The topic of climate change and the dangers that lie ahead is part of the debate in land management. The dynamics of global change and the sovereign approach of global governments have opened new perspectives on land management issues. One of the hidden challenges in this regard is the increasing risk of the occurrence of floods. The purpose of this study was to undertake metric or measurement model as a spatial basis unit to predict flood occurrence. In the present article, in line with using MikeUrban 2019 software, a wide range of tools and quantitative processing steps were used in accordance with the research objectives. In order to predict floods, the past incident factors were studied, namely a review of the principles and operational indicators related to each parcel using the OLI sensor images of Landsat 8 satellite in the year 2020 through the integrated interpretation method and an examination of the basic map of Ilam city in wet seasons (autumn, winter, and spring). Then, the city coverage map was prepared in two uses, i.e., False Color (Urban) and Land / Water. Next, Google Earth images were used to determine the accuracy and precision of the coverage maps. By combining four selected measures with the highest spatial correlation in 50 random points of the city, hexagonal measures with optimal areas were selected and spatial patterns were analyzed. According to the results, in the actual event (1), eight spatial measures with an area of ​​68 hectares and coverage of 1.5% of the entire city are at risk of flood. In events 0.8 and 0.9, 19 measures with an area of ​​170 hectares, 3.6% of the land use coverage of the area, are at potential risk. While there is a high correlation between flood event and type of measure, amount and direction of slope, as well as density and width of road network on one side and drainage network on the other side, in high events (1-8), 28 measures in the residential uses in the detailed design scale with an area of ​​76.5 hectares, barren and enclosed uses with an area of 70.55 hectares, roads network with an area of 29.75 hectares, and parks and green spaces with 17 hectares were identified as the uses targeted by the flood danger. Among all risky user groups, 29.5% were identified in the newly built group, 44.5% in the maintainable group, and 18% in the decayed urban environment group.

The habitat development and establishment are directly related to the natural bedrock and geomorphologic complications. Due to topographical and geological conditions, the area under study has certain limitations in locating and developing human settlements. In order to reduce the hazards in the southeast of Khorasan Razavi province and modify plans for the development and establishment of human settlements, the feasibility of the area under study for residential development was investigated. After conducting library and field studies and selecting appropriate criteria, the fuzzy logic model was applied using the GIS software to identify areas for habitat development and establishment. In this study, to identify the potential areas for habitat development and establishment based on geomorphologic landforms, eleven parameters – including slope, slope direction, elevation, soil, land use, elevation, distance from fault, distance from river, distance from road, distance from settlement, and geomorphology – were used as independent variables in identifying geomorphological abilities and bottlenecks in the area. The results of zoning based on the fuzzy model showed that about 61% of the study area is located in very inappropriate and inappropriate classes, which means that geomorphological conditions in this part of the study area are unfavorable for the development and establishment of human settlements. About 14.58% of the study area has moderate conditions and about 24% of the study area shows favorable geomorphological conditions for construction activities and creation of new habitat areas. Alluvial fan units and alluvial plains are the most suitable sites for habitat development and establishment.

The detection of urban landscape changes in urban areas is of utmost importance for the maintenance of the safety of environment and the promotion of sustainable development. To this end, the consideration of the spatial metrics capabilities to describe the landscape structure can be a valuable move to identify the growth models in metropolises. The purpose of this study was to provide the urban-rural gradient analysis of the landscape metrics in Tehran metropolis in the year 2018 as well as the analysis of their change trend in order to investigate the spatial-chronological changes in the landscape. In order to analyze the metrics, the moving window method was used at landscape and class levels. To this end, Landsat 8 satellite images were used, and the landcover was divided into human-made, open, vegetation, and water lands in a supervised manner. As with the gradient analysis, transects with 4km*4km dimensions at four directions – namely center-northeast, center-southeast, center-northwest, and center-southwest were directed from District 12 of Tehran Municipality in GIS 10.2 software. The results showed that at the landscape level, the closer we go to the business center of Tehran Metropolis, the number and density of patches increase, while the closer we go to rural areas the average index of landscape shape has relatively uniform changes. At the class level, the more distant we get from the business center of Tehran metropolis, the percentage of human-made patches and open lands increases and that of the vegetation patches decreases. Then, it might be concluded that urban development has brought about an increase in the density of patches in landscape, such that in the central transect, the continuity of landscape is reduced, and the fragmentation of the structural elements of landscape is increased. The land use changes have led to the expansion of the city toward the country and have negatively affected the vegetation and water resources.