Aliakbar Anabestani; Zahra Anabestani; Ebrahim Akbari
Abstract
Extended Abstract
Introduction
Determining landscape changes and the impact of urban development requires analyzing land surface changes and identifying appropriate algorithms. And it cannot be ignored that traditional methods for examining land use change and land cover, such as land surveying, are ...
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Extended Abstract
Introduction
Determining landscape changes and the impact of urban development requires analyzing land surface changes and identifying appropriate algorithms. And it cannot be ignored that traditional methods for examining land use change and land cover, such as land surveying, are generally time-consuming and costly and require special skills. In this regard, the advent of remote sensing techniques, GIS has enabled researchers, planners and city managers to have a comprehensive view of land and land use change over time at a lower cost. However, these tools alone cannot describe the main trends and patterns of the city and urban development; Therefore, a combination of land use metrics and development index was proposed, which, along with remote sensing and GIS, lead to more desirable and accurate results. As a result of the present study, with the aim of analyzing the structural changes of the landscape and urban development patterns of Mashhad city using multi-time satellite images during the years 2000, 2010 and 2020 has been done. Also, in this regard, the main research questions are as follows: 1- Which direction will the growth and development of Mashhad city from 2000 to the horizon of 2040? 2- What kind of growth has followed the expansion of Mashhad from 2000 to 2040?
Materials & Methods
The present study is descriptive-analytical in nature. Information was prepared and adjusted through Landsat TM satellite images of 2000 and 2010, OLI sensor for 2020. Before performing the operations related to image processing, radiometric and atmospheric corrections were used using ENVI5.3 software and the FLAASH method was used for atmospheric correction. The images were then categorized using the maximum probability algorithm. In this method, educational samples were used to classify the pixels. Markov chain model in TERSET software was used for prediction on horizons 2030 and 2040. Then the generated maps were entered into FRAHSTATS4.2 software to measure the metrics of the landscape. Also, the Urban Growth Type Outlook Development Index (LEI) was evaluated using GIS software.
Results & Discussion
According to the land use map prepared for a period of 20 years, land related to the city in this period for the city of Mashhad due to population growth and demand for land as a result of urbanization growth in recent decades has the most area changes. So that the area of these lands has increased from 7% in 2000 to 12% in 2020 and this shows a 5% growth in the land area of this land use during this period. Agriculture and gardens from 2000 to 2020 has had an increasing trend 1. Therefore, the area of this user has increased from 11% in 2000 to 17% in 2010 and this shows a 6% growth in the area of this user. But from 2010 to 2020, the area of agricultural use and gardens has been drastically reduced. As a result, the area of this user in 2010 is equal to 17% and for 2020 is equal to 8%, which indicates a 9% decrease in the area of this user. Desert land use has been declining over the period, with a 4% reduction in area. The use of rangelands has not changed much during this period.
The analysis of metrics on the surface of the land for the horizon of 2030 Mashhad showed that the area of this city will not change. The number of spots will decrease, indicating that the shape of the city will become more cohesive over time. The index of the largest spot and the density of the margin will have a decreasing trend, and this indicates that the city will become more cohesive on the horizon of 2030. Landscape shape index will have a decreasing trend. Also, the analysis of metrics on the surface of the land for the horizon of 2040 Mashhad showed that the area of this city will not change. The number of spots will decrease, indicating that the shape of the city will become more cohesive over time. The index of the largest spot and the density of the margin will have a decreasing trend, and this indicates that the city will become more cohesive on the horizon of 2030. Landscape shape index will have a decreasing trend.
Conclusion
In examining the first question based on the growth and development of the city of Mashhad from 2000 to 2040, which direction will it be? According to the maps classified in a period of 20 years and the projected maps for the horizons of 2030 and 2040 for the city of Mashhad, it was determined that the most change is related to the city limits, so that in this period, the constructions and physical growth of the city have been in the northwest direction, and on the other hand, because the constructions are usually done on lands related to gardens and agriculture. In this part of the city, we are witnessing a decrease in agricultural lands and gardens, followed by an increase in urban areas. According to the map of 2020, agricultural lands and gardens in the southeast side still remain and one of the reasons could be the lack of development of the city in this direction. Also, in reviewing the second research question, what kind of growth has followed the expansion of Mashhad from 2000 to 2040? Findings showed that according to the urban development index and based on the numerical value given to the buffer, it was found that the development of Mashhad in the period between 2000 to 2040 is of the type of development from the edge of the city (edge-expansion).
