Milad Soltani; Adel Soltani; Mahin Kalehhouei; Karim Solaimani
Abstract
Introduction
Drought is a serious danger with very extensive impacts on the soil, economy, and the threat to the livelihood and health of local communities. This disaster as an unpleasant climatic phenomenon that directly affects the communities through restrictions on access to water resources, causes ...
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Introduction
Drought is a serious danger with very extensive impacts on the soil, economy, and the threat to the livelihood and health of local communities. This disaster as an unpleasant climatic phenomenon that directly affects the communities through restrictions on access to water resources, causes high economic, social and environmental costs. Meteorological drought indicators are calculated directly from meteorological events such as precipitation, and in the absence of these data, drought monitoring will not be useful. Due to the fact that meteorological drought indicators are only valid for a single location and do not have the required spatial resolution and are also dependent on weather station information, and these stations are often distributed distantly, the reliability of these indicators has been questioned. Given the characteristics of satellite data such as spatial and temporal resolution, extensive coverage of studied areas, and direct investigation of vegetation status by satellite indices, many studies have been carried out for drought modeling using this technology and these indicators. Over the past four decades, far-reaching drought monitoring tools have been widely developed and drought monitoring models are widely proposed, which are generally based on vegetation indices, surface temperature, humidity and reflection in the visible and infrared regions. These include leaf water content index, vegetation cover index and temperature - drought - vegetation index. Therefore, remote sensing techniques can be a useful tool in drought monitoring. The purpose of this study is to monitor drought and vegetation health in the city of Kermanshah using LANDSAT satellite imagery. For this purpose, first, by examining the rain-gauging and synoptic data of existing stations and using the standard precipitation index model, the driest year and one wet year were selected as the sample. In this study, two years of 2015 and 2016 were selected as the dry and wet years and then, the vegetation cover of the region was compared with the Landsat images. To use these images, it is first necessary to make sure that there is no geometric error. For this purpose, the road vector layer was used, which was revealed that the images have geometric errors. Images with less than a half-pixel error were corrected geometrically using 21 and 24 auxiliary points. The adaptation of the vector layers with the roads existing in the image indicated the accuracy of the correction. At the next stage, the driest year and one wet year were selected as samples by examining the rain-gauging and synoptic data of the existing stations and by using the standardized model of rainfall index. At the next stage, the Temperature Condition Indices and Vegetation Health Index (VHI) were compared in two wet and drought periods were studied in order to determine the differences of these indices during a dry year and a year with high precipitation. For this purpose, each of the aforementioned indices was built using the LANDSAT-8 imagery, and the stages of building these indices were subsequently presented. The required pre-processing and processing as well as the geometric and radiometric corrections were first performed on the satellite images. Then, temperature condition indices, vegetation status index and vegetation health index were prepared for drought monitoring. Considering that, the meteorological drought indices are only valid for a single location and lack the required spatial resolution and are also dependent on the information of the meteorological stations, and these stations are often distributed far apart from each other, the reliability of these indexes has been questioned. Satellite data characteristics like high spatial and temporal resolution, extensive coverage of the study areas, and direct survey of the vegetation status by the satellite indexes have led to a large number of studies on drought modeling using this technology, and the confirmation of the use of these indices. The aim of this study is to determine the moisture, heat and health of the vegetation using the LANDST images. Thus, the results of the study in the next stage indicated that the LANDSAT images and the built indices have the required capabilities to monitor drought. The results of this research can be a proper option for decision-makers to effectively supervise, examine and resolve the drought conditions and double the necessity of profile definition. Supplementary studies are suggested for spatial drought monitoring by satellite imagery through ground measurements of the quantitative changes in the coverage and temperature of the earth’s surface. There are limitations in the use of NDVI and satellite thermal bands. These include weather and cloud conditions that should be considered. Using maps obtained from the drought monitoring and evaluating indices can help improve drought management programs and play a significant role in reducing the effects of drought. Using vegetation health status index, it was determined that the vegetation status has had a lot of changes during drought compared to the wet period, hydrological drought has had a major share in the destruction of vegetation and drying of the lakes and, consequently, the abandonment of agricultural lands and the lack of access to alternative water resources, as well as the lack of groundwater resources or the lack of alternative surface water resources have intensified, and it seems that, this part of Iran will face numerous problems if the drought continues in the coming years and the appropriate methods are not used to deal with it. Also, given that the water resources of the region are going to decrease in the coming decades, the necessity of using comprehensive water management methods in all sectors, including the reserve, transfer and distribution sectors seems very essential and inevitable. Finally, it is expected that the trend of destruction of vegetation decreases in the future by applying proper management practices, sustainable water distribution, regional negotiations, methodical agriculture as well as the establishment of optimal hydrological conditions.
Seyed Hojjat Mousavi
Abstract
Introduction About one quarter of world’s deserts are covered with quick sands, whereby, sand fields are the most common landforms. The movements of the sand fields are considered as a threat to the roads, natural resources, urban areas, agriculture and infrastructure.Factors such aspoverty of ...
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Introduction About one quarter of world’s deserts are covered with quick sands, whereby, sand fields are the most common landforms. The movements of the sand fields are considered as a threat to the roads, natural resources, urban areas, agriculture and infrastructure.Factors such aspoverty of vegetation, increasing of drought due to global warming have led to the dynamic of sand fields with different speeds in manydirections that threat the transportation, health, economic and human activities. Thus, the spatial-temporal monitoring of sand fields dynamic behavior and identifying their directions of development are of great importancein the management of dry regions and conservation of natural resources. Therefore, the aim of this research is the Multi-temporal monitoring of sand field dynamic behavior in the west of Damghanplaya from 1972 to 2016, in the form of three 15-year period through data and remote sensing methods. Materials and Methods Damghanplaya Basin with an area of 18070.918 km2issituated between Toroud-ChahShirin Horst and the Alborz Mountains with an elevation of 2319 and 3884 meters respectively. Its general slope is towards the center of Damghan desert with an elevation of 1028m. Damghan playa is a tectonic-sedimentary hole, which is presently influenced by different geomorphic and climatic morphogenetic processes. Because of the vegetation and precipitation shortage,the wind morphogenetic systems dominate other processes. Thus, several types of wind erosion landforms can be observed in this region. The study area is the western erg of Damghanplaya with an area of 71.155 Km2 which is situated in Damghan Basin in the north of Iran’s great central desert. The region is located between latitudes 35° 51´ to 35° 58´ N and longitudes 54° 13´ to 54° 25´ E. This is an applied research and its methodology is a combination of remote sensing analyses. In this regard, topographic maps with a scale of 1: 25,000, geological maps with a scale of 1: 100,000 and Google Earth’s satellite images were used first to determine the position of the study area. Then, spatial database was completed through receiving Landsat satellite images during the period 1972 to 2016. Sinceseveral series of remote sensing satellite images belonging to multiple time periods are needed for monitoring the dynamic behavior of the sand field, four series of Landsat satellite images, MSS, TM , ETM+ and OLI sensors related to three 15 year periods of 1972,1987, 2002 and 2016 respectively, were used in this research. The aforementioned images were obtained from the Landsat satellite archive on the American geological organization website (http://earthexplorer.usgs.gov/). Then,color combinations, IHS transformation, and supervised classification of Maximum Likelihood methods were used to enhance the spatial area of the sand field, and the method of images difference and the calculation of the changing classes level were used to examine the type and trend of the changes.. Findings and Results The results show that the maximum and minimum area of the sand filed are observed in 2002 and 2016 with an area of 92.2641 and 49.2803 km2 respectively. The results of change detection show that there are three types of changes including increasing, decreasing, and no-changes. As it can be observed,the maximum area of the classes of change belongs to the no change class that the periods of 1972 to 1987 and 2002 to 2016 with the amounts of 58.3506 and 48.2841 km2 respectively,have the highest and lowest areas, while, the minimum area of the classes of change belongs to the class of incremental changes that the periods of 1987 to 2002 and 2002 to 2016 have the highest and lowest areas with the amounts of 38.2833 and 1.0359 km2 respectively. The maximum and minimum areas of decreasing class of changes belong to the periods of 2002 to 2016 and 1987 to 2002 with the amounts of 43.9829 and 14.2693 km2 respectively. In this regard, the no-change and increasing change classes with the standard deviation of 5.0445 and 19.4699 respectively, have the minimum and maximum range of changes during the entire period of 44 years. The results obtained fromstudying thetemporal trend of changes indicate the existence of a decreasing trend in the no-change and increasing change classes, and also the existence of an increasing trend in the class of decreasing changes.Descending trend of no-change class is uniform and continuous. In contrast, the trend ofincreasing and decreasing classes of changehas a periodic jump in the second time period (1987-2002), but their overall trend is almost uniform. Discussion and Conclusion Western erg of Damghanplaya has decreased by approximately 6.7225 km2 in 1987 compared to 1972. Most of this reduction has occurred in the southwestern and eastern parts of the sand field. The southwestern contraction of the erg is in accordance with the pediment and the sand harvesting area, the causes ofwhich are the sand transfer by local winds blowing from the southwest to the northeast, as well as the formation of the desert pavementfacies. In contrast, the eastern contraction of the erg is due to the increase in moisture content from the Haj Aligholiplaya and the increase in humidity caused by agricultural lands adjacent to the erg. In the second period, the trend was completely reversed and the sand field was expanded in 2002 by approximately 17.3659 and 24.0885 km2in 2002 compared to the years 1972 and 1987 respectively. This period is considered to be the most risky periods in terms of environmental hazards. In this period, major spatial expansion of the erg has taken place to the east and especially to the northeast. This expansion can be due to the increased drought severity and the continuation of dry periods and the release ofthe agricultural lands in some cases. In the third period, the situation has improved and the dynamic of sand has reduced, so that the extent of sand field has decreased in 2016 by 25.6178, 18.8952 and 42.9837 km2compared to the years 1972, 1987 and 2002 respectively, which represents the negative balance in the erg. In other words, the amount of the sand entering the erg is far less than that of the sand going out. In terms of location, the contraction of this period on the margins of the ergextends continuously and almost uniformly, but the largest contraction isobserved in the eastern, northeastern and southwestern parts. This decrease is due to the implementation of desert greening plans in the form of quick sands stabilization projects by planting Haloxylon. This indicates the positive and successfulfunction and role of desert greening projects. Also, due to the favorable natural and climatic conditions, the species of Haloxylon has been able to regenerate naturally in the area under cultivation. This has had a positive impact on the stabilization of quick sands and the reduction of erg changes.
