University of TehranEarth Observation and Geomatics Engineering2588-43524220201201Thermal anomaly detection using NARX neural network method to estimate the earthquake occurrence time981088105910.22059/eoge.2021.292253.1067ENMehranNekoeeSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranRezaShah-HosseiniSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-7552-5392Journal Article20191009In this study, the remotely sensed thermal data from the earth’s surface of the center zone of the earthquake was used to predict the time of earthquake occurrence. The provided methods for approximating the time and severity of the earthquake are classified into two categories of non-smart and smart. In non-smart methods, the earthquake predicting parameters must be obtained continuously and point to point, to prevent the errors caused by interpolation uncertainty, which requires high levels of cost and furthermore we will be limited in terms of tools in these methods. The smart methods which include Artificial Neural Networks (ANN), Support Vector Machine (SVM), Genetic Algorithm (GA), etc., contain different uncertainties depending on their training algorithms in such a way that by defining an inappropriate threshold between the predicted value and the real ones, they are not able to isolate the variable but natural behavior of the under-study area from anomaly. Because a series of time-dependent data should be used in studying earthquakes, the prediction of theses time series can be done using Artificial Neural Networks. To make more accurate, two different methods of dynamic NARX (Nonlinear Auto Regressive with eXternal input) neural network algorithm namely Levenberg-Marquardt and Scaled conjugated gradient has been applied. The responses of these two methods have been compared with the response derived from mean and variance. The important advantage of the NARX neural network is that small thermal anomaly due to the natural climate changes did not detect and considered as earthquake pre-indicator. The results elucidate that the earthquake, 7 days before (first method response) and 12 days before (second method response) occur has been predicted. The thermal anomaly about 5 degrees of kelvin of earthquake center zone detected. Thus the thermal anomaly detected by this method can be a good pre-indicator for earthquake prediction.https://eoge.ut.ac.ir/article_81059_c289499484141d7065de1a1e0ac73742.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43524220201201Developing a spatial solution for earthquake crisis management using volunteered geographic information and genetic algorithm: A case study of an earthquake, Tehran, Iran1091188109310.22059/eoge.2021.309028.1085ENFarhadHosseinaliShahid Rajaee UniversitySarahFarhadpourDepartment of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee UniversityJournal Article20191001Natural disasters, such as floods and earthquakes, affect the societies more than people think. These effects range from economic effects to social harms and casualties. An earthquake may only last a few seconds, but its damage lasts for years. The purpose of this study is to collect volunteered geographic information from people in the affected areas using smartphones and to identify areas of high priority for relief using the collected data. Then, spatial analysis enables us to assess the condition of the road network after the earthquake and determine the degree of damage due to debris. Ultimately, using the genetic algorithm, the process of assigning rescuers to crisis points and routing is done considering the extent of road damage. The case study is district 2 of Tehran. In this paper, it will be shown that a mobile information system is necessary to fill the gap between the people, the crisis headquarters and the relief teams. Such systems collect crisis-related data with the help of people in crisis areas and help headquarters and relief decisions to be faster and better. The results indicate a high vulnerability of roads in most areas of district 2 of Tehran. Eventually, about 243.5 km of the region's roads, which also make up a quarter of the region's vital arteries, are damaged by at least 80% that make the relief process difficult.https://eoge.ut.ac.ir/article_81093_fb28c8fabaeb932739a6583d5ef4d6a0.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43524220201201Trend analysis development of urban heat island using thermal remote sensing1191318128910.22059/eoge.2021.309046.1086ENMahsaBozorgiDepartment of Environmental Science, Yazd University, Yazd, Iran, mahsabozorgi@stu.yazd.ac.ir0000-0001-8167-7918FarhadNejadkoorkiDepartment of Environmental Science, Yazd University, Yazd, IranNedaBihamta ToosiDepartment of Natural Resources, Isfahan University of Technology, IsfahanJournal Article20200310Population growth and urbanization development are the major factors in increasing land surface temperature (LST) in urban areas which lead to urban heat Island (UHI). Green covers play an important role in improving the comfort level of citizens and achieving sustainable urban environment through decreasing temperature, increasing humidity and finally dwindling UHI. The current study aims to analyze and evaluate the changes of green covers and LST in Isfahan Metropolitan Area (IMA), Iran, from 1998 to 2014. This study emphasizes on the impact of green covers on IMA temperature pattern. Accordingly, Normalized Difference Vegetation Index (NDVI) threshold method was applied to obtain the land surface emissivity (LSE). In addition, Planck’s law for TM image and Split Window (SW) algorithm for OLI/TIRS image were utilized in order to retrieve LST. It was validated with data collected from 5 stations within the city. Temporal and spatial changes in IMA’s LST were then analyzed using statistical methods, Mann-Kendall analysis and Urban-Heat-Island Ration Index (URI). The result indicates that LST in IMA had an increasing trend over the study period and its intensity, generally, concentrated in the northwest and the northeast of the city, the bed of dried Zayandeh-Rood and green covers along the river bank which destroyed. Also, there was an increasing trend in URI from 0.25 in 1998 to 0.312 in 2014. All in all, it can be concluded Mann-Kendall trend test and URI were appropriate outfits to analyze satellite images in order to identify the spatio-temporal change of UHI.https://eoge.ut.ac.ir/article_81289_5020e282b4b803bd25ffc4fea65f1250.