Mahmoud Ahmadi; Zahra Alibakhshi; Manouchehr Farajzade Asl
Introduction: Change detection is a process to find the paradoxical regions in different temporal imageries of a similar area. Vegetation is very effective at the absorption of grime and lead, prevention of the spread of contaminations in urban environments, clearing the air, and reduction of heat islands. ...
Introduction: Change detection is a process to find the paradoxical regions in different temporal imageries of a similar area. Vegetation is very effective at the absorption of grime and lead, prevention of the spread of contaminations in urban environments, clearing the air, and reduction of heat islands. The need to investigate the decrease or increase in vegetation is extremely important in Tehran as a metropolis, as well as its satellite counties because of the increase in population and construction. The purpose of this research was to investigate the spatiotemporal changes in the vegetation of Tehran and its satellite cities in association with temperature during different temporal periods. The results of this research can be useful in studies concerning urban viability, reducing the effects of urban heat islands, and environmental sciences. Material and methods: Initially, the extraction and preparation of data were carried out using the ETM+ sensor of Landsat 7 satellite from 2001 to 2015, with June being selected as the hottest month of the study area. Then, the selection of days to be studied and correcting imagery, preparing LULC maps and plotting the area percentage was done. The computation of vegetation indices and built-up areas and the calculation of land surface temperature along with the assessment of the accuracy of surface temperature data were other stages of the research methodology. Finally, the area percentage of each index, as well as the scatter plot and Gaussian function chart were produced and the spatial variation of vegetation was studied. Results and discussion: According to the land use and land cover map (LULC) in 2001, 2005, 2010, and 2015, the vegetation significantly increased in 2015 compared to previous courses. The development of the residential area in the west region was higher than in other regions. In the charts of the area percentage for each land use class and its change over the four selected years, the vegetation percentage has been decreased since 2001, which continued in 2010 and 2015. In this study, the relationships between surface temperature and NDVI and SAVI indices were not linear, which showed that there is another controlling factor. In the normal density function chart, which is usually described by mean and standard deviation, variations of NDVI and SAVI indices were similar in the second and third periods, and the mean increased in these two periods compared to the first period, and the height of curve increased due to the reduction of variance. In this study, the results showed a decrease in the value of LST in the second and third periods from 2006 to 2015. On the other hand, the vegetation area was increasing in the region. From a spatial point of view, Tehran has the highest percentage of class one of NDVI that have no vegetation surfaces. Conclusion: Regarding the study of NDVI, SAVI and NDBI indices, the overall trend of vegetation cover in the study area was increasing. Considering the values of 15R2"> , the vegetation in Ray County was defunct. In the cities of Robat Karim and Tehran, vegetation cover was increasing. The high growth of satellite towns in the surroundings of Tehran has led to the allocation of land and fields and vegetation to residential areas, which exacerbate the heat islands and the unfavorable conditions of life.
Mahmoud Ahmadi; AbbasAli Dadashi Roudbari; Hamzeh Ahmadi
Volume 16, Issue 1 , April 2018, , Pages 47-68
Introduction: The air temperature parameter is one of the most important measures for identifying the climatic and environmental conditions of each region. Today, by using thermal infrared data, LST maps can be prepared without physical contact with objects or surfaces. Awareness of the spatial and temporal ...
