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Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (27 July 2025) | Viewed by 9791

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Special Issue Editors

Dr. Hariklia D. Skilodimou

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Guest Editor

Department of Geology, University of Patras, ZC 26504 Patras, Greece
Interests: GIS; geological mapping; environmental geology; natural hazards; land use planning
Special Issues, Collections and Topics in MDPI journals

Dr. George D. Bathrellos

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Guest Editor

Marine Geology & Geodynamics, Sector of General, Department of Geology, University of Patras, ZC 26504 Patras, Greece
Interests: natural hazards; urban planning; geomorphology; modeling
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Konstantinos G. Nikolakopoulos

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Guest Editor

Applied Geology & Geophysics, Department of Geology, University of Patras, ZC 26504 Patras, Greece
Interests: GIS; remote sensing; photogrammetery; hydrology; geological mapping
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the Earth’s growing population, the environment faces a wide array of new challenges. Detailed knowledge, as well as continuous monitoring and evaluation of the environment, is crucial to promote a sustainable geological environment. In recent decades, remote sensing (RS) has made it possible to gather huge quantities of geographical information and data. Additionally, a Geographical Information System (GIS) serves as an outstanding and effective tool in the spatial analysis of various natural phenomena. The integration of RS with GIS further enhance the process of collating and updating multiple information, thereby offering a cost-effective way for environmental monitoring, evaluation, and change detection. These geospatial technologies are particularly helpful for both basic and applied geology, mapping, characterizing natural resources, assessing contaminated environment risk, estimating natural hazards, identifying community susceptibility to hazards, and land use planning. Therefore, RS and GIS have become necessary tools in addressing geoenvironment.

This Special Issue aims to present research on the application of RS and GIS in addressing geoenvironmental phenomena, underscoring how and why monitoring and evaluating changes in the environment are rather important to encourage the geological environment's sustainability and ensure a good quality of human life. This Special Issue invites submissions of original research articles and reviews. Potential topics may include (but are not limited to) the following:

Environmental pollution, air, water and soil pollution/degradation, waste, hazardous materials incidents, pipelines, radiological events, transportation, salinization, desertification, fires, land use changes, infrastructure failure, natural resource depletion, coastline changes, and loss of biodiversity;
Land use, urban planning, climate changes, and natural resource supply;
All types of atmospheric, hydrologic, geologic and geomorphologic phenomena;
Natural hazards.

We look forward to receiving your submissions.

Dr. Hariklia D. Skilodimou
Dr. George D. Bathrellos
Prof. Dr. Konstantinos G. Nikolakopoulos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

natural resourses
mapping
natural hazards
environental pollution
planning

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Published Papers (7 papers)

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Research

24 pages, 16546 KiB

Open AccessArticle

Long-Term NDVI Trends and Vegetation Resilience in a Seismically Active Debris Flow Watershed: A Case Study from the Wenchuan Earthquake Zone

by Wen Zhang, Zelin Wang, Minghui Meng, Tiantao Li, Jian Guo, Dong Sun, Liang Qin, Xiaoya Xu and Xiaoyu Shen

Sustainability 2025, 17(11), 5081; https://doi.org/10.3390/su17115081 - 1 Jun 2025

Viewed by 498

Abstract

Vegetation restoration in seismically active regions involves complex interactions between geological hazards and ecological processes. Understanding the spatiotemporal patterns of vegetation recovery is critical for assessing disaster evolution, evaluating mitigation effectiveness, and guiding ecological resilience planning. This study investigates post-earthquake vegetation dynamics in the Chutou Gully watershed, located in the 12 May 2008 Wenchuan earthquake zone, using NDVI data from 2000 to 2022. Results reveal a sharp decline in vegetation cover following the earthquake, followed by a steady recovery trend, with NDVI values projected to return to pre-earthquake levels by 2030. Degradation was concentrated in debris flow channels, while more stable adjacent slopes exhibited stronger recovery. Over time, the area of poorly restored vegetation significantly declined, indicating increased ecosystem resilience. The findings highlight the need for site-specific ecological restoration strategies tailored to localized recovery conditions. This study provides valuable insights for disaster mitigation agencies, ecological planners, and local governments working in mountainous hazard-prone regions, and contributes to the long-term sustainability of ecosystems in disaster-prone areas. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment)

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16 pages, 9080 KiB

Open AccessArticle

Drainage Network Generation for Urban Pluvial Flooding (UPF) Using Generative Adversarial Networks (GANs) and GIS Data

by Muhammad Nasar Ahmad, Hariklia D. Skilodimou, Fakhrul Islam, Akib Javed and George D. Bathrellos

Sustainability 2025, 17(10), 4380; https://doi.org/10.3390/su17104380 - 12 May 2025

