Showing 11 results for Landsat
Ms Zahra Sharghi, Dr Mostsfs Basiri, Dr Mahsa Faramarzi Asl,
Volume 0, Issue 0 (3-1921)
Abstract
The basic purpose of this research is to reveal the physical development process of the new city of Sahand, as one of the new cities of the country, using Landsat satellite images during the statistical period of 1401-1373. In this regard, satellite images required for 4 statistical periods of 1373, 1383, 1393, and 1401 were obtained from two Landsat 5 and 8 satellites. By running a band calculation function on the images of TM and OLI sensors, the values of the physical changes of the urban fabric during the investigated time steps in Sahand city were calculated and extracted. The results of this research indicated that the physical growth and development of the city of Sahand has started since 2013. This year, the area of the urban fabric has reached 282 hectares, which is a 28-fold increase compared to 2013. But in the next decade, i.e. 2013, the area of the city reached 570 hectares with a 100% growth compared to the previous decade, and finally, in the last decade, the area of the city reached 850 hectares with a growth rate of 50%. District 6 of Sahand city, which accounts for about 35% of the physical fabric of the city, has been one of the fastest growing areas of the city during the decades of 1393-1400. Considering that a significant correlation at the confidence level of 0.95 (P_value=0.05) was revealed between the population growth and the physical development of Sahand during the statistical period of 1380-1400 (R=0.91), therefore, the fitted regression model between the population growth And the growth of the urban fabric, by placing the proposed population density of this city after the implementation of Mehr housing policies (185 thousand people), it showed that the area of the physical fabric of this city will reach 1181 hectares in the next decade and will face a growth of 38%.
Mohamad Reza Mobasheri:, Samira Ranjbar,
Volume 17, Issue 44 (3-2017)
Abstract
The goal of this study is to identify farms which are affected by wheat rust disease. For this, the sensor data of Landsat 7 satellites in growing season of 2013 and 2014 along with some laboratorial data containing reflectance spectrum of leaf and leaf health degree in different levels of disease are used. The reflectance values of leaf are collected by an ASD spectroradiometer in the range of red and near infrared spectrum. The spectral are simulated for Landsat sensor bands using their spectral response functions. Then with the index of DVI and data obtained for leaf health, the Wheat Health Index was introduced. The correlation coefficient obtained is 0.82 and the relevant RMSE is 0.089 which is really good result for diagnosing highly advanced disease. The results show that, this index has a good performance in wheat high growing season when the greenness is high. It can diagnose regions that are healthy from those whom are blighted. Because the WHI index is a spectral index and is sensitive to leaf color, if the acquired images are close to the harvesting time, its performance will be weakened. The selected region in this survey is located in Fars, province, Saadatshahr city.
Dr Vahid Riahi, Dr Parviz Zeaiean Firouzabadi, Dr Farhad Azizpour, Ms Parastoo Darouei,
Volume 19, Issue 52 (3-2019)
Abstract
The cognition of cropping pattern is important for planning and resource management .Remote sensing as a science and technology of spatial information and geographic information system due to having the analytical facilities can play a key role in determining the distribution of crops and their lands under cultivation. In this research, in order to identify and separate the lands under cultivation of the dominant crops in Lenjanat of Isfahan province, the multi-temporal images of Landsat 8 satellite, OLI sensor were used in the dates of April 17, July 6, and August 23 in 2016. Using maximum likelihood classification and normalized difference vegetation index (NDVI) of the agriculture crops in different periods of growth and according to their cropping calendar, the map of the cropping pattern of the area was determined. To evaluate the accuracy of the results, the produced maps were examined with reference data. Kappa coefficient and overall accuracy were 0.88 and 90%, respectively, in maximum likelihood classification, and 0.90 and 93%, respectively, in NDVI. Furthermore, statistics presented by Agricultural Jihad Organization of Isfahan province in the 2015-2016 crop year was used for evaluation. The results showed that there were differences equal to 10.2%, 18.6% and 1.8%, in the area under cultivation of wheat and barley, rice, and potato and forage, respectively, in maximum likelihood classification, comparing with the statistics of Agriculture Jihad while the results of NDVI comparing with Jihad statistics showed the errors equal to 6.6 %, 6.5 % and 3.2%, respectively, that indicated the better performance of temporal vegetation indices in estimation of area under cultivation according to its phenology. Investigation of land use and cropping pattern of this area indicate a high centralization of agricultural lands with high water requirements and industries on the proximity of Zayanderud River which necessitates the spatial analysis of land use in this area.
