Submit to Sustainability Review for Sustainability Propose a Special Issue

Journal Browser

Sustainable Applications of Remote Sensing and Intelligent Geospatial Information Systems

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Published Papers

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

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 4478

Share This Special Issue

Special Issue Editors

Prof. Dr. Nebiye Musaoğlu

E-Mail Website
Guest Editor

Geomatic Engineering Department, Civil Engineering Faculty, Istanbul Technical University, 34469 Maslak Istanbul, Turkey
Interests: remote sensing; environmental monitoring; geographic information systems

Prof. Dr. Esra Erten

E-Mail Website
Guest Editor

Geomatic Engineering Department, Civil Engineering Faculty, Istanbul Technical University, 34469 Maslak Istanbul, Turkey
Interests: synthetic aperture radar (SAR); polarimetric SAR; multidimensional SAR; multivariate statistics; uncertainty qualification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is now widely accepted that Earth is experiencing global warming and human-induced climate change, which is causing sudden and rapid changes. The United Nations has announced the Sustainable Development Goals (SDGs) to protect the planet and work toward sustainability. In order to achieve these environmental protection goals, it is necessary to understand and monitor disasters. Dozens of wildfires, floods, storms, earthquakes, droughts, etc. are recorded worldwide every year. Wildfires release as much carbon dioxide as just one small country’s total emissions. Similarly, drought and floods affect millions of people around the world, undermining all the SDGs. In this context, to preserve the worlds’ sustainability, an integrated multidisciplinary approach that monitors Earth while ensuring the rapid response to change is needed. One of the best ways of achieving this is to combine different Earth observation (EO) data in an intelligent geospatial information system (GIS). With the contribution of GIS, EO data from satellites carrying imaging, meteorological, and light detection payloads can be used to discover sustainable solutions for tomorrow.

The aim of this Special Issue is to deliver and demonstrate innovative, geospatial, and intelligent solutions for Earth sustainability applications with a multidisciplinary approach.

Contributions should focus on topics including (but are not limited to):

*Life on land;

*Spatial intelligent for Earth observation;

*Sustainability of crop production under climate change;

*Water surface change;

* Forest wildfires;

*Sea/land surface temperature change;

*Earth observation for structural health monitoring;

*Climate change/risk/vulneariblity/disaster;

*Multisensor Earth observation data For vulnerability assessment and disaster response.

Prof. Dr. Nebiye Musaoğlu
Prof. Dr. Esra Erten
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.

Published Papers (3 papers)

Download All Papers

Research

15 pages, 2450 KiB

Open AccessArticle

Comparison between Post-Fire Analysis and Pre-Fire Risk Assessment According to Various Geospatial Data

by Cumhur Güngöroğlu, İrem İsmailoğlu, Bekir Kapukaya, Orkan Özcan, Mustafa Yanalak and Nebiye Musaoğlu

Sustainability 2024, 16(4), 1569; https://doi.org/10.3390/su16041569 - 13 Feb 2024

Viewed by 888

Abstract

Wildfires in forest ecosystems exert substantial ecological, economic, and social impacts. The effectiveness of fire management hinges on precise pre-fire risk assessments to inform mitigation efforts. This study aimed to investigate the relationship between predictions from pre-fire risk assessments and outcomes observed through post-fire burn severity analyses. In this study, forest fire risk was assessed through the Fuzzy Analytical Hierarchy Process (FAHP), in which fire-oriented factors were used as input. The degree of burn was determined by the Random Forest method using 11,519 training points and 400 test points on Sentinel-2 satellite images under three different classes. According to the results obtained from 266 selected test points located within the forest, all primary factors put forth increased high burn severity. Climate, in particular, emerged as the most significant factor, accounting for 52% of the overall impact. However, in cases of high fire severity, climate proved to be the most effective risk factor, accounting for 67%. This was followed by topography with 50% accuracy at a high fire intensity. In the risk assessment based on the FAHP method, climate was assigned the highest weight value among the other factors (32.2%), followed by topography (27%). To evaluate the results more comprehensively, both visually and statistically, two regions with different stand canopy characteristics were selected within the study area. While high burn severity had the highest accuracy in the Case 1 area, moderate burn severity had the highest in the Case 2 area. During the days of the fire, the direction of spreading was obtained from the MODIS images. In this way, the fire severity was also interpreted depending on the direction of fire progression. Through an analysis of various case studies and literature, this research underlines both the inherent strengths and limitations of predicting forest fire behavior-based pre-fire risk assessments. Furthermore, it emphasizes the necessity of continuous improvement to increase the success of forest fire management. Full article

(This article belongs to the Special Issue Sustainable Applications of Remote Sensing and Intelligent Geospatial Information Systems)

