Iranian Journal of Remote Sensing & GIS

علمی - پژوهشی

Comparison of the Efficiency of Local Climatic Zone Algorithm in Separating Built-Up Area Compared to Built-Up Indices

Najme Satari; Malihe Erfani; FATEMEH Jahanishakib

Volume 15, Issue 4 , February 2024, Pages 1-16

https://doi.org/10.48308/gisj.2022.102576

Abstract

Trend analysis of growth of cities and predicting their changes in the future are essential for spatial planning. For this purpose, it is necessary to map build-up areas. In many areas, especially in arid climate, it is not possible to separate the build-up areas from the surrounding land cover simply. ... Read More

علمی - پژوهشی

Improving the Accuracy of Ground Surface Ozone Concentration Estimation Using Satellite Products and Machine Learning

Rasoul Atashi Deligani; Mina Moradizadeh; Behnam Tashayo

Volume 15, Issue 4 , February 2024, Pages 17-30

https://doi.org/10.48308/gisj.2022.102758

Abstract

Ground surface ozone is one of the most dangerous pollutants that has significant harmful effects on the residents of urban areas. The purpose of this study is to identify the factors affecting ozone concentration and modeling its changes using satellite data and different machine learning methods in ... Read More Ground surface ozone is one of the most dangerous pollutants that has significant harmful effects on the residents of urban areas. The purpose of this study is to identify the factors affecting ozone concentration and modeling its changes using satellite data and different machine learning methods in Tehran. For this purpose, pollutant concentration and meteorological data were used along with the satellite product of land surface temperature (LST) in the period from 2015 to 2021. After calculating the correlation between ozone concentration and independent parameters, ozone concentration modeling was done in five different modes in terms of input parameters and learning method and applying data refinement. In the first and second mode, modeling was done using pollutant concentration and meteorological data through multivariate linear regression method. The only difference between these two modes is the filtering of the input data using the WTEST method in the second mode. In the third mode, the LST product was added to the input data, and in the fourth and fifth mode, ozone modeling was done using multilayer neural network and recurrent neural network, respectively. The comparison of the five modes showed that the modeling of the first to fifth stages with adjusted coefficient of determination of 0.5, 0.64, 0.69, 0.74 and 0.8 were able to recover the ozone concentration, respectively. It was also found that among different pollutants, nitrogen monoxide, nitrogen dioxide and nitrox have the greatest impact on ozone concentration, just as temperature, humidity and wind speed are the most influential among meteorological data. Although the use of WTEST statistics led to the identification and elimination of inconsistencies and errors in the observations of pollution measurement stations, the neural network learning method showed better performance in modeling than multivariate regression due to its less sensitivity to noise. As a notable result, adding the LST product to the input data brought a 5% increase in accuracy in estimating ozone concentration.

علمی - پژوهشی

Zoning of Soil Shear Strength Parameters (Case Study: Kermanshah)

Hassan Sharafi; Reza Faraji

Volume 15, Issue 4 , February 2024, Pages 31-40

https://doi.org/10.48308/gisj.2022.102887

Abstract

In order to understand the site, it is necessary to obtain soil strength parameters, which are both costly and time-consuming. In this research, utilizing 135 geotechnical boreholes drilled in Kermanshah, the zonation of soil shear strength parameters (friction angle and cohesion) using ArcGIS software ... Read More

علمی - پژوهشی

An analysis of the Trend Changes in Water Resources and Factors Affecting it in the Central Plateau of Iran Using Satellite Products

Mohsen Ebrahimi; Zohre Ebrahimi-Khusfi

Volume 15, Issue 4 , February 2024, Pages 41-60

https://doi.org/10.48308/gisj.2022.102889

Abstract

The Central Plateau of Iran, due to climate changes and the reduction of available water resources on one hand, and the increase in population and the consequent increase in demand on the other hand, is facing a severe water crisis. The science of remote sensing and the availability of numerous satellite ... Read More

علمی - پژوهشی

Application of Sentinel- 2 Satellite Data in Investigating Land Cover Changes in the Bed of Anzali Wetland

Maryam Haghighi Khomami; Mohammad Panahandeh; Mohammad javad tajaddod; Fariborz Jamalzad Fallah; Mahsa Abdoli

Volume 15, Issue 4 , February 2024, Pages 61-82

https://doi.org/10.48308/gisj.2022.102888

Abstract

Wetlands as an integral part of the global ecosystem in flood prevention or mitigation, feeding aquifers and providing unique habitat for plants and animals and other services and benefits are key elements of a regional conservation strategy. Anzali International Wetland in Guilan Province is one of ... Read More

علمی - پژوهشی

Evaluation of Spatio-Temporal Downscaling Algorithms of MODIS Data to Sentinel- 2 Data in Different Land Cover Classes

Nahid Haghshenas; Ali Shamsoddini

Volume 15, Issue 4 , February 2024, Pages 100-83

https://doi.org/10.48308/gisj.2023.103096

Abstract

Normally, images with a high resolution (temporal or spatial) are available, while there is a limitation in accessing images which are simultaneously high spatial and temporal resolution. While, in some applications, access to images with high spatial and temporal resolution is necessary. Therefore, ... Read More

علمی - پژوهشی

The Effect of Salt Dust Storms on the Health of Plants in the Eastern Basin of Urmia Lake

fariba gilreyhan; Khalil Valizadeh Kamran; davood mokhtari; ali akbar rasouli

Volume 15, Issue 4 , February 2024, Pages 101-118

https://doi.org/10.48308/gisj.2023.103099

Abstract

Urmia Lake is one of the largest saltwater lakes in the world, which unfortunately is drying up and has caused many dangers and concerns, especially in relation to salt dust in its dried areas. Therefore, in this research, we tried to investigate the relationship between vegetation and dust in the cities ... Read More Urmia Lake is one of the largest saltwater lakes in the world, which unfortunately is drying up and has caused many dangers and concerns, especially in relation to salt dust in its dried areas. Therefore, in this research, we tried to investigate the relationship between vegetation and dust in the cities around Lake Urmia. Salinity in plants causes physiological disorders; salt stress causes growth, photosynthesis, protein, respiration, energy production, premature senescence, water reduction in plants. Considering these effects, it was tried to evaluate the overall health of plants by using related indicators including NDVI, CIre, GCI, CRI2, NDWI, NDII, MSI, PSRI. These indicators evaluate the amount of plant water, plant water stress, photosynthesis capacity, plant growth and water deficit, the amount of chlorophyll, nitrogen and pigments, which are related to plant energy and health. According to these indicators, the health of plants is generally in a favorable condition, and mostly the highest numerical values of the indicators were assigned to gardens. Using Landsat and Sentinel 2 images and the NDVI index, the vegetation changes of the region were determined in the period from 2010 to 2020, and then using the MERRA-2 database, the amount of dust concentration was also extracted for the mentioned years. The results showed that the average NDVI in the studied area follows a constant trend with an overall average of 0.2957 and sometimes it increases or decreases due to the influence of external factors such as dust. Based on this, the highest (0.3495) average NDVI is related to 2018 and the lowest (0.2579) is related to 2013. Also, two methods of linear and logarithmic regression were used to investigate the relationship between vegetation cover and dust, and the results showed that based on the linear (0.7703) and logarithmic (0.7915) regression, the highest coefficient of explanation between the two mentioned indicators was in May.

