Modeling urban expansion in Zahedan’s dry climate: insights from the SLEUTH model

IntroductionRapid uncontrolled growth of build-up areas has increasingly challenged the sustainable use of urban area simulating the growth patterns of fastest-growing cities is more necessary in dry climates, due to low ecological suitability for urban development and meeting the needs of citizens. Therefore, this research conducted aiming at predicting the expansion of urban land use in Zahedan City, Iran, which has a dry climate with an evenness landscape.MethodsUrban Expansion in Zahedan Modeled using SLEUTH (slope, land use, exclusion, urban extent, transportation and hillshade) in two historical and environmental scenarios until 2050. The input data were extracted from processing on DEM and remote sensing data and the SLEUTH model was calibrated in four stages from 1990 to 2020.Results and discussionThe results showed that the increase in Ahead extent in 2050 is more than twice as much as in 2020, and this increase was associated with a less dispersion of urban patches in the environmental scenario compared to the historical scenario. Also, the results clarified that the developable spaces are saturated in terms of slope in the east and there is the lack of urban green spaces. These results reveal the need for the attention of city managers in predicting the urban green space in the expected growth areas and compensating for the lack of vegetation cover in the former urban areas. Geographic extension of predicted urban land can be used in future environmental planning and urban developing strategies, as well as it is suggested to adopt this approach as a plan for urban planning in dry climates

Systematic design of habitat services network (HSsN) for updating conservation areas in iran's arid and Semi-Arid ecosystems

Threats caused by human activities have reduced the quantity and quality of wildlife habitats connectivity. This research seeks to protect habitat biodiversity by creating a network of high quality habitats that remained. Therefore, it is very necessary to know about the dynamic effects of changes in the landscape pattern on the quality of the habitat, because it helps to preserve biodiversity, guarantee ecological security, and environmental sustainability. In the present study, a systematic process was used to design a network of habitat services comprising hotspots and corridors in arid and semi-arid ecosystems of eastern Iran, South Khorasan Province. In this process, habitat quality was first modeled using the InVEST software, then data mining methods were used to identify habitat hotspots and their spatial distribution. In the next step, habitat corridors were extracted based on the circuit theory and using the Circuitscape software. In the ultimate step, using graph theory based on the concept of ecological security, the connectivity of the habitat network was evaluated. The results of habitat network construction showed that 8% and 6% of the total area of the study area included key habitat patches and corridors, respectively. On the other hand, the overlapping of habitat network components with the conserved areas of the study area showed that free or non-conservation areas make up a significant amount of network components (49.18% of the habitat patch and 80.02% of the habitat corridor). These results reveal the existence of habitat protection potential and can help in updating the new boundaries of conservation areas. Also, the composite indices of dPC and dIIC could determine the importance of each of the network's components in evaluating the connectivity of the habitat network, so that the application of the results can show the priority options to the land managers for protecting the habitat network. In general, the systematic process proposed in this research can be used in planning the sustainable conservation of habitat networks, identifying patterns of ecological security, evaluating and constructing habitat networks in lands with similar climates, and changing and wisely reviewing the conservation area boundaries

Changes detection of birds and fishes indicators using cross-impact matrix of KSIM in Hamoon international wetlands

In recent decades, the drastic ecological changes of Hamoon international wetlands placed them on the Montreal blacklist. Therefore, this study aimed to predict and validate the changes of birds and fishes indicators for the future of these wetlands. KSIM is the used method (Kane Simulation Technique to measure the impact of different variables ranged from +3 (severe and positive effect) to -3 (severe and negative effect); is evaluated by environmental experts. Due to the limitations of this method in multivariate analysis (because of the numbers and abundance of variables), the affecting factors on indicators have been grouped into four categories of economic, social, wildlife management and water resources management. To obtain probabilities of variables and predict the value of indicators in 2034, the mode of experts' ideas was used and future trends were simulated. Model validation was performed by field surveying in two consecutive years. The results of the KSIM simulation estimated that the bird and fish indicators will continue to decrease during the period 2004-2034; from 0.77 to 0.28 and 0.60 to 0.22, respectively. Based on the validation results, the validity of the model is acceptable, which can be confidently used based on the results obtained from the experts' ideas in the cross-effects matrix. This study showed that the KSIM method can properly investigates the interactions between system components and therefore is able to predict future conditions. Economic and social problems lead to the decline of fishes and birds indicators; and deterioration of the situation put relatively more pressure on resources. The downward trend in wildlife management and water resources is also a serious warning that must be considered in decision-making processes

Habitat Quality Assessment Using InVEST Model and its Valuation Through ‎Cost Compensation Method‎ in ‎Kerman ‎Province

Increasing development activities have led to a reduction in habitat quality and biodiversity loss. Utilization of industrial and mining capacities and the development of infrastructure are among the most important components of habitat quality decline in Kerman province. In this study, the quality and destruction of habitats in Kerman province were modeled using Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The habitat quality map of the ungulates was valued using the cost compensation method, and the average habitat quality value was used as an independent variable in the regression analysis to predict the economic value of the habitat. The results showed the highest degradation of the habitats in the northwest of the province, where most of the threat factors are present. The northeastern parts of the province have experienced the least degradation. The highest-quality and most valuable areas, which cover 42.8% of the province, have the highest level of habitat degradation. These habitats are mainly cover by dense forests and rangelands. The total habitat value of Kerman was estimated at 2437 billion Tomans. The final habitat valuation map can be used as a decision-making criteria in environmental management for locating development projects, estimating damages, and updating the boundaries of protected areas

Accuracy and validity assessment of application algorithms in land use allocation into comparison LP, SA, MOLA and MDCHOICE

The main viewpoint of land use planning is to resolve the conflict between competing land uses in one place that is carried out based on their economic, social and environmental suitability. Many different approaches have been designed to resolve this conflict but any of them have done. This study aimed to assess accuracy and validity compared four optimization algorithms, including linear programming (LP), simulated annealing (SA), multi-objective land use allocation (MOLA) and multidimensional choice (MDCHOICE) for land use planning in Gorgan Township. At first, land use allocation was done through the LP algorithm. Then, using achieved pixels quantity from LP optimization, the land uses was optimized in term of spatial suitability by other algorithms. The allocation maps generated through these algorithms were compared using statistical methods and landscape metrics. The map provided through MDCHOICE was used as a reference map and that generated through MOLA, SA and LP as a comparative one in a validation process. The similarities and agreements of the two maps were evaluated with various algorithms in IDRISI and MCK software. The results demonstrate that: (1) It follows that the LP algorithm to determine the optimal number of pixels to lead MDCHOICE has helped in the spatial allocation properly. (2) MOLA had a better performance for development in terms of all landscape metrics and SA algorithm was better in forestry land use allocation. Therefore the quality of spatial allocation both of them needs to be improved. (3) Although the LP algorithm is not superior to the algorithms based on the dimensions studied in this research, in terms of achieving the defined goals and the degree of deviation from the number of cells defined for each land use has the least violation. (4) The superiority of MDCHOICE over MOLA, SA and LP and applicability of various kappa statistics for comparing the maps for a more in depth analysis of agreements and disagreements