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Showing 7 results for hashemi

Dr Bahram Imani, Mrc Roghayyeh Farshi, Mr Reza Hashemi Masoomabad,
Volume 17, Issue 46 (12-2017)

In this study, to show the inequality between different cities in Ardebil province, 60 developmental indicators in different sections including health care, social, educational, cultural and infrastructural sections have been analyzed through VIKOR model. Moreover, for data analysis and graph and table representation of data Excel, SPSS, and ARC Map 10.1 software was used. For determining validity of the research indicators, questionnaires were completed by experts (16 experts and professionals in the related area) through AHP model. A survey in 2011 showed that from among 10 cities in Ardabil province, Ardebil city; Serein Germy and Khalkhal; Parsabad, Bilesavar and Namin; Meshginshahr, Nir and Kosar were developed, developing, less developed, and undeveloped areas, respectively. This inequality is the result of environmental, economic and political factors and it also reflects inadequacy of spatial planning, which places Ardabil in its high priority for development. Furthermore, according to the conducted analyses it is concluded that there is an imbalanced regional inequality on city scale in Ardabil province; there is a meaningful and positive relationship between the population of a city and the degree of its development; finally there is a meaningful and positive relationship between the distance from the provincial capital and the degree of its development. 

Mr Sirous Hashemi Darebadami, Dr Ali Darvishi Boloorani, Dr Seyed Kazem Alavipanah, Mr Mohammad Maleki, Mr Reza Bayat,
Volume 19, Issue 52 (3-2019)

The term urban heat island (UHI), described the phenomenon of climate change in urban areas compared with surrounding rural areas. UHI effects include: increasing in energy and water consumption, air pollution expansion and interfering in thermal comfort. Surface urban heat island (SUHI) contains patterns of land surface temperature (LST) in urban areas that has interaction with UHI in urban canopy layer and urban boundary layer and investigate with thermal remote sensing. SUHI has diurnal and seasonal variations so requires multi-temporal data to analysis SUHI. In this study, the multi-temporal MODIS (Aqua and Terra) data product were used to analyze the SUHI in day and night in Tehran metropolitan. Physical and biophysical surface properties such as: land cover/land use (LULC), elevation, albedo, vegetation index (NDVI) and impervious surfaces index (NDBI) were used to interpretation of the LST and SUHI changes. The results showed that SUHI in Tehran, has spatial-temporal diurnal and seasonal variation. So that during warm days the surface urban cool island (SUCL) is formed in Tehran. At night times, SUHI index values was different between 2 and 5 ° C (maximum in the spring). The results also showed that different of land cover thermal properties, albedo and elevation was the most important factors is the diurnal changes of SUHI while phonological changes of vegetation and albedo, was the most important factors in seasonal changes of SUHI.

Dr Alireza Mohammadi, Mr Reza Hashemi Masoomabad, Mrs Chnour Mohammadi,
Volume 21, Issue 63 (2-2022)

One of the most important and urgent issues of urban planning is the equitable distribution of facilities, services and accessibility of citizens at the urban level. Economic and commercial centers, including banks and financial institutions, are one of the most important economic sectors of cities and can be sustained. Social, economic, physical, and environmental impacts of neighborhoods. The purpose of this study was to investigate the extent of citizenschr('39') access to commercial land use in Ardebil neighborhoods. Therefore, the present study is applied in terms of purpose and descriptive-analytical in nature. The statistical population of the study is 44 localities of Ardabil city. Spatial statistics models, Hot Spot Analysis, and GIS software were used for data analysis. Finally, regression function in Idrisi Selva software was used to analyze the correlation between commercial user and population as well as to determine the relationship and correlation of this user with other service users. The results show that in Ardabil neighborhoods there is inequality in terms of overall business use. As a result, the neighborhoods have high commercial use weights and high concentrations of hot spots in optimum condition, including areas 3 and 5 from zone 2, zone 7 from zone 1 and zone 6 from zone 3. Also, commercial low weight blocks and low concentrations of hot spots, which include areas 8 and 11 from zone 2, area 11 from zone 3, are lower in urban sustainability. Finally, based on the results of the research, some suggestions have been made.

