Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran
In recent years, lifestyle changes and urbanization of societies, as well as macro-environmental changes, i.e. climate changes (CCs), have caused changes in the land spatial structure and the transfer of resources between different economic sectors of the land. The development of long-term spatial d...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023069931 |
| _version_ | 1797669746621022208 |
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| author | Hossein Karami Romina Sayahnia Shahindokht Barghjelveh |
| author_facet | Hossein Karami Romina Sayahnia Shahindokht Barghjelveh |
| author_sort | Hossein Karami |
| collection | DOAJ |
| description | In recent years, lifestyle changes and urbanization of societies, as well as macro-environmental changes, i.e. climate changes (CCs), have caused changes in the land spatial structure and the transfer of resources between different economic sectors of the land. The development of long-term spatial development plans (SDPs) needs to be compatible with CCs, especially in hyperarid areas with low supplies and high demands. In this research, machine learning methods; including Cellular Automata (CA), Random Forest (RF) and regression models through PLUS model were used to simulate the amount of supplies and demands based on land cover (LC) maps during the years 2000, 2010 and 2020 in the hyperarid areas of Kerman, Iran. Then, the best predicted model (Kappa = 0.94, overall accuracy = 0.98) was used to simulate changes in LC classes under climate change scenarios (CCSs) for 2050. The results showed the efficiency of machine learning in simulating land cover changes (LCCs) under CCSs. Findings revealed that SDPs of these areas are not compatible under any possible consideration of CCSs. The modeling results showed that spatial development plans under CCSs is not environmentally efficient and there is no compatibility between supplies, based on agricultural lands, and demands, based on increased population, by 2050. Overall, under the scenario of RCP 8.5, man-made, agriculture and natural LC classes with 106.9, 2.9, and 18.6% changes, respectively, showed the greatest changes compared to 2020. Population control, adjustment of infrastructures, and changes in LC plans can reduce socio-economical and socio-environmental problems in the future of hyperarid areas to some extent. |
| first_indexed | 2024-03-11T20:49:01Z |
| format | Article |
| id | doaj.art-0b9bbc49bdf542c6bc2ff3b269e4df59 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-11T20:49:01Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-0b9bbc49bdf542c6bc2ff3b269e4df592023-10-01T06:01:16ZengElsevierHeliyon2405-84402023-09-0199e19785Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, IranHossein Karami0Romina Sayahnia1Shahindokht Barghjelveh2Department of Environmental Planning and Design, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, 1983969411, IranCorresponding author.; Department of Environmental Planning and Design, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, 1983969411, IranDepartment of Environmental Planning and Design, Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, 1983969411, IranIn recent years, lifestyle changes and urbanization of societies, as well as macro-environmental changes, i.e. climate changes (CCs), have caused changes in the land spatial structure and the transfer of resources between different economic sectors of the land. The development of long-term spatial development plans (SDPs) needs to be compatible with CCs, especially in hyperarid areas with low supplies and high demands. In this research, machine learning methods; including Cellular Automata (CA), Random Forest (RF) and regression models through PLUS model were used to simulate the amount of supplies and demands based on land cover (LC) maps during the years 2000, 2010 and 2020 in the hyperarid areas of Kerman, Iran. Then, the best predicted model (Kappa = 0.94, overall accuracy = 0.98) was used to simulate changes in LC classes under climate change scenarios (CCSs) for 2050. The results showed the efficiency of machine learning in simulating land cover changes (LCCs) under CCSs. Findings revealed that SDPs of these areas are not compatible under any possible consideration of CCSs. The modeling results showed that spatial development plans under CCSs is not environmentally efficient and there is no compatibility between supplies, based on agricultural lands, and demands, based on increased population, by 2050. Overall, under the scenario of RCP 8.5, man-made, agriculture and natural LC classes with 106.9, 2.9, and 18.6% changes, respectively, showed the greatest changes compared to 2020. Population control, adjustment of infrastructures, and changes in LC plans can reduce socio-economical and socio-environmental problems in the future of hyperarid areas to some extent.http://www.sciencedirect.com/science/article/pii/S2405844023069931Climate change scenariosHuman developmentLand coverSupply and demand |
| spellingShingle | Hossein Karami Romina Sayahnia Shahindokht Barghjelveh Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran Heliyon Climate change scenarios Human development Land cover Supply and demand |
| title | Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran |
| title_full | Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran |
| title_fullStr | Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran |
| title_full_unstemmed | Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran |
| title_short | Integrating climate change adaptation policies in spatial development planning in hyperarid regions of Kerman province, Iran |
| title_sort | integrating climate change adaptation policies in spatial development planning in hyperarid regions of kerman province iran |
| topic | Climate change scenarios Human development Land cover Supply and demand |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023069931 |
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