Positioning lands prone for cultivating ficus fars province using fuzzy logic and the GIS approach

Ali shamsoddini; hasan mehrzad; babraz karimi

Volume 10, Issue 3 , January 2019, , Pages 1-16

Abstract

Agriculture is one of the most important economic parts in each country, which each product requires specific climatic and environmental conditions. So climatologists pay special attention to landuse planning and managing ecological resources with appropriate methods. The purpose of this study is to ... Read More

Estimation of Soil Surface Moisture Using ALOSPALSAR-2 Data

Sadolla Sangini; Hadi Fadaei; Amir Sadoddin; Vahed berdi Sheikh; Chogi Bairam Komaki

Volume 13, Issue 3 , November 2021, , Pages 93-112

https://doi.org/10.52547/gisj.13.3.93

Abstract

Temporal and spatial distribution of soil moisture is a key variable for hydrological planning. In the research area, increasing soil moisture accelerates the formation of runoff. The purpose of this study is to investigate the L-band potential of the Pulsar 2 sensor from the ALOS satellite in estimating ... Read More

Developing an Agent-Based Model for Intelligent Control of Traffic Lights and Dynamic Routing

M Akhondi; M Mesgari; M. R Malek; O Askari Sichani

Volume 9, Issue 2 , December 2017, , Pages 1-20

Abstract

Nowadays, heavy traffic is one of the major problems of living in big cities. In recent years, to overcome this problem, various solutions are proposed, many of which have been on the basis of general and comprehensive models. However, because of the essential complexity of urban environment and because ... Read More Nowadays, heavy traffic is one of the major problems of living in big cities. In recent years, to overcome this problem, various solutions are proposed, many of which have been on the basis of general and comprehensive models. However, because of the essential complexity of urban environment and because of the diversity of parameters affecting urban traffic, those models cannot represent the dynamic space of urban traffic, properly. In contrast to them, agent based approach is a promising approach for modeling of urban traffic. This is mainly because of its ability in modeling the interactions of traffic components, and in the modeling of the dynamic nature of urban environment. Much research has been made in the field of application of agent technology to the modeling of urban traffic. The majority of these researches are focused on a particular area of traffic phenomenon. Some of them are on providing traffic lights with some levels of intelligence. Others try to simulate the behavior and decision making of the drivers. In other cases, agent based modeling is used for simulation of dynamic vehicle routing systems using real-time traffic information. Nonetheless, less attention is paid to the more comprehensive modeling of traffic using intelligent agents. Therefore, in this research, an agent based model is proposed for improving the navigation of vehicles, on the basis of communicating traffic information amongst traffic components. The urban environment is modeled as a vector space. The model components include the two-way streets, intersections, traffic lights, origin and destination of cars. Environment comprises of intersections, streets between intersections, and streets between intersections and the origin/destination points. Active agents are the cars, traffic lights and traffic control center. In this agent based model, the green-red changing of traffic lights is controlled and programmed based on the traffic jam condition (number of cars) of the streets connected to the light. It is assumed that all vehicles are equipped with GPS and necessary communication media. The system is implemented using JADE platform and its class libraries. The data of a simulated traffic network is entered to the model. The main result of this study is a simple model of the basic part of the urban traffic, in which mobile vehicles and traffic lights have access to online traffic information. In this model, all three types of agents, i.e. cars, traffic lights and traffic control center, can communicate with each other. By defining some criteria, the impact of such communications and access to online information can are assessed. In other words, the results of different scenarios are evaluated using criteria such as traffic jam and average of traveling time. An important aspect of the model is that, although communicating with each other, all agents including drivers and traffic lights act and decide independently, i.e. without any centralized decision-making system. In this study, no GIS software is directly used. However, the behavior of vehicles and traffic lights are modeled on the basis of metric spatial relationships (distance calculations) and topological relations (connections of the street edges with each other and with traffic lights). In other words, in this study, a simple spatial environment and simple spatial behaviors are modeled. Spatial environment of two-way street and moving in them is represented by movements in a set of simple lines in the direction of X and Y axes. This model is the first step towards a more complete modeling of urban traffic. In this model, the spatial movements of vehicles are modeled as vectors. The lengths of these vectors are calculated using the assumed vehicle speeds, the distance between points, and simple estimations of traffic jams.

Cropland Mapping through Integration of Segmentation and Classification Techniques in Google Earth Engine

Alireza Taheri Dehkordi; Mohammad Javad Valadanzouj; Alireza Safdarinezhad

Volume 14, Issue 1 , June 2022, , Pages 1-20

https://doi.org/10.52547/gisj.14.1.1

Abstract

Map of croplands is one of the information layers required in the efficient management of these lands. Having such maps makes it possible to monitor agricultural fields during the growing season continuously. In this study, a solution to produce map of Shahrekord’s agricultural lands in two agricultural ... Read More

Applying the SAM Supervised Classification Algorithm to Prepare a Map of Rock Units Using Satellite Images

P Zeaiean Firozabadi; P Safarbeyranvand; A Hosseinhgholizade; R Hasanitabar; M Safarbeyranvand

Volume 10, Issue 1 , June 2018, , Pages 1-16

Abstract

The issue of the mapping of rock units in an ever-expanding area has now reached a point where the detection and classification of rock units is carried out through the aid of hyperspectral image. In this research, Hyperion images are used in the light of the work of previous researchers and the application ... Read More

علمی - پژوهشی

Effects of Climate Change on Vegetation Phenology of Urmia Lake Basin Using AVHRR Time Series Data

farzaneh hadadi; Davod Ashourloo; Alireza Shakiba; Aliakbar Matkan

Articles in Press, Accepted Manuscript, Available Online from 17 April 2021

https://doi.org/10.48308/gisj.2021.100998

Abstract

Climate change is one of the most important challenges facing mankind. This phenomenon has already had significant impacts on agricultural products in most parts of the world, especially arid and semiarid regions. Also, average temperature has risen in many regions in recent decades. Nowadays, in various ... Read More Climate change is one of the most important challenges facing mankind. This phenomenon has already had significant impacts on agricultural products in most parts of the world, especially arid and semiarid regions. Also, average temperature has risen in many regions in recent decades. Nowadays, in various researches, remote sensing indices are used as one of the new methods in identifying climate change. One of the important indices of remote sensing is the phonological characteristics of vegetation, which in recent studies has shown great potential in identification and estimation of vegetation. In the present study, using the 5-day normalized vegetation index (NDVI) time series of NOAA-AVHRR images and plant phenology parameters, vegetation changes in rangelands and dryland areas of Lake Urmia Basin during 1984-2013 were investigated. Climatic temperature and precipitation data was obtained from the meteorological stations of Lake Urmia basin and was compared with the results of satellite images. The results of time series analysis over thirty years of statistical period in Lake Urmia basin showed that the beginning of the growing season in Oshnavieh, Saghez and Sarab started earlier in 2013 than in 1984. But in the Maragheh area it began later. The end of the growing season in Oshnaviyeh, Saghez and Takab has ended earlier. Also, the peak growth parameter in the above mentioned vegetation reached its maximum value earlier. The length of the growing season has been decreased in the cities of Oshnavieh, Maragheh and Saghez, respectively. The results of statistical analysis obtained from satellite images and climatic data showed that changes in phonological parameters are location dependent and also decreased and increased in cold nights and hot days at the beginning of the growing season, respectively. But at the end of the growing season, the warm days have increased. These changes increased the slope of the plant growth phenology curve at the time of plant aging and ultimately reduced the length of the growing season.

علمی - پژوهشی

A new forecasting approach using the combination of machine learning to predict flood susceptibility (case study: Karun catchment)

Bhareh gharedaghy; amir ghasemzadeh

Articles in Press, Accepted Manuscript, Available Online from 15 October 2022

https://doi.org/10.48308/gisj.2022.102813

Abstract

Due to its high environmental diversity, Iran has a high rank in crises caused by natural disasters. Flood as one of the natural disasters, following the rapid growth of cities and climate changes in many regions, has caused severe social and economic, health and environmental damage. For this reason, ... Read More

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علمی - پژوهشی

The advances, challenges and perspectives in the correction field of free Night light satellite image

Fatemeh Ahmadi; yasser Ebrahimian Ghajari; Abbas Kiani

Articles in Press, Accepted Manuscript, Available Online from 15 November 2022

https://doi.org/10.48308/gisj.2022.102886

Abstract

Abstract: Remote sensing provides a powerful data source for mapping urban areas and monitoring urban dynamics on various scales. Among remote sensing data, images taken at night provide an effective way to monitor human activities on a global scale. Because the features and capabilities of these images ... Read More Abstract: Remote sensing provides a powerful data source for mapping urban areas and monitoring urban dynamics on various scales. Among remote sensing data, images taken at night provide an effective way to monitor human activities on a global scale. Because the features and capabilities of these images can enable separating urban areas and other human activities, the main feature of which is the use of light at night by accurately measuring the location, from the background without light. Via providing uninterrupted and continuous monitoring from the night world perspective, these images provide valuable source and results of human activities from the past to the present; the time series analysis of this data is highly valuable for discovering, estimating and monitoring social and economic dynamics in countries, especially sub-regions where there are no official statistics. With the development of night data satellite sensors in recent years and new research conducted in the field of night-time data, this study aims to review the advances in night-time sensors, introduce the existing data and products, review and express the advantages and disadvantages of each one and review methods and solutions presented in previous research for solving the existing problems and limitations in order to improve these images. Therefore, according to the reviews of 225 articles on night light from various credible journals, the results demonstrated that 65% of the available articles were from night light data in the urban field (59% related to urban dynamics extracting and studying and 6% for population surveys) and 35% for non-urban field (17% for energy consumption, 13% for economic issues and 5% for other issues such as pollution) in a more detailed look. Articles that have tried to provide methods for correcting night images can be categorized as follows: in the DMSP-OLS data, 44% of the articles were urban surveys, 14% were for economic purposes, 38% for the general purpose of correction and 4% for other purposes. Visible and infrared imaging radiometer suite (VIIRS) data were 57% for economic purposes, 36% for urban surveys and 7٪ for other purposes. The results and findings of this study can provide a general overview for researchers to familiarize and understand the trends of various studies in the use of night light data. It can also help researchers choose the right data and algorithm according to their purpose and study field.