Dr Sayyad Asghari, Hadi Emami,
Volume 19, Issue 53 (6-2019)
Abstract
Earth surface temperature is an important indicator in the study of energy equilibrium models at the ground level on a regional and global scale. Due to the limitation of meteorological stations, remote sensing can be an appropriate alternative to the Earth's surface temperature. The main objective of this study is to monitor the surface temperature and its relationship with land use, which is monitored using satellite imagery. For this purpose, the images were first obtained and the necessary pre-processing was applied to each one. Then it was compared to modeling and classification of images. Firstly, in order to investigate the changes in user-orientation, a user-defined classification map for each object was extracted using the object-oriented method. Then, to investigate the land use change, a map of user-landing changes map was extracted in an 18-year time period (2000-2017). Finally, in order to monitor the surface temperature, the surface temperature map of Ardebil was extracted. The results showed that there is a strong relationship between land use and surface temperature. As a user, urban users have a temperature of about 41 ° C (2017), which is also due to heat-absorbing urban temperatures. This is despite the fact that the use of hydrocarbons is due to a lower heat absorption of 34 ° C (2017). This shows the role of different uses in determining surface temperatures. Also, the relationship between surface temperature and vegetation cover was investigated in this study. The results showed that areas such as soil and urban areas with a lower coverage than areas such as agriculture and pasture, have a higher temperature. Because the coating is always an obstacle to the entry of heat, it has an inverse relationship with superficial heat.
Miss Rahimeh Rostami, Dr. Ali Mohammad Khorshiddust, Dr. Mohammadreza Nikjoo, Dr. Hassan Mahmudzadeh,
Volume 19, Issue 55 (12-2019)
Abstract
The drying of Lake Urmia has had many environmental impacts on the surrounding areas of the lake. In this research, efforts have been made to identify vegetation coverings that are compatible with the study area and then it use of multiplicative decision-making models for identify areas susceptible to cultivation of these products. In the present study, following the study of species in the region of rapeseed, was selected as a suitable halophytes plant. Initially, using Landsat 5 and 8 images, the changes in the land use type and vegetation cover type of the region were investigated from 2000 to 2016, and after calculating the changes, the potential planting of the halophytes plant was sought. The ANP Fuzzy method was used to estimate the ability to cultivate rapeseed. Main criteria used in this research are topography, soil and meteorology. The topographic sub criteria are included: height, slope and tilt direction, soil criteria including soil texture, soil salinity, and soil pH and soil organic matter. Finally, the criteria for meteorological data are total annual precipitation, Relative humidity, average annual temperature, maximum annual temperature and annual minimum temperature. These layers first be changed to fuzzy and then, applying the weight of each of the following criteria, a map of the main criteria of soil, topography and meteorology was prepared and finally, by combining these three main parameters, the potential mapping was obtained. The results indicate a 25.43 percent reduction in water content and an increase of 21.03 percent in saline areas between 2000 and 2016, and the results of identifying areas susceptible to cultivation of halophytes plants have identified 14.28 percent of the study area suitable for rapeseed cultivation.
