Showing 11 results for Khuzestan
Mr Danesh Nasiri, Dr Reza Borna, Dr Manigheh Zohorian Pordel,
Volume 0, Issue 0 (3-1921)
Abstract
Widespread and frequent droughts in recent decades in Khuzestan province have become one of the most important challenges of this province. The use of remote sensing products in temporal and spatial monitoring of drought can play a key role in managing this risk and reducing and adjusting its destructive effects. The main goal of this research is to provide a remote sensing index for temporal and spatial monitoring of drought in Khuzestan province and its validation using station meteorological drought indices. In this research, by using the products of vegetation (MOD13C2) and land surface temperature (MOD11C3) of MODIS sensor, a drought index based on vegetation called VHI plant health index was produced. SPI Meteorological Drought Index, which was based on station rainfall data during the statistical period of 2000-2012, was used to evaluate and quantify this index. The comparison of VHI drought index with three-month SPI meteorological drought index values showed a significant correlation between 0.68 and 0.75. By identifying 4 years with widespread and relatively severe drought in Khuzestan province (based on both VHI and SPI indices), which included the years 2000, 2005, 2012, 2015, the spatial distribution pattern of meteorological drought and VHI plant drought to In general, it indicated that the northern parts of the province were generally involved in mild to moderate droughts and the southern parts were generally involved in moderate to severe droughts. The spatial correlation matrix based on the number of 2500 pixels with dimensions of 5x5 km, which included VHI and SPI values of selected drought years, indicated the existence of a significant spatial correlation between the two mentioned indicators. In the widespread drought of 2000, at the level of Khuzestan province, two drought indices VHI and SPI, the correlation was equal to 0.47, and in 2005, equal to 0.35, and
Mrs. Zeinab Zaheri Abdehvand, Dr. Mostafa Kabolizadeh,
Volume 0, Issue 0 (3-1921)
Abstract
In vast areas, the possibility of simultaneous access to satellite images with appropriate spatial resolution, such as Landsat images, is always a challenge. In addition, the temporal resolution of the Landsat satellite does not provide the possibility of examining short-term changes in phenomena such as vegetation. The aim of this research is to use the temporal and spatial fusion techniques of Landsat-8 and MODIS satellite images in preparing the Normalized Vegetation Detection Index (NDVI) map. For this purpose, six image fusion algorithms, including NNDiffuse (Nearest Neighbor Diffusion), PC (Principal Component), Brovey, CN (Color Normalized), Gram-Schmidt, and SFIM, have been used in an experimental area in Khuzestan province. After evaluating the results of the algorithms and choosing the most appropriate fusion algorithm, based on the statistical indicators of the spectral (correlation coefficient) and spatial (Laplacen filter) criteria of each of the algorithms, the spectral and spatial information of the reflection of red and near-infrared of 8 mosaicked Landsat-8 images (30 m) were combined with the red and near-infrared bands of one MODIS image (250 m). In order to investigate the vegetation cover, the NDVI was prepared with the fused satellite image in the Khuzestan province. The results of the research have shown that the NNDiffuse integration fusion algorithm has a very good accuracy among other algorithms in terms of the spatial evaluation index and spectral quality criteria. Therefore, this algorithm was recruited to combine the red and near-infrared bands of Landsat-8 and MODIS images. Compared to the original Landsat-8 image, the NDVI map prepared by this algorithm has the lowest statistical error of RMSE (0.1234) and MAE (0.081), respectively.
Saeed Balyani,
Volume 16, Issue 43 (12-2016)
Abstract
Knowing of precipitation values in different regions is always of main and strategic issues of human which has important role in short- term and long-term decisions. In order to determine of precipitation model and forecasting it, there are different models, but given that the precipitation data have a spatial autocorrelation, the spatial statistic is a powerful tool to recognition of spatial behaviors. In this research, for determine of precipitation model and predicting of it with geographical factors e.g. altitude, slope and view shade and latitude- longitude by using spatial regressions analysis such as ordinary least squares (OLS) and geographical weighted regressions(GWR), 13 synoptic stations of Khuzestan province from establishment to 2010 were used. Results showed a powerful correlation between precipitations with geographical factors. Also results of modeling through OLS and GWR representative that forecasting of GWR is close to reality, so that in GWR, the sum of errors of residuals is less, the 
is more and there aren't any spatial autocorrelation in residuals and the residuals are normal. The of OLS can only justify 75 percent of precipitation variations with spatial factors while in GWR this quantity is 82- 97 percent. Accordingly, it was found that, in east, northeast and north of province the altitudes, in east and northeast and Zagros Mountains the view shade and slope are the most important spatial factors, respectively.
