Fatemeh Shokrian; Karim Solaimani
Abstract
Investigating land use changes requires the integration of layers in a certain period. This research aims to investigate land use changes in Haraz Plain from 1980 to 2021. Therefore, Landsat data was used to measure the changes. By applying atmospheric, geometric and radiometric corrections, image enhancement ...
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Investigating land use changes requires the integration of layers in a certain period. This research aims to investigate land use changes in Haraz Plain from 1980 to 2021. Therefore, Landsat data was used to measure the changes. By applying atmospheric, geometric and radiometric corrections, image enhancement operations were performed and land use change maps were produced based on the supervised classification method, maximum likelihood algorithm and basis component analysis functions. The type of land use changes was determined from the difference function of the identification images and the accuracy of the maps using the overall accuracy test and the Kappa statistic. The results showed that from 1980 to 1990, the area of forest lands decreased by 4 km2. The rangeland area also decreased from 450 to 436 km2. From 2000 to 2010, the area of forest land decreased from 272 to 270 km2 and rangeland decreased from 432 to 420 km2. Finally, between 2011 and 2021, the area of forest lands decreased by 9 km2 and the rangeland area decreased by 5 km2. The results of the investigation of the changes in land use in the region indicate that the area of forest and rangeland lands decreased and the area of agricultural lands and residential areas increased. These results can help planners find the factors affecting land use changes and make correct management decisions in the future.
karim solaimani; Fatemeh Ruhani; Morteza Shabai; Mohsen Rohani
Abstract
The increase in population and the development of urbanization and, consequently, diforested areas have caused an increase in the surface temperature in urban areas, which results in an urban heat island. The heat islands of the city is one of the factors that has become important at the same time with ...
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The increase in population and the development of urbanization and, consequently, diforested areas have caused an increase in the surface temperature in urban areas, which results in an urban heat island. The heat islands of the city is one of the factors that has become important at the same time with the development of the city and today it can be calculated and evaluated using satellite images. The objectives of this study are to evaluate the points of temperature changes, land use, vegetation, traffic and soil types relationship with surface temperature in Sari and the trend of its spatial changes during the two time periods of 1988 and 2018. For this purpose, TIRS and Landsat 5 and 8 TM images in a period of 30 years (1988-2018) were used to study the heat island changes and calculate the surface temperature with a single-channel algorithm. The results showed that during a period of 30 years with a decrease of 235.3 hectares of green space and a 34% increase in land occupation in Sari, the area of heat islands increased by 21.83%. Also, considering the value of P-value less than 0.05, it showed that there is a significant relationship between vegetation index and city occupation level with land surface temperature and it can be argued that land use change, vegetation and traffic due to population growth and land use change is one of the main factors in increasing spatial changes in the heat islands of Sari.
Zahra hemmati; Karim solaimani; Mir hasan Miryaghoubzadeh
Abstract
Takab watershed basin is one of the most important basins of Lake Urmia. The basin is quite hilly and mountainous, and the runoff from its snow melting is of substantial significance. Snow accumulation in winter is considered to be crucial in the spring of the following year, and the water from snow ...
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Takab watershed basin is one of the most important basins of Lake Urmia. The basin is quite hilly and mountainous, and the runoff from its snow melting is of substantial significance. Snow accumulation in winter is considered to be crucial in the spring of the following year, and the water from snow melting is especially important for water facilities in a way that it results in serious floods when the snow melts with warm spring rain. Therefore, the prediction of snow melting seems necessary. Furthermore, managing water resource and reservoirs as well as planning of rivers hydrology would not be possible without considering this factor. The SRM snow melt runoff model was used to simulate the flow considering the 83-84 water years. Furthermore, to test the validity of the model, the 84-85 water years was used. Due to the fact that the MODIS images have the appropriate time resolution, such images have been used to estimate the underlying snow area. Results of the study showed that the use of snow cover maps, derived from MODIS images, is useful in predicting the runoff of the basin. The findings also show that the model has the ability to simulate the snowmelt runoff. To evaluate the model, two indexes, namely, the coefficient of determination and volume difference were used which were obtained as 0.75 and 27.84%, respectively. The obtained values indicate that the model has high accuracy in estimating the runoff from snow melting in this basin and represents the applicability of the model to other basins in the region.
Karim Solaimani; Shadman Darvishi; Fatemeh Shokrian; mostafa rashidpour
Volume 10, Issue 3 , January 2019, , Pages 77-104
Abstract
Snow is a major source of water flow in each region. Therefore, knowledge of the spatial and temporal distribution of snow is essential for proper management of water resources in the region. Due to the severe physical conditions of mountainous environments, there is no permanent ground measurement for ...
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Snow is a major source of water flow in each region. Therefore, knowledge of the spatial and temporal distribution of snow is essential for proper management of water resources in the region. Due to the severe physical conditions of mountainous environments, there is no permanent ground measurement for estimating snowfall resources and the establishment of a database. So, using remote sensing data to monitor snow level changes is very effective. Therefore, the aim of this study was to investigate the temporal and spatial variations of snow cover in Kurdistan province using MODIS (MOD10A1, MOD10A2) snowstorm products in the 17-year period (2000-2017). Also, to evaluate the accuracy of the images and to analyze the relationship between snow changes with rainfall and temperature data, the synoptic station data of the study area was used. The results of the evaluation of the images with the weather station data show that these images have the appropriate accuracy in extracting snow surfaces. Also, the results of snow cover variations in Kurdistan province indicate that the highest snow cover area was in 2000, 2001, 2004, 2006, 2007, 2008, 2010, 2011, 2012, 2013, and 2015, respectively, and the lowest in the years 2005, 2009, 2016 and 2017, with the largest snow cover area in December 2007 with a 2.8914 square km area. The study of snowfall variations in the province shows that the highest snowfall in the province from November to March was in the city of Diwandareh (November 2004, 59.57%) in Bijar (Feb. 2000, 25.93%) and Qorveh city (January 2017, 25.38%). Also, the analysis of the relationship between snow melting and climatic data shows that in the months of April and May rainfall increased and in June, with decreasing rainfall, the increasing trend of temperature caused the snow depths to melt in the province.