Manuchehr Farajzadeh; Mohsen Ahadnejad; Hadi Targholizadeh
Abstract
Extended Abstract
Introduction
Due to the large dimensions of earthquake damages and losses, more rapid procedures are required to identify damaged buildings. Field studies and old procedures are no longer efficient enough because of being time consuming, costly and requiring lots of workforce. ...
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Extended Abstract
Introduction
Due to the large dimensions of earthquake damages and losses, more rapid procedures are required to identify damaged buildings. Field studies and old procedures are no longer efficient enough because of being time consuming, costly and requiring lots of workforce. This research seeks to identify the buildings damaged by earthquakes through analyzing the spectral response of urban houses to the reflective bands and effective factors, before and after the earthquake, for recognizing buildings damaged in the earthquake and compare the results of the reflective bands with each other, and then, determine the most efficient band among them. The earthquake stricken city of Bam was selected as the case study of this research. In order to identify the damaged urban houses, satellite imagery and remote sensing reflective bands were considered for detecting the changes, distinguishing the bands, and analyzing the spectral reflection profile.
Materials and Methods
The high resolution Quick bird satellite, photographed the city of Bam just eight days after the earthquake on January 3, 2004. The satellite also had taken a clear image of Bam about three months before the earthquake on September 30, 2003, that, with regard to the objectives of the research and the capabilities of the images taken, these Quick Bird satellite images were selected to study and investigate in this field. The method of this research is to analyze the spectral reflection profile and the factors affecting it. Since the multi-spectral remote sensing is a set of reflective, emissive or backscattering energy from the study area in electromagnetic multi-spectral bands, the aim of this research is to describe why terrestrial phenomena show different responses to the electromagnetic spectrum, and to analyze their spectral curve as well. To this end, we established an analytical strategy to achieve a better interpretation of the blue (band 1: 450 - 520 nm), green (band 2: 520 - 600 nm), red (band 3: 630 - 690 nm), and infrared (band 4: 760 - 900 nm) reflective bands. And the earthquake stricken city of Bam was selected as the case study of this research in order to identify the damaged urban houses by analyzing the spectral reflection profile and factors affecting it.
Results and Discussion
Urban housing is composed of various materials (concrete, asphalt, metal, plastic and soil) by man in various ways for building houses. When earthquake strikes, these houses might be destroyed. Therefore, satellite multi-temporal images before and after the earthquake were selected as data for analyzing the electromagnetic spectrum curve of the study area. In this research, the vulnerability of urban houses is different from one place to another. Therefore, educational samples of the case study from different parts of the city such as those which have been completely destroyed, partially destroyed or have remained intact, were selected. Then, the spectral response analysis of the urban houses was carried out in 4 blue (band 1: 450 - 520 nm) green (band 2: 520 - 600 nm) red (band 3: 630 - 690 nm) and Infrared (band 4: 760 - 900 nm) reflective bands before and after the earthquake in order to identify effective factors and the bands independent of these factors comparing with other bands. The results show that, before the earthquake occurs, some factors such as shadows cause a sharp decrease in the reflection in all bands, the atmospheric scattering at short wavelengths with increasing spectral reflection, the angle of sunshine, type of material, the surface smoothness or roughness of the surface, the time of the day, the height and texture had a great impact on the 3 blue, green and red reflective bands. Infrared band with a rectangular shape in spectral curve is a band independent of the aforementioned factors (with the exception of the shadow and surface smoothness of the materials).
Conclusion
The results obtained from analyzing the spectral response of the urban houses in four reflective bands (Blue, Green, Red and Infrared) indicated that in general, the urban houses had high reflection and shadows had less reflection before the earthquake. After the earthquake, urban houses showed an irregular and significant reduction in spectral reflection, and the spectral reflection curve was irregular as well. However, the method of analyzing the spectral reflection profile is a point estimation method and does not result in a map, and this method is often used to check the accuracy of other methods.
Hamid Ebrahimy; Aliakbar Rasuly; Ahmad Ahmadpour
Abstract
Extended Abstract
Introduction
Land use is one of the most important indicators of economic and social development in urban areas, and has resulted in extensive changes in available structures and procedures of these areas. Therefore, human activities are known as one of the main principles and components ...
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Extended Abstract
Introduction
Land use is one of the most important indicators of economic and social development in urban areas, and has resulted in extensive changes in available structures and procedures of these areas. Therefore, human activities are known as one of the main principles and components of change in land use. Generally, land use changes are inevitable product of interactions between human activities and environmental elements. Remote sensing technology with capabilities such as providing update and reliable information about natural and urban areas, digital processing of satellite imageries, providing the possibility of temporal and spatial comparing of different phenomena, diversity of products, and etc. is considered to be a powerful tool in improving the efficiency of urban management. Consequently, remote sensing data are used to determine type, quantity and location of land use changes. Moreover, remote sensing technology is used extensively in land use maps all over the world. Many models have been applied to predict land use changes, which due to the complex, dynamic, and non-linear nature of the issue gained little attention. However, CA-Markov model, which is a combination of Markov chain and cellular automata, is commonly considered to be an appropriate and good method for spatial-temporal modelling of land use changes. In the present study, land use changes were investigated for a 15-year period in Shiraz using object- based image analysis. Then, a land use map was produced using cellular automata-Markov (CA-Markov) model to predict land use changes in the study area in 2020.
Material & Methods
The present study includes two main phases. In the first phase, land use map of Shiraz was produced using Fuzzy object based analysis of satellite imageries. In the second phase, modeling and predicting of land use changes in 2020 were performed. Landsat imageries of the study area in 2005, 2010 & 2015 were used in this research. After preprocessing and preparing the imageries, segmentation procedure was performed as the first stage of object based classification using multiresolution segmentation algorithm. The nearest neighbor algorithm was used for object based classification of satellite imageries. Classification conditions were defined in accordance with each class properties, and classification was performed based on fuzzy operators of the classification operation. In CA-Markov model, the possibility of changing from one class of land use to another was calculated using transfer matrix table. Then, land use map of future years will be predictable in accordance with the transfer probability matrix, and desired time interval.