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علمی - پژوهشی

Monitoring the changes of vegetation phenological cycles in Ahvaz city using remote sensing images

morteza Sharif; S Attarchi

Articles in Press, Accepted Manuscript, Available Online from 16 November 2022

https://doi.org/10.48308/gisj.2022.102890

Abstract

The phenological cycle of plants plays an important role in the global carbon cycle. Considering the importance of the role of plants in the urban ecosystem and its role in the health of socity, it is necessary to study and monitor the phonological cycle of plants in different seasons of the year in ... Read More The phenological cycle of plants plays an important role in the global carbon cycle. Considering the importance of the role of plants in the urban ecosystem and its role in the health of socity, it is necessary to study and monitor the phonological cycle of plants in different seasons of the year in urban areas at different spatio-temporal scales In this study, the two widely used NDVI and EVI indices calculated from OLI sensor of landsat satellite and MOD13Q1 product of MODIS sensor images were used to investigate the plant phenology cycle in Ahvaz metropolitan area from the period 2015 to December 2019. In this research, satellite images were retrieved and prepared through the Google Earth Engine platform. Then, according to the type of vegetation, the phenological cycle of the plants was obtained based on the vegetation indices and compared with the phenological cycle obtained from the ground surveys. Due to the possibility of noise and pixels with spectral mixing, Savitzky-Golay filter was used to smooth the phenological cycle of plants. The results show the increasing trend in the values of both NDVI and EVI indices by 0.03 and 0.04 in the OLI sensor and 0.01 in the MOD13Q1 product (annually), respectively. These changes were positive in January, March, October, November and December on both sensors. Differences were observed in both sensors during plant phenology phases. The largest difference between two sensors was observed in 2018 and 2019. This shows, in case the weather provides better condition, the plant chlorophyll content will increase. This will lead to the difference between the results of both sensors. The growing season transition periods obtained from the OLI sensor showed more detail than the MODIS medium resolution dataset. The MODIS sensor shows the growing season period start earlier than the OLI sensor. In general, according to the MODIS product, the duration of the growing season (between the beginning of the growing season (mid-winter) and the end of growing season (EOS) (early summer) is four-month. The lowest difference between the periods of the growing season of plants with ground observations in OLI and MODIS sensors, was 7 and 10 daye for Start of growing season (SOS), respectively. The biggest defference was observed at the peak of the growing season with 20 and 35 days, and for the end of growing season (EOS), 20 days later and 20 days earlier, respectively, according to ground observations. However, the length of growing season (LOS) in the OLI sensor is about five months. That the results of OLI sensor are closer to ground observations.This difference is due to the increase in heterogeneous conditions in the target phenomena and/or the spatial resolution of the MODIS sensor images. It is concluded that, the results of the OLI sensor improve our understanding of human interactions with natural environment in urban areas. Therefore, addressing them in future studies can mitigate many environmental challenges and provide more realistic information for planning.

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علمی - پژوهشی

Optimizing the results of ML-Based GMDH algorithm in order to increase the accuracy of dust detection and horizontal visibility depth through TLBO algorithm

مهدی Amiri; Farzad Amiri; Mohammad Hossein Pourasad; Seyfollah Soleimani

Articles in Press, Accepted Manuscript, Available Online from 23 November 2022

https://doi.org/10.48308/gisj.2022.102900

Abstract

Clean air quality, as one of the most essential needs of living organisms, has been compromised by natural and artificial activities. Dust storms have been constantly increasing in recent years, which have resulted in countless social, economic and environmental health damages for residents of southern ... Read More

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علمی - پژوهشی

Spatial analysis and modeling of Covid-19 outbreak using spatial regression techniques

Somayeh Rafati alashti; Abozar Ramezani; Alireza Sadeghinia

Articles in Press, Accepted Manuscript, Available Online from 26 November 2022

https://doi.org/10.48308/gisj.2022.102903

Abstract

The Covid-19 pandemic is considered as a geographical phenomenon, so spatial analysis and its geographical impact on decision-making are very important. Geographic information system and spatial analysis can play an important role in analysis of the spread of Covid-19 at the global level. This study ... Read More

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علمی - پژوهشی

Classification of Hyperspectral Images Using a Combination of Features Extracted from the Weighted Local Kernel Matrix of Spectral and Fractal Features

Behnam Asghari Beirami; Mehdi Mokhtarzade

Articles in Press, Accepted Manuscript, Available Online from 04 January 2023

https://doi.org/10.48308/gisj.2023.103055

Abstract

The use of spatial features to improve the classification accuracy of hyperspectral images has become popular in recent years. Various methods for spectral-spatial classification of hyperspectral images have been introduced to date, and relevant research is being conducted to develop methods with a more ... Read More

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علمی - پژوهشی

Crop mapping using a combination of Sentinel-1 and 2 images in Ardabil province

Ali shamsoddini; Bahar Asadi

Articles in Press, Accepted Manuscript, Available Online from 25 January 2023

https://doi.org/10.48308/gisj.2023.103095

Abstract

Identifying and mapping crops provides important information for managing agricultural lands and estimating the area under cultivation of crops. This study investigates the importance of red edge bands for segregation of crops including wheat, barley, alfalfa, beans, broad beans, flax, corn, sugar beet ... Read More

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Original Article

Identifying Spatial and Temporal Patterns of Urban Activities Using Mobile Phone Data

Hanieh Zhendeh Khatibi; Afshin Shariat Mohaymany; Matin Shahri

Articles in Press, Accepted Manuscript, Available Online from 25 January 2023

https://doi.org/10.48308/gisj.2023.103097

Abstract

Recently, the use of big data from mobile devices has received considerable attention in transportation studies. The need to do activities is the main inducement for urban trip generation. In addition, urban activities and their patterns vary over space and time. Mobile phone data, as a kind of continuous ... Read More

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علمی - پژوهشی

Potatoes fields mapping based on the phenology feature and Support Vector Machine utilizing Google Earth Engine platform

Salman Goodarzdashti; Mohamad Seifi; Mahshid Kohandel; Davoud Ashourloo; Hossein Aghighi

Articles in Press, Accepted Manuscript, Available Online from 06 February 2023

https://doi.org/10.48308/gisj.2023.103148

Abstract

Potatoes are the fourth most cultivated crop worldwide. Regarding the strategic role of this crop in food security, accurate potato mapping provides essential information for national crop censuses and potato yield estimation /prediction at any scale. Although remote sensing (RS) approaches based on ... Read More Potatoes are the fourth most cultivated crop worldwide. Regarding the strategic role of this crop in food security, accurate potato mapping provides essential information for national crop censuses and potato yield estimation /prediction at any scale. Although remote sensing (RS) approaches based on optical and/or microwave sensors have been widely employed to monitor cultivated land (including crop area, type, condition, and yield forecasting), the identification of potato planting areas using RS data has not been much addressed. Hence this study addresses the literature gap by suggesting an effective potato mapping approach that uses the time series of the Sentinel-2 (S2) images, Google Earth Engine (GEE) platform and machine learning methods. Since most crops have specific spectral and temporal characteristics during the growing season, this research has presented a method to discriminate potato fields from other crops using time series images without explicit thresholding. We employed 1648 ground truth data to optimize, train, and evaluate the model at the study site, which includes potatoes and other fields. A handheld GPS receiver was used to collect these data. The performance of this approach is evaluated by conducting a set of experiments in Hamedan and Bahar cities, as the regions grow more potatoes than any other places in Iran. Accurate identification of potato fields was completed by extracting the required features, namely the potato phenology feature and NDVI medians, from the time series of the S2 satellite bands. After that, these features were utilized as the input parameters to Support Vector Machine (SVM) technique. In order to train the most optimal SVM model using RBF kernel, Gamma and C values were optimized with the help of the 5-fold cross-validation method. These values were then employed during the algorithm's implementation on GEE platform. The estimated overall accuracy and Kappa coefficient are 90.9% and 0.82 for Hamedan and 93.3% and 0.87 for Bahar, respectively. The results of this research indicate the efficiency of SVM technique in potato acreage mapping. Moreover, the selected features such as potato phenology feature can be considered as discriminating features for improved identifying of crop farms.