Viewed by 556

Abstract

Mapping urban pluvial flooding (UPF) in data-scarce regions poses significant challenges, particularly when drainage systems are inadequate or outdated. These limitations hinder effective flood mitigation and risk assessment. This study proposes an innovative approach to address these challenges by integrating deep learning (DL) models with traditional methods. First, deep convolutional generative adversarial networks (DCGANs) were employed to enhance drainage network data generation. Second, deep recurrent neural networks (DRNNs) and multi-criteria decision analysis (MCDA) methods were implemented to assess UPF. The study compared the performance of these approaches, highlighting the potential of DL models in providing more accurate and robust flood mapping outcomes. The methodology was applied to Lahore, Pakistan—a rapidly urbanizing and data-scarce region frequently impacted by UPF during monsoons. High-resolution ALOS PALSAR DEM data were utilized to extract natural drainage networks, while synthetic datasets generated by GANs addressed the lack of historical flood data. Results demonstrated the superiority of DL-based approaches over traditional MCDA methods, showcasing their potential for broader applicability in similar regions worldwide. This research emphasizes the role of DL models in advancing urban flood mapping, providing valuable insights for urban planners and policymakers to mitigate flooding risks and improve resilience in vulnerable regions. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment)

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26 pages, 5114 KiB

Open AccessArticle

Evaluation and Prediction of Ecological Quality Based on Remote Sensing Environmental Index and Cellular Automata-Markov

by Weirong Qin, Mohd Hasmadi Ismail, Mohammad Firuz Ramli, Junlin Deng and Ning Wu

Sustainability 2025, 17(8), 3640; https://doi.org/10.3390/su17083640 - 17 Apr 2025

Cited by 1 | Viewed by 549

Abstract

The evaluation and prediction of ecological environmental quality are essential for sustainable development and environmental management, particularly in regions experiencing rapid urbanization and industrial growth like Johor in southern Peninsular Malaysia. This study evaluates the temporal and spatial changes in ecological environmental quality in Johor from 1990 to 2020 using the Remote Sensing Environmental Index (RSEI) and Cellular Automata-Markov (CA-Markov). A CA-Markov model was employed to predict ecological environmental quality for the next 12 months based on historical data. The results reveal significant changes over the 30 years, highlighting the dynamic nature of ecological conditions. The prediction results indicate that areas with excellent ecological quality are primarily focused in the central and northern regions, while the southern and eastern edges show mixed ecological conditions. The western region, characterized by intensive land use, shows significant environmental degradation. The poorest ecological points are mainly distributed in urban and semiurban areas with frequent human activities, such as cities, ports, and villages. These findings highlight the need for targeted environmental policies and management strategies to mitigate ecological degradation and promote sustainable development in Johor State of Peninsular Malaysia. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment)

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19 pages, 18377 KiB

Open AccessArticle

Natural Hazard Assessment in the Southeastern Margin of the Ría de Arosa (Pontevedra, Spain) Using GIS Techniques

by Carlos E. Nieto, Antonio Miguel Martínez-Graña and Leticia Merchán

Sustainability 2024, 16(22), 10101; https://doi.org/10.3390/su162210101 - 19 Nov 2024

Cited by 1 | Viewed by 1071

Abstract

The characterization of natural hazards in coastal environments is of great necessity, especially in the current context of global climate change and increasing population concentrations. This research focuses on a multi-hazard analysis of the main geotechnical, geomorphological, hydrological, and lithological risks in the southeastern margin of the Ría de Arosa using Geographic Information System techniques. The integration of geotechnical characterization maps and natural hazard maps has allowed for the identification of areas with a high susceptibility to natural disasters, which is crucial for territorial planning and management in the context of growing urban pressure and global climate change. The results indicate that poorly consolidated surface formations, especially in transitional areas such as dunes and marshes, are particularly vulnerable. Additionally, areas with higher lithological competence have been identified, where slope changes contribute to ground instability. This analysis provides valuable tools for decision-making and the implementation of risk management policies, promoting sustainable development, the protection of coastal ecosystems, and the prevention of risks from urban planning and civil engineering activities in the Ría de Arosa. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment)

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28 pages, 18631 KiB

Open AccessArticle

Analysis of Paddy Field Changes (1989–2021) Using Landsat Images and Flooding-Assisted MLC in an Urbanizing Tropical Watershed, Vientiane, Lao PDR

by Iep Keovongsa, Atiqotun Fitriyah, Fumi Okura, Keigo Noda, Koshi Yoshida, Keoduangchai Keokhamphui and Tasuku Kato

Sustainability 2024, 16(22), 9776; https://doi.org/10.3390/su16229776 - 9 Nov 2024