Mokhtar Karami,, Rahman Zandi,, Jalal Taheri,
Volume 20, Issue 56 (3-2020)
Abstract
In recent years with the development of cities coatings of the Earth's has changed surface. These changes have caused some urban areas to have a few degrees higher than the surrounding temperature. This phenomenon is known as thermal islands. Mashhad is one of the major metropolises in Iran with the problem of thermal islands. Various parameters affect the formation of thermal islands in this city that should be considered. In this study TM, ETM+ and OLI images were used to obtain surface temperature over the period 1987-2016. The study of temporal variations in surface temperature showed that in the studied period, thermal islands were transferred from outside the city to the city. The model for describing the temperature of the surface of the earth has changed and has diminished from the temperature of the city's moderate and cool temperatures, and in contrast, the amount of high temperatures (thermal islands) has increased significantly. The TOPSIS method was also used to obtain the thermal forming factors. 13 natural and human factors affecting the formation of thermal islands were identified. Each expert opinion factor was used to determine the degree of importance. According to experts, the distance from the sanctuary with a weight of %234 and traffic of %155 is the most important and the height with a weight of %022 is least important in the formation of thermal islands. The final results obtained from this model showed that the factors affecting the formation of thermal islands are well recognized and the temperature decreases with these factors.
Dr Mohammad Ebrahim Afifi,
Volume 20, Issue 56 (3-2020)
Abstract
Land use maps are considered as the most important sources of information in natural resource management. The purpose of this research is to review, model, and predict landslide changes in the 30-year period by LCM model in Shiraz. In this research, TM Landsat 4, 5 and OLI Landsat 8 images were used for 1985, 2000 and 2015 respectively, as well as topographic maps and area coverage. Subsequent validation and detection of changes were made using the prediction model of variation The use of LCM markov and the model of user change approach. The images were classified into four classes of Bayer, garden, urban lands, and arable land for each of the three periods. According to the results, aquaculture is the most dynamic user in the area, which has led to an upward trend during 1985-2015, so that the amount (4337 ha, 12.7%) has been added to this area. The Bayer user change trend was also a downward trend during 1985 to 2015, reducing the 99.1995 hectares of this class. The results of the change in the 1985 changes with a kappa coefficient of 0.88, in the 2000 period with a CAAP of 0.77, and in the period 2015 with a Kappa coefficient of 0.92. The results of the change detection in 2030 are such that if the current trend continues in the region, 20.33% will be added to the crop category, so that in 2030, agricultural cropping will be 95.60% of the area of the area Gets In the Bayer and Garden uses 21.22% and 0.21% of the total area of each user has been reduced and has been added to the urban area. The prediction map derived from the Markov chain model is very important for providing a general view for better management of natural resources.
Dr Sayyad Asghari, Roholah Jalilyan, Dr Noshin Pirozineghad, Dr Aghil Madadi, Milad Yadeghari,
Volume 20, Issue 58 (9-2020)
Abstract
Water is one of most important human needs for life. According to importance of subject, discussion of management and utilization of water resources has become one of the most important global issues. Remote sensing data are often used in water body extraction studies and type of remote sensing data used plays an important role in water body extraction. In this study, ability of Landsat satellite with application of water indices, to extraction of Gamasiab River in Kermanshah and comparing these indices have been investigated. Specific feature of Low width and shallow rivers has increased the complexity of studies of such rivers using available data. Water body extraction from remote sensing images has been over the past two decades. Water indices were first developed using Landsat TM and Landsat ETM. But its better performance in Landsat 8 is well documented by the researchers. In this study, NDWI, MNDWI, AWEI_nsh, AWEI_sh and WRI indices were used. With extracting optimal threshold from histogram of indices and applying this threshold, the study area was classified into two classes of water and non-water. Then overall accuracy and kappa coefficient values were taken from each of the indices. Finally, AWEI index with overall accuracy of 99.09% and a Kappa coefficient of 0.98 was the best response among the indices in the study area. The results this study showed that approach can easily extract water from satellite imagery.
