Remote Sensing (RS)
Moslem Darvishi; Reza Shah-Hosseini
Abstract
Extended Abstract IntroductionWith the expansion of the urban limits, some of the lands that were used for gardening years ago have been located within the urban limits. The difference between the value of garden land use and urban land use, such as residential and commercial, encourages gardeners to ...
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Extended Abstract IntroductionWith the expansion of the urban limits, some of the lands that were used for gardening years ago have been located within the urban limits. The difference between the value of garden land use and urban land use, such as residential and commercial, encourages gardeners to change their land use. Urban managers try to prevent this change of use by enforcing strict rules.Assessing the success of such plans requires examining land-use change in the urban over a long periodof time. The main purpose of this study is to detect abandoned urban gardens using Landsat satellite imagery. The second goal is to determine the extent of changes in urban gardens in the study area over the past 30 years. In this study, based on Landsat satellite images in 2018 and 1988 for the northern slope of Alvand Mountain in Hamadan province and the city of Hamadan, the normalized differential index of vegetation (NDVI) along with land surface temperature (LST) in 9 time periods per year was extracted. The results indicated a 4/75 ° C increase in LSTfor the region over 30 years. Also, the inverse relationship of LST with NDVI is confirmed. Based on the separation of urban gardens, a comparison was made between 2018 and 1988, which showed a decrease of 175 hectares of urban gardens in the study area, which is equivalent to a 49% reduction in urban gardens. In the main part of the research, based on the behavioral evaluation of urban gardens, in these two characteristics, a differentiation index for active and abandoned gardens is presented. Examination of the results based on ground truth data including 25 active gardens and 25 abandoned gardens suggested that the proposed method had an overall accuracy of 82% and a Kappa coefficient of 0/64.Materials & MethodsThe study area includes a part of the northern slope of Alvand Mountain, which is limited to the southern part of Hamedan and has a latitude of 34 degrees and 45 minutes to 34 degrees and 48 minutes north and a longitude of 48 degrees and 27 minutes to 48 degrees and 31 minutes east. Ground truth data including 25 active gardens and 25 abandoned gardens were collected as field visits using a Garmin GPSMAP 62s handheld navigator so that coordinates were collected by attending the location of abandoned and active gardens. The satellite data used in this study concern the time series data of Landsat 8 satellite OLI and TIRS sensors for 2018 and Landsat 5 satellite TM sensor for 1988.To achieve the first objective and separate active and abandoned gardens in 2018, the land surface temperature (LST) and the normalized difference vegetation index (NDVI) are calculated and the behavior pattern of these two components is examined during the year for active and abandoned gardens in nine periods according to the proposed method, a final index for separating active and abandoned gardens is presented based on the NDVI behavior pattern throughout the year. The time series of NDVI for each year is evaluated in 9 periods and garden maps are extracted in 1988 and 2018 to achieve the second objective and prepare the maps of 30-year changes in active gardens in the study area. The rate of change of area and the percentage of changes in the class of gardens are obtained by comparing the maps.Results & DiscussionSince this study is conducted mainly to identify abandoned gardens in urban space, two criteria for assessing user accuracy and errors of commission in the abandoned garden class are very important. In other words, in this problem, the number of gardens that are properly divided into the abandoned garden class is important, and the proposed method provides an accuracy of 86%. The most important issue is the number of abandoned gardens that the proposed method has mistakenly labeled as active gardens, which is 14% in this method. Both accuracies provided are evaluated as acceptable. The overall accuracy of the proposed method is estimated at 82%, which is acceptable, indicating the efficiency of the proposed method.ConclusionOne of the problems facing human societies today is the reduction of forests and gardens. Given the important role that trees play in improving the quality of human life, protecting them is one of the inherent duties of rulers. Various factors cause the destruction of trees, one of which is the development of urban areas in the vicinity of forests and gardens. Traditional methods of conserving natural resources and monitoring their changes have failed in practice. For example, in the study area, 49% of the tree-covered areas have declined over the past 30 years. However, the ban on construction in the area has always been emphasized by city managers in the years under study, and the inefficiency of the methods used has been proven by the statistics provided. New methods of monitoring changes based on satellite image processing can be alternatives to traditional methods due to their high accuracy and speed and significant cost reduction. The proposed index is recommended to be evaluated to separate active and abandoned gardens in other areas facing this problem using images with higher spatial resolution. In different cases of threshold limit, the overall accuracy of the proposed method is examined based on the ground truth data of the evaluator. At best, the separation of active and abandoned gardens is associated with an overall accuracy of 82%.