Parisa Ahadi, Shahriar Khaledi, Mahmoud Ahmadi,
Volume 21, Issue 60 (3-2021)
Abstract
Dust is referred to sediments of less than 100 microns in size which are transmitted as suspended particles. Dust storms are events which naturally occur in arid and semi-arid areas, especially in subtropical latitudes. One of the most known sources of dust is the west of Asia, including Arabian Peninsula, Syria, Iraq, and Iran, especially Khuzestan Province. The purpose of this study is to investigate the frequency and trend of dust phenomena on hourly, monthly, seasonal and annual scale between 1995 and 2015 in Khuzestan Province. The method in this study is based on statistical computation of dust parameters and also the trend analysis of data based on Mann-Kendall test and spatial distribution maps of dust phenomena. The results suggests that 78.57 percent of dust event are occurred between 9.30 am to 15.30 pm local time, concurrent with peak of sun radiation and earth surface warming, dryness of soil and local pressure difference. The hourly trend analysis is increasing and significant in all hours and the highest increase occurred at 9.30 pm to 12.30 pm.49 percent of dusty days occurred in June, July and May and also 73 percent of them are in spring and summer as following from temperature increase and water and soil resources drying in the province. The seasonal and annual spatial distribution of dust indicates that most of dusty days in all seasons are located in west of province which suggests dominance of external sources as the main source of dust and the importance of topography factor in this area.The Z value spatial analysis suggests high increase of dust event in recent 20 years in southeast, south and central areas of the province and also on last hours of day which demonstrator development of internal sources activities in increasing trend of dust event in recent decades.
Nafise Marsousi, Majid Akbari, Nazanin Hajipour, Vahid Boustan Ahmadi,
Volume 21, Issue 63 (12-2021)
Abstract
According the increasing population, especially the urban population in the world and increasing environmental pollution caused by it, The need for urban planning and management approaches based on indicators such as Healthy Cities approach seems inevitable. The purpose of this paper is to analyze the efficiency and ranking of healthy city indicators through 36 indicators (socioeconomic, health services, environmental and health care). research method applied research is descriptive, analytic and development. To analyze the data from the non-parametric linear programming technique of data envelopment analysis, cross ineffective, models and software Dea slover Shannon entropy is used. The geographic area of this study is Khuzestan province and its statistical population is 22 cities according to the census of 2016. The results of this research show that in terms of relative efficiency of Ahwaz city due to the centrality of the province and the availability of infrastructure and sanitary services with a relatively high distance with the highest performance and high level of performance was in the first rank. And the cities of Dezful, Shosh, Khorramshahr, Shoshtar, Abadan, Masjed Soleyman and Behbahan were selected as semi-efficient cities. Finally, it can be concluded that in terms of having the indicators of the healthy city, most of the cities of the province are Inefficient (64%).
Mrs Zahra Hejazizadeh, Mr Farshad Pazhoh, Mr Fardin Ghadami, Mrs Haniyeh Shakiba,
Volume 22, Issue 65 (6-2022)
Abstract
The aim of this study is to synoptic analyze of the number of frost days in a year of Khuzestan province. For this purpose, using the minimum daily temperature data of 12 stations during the statistical period of 1992 to 2017, the Meteorological Organization of the country, 54 days of frost was identified. Sea level pressure, Geopotential Height, Zonal and meridian wind and temperature of 500 hPa data with size of 2/5 * 2/5 degree arc from the National Oceanic and Atmospheric United States of America were extracted. On the matrix of the variance of sea level pressure data in 54 days, the analysis of the basic components was performed and 10 components which identified 83% variance of the sea level pressure. Then, by applying the hierarchical cluster analysis method, the integration method was applied to the scores of the 10 components and 5 patterns of sea level pressure were identified. The results showed that frost phenomenon in Khuzestan province occurs from November to march and its trend is decreasing during the statistical period. Also northern and western parts of the province have allocated the most frequency of frost. Also the synoptic condition analysis of troposphere showed that 5 sea level pressure pattern with different make ups lead to pervasive frosts of Khuzestan province. Weak and moderate frosts formed by the influence of Siberian and European cold high pressure systems. But severe frosts occur with spread of Iceland low pressure to Iran, along with strong cold pressures. Meanwhile, the powerful Siberian high pressure is present in most of the patterns, which its interaction with sub polar and Icelandic low pressure, plays the most role in the most severe frost in the province of Khuzestan. Also in the middle level of troposphere penetration of deep troughs from northern latitudes and east European huge blockings has the most role, which has advection of cold air from the side west of troughs on the country and during the intensity of the frost added to its continuity.
