Identifying suitable areas for locating multi-purpose urban green spaces for temporary housing after the crisis, case study: Rasht city

Identifying Suitable Areas for Locating Multi-Purpose Urban Green Spaces for Temporary Housing After the Crisis

Case Study: Rasht City

Extended Abstract

Introduction

Redefining the concept of urban green space not only as a place for recreation but as a flexible and multi-purpose use in different conditions can be effective in the resilience of urban living and life after disasters. In this regard, the current research is an attempt to optimize urban green spaces in Rasht city, which, in addition to the social, welfare, and recreational functions, examines the hidden capacities of these spaces to reduce the risks caused by disasters. Spaces that, in addition to providing various types of services under normal conditions, can turn into places for citizens to settle in the shortest time after a crisis, and access to other services is also easier in these places than in other areas. Moreover, they have the highest safety conditions. Among these capacities is the establishment of temporary accommodation bases in multi-purpose green sites, and the optimization of suitable locations for these bases and their spatial analysis are on the agenda of the present research.



Methodology

The current research is applied based on the purpose and descriptive survey regarding the data collection method. The spatial territory of the research is Rasht. The number of 4 criteria and 26 sub-criteria effective in locating multi-purpose green spaces has been extracted through library studies and confirmation by experts. In the next stage, with experts' opinions, the weight of criteria and sub-criteria was determined using the "best-worst" multi-criteria decision-making method by distributing a multi-stage questionnaire among 15 experts and specialists. The inconsistency coefficient calculated for all 15 experts in all pairwise comparisons was less than 0.1, which shows the reliability of the questionnaire and compatibility. Next, in order to perform spatial analysis, the information layers of the indicators are digitized in GIS software, and by converting the information layers into a raster and standardizing them, the final composition of the layers is discussed. Then, the fuzzy areas were divided into five classes by reclassifying the final overlap map. After classifying the zones and optimal areas for the construction of multi-purpose green spaces in Rasht, the area of optimal zones was calculated separately to check the capacity and capabilities of each area of Rasht.



Results and discussion

The results of the implementation of the BWM model showed that at the level of comparison of criteria, the "efficiency" criterion with a weight of "0.3088" is the most important criterion among other criteria. After determining the layers' weights by multiplying the criteria' weights in the sub-criteria, their ranking was done separately for each dimension. Therefore, at the sub-criteria level, "population density" with a weight of "0.120" was identified as the most important sub-criteria in the efficiency dimension. In the dimension of incompatibility, "distance from high-risk facilities" with a final weight of "0.023" was determined as the most important sub-criterion. "Proximity to residential areas" with a final weight of "0.137" and "distance from the fault" with a final weight of "0.137" were also determined as the most important sub-criteria in the criteria of "compatible uses" and "natural features." After the weighted final layers were standardized and analyzed based on fuzzy functions, the final combination of weighted layers was attempted to reach the zoning map of the optimal locations of multi-purpose green spaces in Rasht. Then, by reclassifying the final overlap map of gamma 0.9, the specified areas were classified into five categories as very suitable, suitable, relatively suitable, unsuitable, and very unsuitable. Finally, this research identified two suitable and very suitable floors as optimal ranges for multi-purpose green spaces in five districts of Rasht. After classifying the zones and optimal areas, the area of the optimal zones was calculated separately to check the capacity and capabilities of each district of Rasht.



Conclusion

In this research, by emphasizing the capabilities of green spaces to improve the management of residential areas after the crisis, especially planning for temporary accommodation and creating secondary shelters for residents, the optimization of the location of multi-purpose urban green spaces in Rasht was done. For the final zoning of the optimal areas for the construction of multi-purpose green spaces and temporary accommodation, by extracting and scoring the essential sub-criteria in the form of four criteria as "efficiency," "closeness to compatible uses," "away from incompatible elements," and "natural features," using the integration of the new BWM multi-criteria decision making approach and fuzzy functions in the GIS environment, it was determined that the largest area of the optimal area with an area of 413.64 very suitable hectares and 553.86 suitable hectares is related to the District 3 of Rasht. Also, District 1, with 262.59 hectares of very suitable area and 455.98 hectares of suitable area, was ranked second among the five districts of Rasht. The lowest area of the optimal zones, with an area of "312.866" hectares, is related to District 5 of Rasht. After re-evaluating the optimal areas according to field observations and analysis of satellite images, it was determined that there are many empty and barren lands, proximity to residential, healthcare, and sports areas, distance from incompatible uses such as polluting industries, high-risk facilities, lines electricity and energy transmission, safety and efficiency levels such as proximity to roads and densely populated areas in Districts 1 and 3 are higher than other areas. In other words, it can be acknowledged that the criteria used in the research, the analysis done on them, and the research results are consistent with the real field of the studied area. Therefore, based on the findings of this research, Districts 1 and 3 of Rasht have the most significant ability to build urban multi-purpose green spaces and establish temporary accommodation sites.