Result & Discussion
In this study, scale parameter of 10, shape index of 0.4, and compactness index of 0.2 were extracted as the optimum conditions for segmentation. Apart from spectral data, information regarding the location, context, texture, normalized difference vegetation index, enhanced vegetation index, and digital elevation model were also used to improve the efficiency of classification phase. The results of model validation shows an overall accuracy of 89% and kappa coefficient of 0.87. Therefore, the results of CA-Markov model shows a very good potential for predicting land use changes in Shiraz. Thus with the adjustment and calibration of model parameters and based on land use maps of 2010 and 2015, Shiraz land use in 2020 was predicted.
Conclusion
Due to the complexity of modeling dynamic changes in urban land use, utilizing efficient and update methods of data analysis is crucial. Therefore, satellite imageries and object based image analysis techniques were used to prepare land use map of Shiraz based on the data collected over a 15 year period. By considering the defined land use classes (residential area, barren lands, street network and urban green space), optimum image segmentation parameters were found. Then, classification conditions were defined for each class using the nearest neighbor algorithm and fuzzy operators. In this way, image classification was performed. By analyzing land use changes during the 20-year period, we understand that residential area has increased from 38 square kilometers in 2005 to 142 square kilometer in 2020. Additionally, green space area faced a reduction of 4 km in the first 5 years of the period, while in the next 15 years green space area shows an increasing trend.
Abolfazl Ranjbar-Fordoei; Sayed Hojjat Mousavi; Vahid Vaisi
Abstract
Extended abstract Introduction Energy is one of the most important factors in the development of human societies and is one of the essential factors in economic, social development and quality of life.Population explosion and growing energy demand, increasing living standards, the risk of global warming ...
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Extended abstract Introduction Energy is one of the most important factors in the development of human societies and is one of the essential factors in economic, social development and quality of life.Population explosion and growing energy demand, increasing living standards, the risk of global warming due to the greenhouse phenomenon, falling of acid rains, environmental problems and threats to human health, and finally lack of fossil energy sources are among the issues that attract the attention of the world's nations to the use of renewable energies,so that, in their planning, they take the provision of a percentage of the energy needed by their country through wind turbines, solar energy, geothermal energy and other renewable energyinto considerations. Due to the limited resources of fossil fuels and savings for future generations, there should be a need to replace and use renewable energies such as solar energy. More than 85% of Iran's territory is covered by arid and semi-arid regions, where the energy share of solar radiation is high.Solar energy, as one of the sources of clean energy and free from environmental degradation, has long been used in many ways. Due to the limitation of fossil sources and their pollution, as well as the increasing demand for energy, it is necessary to take measures to optimize the use of the solar energy source in Iran. Given that most of the work done in the field of estimating radiation energy has been made using weather or climatic data such as temperature, cloudiness, radiation, etc., and remote sensing data and satellite imagery have not been used generally, therefore, the purpose of this research is to investigate the radiation potential in a part of the central regions of Iran using remote sensing data and albedo, brightness, vegetation, moisture and land surface temperature indices. Material and Methods The study area is situated in central region of Iran in the geographical range 33º, 41ʹ,50ʺ-35º, 28ʹ, 30ʺ northern latitudes and 50º, 41ʹ, 40ʺ-52º, 30ʹ, 27ʺ eastern longitudes. The present research is an applied one, and its methodology is a combination of remote sensing and Geostatistical analysis. The data used in this research was obtained from the May 17, 2015 images of Landsat 8 satellite, with the course 164 and the row 36. In order to study the radiation potential, indices such as albedo, brightness, NDVI, greenness, moisture, and ground surface temperature were used. To calculate each of the aforementioned indices, the equations and functions related to each index on the Landsat 8 image were used in ENVI 5.3 and GIS 10.3 software. In order to calculate the Earth's surface temperature index (LST), the thermal bands 10 and 11 of Landsat 8 must first be converted into the radiance, and then to the brightness temperature, and finally to the temperature of the satellite's brightness. Then, the map relating to each standardization index, and the potentiometric map were prepared by takingthe mean of all indicators. Finally, the potentiometric map was also classified into five classesaccording to the estimated amount of solar radiation, including very inappropriate, inappropriate, moderate, appropriate, and very appropriate. Results and Discussion The results obtained from Albedo, brightness, NDVI, greenness, moisture and land surface temperature indicators are shown from low to high. For Albedo index, the least amount (6668.87) was observed in the northwest of Qom, south ofGarmsar, southwest of Abu Zaidabad, Niasar, Golestan, northwest of Kashan, and the highest amount (61352.7) was observed in the northern parts of Garmsar, south and southeast of Qom, and West of Aran-o-Bidgol. For the brightness index, the lowest value (15441.9) was observed in the northwest of Qom, south ofGarmsar, southwest of Abu Zaidabad, Niasar, Galak, northwest of Kashan, West of Pishva, Gharchak, and the highest amount (129881)was observed in northern parts of Garmsar, Center and South and South West of Qom and West of Aran-o-Bidgol. For NDVI index, the lowest vegetation cover (-0.393175) was seen in the central and northwestern parts of Qom, south of Garmsar, Abu-zaidabad, north ofAran-Bidgol, northeast of Kashan, and the highest value (0.639655) was observed in the northeast of Garmsar, Qarchak, Pishva, Northwest of Javad-abad, south of the Kahak, west of Niasar, southeast of Kashan. For the greenness index, the lowest value (-43887.6) was observed in the northern parts of Garmsar, in the north of Hassanabad, south and southwest of Qom, south of Javad Abad, southwest andcenterofKashan, west and southwest of Aran-o-Bidgol, and the highest value (-3385.181) was observed in the southern parts of Garmsar, Niasar, Kahak, Northwest of Kashan, Center and Southeast of Abu-zaidabad. For the humidity index, the lowest and highest values (-52599.1 and 11.56 respectively) were seen in the northwest of Qom, south of Garmsar, southwest of Abu-zaidabad, Niasar, and northwest of Kashan. For the LST index, the lowest value (19.585) was observed in Qarchak, Javadabad, southern Garmsar, southwest of Abu Zaidabad, Niasar, Kahak, north and northwest of Kashan and the highest value (577.557) was observed in Garmsar, central Qom, West of Aran-o-Bidgol, eastern and northeastern parts of Abu-zaidabad. The results of the land suitability analysis showed that the solar radiation potential ranged from 0.13882 to 0.71867. These values show the regions with less radiation as it gets closer to 0.13882, and more radiation as it gets closer 0.741867. The regions were classified into 5 categories includingvery appropriate, appropriate, moderate, inappropriate, very inappropriate, on the proportionality analysis map according to the solar radiation potential. Conclusion Surface temperature and radiation are two important factors for the study of solar radiation. Based on these two factors, the best regions with the highest radiation potential and the highest albedo and the highest surface temperature were observed in Aran-Bidgol and Abouzid-Abad regions. The highest value (61352.72) of albedo was observed in the eastern part of Aran-o-Bidgol. However, the highest brightness value (129881) was found in this region. Based on Spatial Approach Analysis Map of solar radiation, the west of Aran-o-Bidgol region has the highest amount of radiation. Based on the results, it can be concluded that the places whereverthe Albedo and the brightness indices are higher, NDVI and greenness will decrease. As a result, the albedo index has a direct correlation with the brightness index and an inverse correlation with NDVI index. Therefore, in the central regions of Iran, it is possible to determine the appropriate regions in terms of radiation potential through quantitative and qualitative calculation of suitable indicators such as albedo, temperature and brightness through remote sensing data and the relationships between each of these indices. Finally, it determines the best areas for acquiring solar energy and the construction of solar power plants. It is suggested that the remote sensing indices be combined with radiation models in order to obtain more accurate information in a shorter time and at a lower cost.
Mehdi Najafi Alamdari; Masoud Torabi Azad; Ali Hakimi
Abstract
Extended Abstract
Introduction
The Mean Dynamic Topography (MDT) of the seas is a quantity which comes from subtracting the Geoid Height (GH) from the Mean Sea Surface (MSS) at every point on the sea. The direction of geostrophic currents is obtained through the calculation of the MDT slope relative ...
