entropy method

Today's Cities affected by the industrial Revolution have had a profound Impact on the Development Process, so that today they are recognized as the main Causes of instability in the World, and any measures of global Sustainability depend on urban Sustainability. The Metropolis of Tehran has witnessed many Changes in recent Decades, especially in the field of Environment. Therefore, in order to get out of the destructive Consequences of traditional and different Development Patterns and Approaches in Tehran Metropolis, the use of environmentally friendly Approaches such as the Green City Approach in the Development Process of this Metropolis and achieving sustainable urban Development is very important. The present research is theoretical-applied in terms of Type, descriptive-analytical in terms of Study method, survey-library in terms of Data collection Method and a questionnaire based on Likert Scale. The Purpose of this Study is to determine the environmental Status of the central and southern Regions of Tehran Metropolis based on the Indicators of the Green City Approach. Therefore, first, using Entropy Method, 32 quantitative Indicators in the form of 7 Criteria were weighed and then, using the TOPSIS Technique in Excell software, a comparison of central and southern Regions of Tehran Metropolis was performed to achieve the Research Goal. The Results show that most of the southern Regions of Tehran are in agreement with the Indicators of the Green City Approach, and accordingly, Regions 12 and 16 are in the best and Regions 10 and 17 are in the worst environmental Condition.

Landslides are one of the most alarming disasters that can cause severe damages to human lives and properties each year. This natural phenomenon can destroy or damage a variety of engineering and human structures, including residential areas, roads, gas pipelines, water and power lines, forests and pastures, agricultural lands and mines. In addition, the social and environmental impacts of this phenomenon such as adverse social effects and increase in the sediment load of rivers should not be overlooked. Due to its mainly mountainous topography, high tectonic activity and seismicity, diverse climatic, and geological conditions, Iran has mainly natural conditions to create a wide range of landslides. So, along with the many natural benefits that exist, the risks involved should not be ignored. The existence of large Zagros faults, alternation of calcareous hard layers and loose marl shale layers in the large anticlines have created favorable conditions for instability of natural slopes throughout Lorestan province. Therefore, this study aimed to prioritize the factors affecting landslide and its risk zonation by using the entropy method in the Ahmadabad basin, Lorestan province.

In this study, 8 factors including slope, lithology, precipitation, land use, elevation, and distance from springs, roads and streams were prepared and quantified as factors affecting landslides. According to the characteristics of the landslides of Ahmadabad basin and expert opinion, each layer was given a score of 1 to 9 based on its importance in occurrence or intensification of landslides. After the classification of layers, the entropy matrix was created. Calculating the entropy matrix and the total weight of the factors (wj) gives the coefficient of occurrence of landslide risk (Hi). The entropy model is expressed as follows.
Ej=-Ki=1npi, jInpi,j                                                                                                                            (1)
pi,j=ri,ji=1mri,j                                                                                                                                           (2)
where, Ej is the entropy value, pij is the decision matrix, and rji is the weight value of each layer, M is the number of landslides, and K is a constant coefficient.
After providing the decision matrix and obtaining the value of Ej, the value of Vj is obtained from Eq. 4.
k=(In m)-1                                                                                                                                         (3)
Vj=1-Ej                                                                                                                                            (4)
Vj is the degree of uncertainty deviation. The Eq. 5 is used to calculate the final weight of all factors (wj).
Wj=Vjj=1mVj                                                                                                                                           (5)
After that, the landslide hazard zonation in the studied basin is evaluated using Eq. 6.
Hi=i=0nWj*ri,j                                                                                                                                (6)

In this research, a bipolar scale is used to convert quantitative and qualitative values. After providing the entropy matrix and converting these criteria to an integer, by calculating the relationships and converting the quantitative values to quantitative ones, the information content in the matrix was first obtained as (pi, j) and, then, the value of Ej is calculated for each factor. The values of Vj and Wj were also calculated using Eqs 4 and 5, and, finally, the regional model of the landslide hazard rate was obtained based on Eq. 6.
Based on the relationship of the landslide risk coefficient, a landslide hazard zonation map has been prepared for the studied basin. Based on the results and in respect with 14.6%, 28.8%, 28.8%, 20.0% and 7.8% of the area were classified as very low, low, medium, high and very high, respectively. Then, the landslide area in each hazard class was determined and the accuracy of the entropy method was estimated using the additive utility method (AUM). The results showed that the accuracy of the method used in predicting landslide hazard zones is about 86%.

In this study, 8 factors have been investigated for zoning landslide risk. Prioritizing the factors affecting landslide using the entropy method shows that three factors including lithology, land use and slope with 24.1, 16.8 and 13.5% of impact have the most important role in landslide occurrence.
Based on the results, more than 56% of the study area is located in medium to high-risk zones, indicating a significant potential for landslide hazards. These zones are mainly located to the north and west of the region, which can be attributed to the sensitive lithology and slope susceptibility of these areas to landslide events. Also, according to the results, 10 villages are located in high to medium risk zones and most of the roads are located in these risk zones.
Therefore, it is necessary to avoid any constructions and increase safety of the existing structures in these areas. The results of the present study showed that the entropy method is suitable for identifying hazardous areas, so it is recommended to use the obtained results in land use decision making and management and regional planning.