Ali Akbar Anabestani; Hedayatollah Noori Zamanabadi; Masoumeh Mollanorozi
Abstract
Extended Abstract
Introduction
Evaluating the ecological capability is so important that if the selected land lacks the appropriate ecological potential for the implementation of a specific land use, implementing the plan (even if there is a socio-economic need for that specific land use) not only ...
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Extended Abstract
Introduction
Evaluating the ecological capability is so important that if the selected land lacks the appropriate ecological potential for the implementation of a specific land use, implementing the plan (even if there is a socio-economic need for that specific land use) not only does not improve the environmental status of the region, but also causes more environmental damages. As an economic activity that somehowsells the natural and cultural heritage of different regions, and depends on the natural environment and its exploitation, tourism is one of the most important environmental potentials. Therefore, tourism is considered to be a path to sustainable development, which through its multidimensional nature not only meets the needs of tourists, but also creates major changes in the systemof the host society. Consequently, in order to achieve sustainability, tourismshould be planned in a way that it does not negatively affect the environment, economy and culture of the host societyand meets the needs of the current generation without overusing what also belongs to the next generations.
Materials & Methods
The present studywas applied in nature and took advantage of a descriptive-analytical method to study the parameters in two main sub-sections.The first part included a library research performed with the aim of investigating related theoretical literature and the research background.The second part included some interviews and a field research performed for data collection. To evaluate the regional environmental capability and overlayingmaps in ArcGIS environment, Weighted Linear Combination (WLC) methodand Fuzzy operatorswere used. First, the final map of ecological capability for the development of sustainable rural tourism was analyzed and evaluated using WLC method based on highly appropriate, appropriate, limited appropriateness, inappropriate, and highly inappropriate classes. Then, fuzzy maps were produced with a gamma value of 0.7, 0.8 and 0.9 to obtain the tourism capacity of the region. And finally, the Kappa coefficient was used to compare the accuracy of classifications obtained from the WLC and fuzzy methods.
Results & Discussion
Findings indicate that with a weight of 0.33,tourism resources are the most important factor or capability in the development of sustainable rural tourism in Neyshabur County. The topography, with a weight of 0.192 is considered to be the second most important factor according to the experts and specialists. The third most important factor is the land cover with a weight of 0.138 and then, climate criteria with a weight of 0.117, hazards with a weight of 0.088, socioeconomic factors with a weight of 0.084 and water resources with a weight of 0.051 had the highest scores. Finally, the scores were applied to the GIS environmentusing the WLC method, and the final map of land capability for sustainable rural tourism in Neyshabur County was obtained.
Also, the statistical information obtained from the final map of land capability shows that 27.27% of the area is located in the very appropriate class, and31.76%is located in the appropriate class, while 22.23% and 4.28% of the region belongs to the highly inappropriate and inappropriate classes respectively.In the next step, tourism capacity maps of the region were prepared using a Fuzzy model with 0.7, 0.8 and 0.9 operators. The study area was divided into five categories: very high, high, medium, low and very low in terms of tourism capability.
The last and the most important step was to find the most accuratemap from those produced using AHP and fuzzy methods with different gamma values of 0.7, 0.8 and 0.9. To reach this aim, field observations and interviews with experts and specialists ofthe field were performed. Therefore, results obtained from the maps were compared with the experts’ opinions. Findings indicates that the operator with a gamma value of0.7 and a kappa coefficient of 0.84 is considered to bemore reliable than the operators with a gamma value of0.8, and 0.9 and AHP model. Thus, the 0.7 gamma operator is considered to bethe most suitable model for environmental capabilityassessmentin the region regarding tourism.
Conclusion
Using natural capabilities and potentials is the most cost-effective and lucrative way to achieve sustainable development. Findings of the present studyindicated that the operator with a gamma value of 0.7 and a Kappa coefficient of 0.84 is considered to be the most suitable model for the assessmentof the region’senvironmental capability for the development of sustainable rural tourism and it is more reliable and appropriate than the AHP model and operators with a gamma value of 0.9 and 0.8.Finally, considering the capabilities and potentials of the Neyshabur County for the development of sustainable rural tourism, it is recommended to consider development of tourism in this county as the priority of rural development plans and to use the natural resources of the area especially in the appropriate and highly appropriate classesas a way to achieve sustainable tourism development of the county in the most cost-effective way. It is also suggested that with appropriate management, planning and using the ideas of academic researchers to improve the capabilities of theaverage class, we can make the most out of the potentials of this area to develop sustainable regional tourism.