Mohammad Kazemi Garaje; Khalil Valizadeh Kamran
Abstract
1- Introduction Direct measurement of physical parameters of water, such as sea surface temperature and water depth through traditional methods is very time-consuming and costly. Thus, new cost-effective methods, such as remote sensing technology, have always been of interest to experts, managers and ...
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1- Introduction Direct measurement of physical parameters of water, such as sea surface temperature and water depth through traditional methods is very time-consuming and costly. Thus, new cost-effective methods, such as remote sensing technology, have always been of interest to experts, managers and decision-makers. Satellite imagery is used to estimate sea surface temperature and water depth. Therefore, the present study seeks to calculate sea surface temperature and water depth and investigate their relation using satellite imagery. 2- Materials and Methods In the present study, Landsat 8 satellite images of Urmia and Van Lake were retrieved from USGS website for August 16th, and August 23rd, 2018. Information about water temperature and water depth of 3 meteorological stations in the study area were also obtained from the Artemia Research Center and the Meteorological Organization of West Azerbaijan Province for a period of three months. In the next step, geometric and atmospheric corrections were performed on the images using ENVI5.3 software. In thermal remote sensing, thermal bandwidth of satellite imagery cannot reflect black-body radiation. Moreover, electromagnetic spectrum of radiation used in the Boltzmann relationship covers a range of 3 to 300 micrometers. This is while the thermal spectrum range of thermal sensors is generally between 10.5 to 12.5 micrometers.Thus, the split-window algorithm was used to calculate the land surface temperature. Water emission coefficient equals 0.98. Multiplying the amount of water emission by the amount of land surface temperature (LST) and subtracting the results from zero Kelvins (-273), we can obtain sea surface temperature in Celsius degrees. 2-1- Calculating relative depth of water As one of the dynamic characteristics of water, water depth has an important role in the management and optimal use of marine resources. Water depth measurement refers to the underwater study of oceans, lakes and rivers. Therefore, Stump Method was used to calculate water depthin the present study. 2-2- Accuracy assessment In order to estimate the accuracy, information about water surface temperature and relative water depth in three stations in Lake Urmia, namely Qalqachi, MalekAshtar and Ashk stations, were collected from the Artemia Research Center and the Meteorological Organization of West Azerbaijan Province. 3- Results Results indicate high accuracy of remote sensing methods in sea surface temperature and water depth measurements. The lowest RMSE of sea surface temperature measurement is related to MalekAshtar station (1/1). This station also has the lowest amount of RMSE (1/5) obtained in water depthmeasurement. According to the results, a negative correlation coefficient is observed between the values of sea surface temperature and water depthvariables. The correlation between sea surface temperature and water depth in Lake Van equals -0.52, while this correlation equals -0.24in Lake Urmia. 4- Discussion Despite their relatively high accuracy, usinginformation collected from meteorological stations to calculate physical parameters of water,such as water surface temperature and water depth, has some limitations. However, new technologies such as remote sensing can overcome the limitations of traditional methods. Remote sensing technology has made estimating the physical parameters of water on a regional to a global scale possible. Results of the present study indicate high accuracy of remote sensing technology in measuring physical parameters of water such as surface temperature and depth. In this regard, shallow water bodies have the highest surface temperature and deeper water show lower temperatures. The results also indicate that fluctuations in the water surface temperature and water depth can increase or decrease the correlation coefficient between these two variables. Thus, higher correlation coefficient between water surface temperature and water depth in Lake Van compared to Lake Urmia is due to its greater depth of water. 5- Conclusion Results indicate that the upstream of Lake Urmia is deeper than itsdownstream and also has a higher level of salinity which reduce evapotranspiration in the upstream of the lake. Thus, theupstreamof Lake Urmia has not been as severely affected by the drought. The correlation coefficient between water surface temperature and water depth of Lake Van also shows that this lake has a relatively lower water surface temperature compared to Lake Urmia due to its greater depth. Therefore, the rate of evapotranspiration in this lake is less than Lake Urmia and the drying process is negligible. Due to the fact that Lake Urmia and Van are in the same climate, the high temperature of the water level of Lake Urmia due to its shallower depth can be one of the causes of Lake Urmiadrying. The amount of water in the lake can be increased by increasing the volume of water entering the lake.This can be achieved by destroying a number of dams built on the rivers flowing into the lake or by water transfer from adjacent water bodies. Therefore, increasingwater depth and reducingwater surface temperature can be considered as one of the main solutions to prevent the drying of Lake Urmia.