Introduction: The air temperature parameter is one of the most important measures for identifying the climatic and environmental conditions of each region. Today, by using thermal infrared data, LST maps can be prepared without physical contact with objects or surfaces. Awareness of the spatial and temporal distribution of LST is essential to determine the land energy balance, the evapotranspiration and meteorology studies is essential. LST is a function of pure energy at the land surface which depends on the amount of energy reaching the land surface, surface emissivity, humidity, and air flow. The present study intends to investigate the state of Daytime LST in Iran in different months of the year based on the output of MODIS Terra images.Materials and methods: In this study, the fifth product of MODIS Terra called (Mod11C3 v005) with a spatial resolution of 5×5 kilometer and a Daytime time period, which became monthly data after the necessary processing, was used. In this study, considering the significant precision of day-night-based physics algorithm, Wan et al. (2002) has used this method to study Daytime LST in Iran. Then, they were decoded and an array with the dimensions of 4855×62258 was obtained. Land surface temperature zoning was conducted by using the geostatistical method of kriging with the lowest error rate and the highest precision in mountainous areas.Results and discussion: The statistical characteristics of LST in Iran during different months showed that the highest average of LST in Iran with 46.1 ° C was in July. In the warm period of the year, and in particular, in the hot zones of Iran (the southern coasts) there is less variation in the temperature of the country, which consequently leads to less variation in LST in the country, and less spatial autocorrelation should be observed in the warm half of the year, which indicates a more stable temperature in the warm period of the year. The study of LST during the 15-year period from 2001 to 2015 based on the output of the MODIS sensor for different months of the year showed that the distribution of LST in Iran was severely affected by geographical conditions, especially its latitude and topographic condition.Conclusion: From the west to the east and from the north to the south, there was an increase in LST in all months of the year. The Lut desert is the warmest area in the country with the temperatures rising to 59° C in the warm days. The spatial processing of Daytime LST in Iran showed that LST was strongly affected by latitude and altitude, and the topographic conditions played an important role in the spatiotemporal distribution of LST, which is completely consistent with the studies conducted by who stated that each temperature range has a high degree of consistency with its environmental and geographical properties, in particular its elevation, latitude and slope characteristics.Although the temperature zones provided for the various months of the year have the considerable spatial continuity, the parts of a temperature cluster have appeared in the form of islands in other zones, indicating the effect of complex topographic and local conditions on the occurrence of these temperature islands compared to its surroundings, which causes a spatial variation in temperature and an increase in the desire to LST clustering in Iran, or in other words, to climatic implantation.
Mahmuod Ahmadi; Mahdi Narangifard
Volume 13, Issue 2 , July 2015, , Pages 111-120
Timely and accurate detection of changes in surface features, to better understand the relationships and interactions between human and natural phenomena, the right decision is very important in urban management. To Detection these changes widely in recent decades, satellite data have been used as primary ...
Timely and accurate detection of changes in surface features, to better understand the relationships and interactions between human and natural phenomena, the right decision is very important in urban management. To Detection these changes widely in recent decades, satellite data have been used as primary sources. This study examines the use of vegetation changes and their impact on temperature patterns in a time period of 25 years within the city of Shiraz one area is made. LANDSAT satellite TM sensor data for the two series on 1986/10/7 and 2011/10/7 ERDAS IMAGINE 9.2 software selection and use land surface temperature (LST) And vegetation indices as a supervised classification algorithm with the maximum likelihood was obtained for urban. The findings showed that over the period of 4 and 63/8 km2 for the loss of vegetation and barren land and 17/13 km2 from the city for the area has been increased. Most lowly the level of the class is very strong vegetation and the greatest increase in of the level is barren. The findings also reveal for changes occurring with temperature patterns and changed most of the distribution is temperature ranges.
Mahmoud Ahmadi; Hasan lashkari; Ghasem Keikhosravi; Majed Azadi
Volume 13, Issue 1 , April 2015, , Pages 1-14
Climate change with changing climate patterns and confounds Ecosystems discipline, imports Serious consequences on the environment. Changes in weather patterns Could lead to severe flooding, extreme heat or cold, more frequent droughts. Each of these phenomena could Put at risk the regional food reserves. ...
Climate change with changing climate patterns and confounds Ecosystems discipline, imports Serious consequences on the environment. Changes in weather patterns Could lead to severe flooding, extreme heat or cold, more frequent droughts. Each of these phenomena could Put at risk the regional food reserves. North east of Iran due to the large area has very varied natural conditions and each of the areas included specific natural features. The extent of the area and factors such as mountains rising, desert areas , stay away from the water zones and different winds lead to variety of weather in each of those area. Based on the results if the man-kendall test and AHP model in north east of Iran, climatic elements with ascending trend (82.25%) much more than climatic elements with descending trend (35.5%) affect on climate change in north east of Iran. Areas that experience most climate changes due to descending elements (number of frost days , average moisture, the number of days with snowfall,24-hour rainfall, annual precipitation) is seen in the South and South east of region. Climatic elements with ascending trend (The average temperature, the minimum temperature, the maximum temperature, hours of sunshine) cover most extent of this region. Only Ghochan and Sabzevar stations demonstrate the least climate changes.