The evaluation of urban land use reflects a clear picture of the city's perspective and how to allocate urban space to the needs of the city over time and in order to achieve the city's development goals. The main objective of this paper is to evaluate the feasibility of service utilities in Shiraz in a comprehensive and detailed plan and to examine the effective factors in its realization and non-fulfillment.

The research method is descriptive-analytic. First, using library-related resources, the concepts related to the use of lands were investigated and then, using statistical methods, the level of feasibility of service utilization of the detailed plan was analyzed in Shiraz areas. Is. In order to achieve the research objectives in this study, the GIS and EXCEL software has been utilized by entropy method. Finally, using the ranking of the regions in terms of per capita utilization of service utilities in the regions relative to the proposed per capita of the master plan in 1368, has taken place.

The results show that the utilization rate of utilities for the comprehensive plan of Shiraz after more than two decades has not been realized. The analysis of the weighted model indicates that the 4,2,6 regions have the highest environmental sustainability and the lowest 1, 7, and 5 regions.

This suggests that the spatial distribution of inappropriate and unfair service utilities in the area of the Shiraz area is inadequate, and analysis of the use of indicators of capacity and social justice indicates a quantitative and qualitative turmoil in the use of nine areas of Shiraz.

1. The pattern has been the same for the planning and management of agriculture in rural areas, which is applied to various forms of state failure and inefficiency of the agricultural development programs. Because this planning and management have not been designed based on needs, talents, and abilities of the rural areas, but based on consensus over the potential and actual needs and abilities. Accordingly, knowledge of the distribution and degree of development of agriculture in this area could be a prerequisite for agricultural and rural development projects and programs to be considered. In this regard, one of the ways that can be useful in planning and managing the development of agriculture is the classification of rural areas according to conventional indicators of agricultural development. Results obtained from the survey studies, showed that due to changes in development, regardless of its natural resources, these regions are among the deprived areas and to achieve the appropriate level of development requires government intervention and planning. Hence, in order to reduce the problems of development, intervention and orientation of the agricultural structure will be an important factor. In this regard, the aim of the present study is to determine the level of agricultural development (Farming Subsector) in rural areas in Dashtroom village in Boyerahmad county to improve rural development planning.
2. The present study, from the objective point is an applied research and from the analitycal point is quantitative research method. The population of the research consisted of rural areas more than ten households in the central part of the Dashtroom village in Boyerahmad county that includes 39 villages. To determine the sample size, Krejcie and Morgan methods was used through families residing in the study area. Sample size of 320 households were calculated, and then in every village, according to its population, a number of farmers who were the heads of households were selected. In this research, the data were primarily collected through field studies and questionnaire. Content validity was checked to determine the validity of the questionnaire which was designed and revised after consulting with university professors and experts. In order to determine the reliability of the questionare, the pre-test (30 questionnaires) was conducted; the Cronbach's alpha coefficient obtained indicated the reliability of the questionnaire. To assess the development of agriculture in the region, the hybrid method of TOPSIS-entropy was used. Data processing was carried out through using MATLAB 7.10 software.
3. The results showed that the agricultural development coefficient (Farming Subsector), in the rural areas of Dashtroom, is the highest (0.90) in Tangary village and the lowest (0.08) in Cheshmeh Baloot village. Thus, the amplitude of the development level in the agricultural sector was estimated 0.82. In addition, villages including Cheshmeh Balutak, Gav Barg, Kooshk Olia, Saadat Abad, Bahareh-e-Barg Khiari, Cheshmeh Khersi Piroozak, Chel Mohammad Bagheri Pereshkaft, Chel Mohammad-e-Bagheri Pereshkaft, Dare Khani Pereshkaft, Moradi Pereshkaft, Dare Galga Pereshkaft, Cheshmeh Roghat, and Chah Pazanan were considered as underdeveloped villages, and Tangary and Hussein Abad Olia as developed villages. Furthermore, the results indicated the unfavorable development of agriculture in the region (with an average of 0.35 in a range of zero to one); thus, most of the villages in the region (58.97 %) are the least developed ones. The calculated dichotomy coefficient reflects the existence of inequality and differences in the rate of development in rural areas. The results showed that the spatial distribution of agricultural development in the region is not in a balanced state. The data indicated that the average rate of development, in the agricultural sector, in terms of economic, social, technological, infrastructure, and environmental dimentions in the region is equal to 0.34%, 0.43%, 0.49%, 0.34%, and 0.52%, respectively. Given the agricultural development dichotomy coefficient, it can be said that, the lowest dispersion, with the coefficient of 0.34, was the technical dimension and the infrastructural dimension, with the coefficient of 0.53, was the maximum amount of dispersion and the lack of balance in the rural districts. Other findings indicated that the natural location of the villages under survey is effective in enhancing the rate of development of rural areas. So that, the villages located in the plain areas had higher development rate. It can be said that, the villages which are in a plain position have been developed more because they are in the normal position of infrastructure and services (i.e., good communication, good access to transportation, fertile lands, etc) for its residents in comparison to the villages in the hills and further development of the forest have created.
4. The findings suggested that, the studied villages have different levels of agricultural development. Tangary village, with the degree of development equal to 0.909%, and Cheshmeh Balootak village, with the degree of development equal to 0.082%, have the highest and the lowest level of agricultural development in the Dashtroom district. Among the five dimensions of agricultural development, dichotomy coefficient of technical dimension was the lowest that is indicative of the relative homogeneity of the villages in this dimension. Infrastructure dimension had the highest level of dichotomy coefficient. Data analysis revealed that, the degree of agricultural development in the region under study in terms of economic, social, technical, infrastructure, and environmental dimensions was 0.34, 0.43, 0.49, 0.34, and 0.52%, respectively, that reflects the superiority of environmental dimension compared to other dimensions. Overall, the results suggested that, the spatial distribution of agricultural development rate in the studied region is not in a balanced state.

