Article
Remote Sensing
Linda Aune-Lundberg, Geir-Harald Strand
Summary: The comparison between the CORINE Land Cover dataset for Norway for the reference year 2018 and detailed national land cover and land use data showed that in general, the classification complied with the definitions, but discrepancies were found in detailed and marginal classes. Using classification based on statistical profiles can improve the accuracy of the classification.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Environmental Sciences
Zander S. Venter, Markus A. K. Sydenham
Summary: A 10 m resolution land cover map of Europe based on machine learning was proposed, achieving higher accuracy compared to other maps at the same resolution. Auxiliary data and spectro-temporal metrics significantly influenced the accuracy of the map.
Article
Green & Sustainable Science & Technology
Qiang Bie, Ying Shi, Xinzhang Li, Yueju Wang
Summary: This study evaluated the consistency and accuracy of three widely used 30 m spatial resolution land cover maps and found that they performed well in the classification of arid regions but varied in their accuracy for other types of regions.
Article
Environmental Sciences
Anca Dabija, Marcin Kluczek, Bogdan Zagajewski, Edwin Raczko, Marlena Kycko, Ahmed H. Al-Sulttani, Anna Tarda, Lydia Pineda, Jordi Corbera
Summary: Land cover information is crucial in European Union spatial management, with the development of the new version CLC+ in progress. Various methods and algorithms are being tested in Catalonia, Poland, and Romania to provide insights and guidance for development.
Article
Environmental Sciences
J. Camilo Fagua, Susana Rodriguez-Buritica, Patrick Jantz
Summary: Improving remote sensing frameworks for land cover mapping is crucial for informed decision-making in policy, development, planning, and natural resource management, especially in tropical countries with limited technical capacity. Specific land cover legend specification is a crucial first step in the mapping process, as it affects the subsequent interpretation and use of results.
Article
Environmental Sciences
N. Tsendbazar, M. Herold, L. Li, A. Tarko, S. de Bruin, D. Masiliunas, M. Lesiv, S. Fritz, M. Buchhorn, B. Smets, R. Van De Kerchove, M. Duerauer
Summary: This study proposes a framework for operational validation of annual global land cover maps, aiming to provide timely and accurate validation information for users regarding the temporal consistency and stability of multi-date GLC maps.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Studies
Xiaofang Sun, Guicai Li, Junbang Wang, Meng Wang
Summary: The study analyzes LULC transitions in the Yellow River Basin using GlobeLand30 data, showing an increase in land transition rates over different time periods and strong evidence of artificial surfaces gains across all regions. Cultivated land decreased in size during both intervals.
Article
Environmental Sciences
Chenxi Li, Zaiying Ma, Liuyue Wang, Weijian Yu, Donglin Tan, Bingbo Gao, Quanlong Feng, Hao Guo, Yuanyuan Zhao
Summary: The study demonstrates that sampling strategies have significant impacts on land cover classification accuracy when the sample size is limited. The proposed object-oriented sampling approach is identified as one of the best strategies for collecting training samples, while stratified sampling and manual sampling perform well in specific situations.
Article
Remote Sensing
David Garcia-Alvarez, Claudia M. Vina, Eduardo Gomes, Filipe Marcelino, Mario Caetano, Jorge Rocha
Summary: This paper evaluates the types of changes, associated uncertainties, and the relevance of the Portuguese backdating approach for consistent time-series of LULC maps. The results show that the national backdating methodology can remove important uncertainties in the CORINE layers distributed by the Copernicus Land Monitoring Service, and can be exported for CORINE production in other European countries.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Environmental Sciences
Mohamed Soliman, Mohamed M. Morsy, Hany G. Radwan
Summary: Flood modeling requires high-resolution land-cover maps and appropriate Manning's roughness values. This study evaluates the accuracy of the LULC 2020-ESRI dataset compared to the NLCD 2019 dataset and proposes a standard reference for Manning's roughness values in the LULC 2020-ESRI dataset.
Article
Environmental Sciences
Zhixin Wang, Giorgos Mountrakis
Summary: This study evaluates the accuracy of eleven global and regional land cover land use products in the United States. The National Land Cover Database (NLCD) and the Land Change Monitoring, Assessment and Projection (LCMAP) perform best, with higher accuracy across classes. However, there is still room for improvement, as the best performing products range between 55% and 70% accuracy.
Article
Environmental Sciences
Yoshie Ishii, Koki Iwao, Tsuguki Kinoshita
Summary: The study aimed to create a land cover map validation dataset with added spatial uniformity information using satellite images and DCP points, addressing the issue of using DCP points for accuracy assessment of global land cover maps. The new method devised in the study can guarantee the spatial uniformity of DCP validation data points at any resolution semi-automatically with a user's accuracy of 0.954, leading to differences in accuracy assessment trends across classes and regions for existing global land cover maps.
