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Remote Sensing
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Innovative Geospatial Information and Earth Observation (GEO) Techniques for Sustainable...
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Innovative Geospatial Information and Earth Observation (GEO) Techniques for Sustainable Development

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: 15 April 2025 | Viewed by 1913

Special Issue Editors

Dr. Chao Yang

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Guest Editor
National Engineering Research Center of Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430074, China
Interests: deep learning; sensor web; social sensing
Prof. Dr. Jie Chen

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Guest Editor
Department of Geo-Informatics, Central South University, Changsha 410083, China
Interests: urban sustainable development
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chaogui Kang

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Guest Editor
National Engineering Research Center of Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430074, China
Interests: travel behabiour; built environment; social inequality
Prof. Dr. Liang Hong

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Guest Editor
Faculty of Geographical Science,Yunnan Normal University, Kunming 650500, China
Interests: intelligent processing and applications of high spatial resolution remote sensing image; big earth data for SDGs
Prof. Dr. Phaedon C. Kyriakidis

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Guest Editor
Department of Civil Engineering and Geomatics, Cyprus University of Technology, Limassol, Cyprus
Interests: spatial analysis; geostatistics; geocomputation; geographic information systems and science; remote sensing; geoinformatics in archaeology and cultural heritage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid progression of urbanization and heightened public attention to urban issues, observations from space, air, and land provide extensive technical methods for understanding urban environments and advancing urban sustainability. We are expecting innovative Geospatial Information and Earth Observation (GEO) techniques can offer timely, comprehensive, and diverse earth observation data for urban sustainable development on aspects such as urban environment, infrastructure, and habitability. Moreover, we are concerned about how to capture and evaluate citizens’ perceptions, awareness, and assessments regarding their living space, encompassing experiences related to urban design, the natural and social environment, public services, and life quality.

This Special Issue aims to demonstrate the innovative geospatial information and earth observation technologies in the field of urban sustainable development. The use of these technologies aligns with the journal’s scope by providing innovative methods, tools, and data for urban governance, contributing to decision-making processes, and enhancing the quality of life for urban residents.

Suggested Themes:

  • Urban Environmental Intelligent Perception Technology;
  • Urban Environment and Resident Adaptability;
  • Urban Mobility and Sustainable Transportation;
  • Sustainable National Spatial Planning;
  • Urban Resilience and Social Resilience.

Suggested Article types:

  • Research article, methodology article, and review article.

Dr. Chao Yang
Prof. Dr. Jie Chen
Prof. Dr. Chaogui Kang
Prof. Dr. Liang Hong
Prof. Dr. Phaedon C. Kyriakidis
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. Remote Sensing 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 2700 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

  • earth observation
  • geospatial sensor web
  • citizen sensing
  • sustainable transport
  • land use change
  • urban resilience
  • nature-based solutions

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

24 pages, 40976 KiB  
Article
Monitoring Anthropogenically Disturbed Parcels with Soil Erosion Dynamics Change Based on an Improved SegFormer
by Zhenqiang Li, Jialin Li, Jie Li, Zhangxuan Li, Kuncheng Jiang, Yuyang Ma and Chuli Hu
Remote Sens. 2024, 16(23), 4494; https://doi.org/10.3390/rs16234494 - 29 Nov 2024
Viewed by 576
Abstract
Amidst burgeoning socioeconomic development, anthropogenic activities have exacerbated soil erosion. This erosion, characterized by its brief duration, high frequency, and considerable environmental degradation, presents a major challenge to ecological systems. Therefore, it is imperative to regulate and remediate erosion–prone, anthropogenically disturbed parcels, with [...] Read more.
Amidst burgeoning socioeconomic development, anthropogenic activities have exacerbated soil erosion. This erosion, characterized by its brief duration, high frequency, and considerable environmental degradation, presents a major challenge to ecological systems. Therefore, it is imperative to regulate and remediate erosion–prone, anthropogenically disturbed parcels, with dynamic change detection (CD) playing a crucial role in enhancing management efficiency. Currently, traditional methods for change detection, such as field surveys and visual interpretation, suffer from time inefficiencies, complexity, and high resource consumption. Meanwhile, despite advancements in remote sensing technology that have improved the temporal and spatial resolution of images, the complexity and heterogeneity of terrestrial cover types continue to limit large–scale dynamic monitoring of anthropogenically disturbed soil erosion parcels (ADPSE) using remote sensing techniques. To address this, we propose a novel ISegFormer model, which integrates the SegFormer network with a pseudo–residual multilayer perceptron (PR–MLP), cross–scale boundary constraint module (CSBC), and multiscale feature fusion module (MSFF). The PR–MLP module improves feature extraction by capturing spatial contextual information, while the CSBC module enhances boundary prediction through high– and low–level semantic guidance. The MSFF module fuses multiscale features with attention mechanisms, boosting segmentation precision for diverse change types. Model performance is evaluated using metrics, such as precision, recall, F1–score, intersection over union (IOU), and mean intersection over union (mIOU). The results demonstrate that our improved model performs exceptionally well in dynamic monitoring tasks for ADPSE. Compared to five other models, our model achieved an mIOU of 72.34% and a Macro–F1 score of 83.55% across twelve types of ADPSE changes, surpassing the other models by 1.52–2.48% in mIOU and 2.25–3.64% in Macro–F1 score. This work provides a theoretical and methodological foundation for policy–making in soil and water conservation departments. Full article
(This article belongs to the Special Issue Innovative Geospatial Information and Earth Observation (GEO) Techniques for Sustainable Development)
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22 pages, 7129 KiB  
Article
Urban Multi-Scenario Land Use Optimization Simulation Considering Local Climate Zones
by Jie Chen, Zikun Dong, Ruijie Shi, Geng Sun, Ya Guo, Zhuopeng Peng, Min Deng and Kaiqi Chen
Remote Sens. 2024, 16(22), 4342; https://doi.org/10.3390/rs16224342 - 20 Nov 2024
Viewed by 924
Abstract
The urban heat island (UHI) effect, a significant environmental challenge within the global urbanization process, poses severe threats to human health, ecological security, and life safety while also impacting the achievement of the United Nations Sustainable Development Goals. This study proposes a multi-scenario [...] Read more.
The urban heat island (UHI) effect, a significant environmental challenge within the global urbanization process, poses severe threats to human health, ecological security, and life safety while also impacting the achievement of the United Nations Sustainable Development Goals. This study proposes a multi-scenario optimization method for urban thermal environments based on local climate zones (LCZs) in Changsha City. The research employs a genetic algorithm to optimize the LCZ quantity structure in order to improve the urban temperature environment. Subsequently, the optimized quantity structure is integrated with the future land use simulation (FLUS) model under multi-scenario constraints to achieve optimal spatial distribution of LCZs, providing scientific guidance for urban planning decision-makers. Results demonstrate that the LCZ-based optimization method can effectively regulate the urban thermal environment and maintain a suitable urban temperature range, offering both theoretical foundation and practical guidance for mitigating UHI effects. Full article
(This article belongs to the Special Issue Innovative Geospatial Information and Earth Observation (GEO) Techniques for Sustainable Development)
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