Dr Gholamabbas Fallah Ghalhari, Fahimeh Shakeri,
Volume 22, Issue 67 (12-2022)
Abstract
In this Research, the maximum temperature of selected stations in Khuzestan province and the numerical values of 8 extreme climatic indicators belonging to the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) were used in the statistical period of 1987-2017. To analyze the trend of extreme climatic indices, the Man-Kendall test was used and to estimate the slope of the trend line, the Sen’s estimator was used. In this study, given the importance of global warming that severely affected all aspects of life, the authors explore the relationship between climatic factors and maximum temperature in Khuzestan province until to rely on it, and ones can predict and forecast air temperature at this region. For this purpose, the temperature of selected stations in Khuzestan province and numerical values of 8 climate indicators in the period 1987-2014 have been used. To understand the relationship between climate indicators and maximum temperature at 1 to 12 months of delays, Pearson’s correlation coefficient was used. The results showed that most of the extreme climatic indicators in the study period had a significant trend. The TX10 and TN10 indices have had negative trend in most stations and the TX90, TN90, TXx, TXn, TNx and TNn indices have had positive trend. According to the results of correlation coefficients can be concluded that all studied signals have a significant effect on the province's maximum temperature. The correlation between maximum temperature and indices PNA, TSA, WHWP, WP and NAO, was more than the other climate indicators. Results also showed that the entire indices except NAO have significant positive correlation with maximum temperature of the province. PNA index with a delay of 10 months has the highest positive correlation with maximum temperature of study area.
Shahla Qasemi, Reza Borna, Faredeh Asadian,
Volume 23, Issue 69 (6-2023)
Abstract
Abstract
In the history of humanity, human always has suffered all difficulties with effort to reach to comfort and well-being until the human provides a way to achieve the comfort. In the viewpoint of climate four elements have significant role in formation of human comfort and discomfort conditions that according to the climatic conditions in different areas, the type and effect of these elements on individuals are also different. The aim of this research is to determine the areas of climatic comfort. For this purpose, temperature, precipitation and humidity data were derived from database of Esfazari for Khuzestan province during statistical period 1965 to 2014. In this process, at first discomfort climate has been defined using temperature, precipitation and humidity based on distribution probability conditional. This research is to determine the areas of climatic comfort in Khuzestan province using multivariate analysis (Cluster analysis and Discriminant analysis) and spatial autocorrelation pattern (Hot Spot index and Moran index) with emphasis on architecture. The results showed that the areas with climatic comfort are included in north and east parts of Khuzestan province. However, the areas of climatic comfort by spatial method have been limited somewhat. Results further indicated that the areas of climatic comfort have decreased significantly towards recent periods especially in cluster analysis and discriminant analysis that a trend of reduction has been remarkable in cluster analysis (from 23.60% in the first period to 17.60% in the fifth period) and discriminant analysis (from 26.97% in the first period to 14.98% in the fifth period).
