A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Land Cover Change Simulation Based on Cellular Automata Using Artificial Neural Network Model Transition in Kedungkandang District, Malang City
Kedungkandang District, Malang City, has experienced a rapid increase in population, so within ten years there has been a conversion of non-built land. In line with population development, Kedungkandang District is also experiencing very rapid infrastructure development, so it is indicated that it can encourage greater land conversion. This study tries to develop a spatial model of land cover change in the Kedungkandang District based on Cellular Automata. The researcher uses the Artificial Neural Network (ANN) model, which is a machine learning technique used to model potential future land cover change transitions. The prediction results show that there is a growth of 166,78 hectares of built-up land from 2016 to 2036. The results of this modeling and prediction can be used as a basis for stakeholders in formulating future needs for infrastructure and public facilities, as well as ensuring effective policies to embody a sustainable environment.
Land Cover Change Simulation Based on Cellular Automata Using Artificial Neural Network Model Transition in Kedungkandang District, Malang City
Kedungkandang District, Malang City, has experienced a rapid increase in population, so within ten years there has been a conversion of non-built land. In line with population development, Kedungkandang District is also experiencing very rapid infrastructure development, so it is indicated that it can encourage greater land conversion. This study tries to develop a spatial model of land cover change in the Kedungkandang District based on Cellular Automata. The researcher uses the Artificial Neural Network (ANN) model, which is a machine learning technique used to model potential future land cover change transitions. The prediction results show that there is a growth of 166,78 hectares of built-up land from 2016 to 2036. The results of this modeling and prediction can be used as a basis for stakeholders in formulating future needs for infrastructure and public facilities, as well as ensuring effective policies to embody a sustainable environment.
Land Cover Change Simulation Based on Cellular Automata Using Artificial Neural Network Model Transition in Kedungkandang District, Malang City
Lecture Notes in Civil Engineering
Swasto, Deva Fosterharoldas (editor) / Rahmi, Dwita Hadi (editor) / Rahmawati, Yani (editor) / Hidayati, Isti (editor) / Al-Faraby, Jimly (editor) / Widita, Alyas (editor) / Hariyanto, Annisa Dira (author) / Yudono, Adipandang (author) / Wicaksono, Agus Dwi (author)
International Conference on Indonesian Architecture and Planning ; 2022 ; Yogyakarta, Indonesia
2023-06-27
19 pages
Article/Chapter (Book)
Electronic Resource
English