Land use Planning
Bahman Veisi Nabikandi; Abolfazl Ghanbari
Abstract
Evaluating and forecasting the changes in habitat quality (HQ) caused by land use/land cover (LULC) variations during urbanization is crucial for establishing a comprehensive ecological planning system and tackling the obstacles to global sustainable development. Over the last several decades, the biodiversity ...
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Evaluating and forecasting the changes in habitat quality (HQ) caused by land use/land cover (LULC) variations during urbanization is crucial for establishing a comprehensive ecological planning system and tackling the obstacles to global sustainable development. Over the last several decades, the biodiversity and environmental quality of the northern provinces have seen significant transformations as a result of population growth, urban development, climate change, and the rise in tourist activities. In this research, the LULC maps of Amol City were created for the years 2000 and 2020 using remote sensing data. Additionally, using the CA-Markov model, a simulation was conducted for the year 2035, considering two scenarios: Business-As-Usual (BAU) and Ecological Protection (EP). To assess the spatiotemporal changes occurring at HQ, we integrated the InVEST-HQ model with the CA-Markov model. The findings indicate a significant decline in overall HQ in the city of Amol between 2000 and 2020, mostly due to urbanization and agricultural expansion. Between 2020 and 2035, according to the BAU scenario, the landscape pattern and HQ will continue to deteriorate, following the previous trend of decline. The EP scenario, on the other hand, will be critical in stabilizing and supporting the area's HQ. This emphasizes the significance of preserving ecological spaces like forests and grasslands. The study's maps and findings may assist local managers and related organizations in implementing more efficient plans and solutions for the preservation of these ecosystems.
Urban Planning
Bratali Khakpoor; Zohre Bolori; Roghayeh davari
Abstract
The purpose of this study was to determine and diagnose the relationship between viability indices of dense neighborhoods. For this purpose, nineteen operators were identified by studying the literature of the subject and interviews with urban planning specialists and urban planning that has been experienced ...
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The purpose of this study was to determine and diagnose the relationship between viability indices of dense neighborhoods. For this purpose, nineteen operators were identified by studying the literature of the subject and interviews with urban planning specialists and urban planning that has been experienced about life. These factors were divided into six general, functional, social, natural, economic, visual and perceptual categories. Then, in order to identify the axial indexes of the model, the cognitive fuzzy mapping was used and the penetration rate of each indicator was determined on each other In the following, the matrix obtained in the FCmapper software was implemented and the fuzzy cognitive map was drawn.In this study, after reviewing 19 indicators, land indices and density, residence satisfaction, parts size, social interactions, diversity of housing and prosperity and flourishing of the neighborhood economy are 6 important indicators in terms of focusing the most effectiveness and effectiveness in relation to other There are environmental indicators, among which the earth and density are more centered than other factors. The size of the components is important in the second rank. These two indicators have the greatest influences in other variables. The satisfaction index of residence receives the most influences from other variables.