Associated Professor Hooshmand Ataei, Mrs Mahsa Ravarian, Mr Seyed Alireza Tashakori Hashemi,
Volume 23, Issue 69 (7-2023)

So far, several models have been proposed for estimating different climate parameters, but due to the lack of valid and long-term data in some meteorological stations, some models have been difficult to use. The SIMETAV V.1.0 model has been developed in cooperation with the University of California Davis and the Water Resources Authority of California in 2005. The SIMETAW model is a new and innovative tool for the estimation of applied water evapotranspiration (ETAW). SIMETAW simulation model is presented to estimate potential evapotranspiration and also estimate the net amount of water required for irrigation (ETaw). In addition, using this model, you can simulate daily meteorological data from meteorological data. The simulation of daily weather information where there are only monthly averages is a great tool for filling out lost data. In this research, Simetaw simulation model predicts different climate parameters such as solar radiation, minimum and maximum temperature, wind speed, dew point, precipitation and evapotranspiration potential in four different semi-arid climate zones (Mashhad). Dry (Bandar Abbas), moderate and humid (Ramsar) and Mediterranean (Sanandaj) during the years (1967-2017). The results of these studies showed that SIMETAW model has high ability to simulate climate variables and has the highest model accuracy in precipitation simulation (R2 = 0.998) and maximum temperature (R2 = 0.997) for semi-arid climate (Mashhad) , Dew point (R2 = 0.998) for temperate and humid climate (Ramsar), for radiation (R2 = 0.998) and wind speed (R2 = 0.9) for Mediterranean climate (Sanandaj) and minimum temperature (R2 = 0.998) for warm and dry climates (Bandar Abbas).
According to the sensitivity analysis of SIMETAW model, the input parameters of the model are respectively their effect on potential evapotranspiration from maximum temperature, precipitation, dew point temperature and minimum temperature, solar radiation and wind speed.
Behrouz Hashemi, Farzaneh Sasanpor, Ali Movahed, Habiallah Fasihi,
Volume 23, Issue 71 (1-2024)

With the rapid growth of population and urbanization since the last century, the complexity and understanding of the spatial organization of the city, as well as the ability to predict urban events in its spaces, have become difficult and in some cases impossible. Karaj metropolis is one of the major metropolitan areas of Iran that has been experiencing rapid population growth and this has led to complexity of space and consequently to complexity of organization recognition and analysis and its spatial structure and impact of livelihood components. It has become a spatial system. The main purpose of the present study is to identify the role and impact of Karaj's spatial organization on its nuclear viability. The research method is quantitative and descriptive-exploratory. The study area was Karaj metropolis and its main nuclei. The statistical population of this study is citizens living in the sub-nucleus of Karaj. The sample size was 378persons. The data used in this study were collected through library and field research. Data were analyzed using spatial statistics, spatial arrangement, and T-test and Friedman test. The results show that the Karaj metropolitan organization and spatial structure are interconnected and connected to some of the major routes, forming sub-nuclei away from the core and thus transferring the functional and service applications from the center to be the peripheral nucleus. This has affected the viability of the core. Decrease in biodiversity has occurred in different physical, social, economic and environmental dimensions that have affected the environmental and economic aspects less than the other two dimensions, so it can be concluded that the Karaj Spatial Organization has an impact on its viability.
Ali Hashemi, Hojjatollah Yazdanpanah, Mehdi Momeni,
Volume 24, Issue 75 (2-2025)

Studying the effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County)
Climatic variables are the most significant factors affecting vegetation changes. Nowadays, the satellite imagery is widely used to investigate the effect of fluctuations in climatic variables on vegetation changes. This research aims to investigate the effect of climatic variables of precipitation, temperature, and humidity on changes in vegetation indices of orange orchards in Hassan Abad, Darab County using satellite data. Hence, observational data, including orange tree phenology data and meteorological data on the agricultural weather station have been collected for over 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on the territorial data and 1:25000 maps of the Iran National Cartographic Center. These images were used to calculate the remote sensing vegetation indices including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on the NDVI and EVI dependent variables. To determine the significance of each of the independent variables in predicting the dependent variables, the artificial neural network method was used. Findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity and maximum humidity with values (0.39, 0.3, 0.13, 0.1 and 0.06) had the greatest effect on EVI, respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients (0.2, 0.28, 0.22, 0.11 and 0.17), respectively. Finally, ARMAX regression method was used to increase the explanatory power of the model. Results showed that this method could increase the explanatory power of the model and reduce the forecasting error.
Hamed Heidari, Darush Yarahmadi, Hamid Mirhashemi,
Volume 24, Issue 75 (2-2025)

Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.

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