Viewed by 2049

Abstract

Paddy fields are essential for food security and sustaining global dietary needs, yet urban expansion often encroaches on agricultural lands. Analyzing paddy fields and land use/land cover changes over time using satellite images provides critical insights for sustainable food production and balanced urban growth. However, mapping the paddy fields in tropical monsoon areas presents challenges due to persistent weather interference, monsoon-submerged fields, and a lack of training data. To address these challenges, this study proposed a flooding-assisted maximum likelihood classification (F-MLC) method. This approach utilizes accurate training datasets from intersecting flooded paddy field maps from the rainy and dry seasons, combined with the Automated Water Extraction Index (AWEI) to distinguish natural water bodies. The F-MLC method offers a robust solution for accurately mapping paddy fields and land use changes in challenging tropical monsoon climates. The classified images for 1989, 2000, 2013, and 2021 were produced and categorized into the following five major classes: urban areas, vegetation, paddy fields, water bodies, and other lands. The paddy field class derived for each year was validated using samples from various sources, contributing to the overall accuracies ranging from 83.6% to 90.4%, with a Kappa coefficient of between 0.80 and 0.88. The study highlights a significant decrease in paddy fields, while urban areas rapidly increased, replacing 23% of paddy fields between 1989 and 2021 in the watershed. This study demonstrates the potential of the F-MLC method for analyzing paddy fields and other land use changes over time in the tropical watershed. These findings underscore the urgent need for robust policy measures to protect paddy fields by clearly defining urban expansion boundaries, prioritizing paddy field preservation, and integrating these green spaces into urban development plans. Such measures are vital for ensuring a sustainable local food supply, promoting balanced urban growth, and maintaining ecological balance within the watershed. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment)

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23 pages, 4271 KiB

Open AccessArticle

Urban Ecological Quality Assessment Based on Google Earth Engine and Driving Factors Analysis: A Case Study of Wuhan City, China

by Weiwei Zhang, Wanqian Zhang, Jianwan Ji and Chao Chen

Sustainability 2024, 16(9), 3598; https://doi.org/10.3390/su16093598 - 25 Apr 2024

Cited by 6 | Viewed by 2268

Abstract

Ecological quality is a critical factor affecting the livability of urban areas. Remote sensing technology enables the rapid assessment of ecological quality (EQ), providing scientific theoretical support for the maintenance and management of urban ecology. This paper evaluates and analyzes the EQ and its driving factors in the city of Wuhan using remote sensing data from five periods: 2001, 2006, 2011, 2016, and 2021, supported by the Google Earth Engine (GEE) platform. By employing principal component analysis, a Remote Sensing Ecological Index (RSEI) was constructed to assess the spatiotemporal differences of EQ in Wuhan City. Furthermore, the study utilized the optimal parameter-based geographical detector model to analyze the influence of factors such as elevation, slope, aspect, population density, greenness, wetness, dryness, and heat on the RSEI value in 2021 and further explored the impact of changes in precipitation and temperature on the EQ in Wuhan. The results indicate that (1) principal component analysis shows that greenness and wetness positively affect Wuhan’s EQ, while dryness and heat have negative impacts; (2) spatiotemporal analysis reveals that from 2001 to 2021, the EQ in Wuhan showed a trend of initial decline followed by improvement, with the classification grades evolving from poor and average to good and better; (3) the analysis of driving factors shows that all nine indicators have a certain impact on the EQ in Wuhan, with the influence ranking as NDVI > NDBSI > LST > WET > elevation > population density > GDP > slope > aspect; (4) the annual average temperature and precipitation in Wuhan have a non-significant impact on the EQ. The EQ in Wuhan has improved in recent years, but comprehensive management still requires enhancement. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment)

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25 pages, 7390 KiB

Open AccessArticle

Research on the Spatio-Temporal Changes of Vegetation and Its Driving Forces in Shaanxi Province in the Past 20 Years

by Ming Shi, Fei Lin, Xia Jing, Bingyu Li, Jingsha Qin, Manqi Wang, Yang Shi and Yimin Hu

Sustainability 2023, 15(23), 16468; https://doi.org/10.3390/su152316468 - 30 Nov 2023

Cited by 4 | Viewed by 1629

Abstract

(1) Background: Vegetation is an important component of ecosystems. Investigating the spatio-temporal dynamic changes in vegetation in various Shaanxi Province regions is crucial for the preservation of the local ecological environment and sustainable development. (2) Methods: In this study, the KNDVI vegetation index over the 20-year period from 2003 to 2022 was calculated using MODIS satellite image data that was received from Google Earth Engine (GEE). Sen and MK trend analysis as well as partial correlation analysis were then utilized to examine the patterns in vegetation change in various Shaanxi Province regions. This paper selected meteorological factors, such as potential evapotranspiration (PET), precipitation (PRE), and temperature (TMP); human activity factors, such as land-use type and population density; and terrain factors, such as surface elevation, slope direction, and slope gradient, as the influencing factors for vegetation changes in the research area in order to analyze the driving forces of vegetation spatio-temporal changes. These factors were analyzed using a geo-detector. (3) Results: The vegetation in the research area presented a growth trend from 2003 to 2022, and the area of vegetation improvement was 189,756 km², accounting for 92.15% of the total area. Among them, the area of significantly improved regions was 174,262 km², accounting for 84.63% of the total area, and the area of slightly improved regions was 15,495 square kilometers, accounting for 7.52% of the total area. (4) Conclusions: The strengthening of bivariate factors and nonlinear enhancement were the main interaction types affecting vegetation changes. The combination of interaction factors affecting vegetation change in Shaanxi Province includes PRE ∩ PET as well as TMP ∩ PET. Therefore, climate conditions were the main driving force of KNDVI vegetation changes in Shaanxi Province. The data supported by this research are crucial for maintaining the region’s natural ecosystem. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS for Promoting Sustainable Geoenvironment)

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