Dr Hoomayoon Molaei, Dr Emamgholi Babadi,
Volume 23, Issue 70 (9-2023)
Abstract
Abstract
Iran is one of the most earthquake-prone countries in the world and its cities have suffered a lot due to this natural phenomenon. The purpose of this study was the spatial analysis of earthquake crisis management. The research method has been applied-developmental. The research area of Khuzestan province and the statistical population included elites in the field of urban planning in Khuzestan province who were selected by targeted sampling method. There have also been two statistical tests. The results of statistical analysis showed that from the perspective of statistical individuals, proper crisis management (organizational structure, proper distribution of emergency services, manpower, equipment and information system) has a positive and significant effect on reducing mortality and financial vulnerability. Also, the results of Hot spot analysis showed that hot and earthquake-prone hotspots in Khuzestan province were mostly located in Behbahan, Masjed Soleiman and Andimeshk counties
Mr Danesh Nasiri, Dr Reza Borna, Dr Manijeh Zohourian Pordel,
Volume 24, Issue 72 (3-2024)
Abstract
Knowledge of supernatural microphysical properties and revealing its relationship with the spatial temporal distribution of precipitation can significantly increase the accuracy of precipitation predictions. The main purpose of this study is to reveal the relationship between the Cloud microphysical structure and the distribution of precipitation in Khuzestan province. In this regard, first 3 inclusive rainfall events in Khuzestan province were selected and their 24-hour cumulative rainfall values were obtained. The rainfall event of 17December2006, was selected as a sample of heavy rainfall, 25 March 2019, as a medium rainfall case, and finally 27 October 2018, as a light rainfall case. Microphysical factors of clouds producing these precipitations were obtained from MODIS (MOD06) cloud product. These factors included temperature, pressure, and cloud top height, optical thickness, and cloud fraction. Finally, by generating a matrix with 64000 information codes, and performing spatial correlation analysis at a confidence level of 0.95, the relationship between the Cloud microphysical structure and the spatial values and distribution of selected precipitates was revealed. The results showed that in the case study of heavy and medium rainfall, the spatial average of 24-hour cumulative rainfall in the province was 36 and 12 mm, respectively. A fully developed cloud structure with a cloud ratio of more than 75% and a vertical expansion of 6 to 9 thousand meters, with an optical thickness of 40 to 50, has led to the occurrence of these widespread and significant rainfall in the province. While in the case of light rain, a significant discontinuation was seen in the horizontal expansion of the cloud cover in the province and the cloud cover percentage was less than 10%. In addition, the factors related to the vertical expansion of the cloud were much lower, so that the height of the cloud peak in this rainfall was between 3 to 5 thousand meters. The results of this study showed that in heavy and medium rainfall cases, a significant spatial correlation was observed at a confidence level of 0.95 between MOD06 Cloud microphysical factors and recorded precipitation values, while no significant spatial correlation was observed in light rainfall case.
Mrs Fatemeh Vatanparast Galeh Juq, Dr Bromand Salahi, Batoul Zeinali,
Volume 25, Issue 77 (6-2025)
Abstract
In this research, the effect of two indicators OMI and RMM of Maden Julian fluctuation on the frequency of dust storms in Abadan, Ahvaz, Bostan, Bandar Mahshahr, Dezful, Ramhormoz and Masjed Soleyman located in Khuzestan province during six months (April to September) of the statistical period (1987 - 2021) was reviewed. Pearson's correlation coefficients between dust data and indicators were investigated and its results were calculated in the form of income zoning maps and the frequency percentage of each indicator for positive and negative phases. The results of the research findings indicate that there is a direct and significant relationship between the positive and negative phases of both indicators with dust, except for Dezful station in the positive phase of OMI and the negative phase of RMM and the highest correlation coefficient for Bandar Mahshahr and Dezful station is between -0.7-20.77 is in the positive phase of the RMM index. The relationship between the Madden Julian Oscillation and dust showed that between 51 and 59 percent of dust storms occurred in the negative phase of the OMI index and 40 to 49 percent in its positive phase. In the RMM index, 56 to 63 percent of dust storms occur in its negative phase and 37 to 50 percent in its positive phase. In fact, the negative phase of the RMM index has a higher percentage of dust storms than the negative phase of the OMI index. According to the results of the Monte Carlo test, the displacement of the positive and negative phases of the RMM index significantly leads to the occurrence of dust storms for most of the stations in Khuzestan province. Tracking the paths of dust entering Khuzestan province with the HYSPLIT model shows the movement of particles from Iraq, Arabia and the eastern parts of Syria towards the studied area.