Khadijeh Mikaeli Hajikandi, Behrooz Sobhani, Saeid Varamesh,
Volume 23, Issue 68 (3-2023)
Abstract
Study of land use/cover changes is widely used in environmental planning. During the last decade, growing increase of aridity in Uromiyah Basin has become a major regional and even national problem. The purpose of this study is to reveal the changes in land use/cover in the southern and southeastern parts of the basin with using 2 images for month of July of 2000 to 2017. Landsat TM and OLI data and NDVI were used for classification this study. Land use/cover maps in the two studied years were provided using Maximum Likelihood Classifier (MLC) algorithm applied on two series data including spectral bands (data series 1) also spectral bands and filter texture layer (data series 2) and six categories of land use/cover containing Irrigated Farmland, Dry Farmland, garden, rangeland, bare land and water bodies were distinguished.. The accuracy of the produced maps were assessed and compared with the training samples derived from Google Earth images and Kappa Index, overral accuracy, producer accuracy and user accuracy. The results demonstrated that the maps produced using the data series 1 have higher accuracy and the overall accuracy of the maps of 2000 and 2017 using the data series 2 are 98.93 and 98.29 and these values for data series 1 were gained 99.28 and 91.45, respectively. In additional, texture filtering decreased amount of mixing between classes of rangeland, Irrigated Farmland and garden. The results of change detection showed considerable increase in the area of Irrigated Farmland (13.44) and garden 1.85 (27.24) an also at the studied period, the area of the water bodies and rangeland were decreased to 1.58 and 22.94%.
Nasrinalsadat Bazmi, Zahra Hejazizadeh, Parviz Zeaiea Firoabadi, Qholamreza Janbazghobadi,
Volume 23, Issue 70 (9-2023)
Abstract
This article was written with the aim of revealing land use changes in Urmia city using remote sensing of Landsat satellite images for 4 periods of 8 years between 1990 and 2019. For this purpose, two categories of data will be used in this research. The first category includes data obtained from satellite images and the second category includes ground data taken from Urmia ground station, which includes temperature and other parameters used in this research. The results showed that urban land use in Urmia city has faced significant changes during the statistical period of 30 years. This user has had an increasing trend during all the studied periods, so that during the study period, it has faced a 5-fold increase. Swampy areas and sludge fields east of Lake Urmia have undergone a significant decline during 1990-2019 and has reached less than 6,000 hectares. The citychr('39')s barren lands, which cover a small percentage of the citychr('39')s area, have been declining over the 30-year period under review. The use of gardens has increased during all periods, so that in 2019, its area has reached more than 20,000 hectares. The use of irrigated agriculture has increased during all the studied periods and its area has reached more than 80,000 hectares by 2019. The area of rainfed agricultural lands, after the rangelands, is the widest land use in Urmia, but with a relatively gentle slope has a decreasing trend. Water areas have also been declining, so that in 2019, it has decreased by about 26% compared to 2012. Rangelands, which is the largest land cover in Urmia city, has gone through three different processes during the study period. From 1990 to 1998, these lands did not change significantly, but from 1998 to 2005, the increasing trend and in 2019, with a 10% decrease compared to 2012, reached its lowest area during the statistical period under study, ie less than 20,000 hectares.
Akbar Mirahmadi, Hojjatollah Yazdan Panah, Mehdi Momeni,
Volume 24, Issue 72 (3-2024)
Abstract
In recent years, the technology of crop production has been greatly expanded using satellite data. Today, Landsat 8 and OLI sensor data, with a spatial resolution of 30 meters, allow the discovery of factors that control phenology on a local scale. In this study, the remote sensing indices - NDVI, EVI, Greenness, and Brightness - obtained from the OLI sensor and the GCC index obtained from digital camera images were used to estimate the phenological stages of the rapeseed plant. The Savitzky-Goli filter was used to remove outlier data and to produce smooth curves of time series of plant indices. The results showed that the curves obtained from the indices of NDVI, EVI, GCC show all four stages of remote sensing phenology – green-up, dormancy, maturity, and senescence - well, but the Greenness index did not show the dormancy stage well. The Brightness index curve shows the inverse behavior to other curves. According to Pearsonchr('39')s correlation test, GCC index data are correlated with NDVI and Brightness index data .we used the ratio threshold, rate of change and first derivative methods, to estimate "start of season" and "end of season" and the results showed that the first derivative and ratio threshold methods with an average difference of 18 and 19 days in the "start of the season" and the rate of change method, with an average difference of 8 days, has the best performance in estimating the “end of the season”. Also, the Brightness index with an average difference of 16 days and the EVI index with an average difference of 7 days have the best performance in estimating "start of season" and "end of season", respectively.