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علمی - پژوهشی

Comparison of four PLSR, RF, GRNN and SVR algorithms to estimate sugarcane sheath moisture during growing season using Sentinel-2 satellite imagery

maryam soltanikazemi; Saeid Minaei; Hossein Shafizadeh Moghadam; AliReza Mahdavian

Articles in Press, Accepted Manuscript, Available Online from 08 February 2023

https://doi.org/10.48308/gisj.2023.103163

Abstract

Sheath moisture is an important parameter during the growth period of sugarcane, which is of special importance from the perspective of water stress and field irrigation management. Remote sensing data has a high capacity to update crop growth monitoring systems. In this regard, satellite images that ... Read More

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علمی - پژوهشی

Modeling the spatial distribution of Dengue fever disease in Iran using Maxent entropy model and Genetic Algorithm

Mohammad Karimi; Sajjad Haghi; Ahmad ali Hanafi Bojd

Articles in Press, Accepted Manuscript, Available Online from 07 March 2023

https://doi.org/10.48308/gisj.2023.103268

Abstract

Dengue fever is Chickenpox is a contagious and viral disease that is transmitted by two species of Aedes Egyptian mosquitoes and Aedes albopicus mosquitoes and is spreading rapidly in the world. The main purpose of this study is to model the spatial distribution of carriers of this disease in Iran. Due ... Read More Dengue fever is Chickenpox is a contagious and viral disease that is transmitted by two species of Aedes Egyptian mosquitoes and Aedes albopicus mosquitoes and is spreading rapidly in the world. The main purpose of this study is to model the spatial distribution of carriers of this disease in Iran. Due to the lack of sufficient carrier data in the country, carrier data available worldwide and also in Asia, in two different scales were used. Among the most important aspects of this research, we can name the use of heterogeneous layer as an auxiliary factor to analyze the presence points and reduce spatial autocorrelation and the use and comparison of two species distribution models based on presence data for Selecting the optimal modeling method. In this regard, first, using the maximum entropy method (MaxEnt) and a type of genetic algorithm called GARP (GARP), the level of habitat suitability in the world with a spatial resolution of 5 km for both species was modeled. To evaluate the mentioned models, the variables of population density, climate, vegetation density, altitude and soil organic carbon were considered. Due to the high accuracy of the MaxEnt method, using this method, the habitat suitability of the Asian continent with a resolution of 900 m was modeled for both species. The values under the curve (AUC) for the two types of carriers were calculated to be 0.9. The results showed that the northern and southern provinces of the country have higher habitat suitability for both species, with the difference that Aedes aegypti species in the southern to eastern parts of the Oman Sea coast has a higher probability of distribution. In implementing the MaxEnt method for Aedes albopicus, the provinces in western Iran were also identified as desirable, which was not properly modeled on a smaller scale. In February 2016, unfortunately, a small number of mosquitoes and AIDS mosquito eggs were discovered in Bandar Lengeh, which was exactly what this research had predicted. The results of this study can be used in line with planning for population management of these vector insects to control the disease at the same time as monitoring populations during epidemic seasons.

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علمی - پژوهشی

Evaluation of the effect of drought on vegetation in Iran using satellite images and meteorological data

samad khosravi yeganeh; mostafa karampour; Behrouz Nasiri

Articles in Press, Accepted Manuscript, Available Online from 18 April 2023

https://doi.org/10.48308/gisj.2023.103394

Abstract

In the coming years, drought is one of the potential threats to low rainfall countries, especially Iran. Iran has always faced big and small droughts. The geographical location and natural conditions of the country are such that severe and weak droughts have occurred in it. Evaluating the effects of ... Read More

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علمی - پژوهشی

An Improved Approach for Spectral-spatial Classification of Hyperspectral Images using Weighted Genetic and Neural Network Algorithms

Davood Akbari; Ali Ashrafi; Mostafa Yaghoobzadeh

Articles in Press, Accepted Manuscript, Available Online from 18 April 2023

https://doi.org/10.48308/gisj.2023.103395

Abstract

The Hyperspectral remote sensing technology has many applications in classifying land covers and studying their changes. With recent developments and the creation of images with high spatial resolution, the simultaneous use of spectral and spatial information in the classification of hyperspectral images ... Read More

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علمی - پژوهشی

Building Detection with Special Roofing in Hyperspectral Images using Marker-based Hierarchical Algorithm

Davood Akbari

Articles in Press, Accepted Manuscript, Available Online from 25 April 2023

https://doi.org/10.48308/gisj.2023.103401

Abstract

The complexity and large volume of data from hyperspectral sensors have led to the consideration of more specialized and advanced methods of data analysis in order to extract information. One of the analyzes performed on hyperspectral images is target detection. With recent developments and the creation ... Read More

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علمی - پژوهشی

Investigating the trend of night temperature changes in Iran and the effect of carbon dioxide

Sajedeh Morady; Majid Rezaeibanafsheh

Articles in Press, Accepted Manuscript, Available Online from 31 May 2023

https://doi.org/10.48308/gisj.2023.103545

Abstract

In this article, night temperature changes in relationship with CO2 emissions in Iran were studied using AIRS satellite images and time series graphs, regression, correlation and Mann-Kendall tests and maps. This research was conducted for the statistical period of 2003-2016 and the months of January, ... Read More

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علمی - پژوهشی

Using network analysis process model and fuzzy techniques in order to determine the optimal range of construction of 63.20 kV substation in GIS platform

Abolfazl Habibitabar; sahar Alian; Davoud Soleimanian

Articles in Press, Accepted Manuscript, Available Online from 20 June 2023

https://doi.org/10.48308/gisj.2023.103606

Abstract

The energy injection point from the transmission network to the distribution network is the 63.20 kV substations. Determining the location of the substation is technically and economically important for regional electricity companies and electricity distribution companies. The purpose of this research ... Read More

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علمی - پژوهشی

Evaluation of classical statistical methods for estimating and reconstructing the daily temperature in Iran

Mohammad Khaledi; Ghasem Zarei

Articles in Press, Accepted Manuscript, Available Online from 24 July 2023

https://doi.org/10.48308/gisj.2023.103725

Abstract

In order to be able to make decisions and manage in the field of sustainable development of natural resources, knowledge of climatic parameters is one of the most important and effective topics of this matter. Meanwhile, the temperature parameter, as one of the most influential climate parameters, plays ... Read More

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علمی - پژوهشی

Modeling the concentration distribution of NO2 and O3 pollutants with an appropriate spatial resolution by combining ground and satellite data.

Amir Hadian; Mina Moradizadeh

Articles in Press, Accepted Manuscript, Available Online from 24 July 2023

https://doi.org/10.48308/gisj.2023.103726

Abstract

Air pollution is one of the most important crises that most countries are facing today due to the progress of industry and technology. The country of Iran and especially the city of Tehran is not exempt from this phenomenon. Air pollution measurement stations at city level, in spite of the high accuracy ... Read More

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علمی - پژوهشی

Identifying and monitoring urban growth and expansion changes using spectral un-mixing of remote sensing imagery and geographic information systems techniques at the micro level, (A case study of Amol city)

Sedigheh Lotfi; Toheed Alizadeh

Articles in Press, Accepted Manuscript, Available Online from 24 July 2023

https://doi.org/10.48308/gisj.2023.103727

Abstract

Land is a vital natural resource for human survival and the basis of all ecosystem services. However, land degradation in the form of land use and land cover changes has been a severe problem in the world. Rural-to-urban migration in developing countries, as well as the conversion of many nearby villages ... Read More

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علمی - پژوهشی

Sensitivity analysis of the spectral response of the plant leaf to the biophysical-biochemical variables using the PROSPECT radiative transfer model

Elaheٍ Akbari; M Hajeb; Mehrdad Jeihouni; Saeid Hamzeh

Articles in Press, Accepted Manuscript, Available Online from 24 July 2023

https://doi.org/10.48308/gisj.2023.103728

Abstract

To determine the effect of the leaf biochemical contents on its spectral reflectance behavior via remote sensing (RS) can help to understand the process of the ecosystem and its parameters such as plant water stress. The present study aimed to do a quantitative analysis of the effect of leaf parameters, ... Read More

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علمی - پژوهشی

Evaluation of environmental criteria affecting citizens' health using geographic information system (case example: Agheh Zaman neighborhood of Sanandaj city)