Mehrdad Hadipour; Hamid Darabi; Aliakbar Davudirad
Abstract
Extended Abstract Introduction With the development of urbanization, a large part of agricultural areas and forests have been replaced by residential areas, industrial centers, and other infrastructures. This is due to human life style and his endeavor to reach sustainable urbanization. A series of changes ...
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Extended Abstract Introduction With the development of urbanization, a large part of agricultural areas and forests have been replaced by residential areas, industrial centers, and other infrastructures. This is due to human life style and his endeavor to reach sustainable urbanization. A series of changes in the reflection of light from different material’s surface, heat storage and heat transfer, have changednatural and artificial landscape orsignificantly affected local climate. Therefore, public concerns about urban sprawl, increasing urban population and quality of urban environmental have motivated planners to seek better perspectives for development of urban areas. Increasing temperature of urban areas is considered to be one of the most important environmental problem in cities. This increasing temperature results in creation of Urban Heat Islands (UHI) in some parts of urban areas, which are significantly warmer than surrounding urban environment. Therefore,a new and successful method of urban planning should be introduced with respect to spatial distribution of land surface temperature (LST) to achieve better urbanization and reduce environmental impacts on cities. Materials & Methods The present study takes advantage of Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) thematic maps to investigate therelationship between air pollution, and two indexes of NDBI and NDVI with land surface temperature (LST) and Urban Heat Islands (UHI) in urban areas. Satellite imageries of Arak (an industrial city in Iran) has been chosen for the case study. Urban and natural areas and impermeable surfaces such as roads, buildings and other constructions are rapidly developing in this city. In the first step of research methodology, necessary pre-processing programs such as radiometric corrections were performed on the satellite imageries. Then satellite imageries were transformed toatmospheric images to produce NDBI and NDVI indexes. Finally,land surface temperature maps wereproduced using the method of Landsat Project Science Institute in Arc GIS 10.3. To classify satellite images, seven land use classes were identified as poor pastures, averagepastures, rich pastures, bare lands, Lake’s Shore, agricultural lands and residential lands.Then, training images classification method was used to collect samples from the study area and classification was performed using maximum likelihood method for monitoring. In order to analyze LST parameter using NDBI and NDVI indexes, air quality data,and statistical methods like Kolmogorov-Smirnov test, paired t test and Pearson correlation test were used. The results of Kolmogorov-Smirnov test indicated that data used in this study was normally distributed. The results of t test, temperature recorded by synoptic stations in Arak and remotely sensed data indicated that the accuracy of the test is more than 5%. Thus, the difference between residential land use and other urban land uses was not statistically significant. Moreover, results indicate that there is a more than 99 percent correlation between temperature recorded by the synoptic stations in Arak and data collected from satellite imageries. Results of correlation with remotely sensed data indicatedthatthere is a significant correlation between99 percent of results and less than 5 micron particles. Results & Discussion Correlation between air pollution data andremotely sensed data (LST) indicated that LST and less than 5.2 micronparticlesare significantly correlated with 99% accuracy. Urban heat island usually occurs in metropolitan area and its surroundings. Due to climate changes, urban heat islands are constantly developing. This results in increased energy consumption for air conditioning systems. Thus, reducing the effects of urban heat islands has become an important global issue. The present study has successfully explained the effects of urban heat islands and their environmental problems on normal life. Detailed program of related measures and policies should reduce the intensityof urban heat island. Final development of the cities should be based on land surface temperatures in surrounding areas in a way that cities can reach a lower surface temperature as compared to the temperature before urban development. Conclusion Following strategies are suggested for a more comprehensive consideration of urban green spaces in urban planning and future development of cities: Paying attention to architecturalcriteria and urban land use, and alsopaying attention to soil and water management parametersbased on the principles of green architecture, paying attention to standards of anthropogenic temperature rise caused by human activities, and the problem of urban heat islands. Moreover, it is crucially important to prepare the necessary situation for the community to reach a good physical and mental health.
