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Volume 15, Issue 38 (4-2015)
Abstract


Saman Alimoradi, Asadollah : Khoorani, Yahya Esmaeilpoor,
Volume 17, Issue 44 (6-2017)
Abstract

The aim of this study is to retrieve land surface temperature (LST), air temperature (AT) and precipitation and to study their relationship with vegetation in rang lands of Karun watershed of Khuzestan province. For this purpose, land surface temperature (LST) and NDVI was drived from NOAA-AVHRR for maximum amount of greenness (April) for a period of 27 years. In order to extract LST, Price algorithm was used. Also air temperature and precipitation were interpolated for selected weather stations using IDW method. Spatial correlation outcomes (on 0.05) between NDVI with LST and air temperature show a reversed relation. This spatial relation is stronger for LST, so that this coefficient is often upper than 0.6, while seldom is 0.4 for air temperature and precipitation. Spatial regression models show that 62 percent of NDVI changes is determined by LST (R2=0.62) and air temperature and precipitation determine very limited amount of NDVI dynamics.


Ali Shamai, Mahsa Delfannasab, Mohammad Porakrami,
Volume 20, Issue 59 (1-2021)
Abstract

The purpose of this study was to investigate the factors affecting housing prices in the Laleh Park district of Tehran. In this study, the data of all real estate traded in the first six months of the year 2016 was used in the study area. Information about the physical properties of the residential units trained is collected from the Real Estate Market Information System of Iran and is used to obtain information on the accessibility features of residential units traded using ARC GIS software. Multivariate regression analysis has also been used to investigate the factors affecting housing prices. The results of this study showed that the physical factors of housing are more effective than the access factors in the housing prices in this district . Among the selected features, the variables of residential area, parking, and skeletal type had the most positive effect on the price of housing in the area under study. On the other hand, some of the features, such as the distance from the residential unit to the nearest main street, the residential unit to the nearest educational user, the residential unit distance to the nearest health care provider, and the residential unit's age, had a negative effect on the housing price in the Laleh Park district .

Mojtaba Shahnazari, Zahra Hejazizadeh, Mohammad Saligheh,
Volume 20, Issue 59 (1-2021)
Abstract

Abstract
In this research, while studying climate conditions in the current period and analyzing changes in temperature, precipitation level, and the sunlight received, current conditions were also analyzed based on daily data from synoptic stations in the region, which had meteorological data recorded for at least 30 years. Given the environmental conditions necessary for the growth of rice, the availability of its phenological data, its high-low temperature thresholds, the Degree Day systems needed for the completion of its life cycle, and the phenological processes related to its economic production, a suitable agricultural calendar was specified. During the March-July period, this calendar showed variations in different provinces. Based on the current temperature conditions and the probable continued warming trend of the planet in the decades to come, nwoDscale was applied to the output from the atmospheric general circulation model MCdaH3 under  scenario using LARS-WG5 model. In this study, years between 1969 and 1990 were used as the base period, while years between 2046 and 2065 were studied as the future period. Temperature and precipitation conditions for the future period were simulated. Obtained output was then studied and compared with temperature conditions that were suitable for the plant to grow in the region. With some differences, results showed that the agricultural calendar for rice in Gilan and Mazandaran provinces will shift to winter. Given the different temperature conditions of Golestan province, its agricultural calendar will shift to spring.
 

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