Mir Saeed Moosavi; Aida Ghafoori; Mahsa Faramarzi Asl

Articles in Press, Accepted Manuscript, Available Online from 17 October 2023

https://doi.org/10.48308/gisj.2023.231601.1157

Abstract

The problems in urban life, such as the diminution of the role of the environment as a place for the presence of citizens and their physical activity, the increase in vehicles and as a result inactivity and the increase in non-communicable diseases, have caused the concern of the world community about ... Read More The problems in urban life, such as the diminution of the role of the environment as a place for the presence of citizens and their physical activity, the increase in vehicles and as a result inactivity and the increase in non-communicable diseases, have caused the concern of the world community about public health. The aim of the research is to evaluate subjectively and objectively the environmental criteria affecting the general health of the residents in three physical, psychological and social dimensions in Agha Zaman neighborhood of Sanandaj city. The collection of subjective and objective research data was done sequentially in terms of time, in this regard, four phases of the research were defined. The first phase is the subjective qualitative assessment of the residents regarding their mental and social health, the second phase is the collection of quantitative subjective data of the residents regarding their physical health, the third phase is the quantitative objective assessment of the environment, and the fourth phase is the examination of the correlation between the research variables. Subjective data was obtained using a questionnaire and objective data was obtained using a geographic information system. To analyze the relationship between neighborhood environmental criteria and physical activities and to determine the relationship between variables, regression analysis was used in SPSS software. Objective data such as the type of block arrangement and the example of the spatial pattern of the neighborhood, the land use layer and the road network, etc., were calculated by the geographic information system and entered into the index of space syntax to determine the pedestrianization of the neighborhood. Finally, the relationships and effects of environmental criteria on public health have been identified using regression analysis in Lisrel software. The results showed that the two measures of comfort and tranquility of the environment with a score of 23 and social interactions and neighborhood culture with a score of 21 respectively have the greatest impact on mental and social health. Also, environmental criteria such as mix of uses with a score of 5.671, visual and aesthetic qualities with a score of 7.961, and special infrastructure for pedestrians and bicycles with a score of 8.475 have the greatest impact on physical work, leisure and sports activities, respectively. As a result, they have physical health. According to the obtained data, Namaki Street with a score of 21 has the highest level of connection and interconnection, depth and control with the whole neighborhood and has the highest level of pedestrian circulation in the neighborhood. The general results show that due to the direct impact and relationship of environmental criteria of urban design on physical activities and on the other hand, the existence of a positive and meaningful relationship between physical activities and general health, it was found that the general health of residents is related to the environmental criteria of urban design. Yes, but this relationship does not happen directly but with the intervention of physical activities.

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علمی - پژوهشی

Spatial Monitoring of Drought Using Indicators of Remote Sensing, case study: Sistan and Baluchestan Province

کمال امیدوار; massumeh nabavi zadeh

Articles in Press, Accepted Manuscript, Available Online from 17 October 2023

https://doi.org/10.48308/gisj.2023.231123.1156

Abstract

Due to the statistical limitations of the data of the Grace satellite, a common time period of 16 years was chosen from 2002 to 2017. Two indices VHI and TSDI were obtained a high correlation in the south, center and some areas of the north. Finally, results of the research were validated by GLDAS ... Read More

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Original Article

Land use change detection based on satellite images in the Haraz watershed plain

Fatemeh Shokrian; Karim Solaimani

Articles in Press, Accepted Manuscript, Available Online from 27 November 2023

https://doi.org/10.48308/gisj.2023.232979.1176

Abstract

Investigating land use changes requires the integration of layers in a certain period. This research aims to investigate land use changes in Haraz Plain from 1980 to 2021. Therefore, Landsat data was used to measure the changes. By applying atmospheric, geometric and radiometric corrections, image enhancement ... Read More

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Seismic hazard assessment using arithmetic-weighted overlay method based on earthquake potential index (EPI), the southwestern Iran

sasan motaghed; amin nakhlian; lotfolla emadali; nasrolla eftekhari; heshmatalla mahmoudian

Articles in Press, Accepted Manuscript, Available Online from 29 November 2023

https://doi.org/10.48308/gisj.2023.229646.1133

Abstract

In this study, an integrated geographic information system (GIS) has been used to assess the seismic hazard in the southwestern region of Iran. In data preparing, the important factors in earthquake hazard were identified and relevant thematic data layers including digital elevation model (DEM), the ... Read More

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علمی - پژوهشی

Estimating the runoff coefficient by combining Arc CN-Runoff, SCS-CN and ICAR empirical relationship (Case study: Selseleh Study area - Lorestan province)

yazdan yarahmadi; hojatolah younesi; Ahmad Godarzi; saeed rostami

Articles in Press, Accepted Manuscript, Available Online from 29 November 2023

https://doi.org/10.48308/gisj.2023.228883.1120

Abstract

Determining the value of the runoff coefficient is one of the biggest problems and the main source of uncertainty in many water resources projects. The aim of the current research is to estimate the runoff coefficient by combining Arc CN-Runoff, SCS-CN and ICAR experimental relationship in the Selseleh ... Read More Determining the value of the runoff coefficient is one of the biggest problems and the main source of uncertainty in many water resources projects. The aim of the current research is to estimate the runoff coefficient by combining Arc CN-Runoff, SCS-CN and ICAR experimental relationship in the Selseleh watershed. Selseleh Study area is located in the north of Lorestan province and is one of the sub-watersheds of Kashkan. In order to carry out this research, data including digital elevation model information, land use classes, soil texture and meteorological and hydrological statistics (rainfall and runoff) related to the research area were used. The map of the land use layer and soil hydrological groups was entered into the Arc CN-Runoff tool environment, and Intersect was applied on two layers the Land soil layer was prepared, and the runoff coefficient map was prepared based on this layer. Finally, the runoff coefficient was estimated in three conditions dry, medium and wet moisture conditions and a comparison was made. The results of the research showed that the runoff coefficient (CR) in the Selseleh Study area is 0.26, 0.53, and 0.77, respectively, in dry, medium, and wet conditions. Therefore, the dry humid state has decreased by 68% compared to the average, and the more humid state has increased by 37% compared to the average. Investigating the correlation between the runoff coefficient and watershed characteristics showed that the runoff coefficient is influenced by the six physiographic features of the Study area: area, slope, length of the waterway and Gravelius coefficient, the maximum height and density of the waterway, which has a significant effect on the value of the runoff coefficient in this Study area. The value of the runoff coefficient in the ICAR method for the entire Study area was 0.48. In the Selseleh Study area, the runoff coefficient has a decreasing trend from April to September. The type of land and soil use in the basin under study is one of the influential factors that affect the runoff coefficient and, consequently, the peak discharge of the Study area. Also, in early spring, the flood potential is high in the said Study area. Among the measures to increase water infiltration are the establishment of a rainwater collection system and the operation of the Farrow meter along with the increase of plant cover with seeding and planting and intercropping of pasture plants.

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علمی - پژوهشی

Land use and land cover classification by combining GLCM, SNIC, and machine learning algorithms in Google Earth Engine environment (case study: part of the lands of North Mahabad, West Azerbaijan)

mahdi naderi

Articles in Press, Accepted Manuscript, Available Online from 29 November 2023

https://doi.org/10.48308/gisj.2023.233271.1181

Abstract

In recent decades, land use and land cover changes information has been successfully derived from remote sensing data at various levels, from local to global scale. Accurate and frequent monitoring of these changes is required for urban planning and sustainable management of land resources. In this study, ... Read More In recent decades, land use and land cover changes information has been successfully derived from remote sensing data at various levels, from local to global scale. Accurate and frequent monitoring of these changes is required for urban planning and sustainable management of land resources. In this study, an object-oriented approach using a combination of GLCM, SNIC, and machine learning algorithms is presented to classify the LULC of a part of the lands of North Mahabad, West Azerbaijan, in 2019 using satellite images in Google Earth Engine. For this purpose, after preparing the initial dataset, which contains the bands of Sentinel-1 and Sentinel-2 images, the ALOS digital surface model, and NDVI, BSI, SAVI, and total scattering power indices, two pixel-based and object-oriented approaches, as well as the random forest algorithm, were used to classify land use and land cover, and their results were compared to explain the best approach in terms of the accuracy of the various classes. In the object-oriented approach, textural measures were extracted by applying the GLCM matrix to the initial dataset. Due to the increase in the number of bands, the PCA method was used to reduce the dimensions of the image. Finally, by combining the segmentation layer obtained from the SNIC algorithm and the PC1 layer, the random forest algorithm was considered to produce land use and land cover maps of the study area. According to the research findings, the object-oriented approach performed better than the pixel-based approach in classifying various land use classes in the study area, with an overall accuracy and kappa coefficient of 86.40% and 0.8307, respectively, compared to 82.73% and 0.8028. The results of the accuracy evaluation criteria showed that the producer accuracy of most of the classes except for corn, fall irrigated vegetables, and wheat, and barley irrigated in the object-oriented approach was higher than the pixel-based method, and their classification accuracy was more than 90%. Additionally, water, build-up, corn, and sugar beet classes have the highest user accuracy in the object-oriented LULC map. The findings showed that the appropriate determination of the super-pixel size of the SNIC clustering algorithm and the use of GLCM texture criteria effectively improved the performance of the proposed approach in land use and land cover classification.

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Modeling land use/cover change with an emphasis on artificial land growth using a combination of CA-Markov model and multi-criteria decision analysis based on GIS (Case study: Aras River watershed)

Masoud minaei; sadegh boulaghi; hanieh afsahi

Articles in Press, Accepted Manuscript, Available Online from 08 January 2024

https://doi.org/10.48308/gisj.2024.233751.1186

Abstract

In recent years, the global population growth and urban expansion have led to significant changes in land use and land cover. This process has numerous detrimental consequences, such as increasing surface temperature, deforestation, desertification, degradation of ecosystem services, biodiversity loss, ... Read More In recent years, the global population growth and urban expansion have led to significant changes in land use and land cover. This process has numerous detrimental consequences, such as increasing surface temperature, deforestation, desertification, degradation of ecosystem services, biodiversity loss, and threats to food security. Therefore, monitoring and modeling these changes are essential to enable optimal land management and sustainable utilization of natural resources. Considering that the Aras River Basin has undergone significant transformations over time, particularly in terms of human-made land developments, the focus of this research is on modeling land use/land cover changes in this area. Initially, land use maps for the region were extracted for the years 2000 and 2020 from the Globeland30 project of the China National Geomatics Center. Subsequently, two maps were prepared to illustrate the potential growth of human-made land based on the scenario of land development. This was achieved using advanced decision-making analysis methods based on GIS, including BWM (Best-Worst Method) and MEREC (Multi-objective Evaluation of the Regional Ecosystem Carrying Capacity). Finally, these two maps, along with the land use maps, were combined to form the input for the CA-Markov model. The modeling process was carried out once using the BWM + CA-Markov combination, and again using the CA-Markov + MEREC combination for the year 2040. The examination of the results demonstrated that in the output of the combined BWM + CA-Markov model, the extent of human-made land increased from 603 square kilometers in 2020 to over 930 square kilometers in 2040. Meanwhile, this figure was approximately 829 square kilometers in the output of the MEREC + CA-Markov model. Furthermore, the final results obtained from the intersection of these combined models also indicated an increase in the extent of this land from 603 square kilometers in 2020 to 930 square kilometers in 2040. The continuous growth of human-made land in this basin can lead to the destruction of environmental resources and ecosystem threats. The findings of this study provide relevant managers with valuable insights for optimal management of future conditions and the provision of necessary infrastructure.

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علمی - پژوهشی

Integration of multi-sensor data and ground observations in order to improve accuracy and spatial resolution in near-surface water vapor retrieval

Mina Moradizadeh; Mohamad Reza Talari

Articles in Press, Accepted Manuscript, Available Online from 08 January 2024

https://doi.org/10.48308/gisj.2024.230453.1146

Abstract

Atmospheric water vapor is a key parameter in modeling the energy balance on the earth's surface and plays a major role in keeping the temperature of the earth's atmosphere balanced. Retrieving of this parameter, as the most influential atmospheric parameter on the sensors received radiance, ... Read More Atmospheric water vapor is a key parameter in modeling the energy balance on the earth's surface and plays a major role in keeping the temperature of the earth's atmosphere balanced. Retrieving of this parameter, as the most influential atmospheric parameter on the sensors received radiance, is of great importance. Since the atmospheric water vapor content in the near of surface is more and its temporal and spatial changes are more intense, the measurements of ground meteorological stations, despite their high accuracy, are not generalizable due to temporal and spatial limitations and point measurements. Therefore, it seems necessary to provide practical satellite-based methods to accurate and continuous retrieval of this parameter with appropriate spatial distribution. Therefore, retrieving the near surface water vapor content with accuracy and appropriate spatial resolution is very important, and the purpose of this research is to provide four innovative and accurate methods to estimate the mass mixing ratio of near surface water vapor in Isfahan province in 1 km resolution. Different sensors measure water vapor with different resolution and sensitivities to this parameter. Thus, providing methods based on the integration of different sensor's and ground observations data is essential to simultaneously improve the spatial resolution and accuracy of water vapor retrievals. In this research, the combination of MODIS and AIRS data and ground station observations have been used. Also, the band ratio method, IDW interpolation and scaling have been used along with the proposed methods. Correcting the bias of AIRS-derieved water vapor during the scaling stage and interpolation error is on the agenda. Validation results of proposed methods show that the method based on the generalization of accurate ground-basedwater vapor observations and removing interpolation error, through integration with MODIS-derieved water vapor values, has the best performance (R2=0.55, RMSE=1.05 Gr/Kr).

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علمی - پژوهشی

Spatio-Temporal Analyses of Pedestrian Accidents Using Time Series and Differential Moran’s I, Case Study: Mashhad

Matin Shahri; Mohammad Amin Ghannadi

Articles in Press, Accepted Manuscript, Available Online from 08 January 2024

https://doi.org/10.48308/gisj.2024.228548.1112

Abstract

Pedestrians are considered as one of the most vulnerable road users due to many reasons including the lack of protective shells or being less visible to drivers, especially in low-light conditions or adverse weather and their accidents lead to many casualties or irreparable injuries. Accordingly, in ... Read More

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علمی - پژوهشی

intelligent relief using geographic information system and Internet of Things

hossein aghamohammadi; reyhaneh saeedi; Ali Asghar Alesheikh; Alireza Vafaeinejad

Articles in Press, Accepted Manuscript, Available Online from 08 January 2024

https://doi.org/10.48308/gisj.2024.229150.1128

Abstract

Intelligent emergency response during crises refers to the effort to improve the performance of emergency response units. This type of assistance is created using modern technologies, especially the Internet of Things, to enhance service quality, reduce costs, and increase supervision over the emergency ... Read More Intelligent emergency response during crises refers to the effort to improve the performance of emergency response units. This type of assistance is created using modern technologies, especially the Internet of Things, to enhance service quality, reduce costs, and increase supervision over the emergency response process. In a new approach to intelligent emergency response, IoT-based routing models are used. These models optimize the emergency response route through the communication between objects and the collection of spatial data, improving the user experience. In this study, a spatial data infrastructure is designed to integrate the system and improve emergency response. The designed portal displays the optimal route from the incident location to the medical center on a map using the desired service and transfers sensor information (such as heart rate, blood oxygen level, blood pressure, thermometer, glucose meter, electroencephalography, and pulmonary function) to the doctor's mobile phone in the ambulance via Bluetooth and shares this information on the portal. Medical centers also determine their priority using an online hierarchical weighting model. In this system, real-time health information of the injured is received through the submission and confirmation from medical centers, and based on this information, the appropriate location for treatment and transfer of the injured person is determined. In a test conducted for this model, an injured person in Tehran Zone 5 on 4/24/1400 at 12:00 noon was accepted. The emergency team arrived at the scene in less than 8 minutes and, after providing initial assistance, sent the real-time health status of the patient to the surrounding medical centers, receiving a confirmation from Omid hospital in the same area, and transferred the injured person to the hospital in 5 minutes via the optimal route. In contrast, in the traditional system, due to the lack of simultaneous use of IoT and spatial data infrastructure, suitable routing algorithms and weighting models, the emergency response process becomes time-consuming, and medical centers are not informed of real-time health information of the injured. Consequently, this research improves the performance of the emergency response system and addresses some of the issues in the traditional system, such as delays in dispatching emergency personnel and patient non-acceptance. Overall, the use of intelligent emergency response methods reduces human, financial, and time costs, provides quicker and better responses to different crises, and allows emergency organizations to make more intelligent decisions regarding resource distribution and human resource allocation using the data collected by geographic information systems and the Internet of Things.