The population of the world during the last few decades has had rapid and drastical growth. It has been documented that during 1950 to 1990 the urban population has increased three times i.e. from 730 million up to 2.3 billion. It is expected that this rapid growth become double until 2020 out of which 93% will be related to urban population of the developing countries. Thus it is essential that the required programs and planning should be considered for the upcoming over load of urban population. Before the few recent decades, most of Iranian cities have a balanced growth rate; however, in recent decades, urbanization has been preferred to urbanism which is due to a set of attractive factors on the part of cities beside the detractive factors of the villages. This is in turn led city expansion to serious problems. The township of Marvdasht, in its 70 year lifespan, has followed a variety of processes and patterns of physical growth, and has developed in an unbalanced order. Marvdasht city with its natural, industrial, economic, and tourism attractions has been recognized as one of the major pole of population and has had a remarkable growth of physical extension over the recent years. This undesirable growth has been due to the existing population as well as the migrated people to the city which has led to unplanned and poor physical construction of the city and has covered the agricultural land in a large scale. The population evolution of Marvdasht city during the current years is the result of turbulence which is affected by economical and social conditions of the region. The population of the city over the last 50 years 5.4% has grown and its population has increased from 8987 to 124350. From structural point of view the city has been formed in an integrative way out of which most of the areas have been located within the legal part of the city. The total areas of the city have been reported 1712 hectares out of which 60% is recognized as normal condition while the other part constitutes the sprawl extension. In fact, this city has had regular population growth and normal physical extension till 1996, but since then due to lack of proper urban planning and policy making there hasn’t been a parallel growth between physical extension and the increasment of population as a result the physical expansion has been more than the population growth and the city has rapidly expanded. The present pattern of physical expansion of Marvdasht city is mixed and has been affected by linear and checkered forms. This condition caused the city to develop along the axis road of Shiraz –Isfahan and its peripheral streets extend in the form of checkered to other parts of the city. On the other hand, during the recent years, the city authorities to reduce the traffic jam and prevent the linear expansion of city have constructed streets suitable direction of major network of western and eastern parts of the city. Although, this policy has played a role in proper checkered formation with extended structure of the city, the special structure of Marvdasht has been formed in a way that the total axis of industrial, transportation, warehouse holding, agricultural and residential areas have been located in the same neighborhood and this situation invokes a specific spacial- location relationship. The present research is done by comparative-analysis study method, by the help of Shannon’s and Heldren entropy models, to analyze how this township has developed. The results indicate that the township has developed in a concentrated manner up to the year 1997; however, after this time, it developed in an urban sprawl (spiral) way, which latter cases amount is specified using these 2 models. The results analyzed by Heldren model shows that during the1966 to 2008 over 67% of the physical extension of the city related to the population growth and the remaining 33% is related to vertical and sprawl growth of city and its affect has been on the reduction of impure density of the population and incensement of impurity of land percapita of city. Although, according to the current growth pattern of the township which is more of a linear form, and secondly, the increase in the entropy value gap due to the horizontal and spiral growth of the city; the latter in turn influenced by the linear growth pattern, now (2008), the best future pattern was determined as centralized sectorial method for the township. For this to take effect, we should use the intra-textual concentration expansion pattern, and simultaneously, contiguous sectorial pattern along with the system of crossover and diagonal communicative network. If so, we will see a reverse inclination towards urbanism prior to urbanization in the next stage, in order to optimize the future development perspectives, a setting of GIS soft ware’s and related models were employed. Last after the indication of index and layers and merging and intercovering of layer, proper town development site were extracted. It is worth mentioning that for the sake of easy and comfortable connection. In the transportation network of the city, along with intersecting network there must be established across network.