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Extended Abstract
Introduction
The Mean Dynamic Topography (MDT) of the seas is a quantity which comes from subtracting the Geoid Height (GH) from the Mean Sea Surface (MSS) at every point on the sea. The direction of geostrophic currents is obtained through the calculation of the MDT slope relative to the Geoid. In this research, a series of GOCE geopotential coefficients resulted from the 4 year collection of GOCE observations was used to estimate the reference geoid height in the Persian Gulf, the Oman Sea and the Indian Ocean, i.e., in the area of interest. Two MDT models data were available at the time of performing this research: Denmark Technical University’s model, named ‘Mean Dynamic Topography of Denmark Technical University 2010’ (MDT_DTU_2010) which has been available on a geographical grid of 2 arc minutes spacing (Knudsen & Andersen, 2010). This model is based on the mean sea surface topography model MSS_DTU_2010 and the 2 month of GOCE geopotential data for the Geoid as the reference surface. The second model is the Mean Dynamic Topography Centre National d'Etudes Spatiales collecte localisation satellites 2009 (MDT_CNES_CLS09) with 15 minutes resolution (Rio et al, 2011). This model contains the east-west and north-south geostrophic current components with itself as well. It is based on MSS_CLS01 (Hernandez and Schaeffer, 2001) and 4.5 years of GRACE geopotential data used for the reference geoid.
Materials and Methods
In this research a new Mean Dynamic Topography (MDT) model with the name of MDT_IAU_TN_2014 is presented. Also, the surface permanent current vectors in a grid with 2 minutes resolutions is computed in the Persian Gulf, the Oman Sea and the north of Indian Ocean. This MDT is formed by a Mean Sea Surface (MSS) model computed from 6 altimetry satellites data (Topex/Poseidon, Jason 1 and 2, ERS 1 and 2 and Geosat Follow-On) and GOCE satellite data with 21 and 4 years ranges in 1992-2013 are calculated. The first step for the Mean Sea Surface (MSS) computation is to calculate the mean of Sea Surface Heights (SSH) along the repeated (in time) sub-tracks of altimetry satellites over the years available in the area of interest. The mean value of SSHs over time in a same track is then called Mean Height (MH). The Basic Radar Altimetry Toolbox (BRAT) version 3.1.0 was used for the MH computation. The correction term includes the tidal periodic variations, physical earth corrections such as troposphere, ionosphere, and sea state biases. All of these corrections are considered from the satellite handbooks T/P (AVISO/ALTIMETRY, 1996), J1 (AVISO and PODAAC USER HANDBOOK, 2012), J2 (OSTM/Jason-2 Products Handbook, 2001), ERS (RA/ATSR products - User Manual, 2001), GFO (GEOSAT Follow-On GDR User's Handbook, 2002). Among altimetry satellites, T/P (J1 and J2) has the highest orbit and longest data sets so it has been selected as a reference for corrections.
Results & Discussion
To homogenize the spectral of MSS and the Geoid, a truncated Gaussian filter with 1.386 degree radius has been used. MDT results have been compared with two global model and have 0.033 and 0.051 RMS of differences in order. Among altimetry satellites used in this research, J2 and GFO satellites have the ability to measure shallow waters. Hence, the data provided by these satellites in shallow waters, i.e. Persian Gulf are valuable. MHS differences between E1 and T/P are larger than the MHS of other satellites, because there are differences between the two missions, i.e., there are 8 km distances between E1 sub-tracks at equator but long repeatability period of 35 days of data acquisition time and T/P sub-tracks spacing are 315 km at equator and short repeatability period of 9.9 days. Also, the orbit elevations are different: T/P at altitude of 1336 km and E1 at altitude of 785 km. Inclusion of E1 data in the MSS_IAU_TN_2014 solution would globally decrease the RMS difference of the solution relative to the MSS_CNES_CLS_2011 model from 0.4 m (without E1 data) to 0.1 m. This improvement by the E1 data is probably due to the higher resolution of the data in the region of interest.
Conclusion
Changing the filtering radius of 1.386 degree down to lower degrees until 1 degree would increase the MDT_IAU_TN_2014 differences (relative to the MDT_DTU_2010) and MDT_CNES_CLS09 from 0.033m and 0.051m RMS up to larger values. At the 1.386 degree, the differences are minimum. For filtering radiuses of more than 1.386 degree the MDT surface would become unreasonably much smoother and the RMS difference would increase. Geostrophic and Ekman velocity currents using 22 years data of surface wind has been calculated. Total currents of the released model in this research have been compared with OSCAR in-situ data and have 0.047 and 0.031 meter RMS of differences in North-South and East-West current components. The total currents from MDT_IAU_TN-2014 model vary between 0 to 0.61 m/s in the north Indian ocean region. The comparison shows that all three models show almost the same range of variations in the region of interest. SLA an In-Situ data could be used to make the MDT_IAU_TN_2014 independent from any other models. The lack of In-Situ data in the region of interest forced MDT_IAU_TN_2014 to use MDT_DTU_2010 to cover filtered parts. Also using other gravity models with higher Spherical harmonic coefficients degree and orders such as EIGEN-6c and EGM08, would make filtering not needed in the dynamic modeling.
Mohammad Mardani Shahrbabak
Abstract
Extended Abstract
Introduction
Recognizing the performance and ability of advanced remote sensing technologies is one of the essential necessities to hide subsurface structures and facilities. One of these detection technologies that has used in Ionospheric Powerful Electromagnetic Heater Systems, ...
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Extended Abstract
Introduction
Recognizing the performance and ability of advanced remote sensing technologies is one of the essential necessities to hide subsurface structures and facilities. One of these detection technologies that has used in Ionospheric Powerful Electromagnetic Heater Systems, is HAARP. This system uses electromagnetic fields signals in the frequency range 3 to 10 MHz. HAARP emits waves into one of the layers of the ionosphere and then warm the desired area. This leads to emit very low frequency waves in the range of VLF and ELF. The main objective of this research is to analyze the exploratory capabilities of the HAARP system remote sensing in detecting subsurface targets. In the case of the accuracy of remote sensing capabilities and the ability to identify subsurface targets by HAARP, it can be concluded that this system is a very serious threat to identifying major subsurface targets in the country and poses a serious challenge to inactive passive actions. Therefore, it is necessary to carry out strategic, operational and tactical planning to deal with this serious threat. However, in case of inaccuracy of this capability, it will resolve the uncertainties and anxieties of the minds of the commanders and officials of the country, especially in the field of passive defense of the country.The only research published in the country by the men of Mardani and Razavi Nejad (Mardani et al., 2011), published as a two-volume book, address the issue of the ability of the HAARP to make climate change. But in the area of detecting subsurface targets, no published scientific research has ever been presented.
Materials and Methods
This research utilizes a combination of multiple data analysis based on analyzing the data collected from scientific and theoretical sources, official and authoritative reports the results of experiments performed and finally the main research question has been answered by taking the viewpoints of experts and scholars of research statistical population. The type of research is applicable and the research method is descriptive-analytical and case-based. In this research, the required information is obtained through the search of Internet resources, authoritative scientific documents, books, internal and external publications, dissertations and researches carried out on the topic, opinions of experts based on interview and used to the Delphi scientific method in the field.The statistical population of this research includes scholars, academic experts and research centers in the fields of remote sensing, Ionospheric Powerful Electromagnetic Heater Systems and high-power radars in the country. The sample population of the study was 32 experts who were purposefully selected from the statistical population of the study.
Results & Discussion
The main objective of this research is to analyze the capability of remote sensing of high-power electromagnetic heat sink systems (HAARP) in identifying subsurface targets. The HAARP system uses electromagnetic fields with signals in the frequency range of 3 to 10 MHz, and can operate in the same way as the frequency domain electromagnetic geophysics. The Harp system, as an ionospheric heater, modifies the ionospheric heating using polar electrodes of the desired frequency waves and uses it as a source of waves for remote sensing and identifying subsurface targets.