► Show Figures

Figure 1

19 pages, 9243 KiB

Open AccessArticle

A Semi-Automated Two-Step Building Stock Monitoring Methodology for Supporting Immediate Solutions in Urban Issues

by Mehmet Isiler, Mustafa Yanalak, Muhammed Enes Atik, Saziye Ozge Atik and Zaide Duran

Sustainability 2023, 15(11), 8979; https://doi.org/10.3390/su15118979 - 02 Jun 2023

Cited by 1 | Viewed by 1290

Abstract

The Sustainable Development Goals (SDGs) have addressed environmental and social issues in cities, such as insecure land tenure, climate change, and vulnerability to natural disasters. SDGs have motivated authorities to adopt urban land policies that support the quality and safety of urban life. Reliable, accurate, and up-to-date building information should be provided to develop effective land policies to solve the challenges of urbanization. Creating comprehensive and effective systems for land management in urban areas requires a significant long-term effort. However, some procedures should be undertaken immediately to mitigate the potential negative impacts of urban problems on human life. In developing countries, public records may not reflect the current status of buildings. Thus, implementing an automated and rapid building monitoring system using the potential of high-spatial-resolution satellite images and street views may be ideal for urban areas. This study proposed a two-step automated building stock monitoring mechanism. Our proposed method can identify critical building features, such as the building footprint and the number of floors. In the first step, buildings were automatically detected by using the object-based image analysis (OBIA) method on high-resolution spatial satellite images. In the second step, vertical images of the buildings were collected. Then, the number of the building floors was determined automatically using Google Street View Images (GSVI) via the YOLOv5 algorithm and the kernel density estimation method. The first step of the experiment was applied to the high-resolution images of the Pleiades satellite, which covers three different urban areas in Istanbul. The average accuracy metrics of the OBIA experiment for Area 1, Area 2, and Area 3 were 92.74%, 92.23%, and 92.92%, respectively. The second step of the experiment was applied to the image dataset containing the GSVIs of several buildings in different Istanbul streets. The perspective effect, the presence of more than one building in the photograph, some obstacles around the buildings, and different window sizes caused errors in the floor estimations. For this reason, the operator’s manual interpretation when obtaining SVIs increases the floor estimation accuracy. The proposed algorithm estimates the number of floors at a rate of 79.2% accuracy for the SVIs collected by operator interpretation. Consequently, our methodology can easily be used to monitor and document the critical features of the existing buildings. This approach can support an immediate emergency action plan to reduce the possible losses caused by urban problems. In addition, this method can be utilized to analyze the previous conditions after damage or losses occur. Full article

(This article belongs to the Special Issue Sustainable Applications of Remote Sensing and Intelligent Geospatial Information Systems)

► Show Figures

Figure 1

20 pages, 4006 KiB

Open AccessArticle

Investigation and Implementation of New Technology Wearable Mobile Laser Scanning (WMLS) in Transition to an Intelligent Geospatial Cadastral Information System

by Abdurahman Yasin Yiğit, Seda Nur Gamze Hamal, Murat Yakar and Ali Ulvi

Sustainability 2023, 15(9), 7159; https://doi.org/10.3390/su15097159 - 25 Apr 2023

Cited by 2 | Viewed by 1701

Abstract

The human population is constantly increasing throughout the world, and accordingly, construction is increasing in the same way. Therefore, there is an emergence of irregular and unplanned urbanization. In order to achieve the goal of preventing irregular and unplanned urbanization, it is necessary to monitor the cadastral borders quickly. In this sense, the concept of a sensitive, up-to-date, object-based, 3D, and 4D (4D, 3D + time) cadastral have to be a priority. Therefore, continuously updating cadastral maps is important in terms of sustainability and intelligent urbanization. In addition, due to the increase in urbanization, it has become necessary to update the cadastral information system and produce 3D cadastral maps. However, since there are big problems in data collection in urban areas where construction is rapid, different data-collection devices are constantly being applied. While these data-collection devices have proven themselves in terms of accuracy and precision, new technologies have started to be developed in urban areas especially, which is due to the increase in human population and the influence of environmental factors. For this reason, LiDAR data collection methods and the SLAM algorithm can offer a new perspective for producing cadastral maps in complex urban areas. In this study, 3D laser scanning data obtained from a portable sensor based on the SLAM algorithm are tested, which is a relatively new approach for cadastral surveys in complex urban areas. At the end of this study, two different statistical comparisons and accurate analyses of the proposed methodology with reference data were made. First, WMLS data were compared with GNSS data and RMSE values for X, Y, and Z, and were found to be 4.13, 4.91, and 7.77 cm, respectively. In addition, WMLS length data and cadastral length data from total-station data were compared and RMSE values were calculated as 4.76 cm. Full article

(This article belongs to the Special Issue Sustainable Applications of Remote Sensing and Intelligent Geospatial Information Systems)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Sustainable Applications of Remote Sensing and Intelligent Geospatial Information Systems

Share This Special Issue

Special Issue Editors

Special Issue Information

Published Papers (3 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI