Article
Environmental Sciences
Citlalli Cabral-Aleman, Armando Lopez-Santos, Jose Manuel Zuniga-Vasquez
Summary: This study analyzed the spatial pattern of potential erosion in the upper Nazas River basin and identified critical areas of soil loss using the Universal Soil Loss Equation and spatial autocorrelation techniques. The results showed that while most of the basin has low erosion levels, there are significant areas with high, very high, and extreme erosion levels, with hotspots and coldspots identified through local spatial autocorrelation tests. This information can help policymakers and researchers assess vulnerability and risk levels related to soil erosion.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Chemistry, Multidisciplinary
Alamirew Mulugeta Tola, Tamene Adugna Demissie, Fokke Saathoff, Alemayehu Gebissa
Summary: The study presented a GIS technique for identifying crash hot spots based on spatial autocorrelation analysis using four years of crash data in Ethiopia. By incorporating various statistical tools, the research successfully identified and ranked crash hot spot areas, particularly focusing on the entrances and exits of Ethiopia's capital city, Addis Ababa.
APPLIED SCIENCES-BASEL
(2021)
Article
Environmental Studies
Dora Isabel Rodrigues Ferreira, Luis Carlos Loures, Jose-Manuel Sanchez-Martin
Summary: This research evaluates the sustainability of agritourism by comparing the profiles of accommodation, farmers, and accommodation with agricultural activities. The study examines cultural/landscape, economic, environmental, and social indicators of sustainability and compares them between groups. It also explores the correlation between spatial distribution and sustainability metrics and discusses the significance of these factors for tourism development policies. The findings suggest that there is no direct relationship between spatial distribution and sustainability inputs, indicating imbalances in agritourism product creation.
Article
Multidisciplinary Sciences
Md Saiful Alam, Nusrat Jahan Tabassum
Summary: Safety experts and transportation departments are using GIS analytical methods to identify dangerous highway zones and evaluate crash occurrences in Ohio. By analyzing crash data over a four-year period and using spatial autocorrelation analysis, this study successfully identifies and rates crash hotspot locations, providing valuable insights for decision-making in highway safety.
Article
Multidisciplinary Sciences
Yanguang Chen
Summary: This paper establishes spatial autocorrelation models based on Moran's index through linear regression analysis, revealing the inherent structure of the model parameters. These models enable the calculation of Moran's index, determining the presence of spatial autocorrelation and aiding in spatial analysis.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Valentina Butto, Siddhartha Khare, Pratiksha Jain, Gian de Lima Santos, Sergio Rossi
Summary: The increasing frequency of extreme weather events and their distinct spatial patterns have raised interest in tree susceptibility. This study investigates the spatial patterns and environmental drivers of spring leaf phenology in maple stands in eastern North America. The results show that the location of the stands and climate factors significantly affect spring phenology.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Chemistry, Multidisciplinary
Fatema Rahimi, Abolghasem Sadeghi-Niaraki, Mostafa Ghodousi, Soo-Mi Choi
Summary: GPS-equipped vehicles were used to study urban population movement patterns, focusing on taxis' origin and destination data. The study successfully modeled parameters affecting population displacement patterns and predicted pick-up and drop-off locations, highlighting the importance of movement patterns in recognizing urban hot spots for policymakers and urban planners. The analysis showed different spatial distribution features during different hours of the day, with a low probability of randomness in the general spatial distribution of locations.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Khaled Hazaymeh, Ali Almagbile, Ahmad H. Alomari
Summary: This study examines the spatiotemporal pattern of traffic accidents in Irbid Governorate, Jordan from 2015 to 2019. By using spatial autocorrelation and hotspot analysis techniques, the study finds that the number of traffic accidents has been increasing annually, with the majority of less severe accidents occurring on internal roads in high traffic volume towns. The analysis also reveals clustering patterns of accidents along the road network, which have evolved over the five-year period.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Forestry
Li Gu, Zhiwen Gong, Yuankun Bu
Summary: This study investigated the spatial-temporal dynamics and spatial determinants of forest quality in Chinese provinces. The results showed significant increases in forest area, volume, coverage, and quality, but uneven distribution is a key feature. The Spatial Durbin Model with fixed effects was found to be the most suitable model for analysis, highlighting the positive correlation between forest quality and factors like annual precipitation and collective forest area ratio.