The results of this research show that the electromagnetic ionospheric heater power systems have remote sensing capabilities and can recognize subsurface targets. Accordingly, in this research, some solutions for passive defense against Remote sensing threats of HAARP system is provided. In general, HAARP provides the capability of a remote sensing system and subsurface radiography globally, and is a good option for underground exploration with the CSAMT approach. In this research, using the combined method of analyzing multiple data based on the description and analysis of data collected from scientific and theoretical sources, official and authoritative reports, examining the results of empirical experiments, and finally obtaining expert opinions and owner the statistical community of the field survey has responded to the main question of the research.
Conclusion
The results of this study show that high-power electromagnetic immune systems (HAARP), has remote sensing and the ability to identify subsurface targets. Accordingly, these systems are considered to be a serious threat to identify sub-targets, and therefore, in-depth research has suggested inaccessible defense strategies against this threat .Also, the results of the research showed that if the equipment is buried in a high conductivity ground, they cannot be detected by the HAARP VLF waveforms. If the waves of the HAARP system are of the type of ELF waves used in the CSAMT method, it can be used to prevent detection in addition to conductive ground, to deploy structures at depths of more than 150 meters.
Fatemeh Jahani Cherebargh; Mehdi Akhoondzadeh Hanzaei
Abstract
Extended Abstract Aerosols are small (sub-micron to several microns) suspended particles in the solid or liquid phase in the atmosphere. The main origins of aerosols are natural and anthropogenic. They can be directly emitted as particles (primary aerosols) into the atmosphere namely, mineral aerosol, ...
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Extended Abstract Aerosols are small (sub-micron to several microns) suspended particles in the solid or liquid phase in the atmosphere. The main origins of aerosols are natural and anthropogenic. They can be directly emitted as particles (primary aerosols) into the atmosphere namely, mineral aerosol, sea salt, volcanic eruptions, organic aerosols, industrial dust, soot, biomass burning, etc. They can also be the result of chemical reactions (secondary aerosols) namely, sulfates from biogenic gases or volcanic and nitrates from transportation and diffusion of aerosol particles from the source region depend on wind vector and wind strength. Aerosols are ever present and highly varying constituents of our atmosphere. They play roles in many physical and chemical processes that shape the composition of the atmosphere and thereby affect cloud formation, visibility, and air quality. They interact both directly and indirectly with radiation and thus affect the amount of radiative energy reaching the surface and reflected to space. The shortwave part of the radiative energy at the surface (insolation) is an important component of the surface energy budget, and a necessary input to models of land-surface processes. Aerosol Optical Thickness (AOT) is calculated by measuring light absorption at specific wavelengths of the visible spectrum. For the most widely used AOT data product, the absorption at 550 nm is the preferred wavelength for measurement (In the visible spectrum, humans perceive a light wavelength measuring 550 nm as a shade of green). AOT is a dimensionless quantity, expressing the negative logarithm of the fraction of radiation (e.g., light) that is not scattered or absorbed on a path. High AOT indicates a large quantity of aerosols, and thus a significant amount of absorption and scattering of radiation (i.e., light). Low AOT indicates clearer air with fewer aerosols and increased transmission of radiation. Increasing aerosol concentrations can thus affect global temperature and the radiation balance of the globe by reducing the amount of radiation reaching the Earth’s surface, and that reduction can result in lower air temperatures. Penetration of the large particles into the atmosphere in certain cases leads to decreasing the particles mobility and then dropping the conductivity, which will increase the electric field but aerosol measurements in the seismically active zones are more complicated due to the mosaic character of the gas emanation in the seismic zones and the uncertainty of aerosol origin in gas probes. Some remote sensing satellites due to their suitable temporal, spatial and spectral resolutions provide useful information of time and spatial distributions of Aerosols. This leads to creating an appropriate database for statistical study of the seismic atmospheric effects. The AOD measurement is taken by the MODIS sun-synchronous instrument onboard Terra and Aqua satellites every day. The satellites provide more continuous coverage nearer to the poles but there are more gaps in the coverage of the satellite nearer to the equator. AOT can be determined by implementing different methods on satellite images, but it is a difficult task to achieve it because solar lights are reflected by the atmosphere and the whole solar lights do not hit the ground. The most famous methods used to derive aerosol parameters are Dark Dense Vegetation (DDV), deep blue algorithm and synergy of Terra and Aqua MODIS (SYNTAM). SYNTAM approach can remove limitations in deriving AOT by combining data from two sensors of MODIS of TERRA and AQUA satellites and this method gives the right results. In this study, SYNTAM method has been applied over a region of Iran to produce an AOT map. The comparison between our results and NASA AOT products for the same time and location shows a good agreement. The result of comparing NASA data and SYNTAM approach with Newton iteration algorithm for the wavelength of 0.55 µm, gives the RMSE equal to 0.253. Therefore SYNTAM could be a robust method to derive AOT map over regions without AERONET ground stations. In the next section, SYNTAM method was combined with nonlinear parametric adjustment model. In this case, the results are more accurate than implementation of SYNTAM method alone. The result of comparing NASA data and SYNTAM approach with nonlinear parametric adjustment model for the wavelength of 0.55 µm, gives the RMSE equal to 0.207.
Mahtab Safari Shad; Mahmoud Habibnejad Roshan; Alireza Ildoromi
Abstract
Abstract The issue of drought is very important in water resources studies. Meteorological drought indices are calculated directly from meteorological data such as rainfall, and in the absence of such data, they will not be useful in monitoring drought. Therefore, remote sensing techniques can be considered ...
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Abstract The issue of drought is very important in water resources studies. Meteorological drought indices are calculated directly from meteorological data such as rainfall, and in the absence of such data, they will not be useful in monitoring drought. Therefore, remote sensing techniques can be considered as a useful tool in monitoring drought. In this research, using MODIS remote sensing satellite images, the trend of vegetation normalized index changes in Isfahan province for the years 2000-2008 was investigated. In addition to vegetation, NDVI index can be effective in addition to natural vegetation for drought monitoring, especially for drought monitoring of dry farming type.Considering this index, the vegetation cover was classified into 4 groups and the area of each of the classes was calculated. Finally, two SPI and NDVI indices were compared. The result of calculating the SPI index show that the occurrence of severe drought is in 2008 and moderate droughts are in 2000 and 2001 in Isfahan province respectively. The calculation of the NDVI index in these three years also indicated that the poor vegetation cover has been significantly increased. High level Pearson correlation (+0.704) was observed between SPI and NDVI in significant level of 0.01. However, the results of the effect of rainfall on the NDVI index showed that there is no coincidence of the occurrence of meteorological drought and agriculture droughts in all years. For the year 2006, despite the fact that precipitation was higher than the years before and the years after and more than the average rainfall of the province, but based on the results of the NDVI index, agricultural drought has occurred this year (Devaluation of the NDVI index). On the contrary, in 2002 and 2004 that precipitation was lower than 2006, but dry farming and pasture conditions were better than 2006. And also, in 2003 with a difference of 2 mm in precipitation compared to 2002, the NDVI index value dropped significantly. The results of this research double the necessity of defining a profile that expresses all of these issues.
Monir Darestani Farahani; Mahdi Akhondzadeh Hanzaei; Farhang Ahmadi Qivi
Abstract
Abstract
Water salinity is one of the important environmental factors of the sea and plays a significant role in the study and prediction of the oceanic surface currents, location analysis of the fish aggregation, density determination and studying its changes, and also in ecological properties. This ...
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Abstract
Water salinity is one of the important environmental factors of the sea and plays a significant role in the study and prediction of the oceanic surface currents, location analysis of the fish aggregation, density determination and studying its changes, and also in ecological properties. This parameter changes greatly with time and location, and proper recognition of it requires measurements at short time intervals (monthly) of multiple points in the study area.
In traditional ways, the assessment and evaluation of one or several specific factors of water quality is often costly and time-consuming, and cannot be a good indication for the entire area of a vast region. But in recent years, satellite and remote sensing technology have been considered as an appropriate tool for evaluating some water quality parameters because, given the digitality of these data, their wide availability, regular measurements, their repetition in short periods of time, Less cost and time, a wide range of projects can be achieved. The purpose of this study is mapping sea surface salinity of the Persian Gulf in Iran and the Gulf of St. Lawrence in Canada using MODIS satellite imagery. In this regard, a software has been produced in Iran for the first time that can prepare salinity, temperature and density maps of the sea surface in three different models with proper accuracy by entering the MODIS satellite imagery and CTD field data. High capability and flexibility of the Artificial Neural Network in approximation of nonlinear and linear continuous functions in hybrid space, led this study to provide a new method based on using this network in which salinity map is determined by a multilayer perceptron network.