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43524220201201Using GIS and DANP in detecting potential areas for Sinkholes1321478106010.22059/eoge.2021.310615.1090ENHadiFadaeiAssistant professor of Amin police university0000-0002-5751-8025VayghanSaeideh SahebiDepartment of Remote Sensing and GIS, Kharazmi University, Tehran, Iran0000-0002-1460-0475RouhollahEsmaili SarteshniziDepartment of surveing engineering,marand technical college,university of tabriz,tabriz, iran,NedaGhasemkhaniDepartment of Geography and Urban Planning, Islamic Azad University, Tehran, IranJournal Article20200319One of the most common surface features of Karst topography is sinkholes. The karst areas provide drinking water for 25% of the world’s population. Identifying sinkholes is crucial in managing water resources, as their contamination leads to the contamination of water resources in the area. The Bisotun-Parav Karstic Basin is essential because it creates spring wells in Bisotun and Kermanshah and supplies part of their water. This study aims to detect potential areas for sinkholes using GIS and Decision Making Trial and Evaluation Laboratory)-based analytic network process (DANP). The criteria which were used are Climatology (precipitation, temperature, evaporation, streams), Topography (slope, elevation), Agriculture(vegetation), Lithology (lithology, soil type, fault). Then the required layers were obtained, and the importance of each factor was determined through a combination of the DEMATEL technique and the ANP. Finally, after combining the layers, a map of potential sinkhole areas was obtained. Sinkholes in the area were detected using the visual interpretation of world imagery and google earth imagery as reference data. The results of the DANP demonstrated vegetation, elevation, and lithology with the value of 22.59%, 12.12%, and 11.94 respectively are the most important factors involved in the formation of sinkholes. The indexes of correctness, completeness, and quality were then used to evaluate the study results and turned out to be 98.73%, 79.86%, and 79%, respectively. The high correctness index indicates high efficacy in detecting the existing sinkholes, but the low percentage of the other two indexes does not indicate the inefficacy of the method; rather, the two indexes of completeness and quality indicate areas with a potential for sinkhole formation that either has no sinkholes or are not in the reference data. This method effectively detects sinkholes and potential areas for sinkhole formation.https://eoge.ut.ac.ir/article_81060_f125d74be5df48b2d5fa1a6cc46dacf9.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43524220201201Mineral prospectivity mapping of porphyry Cu deposit using VIKOR method1481688105810.22059/eoge.2020.305708.1083ENMahyadinMohammadpourMineral Exploration department, School of Mining EngineeringMaysamAbediDepartment of Mining Engineering, University of Tehran0000-0002-5365-0694AbbasBahroudiExploration Department, School of Mining EngineeringJournal Article20200319Naysian Porphyry Cu District (NPCD) is situated at the northeast of Isfahan, in the center of Iran along the Urumia-Dokhtar Magmatic Assemblage (UDMA) belt. Mineral Potential Mapping (MPM) is an important issue in mining to reduce the exploration costs by proposing a layout of drilling over the most favorable regions in association with ore-bearing target. MPM can be defined as a multi-criterion decision-making (MCDM) problem. Out of many MCDM methods, the VIKOR is based on a compromise solution which evaluates issues with inappropriate and incompatible criteria. In this study, seven geospatial indicators related to the NPCD were extracted from geological, geochemical and geophysical criteria. According to the conceptual model of a porphyry copper mineralization system, the highest weight was allocated to the geochemical criterion with a value of 0.499 and to the sublayer of the copper concentration map (0.425). In addition, the lowest weight was allocated to the geophysical criterion (0.113). Two variants of the VIKOR method that are the conventional (C-VIKOR) and the adjusted (A-VIKOR) ones were examined in this study, and their outputs were compared with the index overlay (IO) method as a popular approach in MPM. Taking a threshold value of 0.6 into account for final synthesized indicators, the mineral favorability areas highlighted by the IO, A-VIKOR and C-VIKOR methods have occupied 49.5, 15.8 and 18.7 hectares, respectively. It is worth pointing out that the MPM derived from the A-VIKOR method has superiority over the outputs of the IO and C-VIKOR methods by introducing the lowest favorable area and 92% matching of high grade boreholes with the proposed areas. Comparing the mean grade of copper obtained from boreholes drilled in the area and the values of MPM, a significant correlation between boreholes and prospectivity map was also obtained.