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علمی - پژوهشی

Analysis of the relationship between form and urban access Case study: Tehran metropolis

Mohammad Soleymani lamyani; Amer Nikpour; Sedigheh Lotfi; hammed Abbasi

Articles in Press, Accepted Manuscript, Available Online from 27 January 2024

https://doi.org/10.48308/gisj.2024.233365.1183

Abstract

The form of the city is very important because it forms the basis of urban movements within itself. One of the key components of treating the quality of the urban form is access to urban activities and services. The expansion of the horizontal growth of the metropolis of Tehran in the last few decades ... Read More

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علمی - پژوهشی

Remote Sensing Data Assimilation by Forcing method in Simulation of Silage maize Yield using AquaCrop Model

Elahe Akbari

Articles in Press, Accepted Manuscript, Available Online from 05 February 2024

https://doi.org/10.48308/gisj.2024.233912.1190

Abstract

Estimation and forecast of crop yield using crop growth models is imperative to plan agricultural operations and manage crop yield. To this end, the AquaCrop model parameters were estimated and the model was calibrated with measuring and sampling different requied information of model in the crop growing ... Read More

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علمی - پژوهشی

Evaluation of soil calcium carbonate using of satellite images and NIR spectroscopy

Parinaz Abdoli; Sohayla Hashemi

Articles in Press, Accepted Manuscript, Available Online from 05 February 2024

https://doi.org/10.48308/gisj.2024.233142.1179

Abstract

One of the benefits of remote sensing and Vis–NIR are rapidity, simplicity, and low cost of analysis compared with traditional methods. The aim of this research, is to use Landsat 8 satellite sensors and near infrared spectrum in agricultural and forestry uses in Gyan Nahavand plain, Hamadan province ... Read More

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علمی - پژوهشی

A hybrid approach to the spatial information system for prioritizing the development of high-speed bus lines using the Shannon entropy and Kopras entropy model with an emphasis on the concepts of spatial justice up to the horizon of 1410 (Case Study:

Imam Baharloo

Articles in Press, Accepted Manuscript, Available Online from 05 February 2024

https://doi.org/10.48308/gisj.2024.232377.1166

Abstract

Public transportation and easy commuting in the city are one of the main aspects of urban life, and taking care of a complete, regular and developed transportation system is one of the basic needs of the city. In this respect, it is important to pay attention to the principles of "spatial justice" ... Read More Public transportation and easy commuting in the city are one of the main aspects of urban life, and taking care of a complete, regular and developed transportation system is one of the basic needs of the city. In this respect, it is important to pay attention to the principles of "spatial justice" that have been included in urban planning discussions in order to solve the inadequacies of urban management. In recent years, the city of Isfahan has experienced significant population growth and physical development in different directions. On the other hand, the results of comprehensive transportation studies of Isfahan City indicate that to provide citizens with balanced access to public transportation lines, the creation of 21 high-speed bus lines has been proposed. Therefore, the purpose of this study is to prioritize the development of high-speed bus lines by combining the Shannon, Kopras and entropy models with an emphasis on the concepts of spatial justice up to the horizon of 1410. The distinctive feature of this research is the integration of a geographic information system with spatial justice indicators in order to prioritize bus express routes for implementation. Therefore, in the first step, the status of high-speed bus lines was calculated in terms of permeability, proximity, and accessibility indicators, and the Gini coefficient and Lorenz curve of the current situation was calculated. In the second step, by calculating the Gini coefficient of each of the proposed lines separately and comparing it with the current value, the effectiveness of the proposed lines was evaluated. Secondly, the importance of the desired criteria was weighed by the Shannon entropy method. In the end, using the Kopras method, 21 proposed bus routes were prioritized for development to the 1410 time horizon. The results showed that although the Ayatollah Ghaffari terminal line to the end of Sheikh Sadouq with a length of 14.9 km is one of the medium length lines, it should be implemented considering other criteria as the first priority. Keywords: Spatial Equity, Public Transport, Shannon Entropy, Kopras, Lorenz Curve

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Investigating land use changes in Herat city using satellite images during 2015 and 2022

Mohammad Karim Sirat; Gomroki Masoomeh

Articles in Press, Accepted Manuscript, Available Online from 05 February 2024

https://doi.org/10.48308/gisj.2024.234087.1192

Abstract

Today, land use change detection in urban areas have key role in city management, resource management and city development. So, in this research the land use change detection is investigated. The purpose of this research is to investigate the land use changes in Herat using Landsat 8 satellite images ... Read More

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علمی - پژوهشی

Investigating urban vulnerability against earthquakes using GIS and BWM model (Case study: a part of the Tabriz city)

sara Beheshtifar; Siamak Bakhshali pour gavgani

Articles in Press, Accepted Manuscript, Available Online from 06 February 2024

https://doi.org/10.48308/gisj.2024.232611.1170

Abstract

Earthquake is one of the natural hazards that, due to its unexpected nature, often causes a lot of human and financial losses. Currently, there is no way to prevent earthquakes; But with strategies such as identifying vulnerable areas, the resulting damages can be reduced to some extent. In this research, ... Read More

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علمی - پژوهشی

Temporal-spatial assessment of monthly precipitation based on CHIRPS,TRMM and MERRA data in Iran

Zahra Barkhordari; Ali Shamsoddini

Articles in Press, Accepted Manuscript, Available Online from 11 March 2024

https://doi.org/10.48308/gisj.2024.234268.1194

Abstract

Due to the limitations of real precipitation measurement and the lack of proper spatial and temporal coverage of rainfall measurement in the country, remote sensing technology with high temporal and spatial resolution is considered as a useful tool for estimating the amount of precipitation phenomenon ... Read More

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علمی - پژوهشی

Identification of fire-prone areas in the vegetation of Lorestan province using remote sensing method

mostafa karampour; samad khosravi yegane; hamed heidri

Articles in Press, Accepted Manuscript, Available Online from 17 March 2024

https://doi.org/10.48308/gisj.2024.234303.1196

Abstract

IntroductionIn each region, drought conditions vary from moderate to severe and with different durations, which require continuous and operational monitoring. The longer a drought occurs, the greater its effects on vegetation and water resources, and the more severe the drought, which can limit human ... Read More IntroductionIn each region, drought conditions vary from moderate to severe and with different durations, which require continuous and operational monitoring. The longer a drought occurs, the greater its effects on vegetation and water resources, and the more severe the drought, which can limit human services and alter natural systems. The effects of drought include habitat destruction for wildlife and water quality, reduced access to water resources, etc. and as a result, disruptions such as fire incidents and other natural disasters increase. ). Vegetation in each region, especially in different regions of Lorestan province, is at risk of numerous fires every year due to the lack of rain and dryness of the environment. For this reason, the issue of revealing and identifying fire-prone areas in relation to the most important climatic element (rainfall) has been selected and carried out, which can facilitate appropriate and preventive measures to protect vegetation areas. In this research, a combined method has been used.Material and methods:In this study, an attempt has been made to investigate the drought condition of vegetation in Lorestan province by using Suomi NPP infrared images using NDVI, VCI and TCI indices. The studied period of 2013-2021 corresponds to the first of April to the end of July (week of 13-26 AD) as a weekly average. The monthly average of Standard Precipitation Index (SPI) using precipitation data, the use of monthly precipitation data from Aligoderz, Durood, Khorramabad, Borujerd, Noorabad, Kohdasht and Azna weather stations was done to analyze the precipitation situation well and separate dry and wet months from each other. become Then the correlation coefficient of SPI index with each vegetation index (NDVI, VCI and TCI) is calculated.Results and discussion:Based on the rainfall data recorded in the meteorological stations of Lorestan province, it can be said that there is no rainfall in the study area in the summer season (July, August and September) and only in the autumn, winter and spring seasons. Therefore, the water year in Lorestan province starts approximately from the third decade of September and continues until the second and third decade of June every year. This indicates the very dry air and lack of humidity. Dry air or lack of humidity and increase in temperature provide the necessary conditions for causing fire in the province. In this article, they put a dry season in the summer season of Lorestan province and August is the driest month of the year.ConclusionThe results of this research showed that the vegetation in Lorestan province is always facing the risk of fire and this is very high in the years when there is a lack of rainfall, in different months. It was proved that if there is a lack of rainfall in the first months of the water year, there is a risk of vegetation fire even in the cold months of the year, and this risk increases significantly in the hot months of the year, which is the case in 2021. there have been. SPI calculations showed that the months of July, August and September are negative in Lorestan province. The results show that the best indicator is based on satellite images for monitoring vegetation drought and fire risk in the study area (TCI). In the years 2013 and 2015, the highest fire risk occurred in the western and central regions of Lorestan province. In 2021, the most severe fire risk has occurred in vegetation in the studied area. Due to the large changes and dispersion of vegetation indicators effective in the occurrence of fires in terms of time and place, Spearman's non-parametric correlation has been used.Keywords: Vegetation fire, drought , precipitation, infrared images, Lorestan province