Mojtaba Behzad Fallahpour; Hamid Dehghani; Ali Jabbar Rashidi; Abbas Sheikhi
Abstract
Abstract
Effective factors in SAR images can be divided into five general categories of radar, radar-carrying platform, channel, imaging domain and raw data processing section. In each of these factors, various physical, structural, hardware and software parameters are influential, in such a way that ...
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Abstract
Effective factors in SAR images can be divided into five general categories of radar, radar-carrying platform, channel, imaging domain and raw data processing section. In each of these factors, various physical, structural, hardware and software parameters are influential, in such a way that one can see the role of each of them in the final formed image.
Modeling, Analyzing and, in general, knowing the effect of each of these parameters, will provide a better understanding of how SAR imaging systems operate, and from this point of view, it will not only be an important step in designing and manufacturing these types of systems, but also it will provide the possibility of interpreting and analyzing these types of images. For this purpose, in the present paper, the effect of the angle of incidence and the shape of the targets which are parts of the radar and the imaging domain parameters, are simulated in SAR images. The shapes used in this simulation are cylinders, cones and cubes, which represent buildings, silos, tree trunks, etc., in the real world, so they are very abundant in SAR images. Also, for more comprehensive results, different angles of incidence of 30, 40, 45, 50 and 60 degrees have been selected for simulation. With this simulation and analysis of the results, the behavioral pattern of the above geometric shapes is extracted at different angles of incidence from the perspective of SAR imaging systems. Thus, an important step in identifying and recognizing various shapes, which is one of the most important issues in the interpretation of SAR images will be taken.
Seyyed Hojjat Mousavi; Abolfazl Ranjbar; Mehdi Haseli
Abstract
Due to the changesin land use that is done mostly by human activities, changedetection of landuse and assessment of their environmental impact isessential for future planning and managing the resources. Therefore, the aim of this research is monitoring, detecting andtrending the landuse changes in Abarkooh ...
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Due to the changesin land use that is done mostly by human activities, changedetection of landuse and assessment of their environmental impact isessential for future planning and managing the resources. Therefore, the aim of this research is monitoring, detecting andtrending the landuse changes in Abarkooh basin (1976-2014) in orderto assess the environmental issues such as human stress onearth without considering tolerance capacity, and to identify the regions havingenvironmental stress.In this regard, after classification to identify the type of land uses and applying the base component analysis and tasseled cap functions and difference of images, satellite images data from Landsat, MSS (1976), TM (1990), ETM + (2000 and 2006) and OLI (2014)) sensors, and remote sensing techniques such as supervisory classification and accuracy assessment have been used to monitor the land use changes. The classification results indicate the enhancing of seven typesof land uses including urban lands, agricultural lands, wastelands, rocky lands, rangelands, clayey plain anddesert, and which have the highest accuracy of classification in 2014with kappa coefficient values of82.18%and total accuracy of 0.76. The trending results of changes in land use indicate an upward trend of the area in rangelands (5.65%), rockylands (2.52%),wastelands (3.63%) and agricultural lands (1.04%), and a downward trendof the area in urban land (4.33%), clayey plain (6.89%) and desert (6.03%). From the perspective of base component analysisand tasseled cap functions, 1.748% (306.4912 km2) and 3.989% (699.961 KM2) of the area of the study region were faced with increasing changes of landuse, and in general, the overall trend of the changes of increasing classes is upward. Most of the changes in land use are destructive and devastating, and in terms of spatial changes correspond to the area around human community centers suchas Abarkooh and Mehrdasht cities. It is evident that,due to the continuationof this trend, the Abarkooh basinbecomes a dead inactive ecosystem that lacksany ecological and biological production potential in the near future.
Bakhtiar Feizizadeh; Mojtaba Pirnazar; Arash Zand karimi; Hassan Abedi Gheshlaghi
Abstract
In line with the goal of rapid extraction of land use maps, remote sensing technology has been recognized as an efficient technology which provides the possibility for extraction of land use maps by presenting satellite imagery.By providing different satellite images with various temporal power, remote ...
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In line with the goal of rapid extraction of land use maps, remote sensing technology has been recognized as an efficient technology which provides the possibility for extraction of land use maps by presenting satellite imagery.By providing different satellite images with various temporal power, remote sensing has made the modeling and monitoring of the environmental changes possible, which is an important step in the management of natural resources.The object-oriented classification method based on knowledge-based algorithms is one of the effective methods for classification of satellite imagery which, in addition to the use of satellite imageryspectral information, provides the necessary facilities for using environmental information and physical and geometric properties of the land surface phenomena.The present researchwas conducted with the aim of evaluating the increase rate in the accuracy resulted from the application of knowledge-basedfuzzyalgorithms in the classification of land use / land cover maps.In this research, the AVNIR2 sensor images of the ALOS satellite have been used to compare the object-oriented methods of satellite imagery classification without using fuzzy algorithms and object-oriented methods based on fuzzy algorithms and the land use map for the city of Maragheh has been extracted by both of the aforementioned methods. The results of the accuracy assessment show that the land use map produced by knowledge-based fuzzy methods with a general accuracy of 93.38 is more reliable compared with the land use map produced by the object-oriented method without using fuzzy algorithms with an accuracy of 88.66%. Given the comparative nature of this research, its results have been of great importance in identifying the optimal methods for production and preparation of land use maps, and the produced maps have also a high applied value for the executive organizations (such as agricultural Jihad, natural resources, etc.).
Siavosh Shayan; Gholamreza Zare; Mojtaba Yamani; Mohammad Sharifikia; Mohsen Soltanpour
Abstract
Meanders are one of the typical geomorphological forms that is frequently observed on the southern coasts of Irandue to the availability of environmental conditions. These dynamic and active landforms have strong spatial variations under the influence of the dynamics of the rivers and the ...
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Meanders are one of the typical geomorphological forms that is frequently observed on the southern coasts of Irandue to the availability of environmental conditions. These dynamic and active landforms have strong spatial variations under the influence of the dynamics of the rivers and the gentle slopes of the deltas, in a short period of time. It’s been tried in this paper to extract and analyze the morphological changes of the Mond River bed over a period of 57 years in five time periods of (1955, 1985, 1994,
2000, and 2012) using remote sensing data and field surveys. The results of this research showed that the morphological changes of the Mond river bed have been very high during the years 1955 to 2012, so that, a nearly 3.5 kilometer displacement of the bed was observed on the estuary. Spatial comparison of the river bed in 1955 and 2012 indicated that 42.52 square kilometers were added to the left bank of the river, while on the right riverside, this amount was calculated to be 33.8 km2.The gentle slope of the delta (reduction of water speed and the sedimentary deposition on the river bed), vegetation cover on the riverside and on the river bed (trapping sediments in the river bed) and humans (building dams on the Mond river basin, constructing bridges and protection platforms on the bottom of the river bed and the transferring of water to the shrimp breeding sites) are among the important factors in changing the Mond river bed.
Fatemeh Mohammadyari; Hamidreza Pourkhabaz; Morteza Tavakoli; Hossein Aghdar
Abstract
Knowledge of qualitative and quantitative characteristics of changes are extremely important in environmental planning, land use planning and sustainable development. Currently, using vegetation maps is one of the key factors in data production for macro and micro planning. In this research, information ...
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Knowledge of qualitative and quantitative characteristics of changes are extremely important in environmental planning, land use planning and sustainable development. Currently, using vegetation maps is one of the key factors in data production for macro and micro planning. In this research, information of Landsat ETM + and OLI sensors were used to display the temporal and spatial changes of vegetation in Behbahan city in 1999 and 2013 and the value of NDVI index was calculated for two years. In order to evaluate the quality changes of vegetation, the numerical values of the index were classified into 4 classes of different lush green vegetation including land with excellent, very good, good, and poor coverage. Then, the changes were determined using CROSSTAB. The results showed that the qualitative and quantitative changes in vegetation for the study area have been extensive over 14 years, so that, the area of lands with excellent, very good and poor coverage has increased and the area of landswith good coverage, has decreased. The greatest increase in areashas occurred in lands with excellent coverage, so that, it has increased from 5069.76 hectares (ha) in 1999 to 7735.5 ha in 2013. Also, the highestdecrease in areas has occurred in lands with good coverage thathas reached from 34061.4 ha to 27434.43 ha. Finally, the regression equation was obtained to show better relationship between the two parameters of vegetation and temperature. The results confirmed the point that the areas covered with vegetation have lower temperature and vegetation has cooling effects on the surrounding. Therefore, the degradationof the region’s vegetationwill be followed by the warming of the city and many other environmental consequences.