Article
Computer Science, Information Systems
Pedro Nogueira, Marcelo Silva, Paulo Infante, Vitor Nogueira, Paulo Manuel, Anabela Afonso, Goncalo Jacinto, Leonor Rego, Paulo Quaresma, Jose Saias, Daniel Santos, Patricia Gois
Summary: Road traffic accidents are a major concern for modern society. In this study, a combination of GIS tools, machine learning, and artificial intelligence is used to develop spatial intelligence and analyze road traffic accident patterns in the Setubal district, Portugal from 2016 to 2019. The results identify new meaningful locations of accidents and highlight the importance of understanding the determinants of accidents to develop effective strategies for prevention.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Youngbae Song, Jaeyi Song
Summary: This study improves the accuracy of surface temperature analysis in urban areas by using satellite imagery and land cover data. Reclassifying land cover types and performing supervised classifications based on biotope and climatope maps leads to more accurate surface temperature evaluation.
EARTH SCIENCE INFORMATICS
(2022)
Article
Environmental Sciences
Yan Liu, Jiawei Tian, Wenfeng Zheng, Lirong Yin
Summary: This paper discusses the spatial and temporal distribution of severe haze in China, analyzing the impact of economy and energy structure on haze. It provides references for dealing with haze weather and controlling air pollution in China. The study found that haze and PM2.5 concentrations are mainly distributed in the northern regions of China, with more occurrences in winter and less in summer.
Article
Infectious Diseases
Arsene Brunelle Sandie, Jules Brice Tchatchueng Mbougua, Anne Esther Njom Nlend, Sokhna Thiam, Betrand Fesuh Nono, Ndeye Awa Fall, Diarra Bousso Senghor, El Hadji Malick Sylla, Cheikh Mbacke Faye
Summary: There are spatial patterns for HIV infection in Cameroon and possible hot-spots have been identified.
BMC INFECTIOUS DISEASES
(2022)
Article
Veterinary Sciences
Munyaradzi Davis Shekede, Silvester Maravanyika Chikerema, Moregood Spargo, Isaiah Gwitira, Samuel Kusangaya, Aldridge Nyasha Mazhindu, Daud Nyosi Ndhlovu
Summary: Ticks transmit various diseases that impact livestock production and economy. Studying the spatial distribution of tick hotspots can help in identifying high-risk areas for tick-borne diseases and implementing targeted management strategies. This study in Zimbabwe showed species-specific hotspots of various tick species across different districts, indicating potential for multiple disease transmission in overlapping regions.
BMC VETERINARY RESEARCH
(2021)
Article
Geography
John R. Weeks
Summary: The author, with a background in demography, benefited greatly from Art Getis's expertise in geography. Getis not only taught the author about the concept of geography, but also guided him in analyzing demographic data from a spatial perspective, particularly through the use of GIS approaches. The author acknowledges Getis's profound influence in shaping his own research and the field of spatial demography.
JOURNAL OF GEOGRAPHICAL SYSTEMS
(2023)
Article
Environmental Sciences
Mahdi Panahi, Peyman Yariyan, Fatemeh Rezaie, Sung Won Kim, Alireza Sharifi, Ali Asghar Alesheikh, Jongchun Lee, Jungsub Lee, Seonhong Kim, Juhee Yoo, Saro Lee
Summary: The study successfully predicted radon potential in the northwestern part of Gangwon Province using deep learning models, and the results confirmed the accuracy and reliability of the models.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Mohammad Einali, Ali Asghar Alesheikh, Behnam Atazadeh
Summary: The overpopulation in Iran has led to an increased demand for urban land, but the current land administration system in Iran faces challenges in representing ownership rights for complex building structures. This study proposes a BIM-based approach to address these challenges and provides significant benefits for 3D urban land administration in Iran.
GEOCARTO INTERNATIONAL
(2022)
Article
Geography
Faraz Boroumand, Ali Asghar Alesheikh, Mohammad Sharif, Mahdi Farnaghi
Summary: This research proposes a method called FLCSS based on the longest common subsequence (LCSS), which considers the uncertainty of trajectories caused by positioning and sampling errors using fuzzy theory and the bead model. The results show that FLCSS performs better than other methods in terms of sensitivity to point displacement, noise, and different sampling rates, and has a high correlation with LCSS.
TRANSACTIONS IN GIS
(2022)
Article
Green & Sustainable Science & Technology
Mohammad Tabasi, Ali Asghar Alesheikh, Elnaz Babaie, Javad Hatamiafkoueieh
Summary: Spatiotemporal analysis of COVID-19 cases based on epidemiological characteristics can provide more refined findings about health inequalities and better allocation of medical resources. This study investigated COVID-19 clusters in Golestan province, Iran, based on epidemiological factors. The results showed that the province has experienced an upward trend of epidemic waves, with a higher case fatality rate compared to the national average. Areas with a higher proportion of young adults were more likely to generate clusters, and the infection initially appeared in the west and southwest before spreading to other regions.