Article
Multidisciplinary Sciences
Jiyao Zhao, Le Yu, Han Liu, Huabing Huang, Jie Wang, Peng Gong
Summary: Global land-cover datasets are crucial for climate change studies and have evolved from single-type historical datasets in recent years. This study combined supervised land cover classification and aggregation of multiple thematic land cover maps using the Google Earth Engine cloud computing platform to produce a global land cover dataset.
Article
Environmental Sciences
Vincent B. Verhoeven, Irene C. Dedoussi
Summary: Land cover plays a crucial role in the Earth's climate, food security, and biodiversity. By using classification trees to generate annual land cover maps, it is possible to accurately classify and monitor changes in land cover on the European continent.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Environmental Sciences
Panpan Xu, Nandin-Erdene Tsendbazar, Martin Herold, Jan G. P. W. Clevers
Summary: This study assessed the effectiveness of using existing global datasets to develop a comprehensive and user-oriented GALC database, identifying limitations in current datasets for comprehensive GALC mapping. The results revealed errors and shortcomings in certain maps, highlighting areas for improvement in future GALC characterization.
Article
Engineering, Marine
Mads Christensen, Marina Georgati, Jamal Jokar Arsanjani
Summary: This study evaluates the risk factors associated with Arctic shipping, particularly along the Northern Sea Route, and explores the future potential of the route as a viable and less risky alternative for European-Asian shipping. The study concludes that Arctic shipping not only offers benefits in terms of distance savings, cost reduction, and lower CO2 emissions, but also provides a safer alternative. The findings provide valuable insights for decision-makers in addressing accessibility and safety issues in future Arctic transportation.
JOURNAL OF MARINE ENGINEERING AND TECHNOLOGY
(2022)
Article
Environmental Sciences
Andrea Sulova, Jamal Jokar Arsanjani
Summary: Recent studies have shown an increase in wildfires globally due to climate change. A study developed an automatized workflow using remote sensing data for generating a training dataset of fire events at a continental level to predict fire occurrences in Australia during the 2019-2020 summer season. The findings, particularly using the Random Forest algorithm, were able to identify driving factors of Australian wildfires, which can be valuable for policymakers, environmentalists, and climate change researchers.
Article
Biodiversity Conservation
Mohammad Karimi Firozjaei, Amir Sedighi, Hamzeh Karimi Firozjaei, Majid Kiavarz, Mehdi Homaee, Jamal Jokar Arsanjani, Mohsen Makki, Babak Naimi, Seyed Kazem Alavipanah
Summary: This study evaluated the impacts of mining activities on land-use/land-cover changes by analyzing satellite images and meteorological data of mining areas in Iran, Canada, India, and Germany. The results showed a reduction in forest and green space cover due to mining activities, leading to long-term effects on the environment.
ECOLOGICAL INDICATORS
(2021)
Article
Environmental Sciences
Mohammad Karimi Firozjaei, Majid Kiavarz, Mehdi Homaee, Jamal Jokar Arsanjani, Seyed Kazem Alavipanah
Summary: This study aimed to propose a new method to quantify Urban Surface Ecological Poorness Zone Intensity (USEPZI) using remote sensing data and imagery. By successfully modeling the surface biophysical characteristics of cities and simulating their surface ecological status, a valuation model for urban surface ecological poorness zones can be established using a linear regression function.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Computer Science, Information Systems
Angelina Ageenko, Laerke Christina Hansen, Kevin Lundholm Lyng, Lars Bodum, Jamal Jokar Arsanjani
Summary: A mapping study conducted in Denmark revealed a higher number of landslides than previously acknowledged, suggesting a potential problem. The study aimed to reduce geographical bias and identify landslide-prone areas in the future using machine learning algorithms. The results showed that the Random Forest model performed well in predicting landslide susceptibility in low-lying landscapes of Denmark.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Editorial Material
Computer Science, Information Systems
Flavio Lupia, Jamal Jokar Arsanjani, Cidalia Costa Fonte, Giuseppe Pulighe
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Computer Science, Information Systems
Rasoul Afsari, Saman Nadizadeh Shorabeh, Mostafa Kouhnavard, Mehdi Homaee, Jamal Jokar Arsanjani
Summary: This study aims to propose a spatial decision support tool for mapping flood vulnerability in Tehran under different risk scenarios. Several factors were considered, and their weights were determined using expert opinions and the FAHP method. The vulnerability maps for different scenarios were prepared using the OWA method. The results can be used by stakeholders such as urban planners, decision makers, and hydrologists to plan and build resilience against floods.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Geography
Casper Samso Fibaek, Carsten Kessler, Jamal Jokar Arsanjani, Marcia Luz Trillo
Summary: Recent research has shown that estimating structural area, volume, and population using Sentinel 1 and 2 data at a 10 by 10-m resolution is promising. This study presents a deep learning methodology for population estimation in geographically distinct areas from Northern Europe. The results demonstrate that the proposed methodology shows comparable or better results than the state-of-the-art for the case study areas of Ghana and Egypt.