<strong><span style="font-size: 10.0pt;">ABSTRACT</span></strong>
<span style="font-size: 9.0pt; line-height: 115%;">Naysian <em>Porphyry</em></span><span style="font-size: 9.0pt; line-height: 115%; mso-ansi-language: EN;" lang="EN"> Cu District (NPCD) is situated northeast of Isfahan, in the center of Iran along the </span><span style="font-size: 9.0pt; line-height: 115%;">Urumia-Dokhtar Magmatic Assemblage (UDMA) belt</span><span style="font-size: 9.0pt; line-height: 115%; mso-ansi-language: EN;" lang="EN">. Mineral Potential Mapping (MPM) is an important issue in mining to reduce the exploration costs by proposing a layout of drilling over the most favorable regions in association with an ore-bearing target. MPM can be defined as a multi-criterion decision-making (MCDM) problem. Out of many MCDM methods, the VIKOR is based on a compromise solution which evaluates issues with inappropriate and incompatible criteria. </span><span style="font-size: 9.0pt; line-height: 115%;">In this study, seven geospatial indicators related to the NPCD were extracted from geological, geochemical, and geophysical criteria. According to the conceptual model of a porphyry copper mineralization system, the highest weight was allocated to the geochemical criterion with a value of 0.499 and the sublayer of the copper concentration map (0.425). In addition, the lowest weight was allocated to the geophysical criterion (0.113). Two variants of the VIKOR method that are the conventional (C-VIKOR) and the adjusted (A-VIKOR) ones were examined in this study, and their outputs were compared with the index overlay (IO) method as a popular approach in MPM. Taking a threshold value of 0.6 into account for final synthesized indicators, the mineral favorability areas highlighted by the<span style="mso-spacerun: yes;"> </span>IO, A-VIKOR, and C-VIKOR methods have occupied 49.5, 15.8, and 18.7 hectares, respectively. It is worth pointing out that the MPM derived from the A-VIKOR method has superiority over the outputs of the IO and C-VIKOR methods by introducing the lowest favorable area and 92% matching of high-grade boreholes with the proposed areas. Comparing the mean grade of copper obtained from boreholes drilled in the area and the values of MPM, a significant correlation between boreholes and prospectivity map was also obtained.</span>
https://eoge.ut.ac.ir/article_81058_f26a9573b2ac72791682bd5687ab742e.pdfUniversity of TehranEarth Observation and Geomatics Engineering2588-43524220201201Optimizing the regularization parameters of prior information in sparse coding-based multispectral image fusion1691798200910.22059/eoge.2021.323695.1094ENAfshinAsefpour VakilianSchool of Surveying and Geospatial Engineering,
University College of Engineering, University of Tehran, Tehran, Iran0000-0002-0268-8502Mohammad RezaSaradjian MaralanSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran0000-0002-1734-5860Journal Article20200325Advanced sparse coding-based image fusion methods use some prior information to fuse low-resolution multispectral (LR-MS) and panchromatic images to create a high-resolution multispectral image (HR-MS). This information mainly includes a sparsity term, spectral unmixing, and nonlocal similarities. These prior terms are usually considered in the sparse optimization problem as constraints with specific regularization parameters. During the optimization, the regularization parameter of each prior term is optimized by considering the other two prior terms as constants. This study aims to simultaneously optimize the regularization parameters of prior terms in a sparse coding image fusion method to construct an HR-MS from input LR-MS and Pan images. Several optimization methods, including particle swarm optimization, ant colony optimization, differential evolution, and genetic algorithm were used to optimize the regularization parameters. The results showed that particle swarm optimization had the highest performance in increasing the peak signal-to-noise ratio on the dataset available from the study area. The advantages of the proposed optimized sparse coding (OSC) approach are the ability to, 1) preserve spatial details while eliminating spectral distortions, 2) simultaneously optimize the regularization parameters of prior terms in a sparse coding image fusion framework, 3) considering nonlocal similarities to enhance fusion result, and 4) promising fusion results over heterogeneous regions with highly spectral variations. The relative dimensionless global error in synthesis, spectral angle mapper, universal image quality index, and peak signal to noise ratio criteria were at least 0.76, 1.16, 0.0257, and 2.68 better than those achieved by conventional PS methods, i.e., Gram-Schmidt, Brovey transform, generalized intensity-hue-saturation, smoothing filter-based intensity modulation, and a novel sparse coding-based image fusion method. According to the results, better preservation of spatial details and lower spectral distortions can be achieved using the proposed OSC approach.https://eoge.ut.ac.ir/article_82009_b9c7e03f4777470e370b3af78467e6a3.pdf