Mohammad Fallah Zazuli; Alireza Vafaeinezhad; Mir Masoud Kheirkhah Zarkesh; Fariborz Ahmadi Dehka
Abstract
Dusthazephenomenon in the recent decadeis one of the most important environmental challenges in Iran, West and Southwest Asia.This phenomenon is one of the processes of desertification occurring in arid and semi-arid regions of the world. Remote sensing is thescience and technique for the acquisition ...
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Dusthazephenomenon in the recent decadeis one of the most important environmental challenges in Iran, West and Southwest Asia.This phenomenon is one of the processes of desertification occurring in arid and semi-arid regions of the world. Remote sensing is thescience and technique for the acquisition of information from geographic phenomena without any contact with them.Todetectthephenomenonofdusthaze,large-scaleimagesare needed withwidecoverageandhighfrequency. Therefore,theimagesrelatedtoMODISsensoraresuitablefor thestudies on thephenomenon of dusthazeduetothe presence of highspectralbands. Detection of the generating origin or the source of dust haze particles and its quick monitoring with accuracy and low cost is of great importance. The main objectives of this research are to identify the generating source of dust haze entering the West and Southwest regions of Iran and to monitor the movement of dust haze as well. In this research, the occurrence origin of dust haze phenomenon is related to June 18, 2012 which occurred in the Western and Southwestern parts of the country, and was identified with the help of satellite images and by using visible and thermal bands of MODIS sensor and usingthe Ackerman index.It was found out that, its main origin was the point where Tigris and Euphrates rivers meet, which is within the northern and northeastern parts of Iraq and western Syria, and It was further found that the images of the MODIS sensor are suitable for dust haze monitoring due to its availability, low cost, and its repeatability in 2 periods of time within 24 hours. Also, its synoptic analysis to detect the movement of dust haze from the source into Iran was investigated using 500 hectopascal level synoptic data of geopotential height, sea level pressure and the wind current direction maps of 500 and 1000 hectopascals. The results of the synoptic analysis have optimized the origin detection and the way of dust haze transmission, and makes it more appropriate to predict the path of the dust haze motion. Finally, its movement demonstration from the source into Iran was trackedby the use of GIS and Spatial Analysis Tools. Dusthazephenomenon in the recent decadeis one of the most important environmental challenges in Iran, West and Southwest Asia.This phenomenon is one of the processes of desertification occurring in arid and semi-arid regions of the world. Remote sensing is thescience and technique for the acquisition of information from geographic phenomena without any contact with them.Todetectthephenomenonofdusthaze,large-scaleimagesare needed withwidecoverageandhighfrequency. Therefore,theimagesrelatedtoMODISsensoraresuitablefor thestudies on thephenomenon of dusthazeduetothe presence of highspectralbands. Detection of the generating origin or the source of dust haze particles and its quick monitoring with accuracy and low cost is of great importance. The main objectives of this research are to identify the generating source of dust haze entering the West and Southwest regions of Iran and to monitor the movement of dust haze as well. In this research, the occurrence origin of dust haze phenomenon is related to June 18, 2012 which occurred in the Western and Southwestern parts of the country, and was identified with the help of satellite images and by using visible and thermal bands of MODIS sensor and usingthe Ackerman index.It was found out that, its main origin was the point where Tigris and Euphrates rivers meet, which is within the northern and northeastern parts of Iraq and western Syria, and It was further found that the images of the MODIS sensor are suitable for dust haze monitoring due to its availability, low cost, and its repeatability in 2 periods of time within 24 hours. Also, its synoptic analysis to detect the movement of dust haze from the source into Iran was investigated using 500 hectopascal level synoptic data of geopotential height, sea level pressure and the wind current direction maps of 500 and 1000 hectopascals. The results of the synoptic analysis have optimized the origin detection and the way of dust haze transmission, and makes it more appropriate to predict the path of the dust haze motion. Finally, its movement demonstration from the source into Iran was trackedby the use of GIS and Spatial Analysis Tools.
Vahed Kiyani; Afshin Alizade Shaabani; Aliakbar Nazari Samani
Abstract
Nowadays, remote sensing images are able to provide the latest information for studying land coverage and land uses, and the value and usability of produced maps depend on their accuracy. Hence, the purpose of this study was to evaluate the classification accuracy of LISS-III sensor's image of IRS-P6 ...
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Nowadays, remote sensing images are able to provide the latest information for studying land coverage and land uses, and the value and usability of produced maps depend on their accuracy. Hence, the purpose of this study was to evaluate the classification accuracy of LISS-III sensor's image of IRS-P6 satellite using the Google Earth's database in order to provide a map of land coverage and land uses. Therefore, the QUICKBIRD satellite imagery provided by Google Earth's software was used to determine both educational samples and to evaluate the classification. The studied area is Taleghan city in the Alborz province which is located in the watershed of Taleghan. In this research before determining the educational samples to verify the accuracy of the Google Earth's image, linear digital layers (roads and channels) with terrestrial coordinates were used which obtained an RMSE of 0.77.
In the next step, after determining the educational samples, the mentioned satellite image was classified into 5 categories of garden, agriculture. Pasture, lake and no coverage based on a supervised classification and with maximum probability algorithm using software ENVI 4/2 which obtained a classification KAPPA coefficient of 0.85 and an overall accuracy of 91/4.
The results of this study indicated that Google Earth's software images have a high spatial accuracy in order to evaluate the classification accuracy in some regions and also the use of ecological features such as the slope of the area, hydrologic network and… increase this accuracy. Finally, it is suggested that Google Earth's satellite imagery to be used to evaluate the accuracy of the satellite image classification and even visual interpretation of land coverage and land use.
Abdollah Seif; Tayyebeh Mahmoodi
Volume 23, Issue 89 , May 2014, , Pages 72-80
Abstract
During the last three decades, the process of producing topographic information has observed a development in data producing technology, from traditional and land mapping toward inactive methods of surface measurement and registration (like photogrammetry and remote sensing), and more recently toward ...
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During the last three decades, the process of producing topographic information has observed a development in data producing technology, from traditional and land mapping toward inactive methods of surface measurement and registration (like photogrammetry and remote sensing), and more recently toward active methods (like radar and Lidar). Lidar is a technique used to gather information from the surface which works by measuring distance with laser. Measurement in Lidar is based on this principle: with defined coordinates of the laser sending point, it is possible to measure coordinates of any point on the ground by measuring the oblique distance between pulse sending point and the ground surface and measuring the angle of wave sent between the pulse sending point and ground level. Images produced using Lidar data have a 472*697 pixel dimension. In fact, Lidar is a supplementary tool for collecting 3 dimensional information which aid spatial photogrammetry and remote sensing. The most important information received from this device is the distance between sensor and ground level which is measured by calculating the time period between pulse impact with earth surface and its return to the sensor. Moreover, the distance between ground surface and flying level of the airplane is repeatedly measured which determines ground surface and vegetation. Digital elevation model and digital surface model are products of Lidar. Features like plot parameters, average elevation of trees, surface of vegetation crown, elevation of the vegetation crown, diameter at breast height, single trees and jungle structure can be exploited by Lidar. The present article seeks to introduce Lidar and investigate its functions and applications.
Mohammad Rahimi; Ali Akbar Damavandi; Vahid Jafarian
Volume 22, Issue 88 , January 2014, , Pages 115-128
Abstract
Due to the increasing complexity and development of dynamic phenomena like land degradation and desertification in the present century, new technologies have focused on their evaluation and monitoring (Alavi panah, 2003). Remote sensing, Geographic Information System and Global Positioning System are ...