Article
Computer Science, Information Systems
Omid R. R. Abbasi, Ali A. A. Alesheikh
Summary: The understanding of geographic space differs between computing systems and human discourse. While humans refer to geographic spaces by place names and reason based on characteristics, computing systems handle geographic spaces using coordinate systems. Therefore, a recommendation method that leverages textual content can enhance understanding. This paper uses NLP techniques, such as PPMI, TF-IDF, and MDS, to infer a conceptual space in a place-based recommender system. The proposed method outperformed baseline models, achieving 88% accuracy in measuring item similarity.
Article
Environmental Sciences
Mahdis Yarmohamadi, Ali Asghar Alesheikh, Mohammad Sharif, Hossein Vahidi
Summary: Dust storms are natural disasters with serious impacts on human life and infrastructure, especially in urban areas. Predicting their movement patterns is crucial for effective disaster prevention and management. This study developed a CNN method to predict the pathways of dust storms in arid regions of central and southern Asia.
Article
Environmental Studies
Azher Ibrahim Al-Taei, Ali Asghar Alesheikh, Ali Darvishi Boloorani
Summary: Multi-temporal land use/land cover (LULC) change analysis is crucial for environmental planning and resources management. However, existing global LULC datasets lack consistency on a regional scale and have limited time coverage. This study developed a high-quality multi-temporal LULC mapping approach using Landsat imagery and a random forest classifier. The results showed accurate performance and identified the most important features for LULC mapping. Severe LULC changes were observed in the Tigris and Euphrates rivers basin, particularly in certain areas where land degradation and dust storms emission are pressing issues.
Article
Computer Science, Artificial Intelligence
Sahar Farmanifard, Ali Asghar Alesheikh, Mohammad Sharif
Summary: In this study, three deep learning models were developed for predicting the trajectory of tropical cyclones. The hybrid MLP-LSTM model performed the best, especially when contextual information was considered. It had the smallest prediction errors compared to the MLP and LSTM models.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Marine
Saeed Mehri, Ali Asghar Alesheikh, Anahid Basiri
Summary: Accurate vessel trajectory prediction is important for safety management at sea. This paper proposes a context-aware data-driven framework for vessel trajectory prediction, which includes trajectory annotation and feature selection. Results showed that the predictions made by this framework are more accurate than those made by an LSTM network.
Article
Multidisciplinary Sciences
Mahdi Nazari Ashani, Ali Asghar Alesheikh, Zeinab Neisani Samani, Aynaz Lotfata, Sayeh Bayat, Siamak Alipour, Benyamin Hoseini
Summary: This research aimed to identify socio-environmental determinants of FMD incidence in Iran at the provincial level through the study of 135 outbreaks reported between March 21, 2017, and March 21, 2018. The findings suggest that using geographically weighted regression and multiscale geographically weighted regression models can better predict spatial heterogeneity and provide useful intervention information for decision-makers.
SCIENTIFIC REPORTS
(2023)
Article
Green & Sustainable Science & Technology
Mohammad Tabasi, Ali Asghar Alesheikh, Mohsen Kalantari, Abolfazl Mollalo, Javad Hatamiafkoueieh
Summary: This study explores the spatio-temporal modeling of COVID-19 spread and the impact of different urban land uses using an agent-based model. The results show that the disease is concentrated in central areas with a high population density and dense urban land use. The proposed model accurately predicts the distribution of disease cases and mortality, as well as the spatial distribution at the neighborhood level. Findings demonstrate that early implementation of control scenarios can effectively reduce the transmission and control the epidemic.
Article
Public, Environmental & Occupational Health
Reza Shirzad, Ali Asghar Alesheikh, Mojtaba Asgharzadeh, Benyamin Hoseini, Aynaz Lotfata
Summary: Leptospirosis, a zoonotic disease, poses a significant health issue in certain tropical areas of Iran with an estimated incidence rate of 2.33 cases per 10,000 individuals over the past decade. The study utilized SaTScan and MaxEnt modeling methods to identify spatiotemporal clusters and develop disease prevalence maps, highlighting the primary cluster in the western regions of Gilan province and showing potential disease spread to western and northwestern regions. The accuracy evaluation of the model yielded high AUC metrics of 0.956 and 0.952 for training and test data, emphasizing the robustness of the model.
Proceedings Paper
Geography, Physical
S. Mehri, A. A. Alesheikh
Summary: This study identifies seven factors influencing oak decline and uses five components that explain 92.49% of the variance as input for oak decline potential classification. The results show that SVM method demonstrates high overall accuracy in oak decline potential classification.
XXIV ISPRS CONGRESS IMAGING TODAY, FORESEEING TOMORROW, COMMISSION IV
(2022)