TRANSACTIONS IN GIS
(2022)
Article
Engineering, Aerospace
Naeim Mijani, Mohammad Karimi Firozjaei, Moein Mijani, Adeleh Khodabakhshi, Salman Qureshi, Jamal Jokar Arsanjani, Seyed Kazem Alavipanah
Summary: The COVID-19 pandemic has both positive and negative impacts on society, the environment, and public health. This study focuses on monitoring the effect of COVID-19 lockdowns on urban cooling. By analyzing satellite images of Milan, Rome, and Wuhan, it was found that the surface temperature in built-up areas decreased during the lockdown period, indicating a reduction in the urban heat island effect.
ADVANCES IN SPACE RESEARCH
(2023)
Review
Environmental Studies
Seyed Kazem Alavipanah, Mohammad Karimi Firozjaei, Amir Sedighi, Solmaz Fathololoumi, Saeid Zare Naghadehi, Samiraalsadat Saleh, Maryam Naghdizadegan, Zinat Gomeh, Jamal Jokar Arsanjani, Mohsen Makki, Salman Qureshi, Qihao Weng, Dagmar Haase, Biswajeet Pradhan, Asim Biswas, Peter M. Atkinson
Summary: In remote sensing, shadows significantly influence the quality of data and play a crucial role in environmental studies. Different types of shadows have been identified, affecting various properties and outputs in remote sensing processes. Modeling and mitigating the shadow effect pose challenges, but valuable information can still be extracted from shadows.
Article
Environmental Sciences
Rasoul Afsari, Saman Nadizadeh Shorabeh, Amir Reza Bakhshi Lomer, Mehdi Homaee, Jamal Jokar Arsanjani
Summary: The purpose of this study is to assess the vulnerability of urban blocks to earthquakes in Tehran using an artificial neural network-multi-layer perceptron. The study classified earthquake vulnerability criteria into three categories and inputted them into the neural network. The results showed that 29% of Tehran's total area is extremely vulnerable to earthquakes, with factors such as proximity to fault lines, high population density, and environmental factors gaining higher importance scores.
Article
Green & Sustainable Science & Technology
Amir Reza Bakhshi Lomer, Mahdi Rezaeian, Hamid Rezaei, Akbar Lorestani, Naeim Mijani, Mohammadreza Mahdad, Ahmad Raeisi, Jamal Jokar Arsanjani
Summary: This study presents a novel risk-based decision support system that helps disaster risk management planners select the best locations for emergency shelters after an earthquake. The system identifies important criteria based on stakeholder analysis, determines their weights through a Large Group Decision-Making (LGDM) model, and assesses the suitability of different locations using the Ordered Weighted Average (OWA) method. Factors such as distance from the fault, population density, access to green spaces, and building quality were found to be significant in selecting the best emergency shelters.
Article
Computer Science, Information Systems
Mohammad Karimi Firozjaei, Naeim Mijani, Saman Nadizadeh Shorabeh, Yasin Kazemi, Yasser Ebrahimian Ghajari, Jamal Jokar Arsanjani, Majid Kiavarz, Seyed Kazem Alavipanah
Summary: This study assessed the effect of urban growth on the surface ecological status of neighboring cities in Iran and found that the surface ecological status significantly decreased as the cities experienced rapid physical growth.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2023)
Article
Environmental Studies
Bahare Moradi, Rojin Akbari, Seyedeh Reyhaneh Taghavi, Farnaz Fardad, Abdulsalam Esmailzadeh, Mohammad Zia Ahmadi, Sina Attarroshan, Fatemeh Nickravesh, Jamal Jokar Arsanjani, Mehdi Amirkhani, Igor Martek
Summary: This study presents a scenario-based spatial multi-criteria decision-making system for evaluating urban environment quality (UEQ). By involving stakeholders and calculating criteria weights, UEQ maps were created for different scenarios and the population distribution in different classes of UEQ was evaluated. The research results showed that a high percentage of the population in the study area live under unsuitable UEQ conditions, indicating the need for improving the current UEQ conditions.
Article
Green & Sustainable Science & Technology
Mohammad Ebrahimi Sirizi, Esmaeil Taghavi Zirvani, Abdulsalam Esmailzadeh, Jafar Khosravian, Reyhaneh Ahmadi, Naeim Mijani, Reyhaneh Soltannia, Jamal Jokar Arsanjani
Summary: The selection and allocation of manufacturing and processing facilities are crucial for sustainable economic productivity and environmental preservation. This study presents a scenario-based multi-criteria decision-making system for modeling the land suitability of pistachio processing facilities. The findings highlight the importance of proximity to pistachio orchards, residential areas, road networks, and industrial areas in determining suitability.