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Due to the increasing complexity and development of dynamic phenomena like land degradation and desertification in the present century, new technologies have focused on their evaluation and monitoring (Alavi panah, 2003). Remote sensing, Geographic Information System and Global Positioning System are among the most important technologies based on spatial information (geoinformatics). In fact, investigating spatial and temporal changes of complex phenomena like land degradation and desertification with the aim of ongoing evaluation and monitoring for proper management and exploitation is inevitable. With the emergence of such modern technologies, it is expected that better and more accurate investigation of land phenomena become possible. Remote sensing, which is based on collecting spatial information (in specified time intervals) by airplanes and satellites, plays a very important role in land degradation and desertification evaluation and monitoring in local, regional and global scale. Multiple capabilities created by this technology (being multi-spectral, inexpensive and digital, having wide field of vision, increasing spectral, land, temporal, radiometric resolution capability, duplicate coverage and spectral variety, easily available data, quick access to distant points and high accuracy) have resulted in the development of a new approach in the studies on the evaluation and monitoring of desertification.
Manoochehr Farajzadeh; Ali Azizi; Hossein Soleymani
Volume 22, Issue 87 , November 2013, , Pages 2-13
Abstract
Direct influence of precipitation on human life and the role it plays in the development of different countries have resulted in an increase in using methods and algorithms for estimating precipitation. A few decades ago, traditional methods were used for predicting precipitation. Then, the presentation ...
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Direct influence of precipitation on human life and the role it plays in the development of different countries have resulted in an increase in using methods and algorithms for estimating precipitation. A few decades ago, traditional methods were used for predicting precipitation. Then, the presentation of meteorological satellite revolutionized this field. Considering the high dispersion of weather stations and rain gauges in developing countries like Iran, free access to images taken by sensors like AVHRR and MODIS is an appropriate opportunity to compensate these deficiencies. We can estimate the volume of water vapor ready to be transformed into precipitation using satellite images, water vapor absorption bands and thermal bands in any time, space, and scale. The algorithms used to estimate precipitation in satellite images are classified into three types- infrared, visible, microwave and a combination of the first two types-based on the sensors’ wave length. Methods based on infrared and visible waves have a good spatial and temporal resolution, while microwaves-based methods measure precipitation directly. Yet, these techniques contain many weaknesses, especially in low earth orbits. Combined techniques are used to compensate these weaknesses. Microwave images are not receivable in Iran, thus we cannot take advantage of microwaves and combined methods. As a result, the present article focuses mainly on visible and infrared wave length.
Vahed Kiani; Jahangir Feghhi; Aliakbar Nazari Samani; Afshin Alizadeh Shabani
Volume 22, Issue 87 , November 2013, , Pages 29-31
Abstract
Multispectral remote sensing data is an important informational resource used for recognizing surface changes. To the extent that today, remote sensing images can provide the latest information on vegetation and land use. The present study seeks to detect changes in vegetation and land use across Taleqan ...
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Multispectral remote sensing data is an important informational resource used for recognizing surface changes. To the extent that today, remote sensing images can provide the latest information on vegetation and land use. The present study seeks to detect changes in vegetation and land use across Taleqan area in time period between 1988 and 2007 using remote sensing. Taleqan is located in Alborz province (Karaj) and Taleqan basin. Results indicate that area dedicated to gardening has increased to 2.28 percent, while agricultural lands have faced a 15.05 decrease. On the other hand, rangelands have decreased to 16.25 percent and bare lands have increased to 28.08 percent. The most important change happened with the construction of Taleqan storage dam in 1999 which submerged more than 1100 hectares of the most desirable lands in the area. Since bare lands have increased and rangelands have decreased, thus from an ecological viewpoint it is possible to say that vegetation is degrading. Therefore, in order to restore bare lands, performing rangeland plans and avoiding unplanned changes can be suggested.
Mohammad Reza Abdoli
Volume 22, Issue 87 , November 2013, , Pages 59-63
Abstract
Human beings have always been interested in reaching a better understanding of their environment and its phenomena. They have experienced different methods to achieve an understanding of land resources, and in this way they have reached new technologies. Using air and space has always been one of their ...
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Human beings have always been interested in reaching a better understanding of their environment and its phenomena. They have experienced different methods to achieve an understanding of land resources, and in this way they have reached new technologies. Using air and space has always been one of their goals in this regard. With the first controllable flying airplane in about a century ago, the first aerial photo was taken from the ground and remote sensing was born. With the outbreak of First World War and military use of aircrafts, the necessity of applying aerial photos in information collecting and identifying land resources was recognized. The second World War followed by the Cold war on one hand, and technological developments on the other hand resulted in the emergence of exploratory airplanes in aviation and remote sensing realms. The present article investigates and reviews the most important exploratory airplanes and their applications in remote sensing. Despite many satellites that have been launched with different sensors, equipment and resolutions, results indicate that still many geographic studies take advantage of exploratory airplanes.
Ali Zangiabadi; Farahnaz Abolhasani
Volume 22, Issue 86 , June 2013, , Pages 63-73
Abstract
System using GIS and RS performed one of the newest methods in land evaluation and land preparations are projects. Therefore, to inform users the full capabilities and limitations of the GIS and RS tools in preparation programs and land management in order to avoid inaccurate assessment will be necessary. ...
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System using GIS and RS performed one of the newest methods in land evaluation and land preparations are projects. Therefore, to inform users the full capabilities and limitations of the GIS and RS tools in preparation programs and land management in order to avoid inaccurate assessment will be necessary. This study assessed agricultural land management using GIS and RS tools was conducted in Isfahan. Methods “descriptive” of the quantitative models used. Population of the study, including the city of Isfahan province Be. And finally to provide part of the information needs agricultural sector, estimated level of agricultural lands and preparing map Isfahan province using GIS has been drawn. The results show that, the city of the province in terms of area of agricultural lands were classified in four levels that city (Isfahan), Located in the First level, Naeen, Khomeini Shahr, Lenjan Khansar in the Fourth level and other. Cities are located between these two levels.
Azadeh Zaeri Amirani; Alireza Sofyanian
Volume 21, Issue 83 , November 2012, , Pages 65-69
Abstract
Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing ...
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Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing landform and the quality of urban environment. Regarding the importance of such surfaces, different methods of mapping impenetrable surfaces and investigating its changes with satellite imagery exist. These methods can be classified into five general groups: subpixel classification, neural network, classification with VIS model, regression tree model, and spectral composition analysis. Generally, each of these methods have their own advantages and disadvantages, but they are mostly used to detect and classify impenetrable surfaces. The present article investigate impenetrable surfaces and their importance, along with different methods of mapping these surfaces.
Maliheh Sadat Madanian; Alireza Sofianian
Volume 21, Issue 82 , September 2012, , Pages 44-49
Abstract
Change detection is the process of identifying changes in an object or phenomenon by observing it in different time intervals. Careful and timely detection of changes in land forms and reliefs provides a better basis for understanding relations and the interactions between human and natural phenomena. ...
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Change detection is the process of identifying changes in an object or phenomenon by observing it in different time intervals. Careful and timely detection of changes in land forms and reliefs provides a better basis for understanding relations and the interactions between human and natural phenomena. In this way, it makes managing and exploiting resources possible. Remote sensing data is a wonderful resource for different applications in detecting changes, due to its temporal magnification, spectral and radiometric variety, appropriate digital format and integrated view. Many methods have been developed to detect changes, all of which have advantages and disadvantages. According to the studies, these methods show different results in the same environment. Generally, change detection methods are classified into 3 different classes: pre-classification comparison, post- classification comparison, advanced methods. The present article analyzes some of these methods like image subtraction, image division, main components analysis, detection of controlled changes, and detection of uncontrolled changes, hybrid, artificial neural networks, vegetation-impermeable surfaces-soil model and geographic information systems. Pre-classification methods detect changes caused by multi-temporal data without producing classified vegetation and land-use maps. Yet, post-classification methods provide a precise matrix of changes and they usually need input analysis. There are diverse advanced methods which are usually developed in response to specific studies. Studies indicate that image subtraction, main components analysis and post-classification methods are the most popular methods used for change detection. However in recent years, artificial neural networks and combinations of remote sensing and geographic information systems are regarded as important techniques.