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علمی - پژوهشی

Preparation of distribution and health map of afforestation in Langroud County using Sentinel-2 sensor images and field data

fatemeh ahmadloo; saeede Eskandari; mahmood Bayat; Mehrdad Mirzaei; Shahryar Sobh Zahedi; Amin Nasrollahian

Articles in Press, Accepted Manuscript, Available Online from 23 April 2024

https://doi.org/10.48308/gisj.2024.234675.1202

Abstract

Monitoring the current status of existing afforestation’s in management decisions is very important for the development of afforestation’s in the future. This study was conducted in order to monitor the area, distribution and health of afforestation’s in Langroud county, Guilan province. ... Read More Monitoring the current status of existing afforestation’s in management decisions is very important for the development of afforestation’s in the future. This study was conducted in order to monitor the area, distribution and health of afforestation’s in Langroud county, Guilan province. For this purpose, first, field surveys were done in the form of land points from the existing afforestation, and the distribution map of afforestation was prepared using the land surveys, GPS Fields Area Measure PRO application (GFAMP), and Google Earth system. Then the Sentinel 2 satellite image related to the growing season in Langroud county was prepared from the Copernicus site. From the Sentinel 2 satellite images, various vegetation indices such as NDVI, TNDVI, SAVI and RVI related to the growing season were extracted and their maps were prepared in the area of afforestation. In the following, the amount of each vegetation index studied was extracted at the points of land harvesting and the correlation of the values of each vegetation index (resulting from satellite images of the growing season of Sentinel 2) with the health of afforestation (resulting from field harvesting) was investigated. For this purpose, Pearson's correlation coefficient was used. Then, the index that showed the highest correlation with the health of afforestation in Langroud county (NDVI) was selected as the most important index to estimate the health of afforestation and its regression relationship with the health of afforestation was obtained. In the following, using the map of the most favorable vegetation index, information of field harvests and the relationship between these two cases, a health map of afforestation in Langroud county was prepared. The results showed that the area of afforestation in this county is 746.2 ha, which are mainly distributed in the southwest of the county. In addition, the results showed that the Normalized Difference Vegetation Index (NDVI) is the most favorable vegetation index for estimating the health of afforestation in Langroud county. Of the current total area of afforestation, 400.56 ha are in full health status, 305.60 ha are in medium health status, and 40.04 ha are in unhealthy status. The results of this research will help the forest managers for quantitative and qualitative monitoring of afforestation and its continuity in certain time periods as well as future afforestation development plans.The results showed that the area of afforestation in this county is 746.2 ha, which are mainly distributed in the southwest of the county. In addition, the results showed that the Normalized Difference Vegetation Index (NDVI) is the most favorable vegetation index for estimating the health of afforestation in Langroud county. Of the current total area of afforestation, 400.56 ha are in full health status, 305.60 ha are in medium health status, and 40.04 ha are in unhealthy status. The results of this research will help the forest managers for quantitative and qualitative monitoring of afforestation and its continuity in certain time periods as well as future afforestation development plans.n addition, the results showed that the Normalized Difference Vegetation Index (NDVI) is the most favorable vegetation index for estimating the health of afforestation in Langroud county. Of the current total area of afforestation, 400.56 ha are in full health status, 305.60 ha are in medium health status, and 40.04 ha are in unhealthy status. The results of this research will help the forest managers for quantitative and qualitative monitoring of afforestation and its continuity in certain time periods as well as future afforestation development plans.Of the current total area of afforestation, 400.56 ha are in full health status, 305.60 ha are in medium health status, and 40.04 ha are in unhealthy status. The results of this research will help the forest managers for quantitative and qualitative monitoring of afforestation and its continuity in certain time periods as well as future afforestation development plans.n addition, the results showed that the Normalized Difference Vegetation Index (NDVI) is the most favorable vegetation index for estimating the health of afforestation in Langroud county. Of the current total area of afforestation, 400.56 ha are in full health status, 305.60 ha are in medium health status, and 40.04 ha are in unhealthy status. The results of this research will help the forest managers for quantitative and qualitative monitoring of afforestation and its continuity in certain time periods as well as future afforestation development plans.

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علمی - پژوهشی

Mineral mapping related to porphyry copper deposits using Aster and Sentinel 2 images with field studies (A Case study of Sahib Divan copper deposit)

Seyedeh Narges Sadati; Mahsa Fahmi; gholamreza Ahmadzadeh

Articles in Press, Accepted Manuscript, Available Online from 23 April 2024

https://doi.org/10.48308/gisj.2024.234278.1195

Abstract

The studied area is located in the structural zone of Alborz-Azerbaijan and on the sheet 1:100000 of Lahrud. In some areas, intrusive bodies with a combination of granodiorite and quartzdiorite with Oligocene age have penetrated into the volcanic rocks, and in the central parts around the village of ... Read More The studied area is located in the structural zone of Alborz-Azerbaijan and on the sheet 1:100000 of Lahrud. In some areas, intrusive bodies with a combination of granodiorite and quartzdiorite with Oligocene age have penetrated into the volcanic rocks, and in the central parts around the village of Qaragol and in the southwest of the region, in the area of Sahib Divan and Doust Biglo, they are the agent of extensive hydrothermal alteration (kaolinite), siliceous and alunite in upper Eocene latitic rocks. In order to introduce training samples after geological surveys, 13 samples from the Sahib Divan analyzed by XRD method. The areas that were representative of the major alterations and the pixels corresponding to them in satellite images were selected as training samples for the base spectrum methods. In the study area, the MNF results were extracted from Aster and sentinel 2A data and used in the classification of the base spectrum and using the software spectral library and training samples from the altered areas of the three minerals kaolinite, muscovite and chlorite respectively was used as indicators for argillic, phyllic and propylitic alteration. The interesting result obtained from this research was highlighting the alteration in the images of the Aster of Sahib Divan mine, which indicated the simultaneous presence of argillic and phyllic alteration in the center and its enclosure with propylitic alteration, which is consistent with the conventional pattern of porphyry deposits. Also, the analysis of Sentinel images showed that hematite, jarosite, goethite and limonite show strong absorption characteristics in the VNIR region and this sensor has been more successful in identifying them. The resulting products were also compared with the published geological map of the studied area and the findings have shown that the resulting maps support the conceptual geological model in the porphyry copper deposit.In the present study, the Aster and Sentinel-2A MSI datasets from the 1:100,000 sheet of Lahrud have been examined with a special attitude to Sahib Divan mine. The main goal of this study is to create a new method by considering remote sensing data, especially Aster and Sentinel 2, in identifying alterations associated with porphyry copper deposits. This identification was based on two approaches: identification of hydrothermal alteration zones associated with porphyry copper deposits (through spectral library) and direct identification of alteration zones and copper-bearing minerals (through direct sampling of the deposit site and using it as a training pixel). In this research, taking into account that the purpose of exploring porphyry copper deposits, acidic to intermediate igneous rocks in which extensive argillic, phyllic, and propylitic alteration had occurred, special attention was paid to alunitic, silicic, and iron oxide alteration. Recent technological advances in the field of spectral/spatial resolution of satellite data in classification algorithms have created interesting opportunities and solutions for geological mapping. Therefore, after taking the geology and conducting XRD studies, base spectrum mineralogical mapping methods such as BE, LSU, CEM were used, among which the BE method gave the best result for separating the target pixels, especially for detecting different types of changes related to porphyry copper deposits. It was shown using training pixels on Aster's images. Although Sentinel images did not achieve satisfactory results for clay minerals due to low spectral resolution in the short infrared range, they were favorable for separating iron-containing minerals such as hematite, jarosite, and goethite, and by using a color combination, it was concluded that it shows the presence of hematite and jarosite at the same time. The results of the investigation of the intrusive masses of the 100000 sheet of Lahrud, siliceous veins and the spread of faults and deformations show that, in general, the extensive altreation in the central part (Salavat and Niaz Qoli-Mashiran) and the southwest of the study area (Saheb Divan and Dust Biglo) is significant. The products obtained from the processing were compared with the published geological map of the studied area and it was shown that the resulting maps correspond to the conceptual geological model of the porphyry copper deposit and the alterations are related to the host rock of this type of deposit.