Multi-Source Remote Sensing and Spatial Statistical Analysis in Urban Sustainability Research

Dear Colleagues,

Today, urban areas are at the forefront of global change, facing multifaceted challenges related to climate change, such as urban heat islands, geohazards, flooding, and biodiversity degradation. Integrating multi-source remote sensing (RS) data (e.g., data acquired from in situ measurement, aerial, and satellite platforms) and spatial statistical tools offers unparalleled insights into critical issues for understanding and managing urban sustainability. We can announce a Special Issue dedicated to exploring the applications of these advanced techniques in urban sustainability research.

We invite submissions that showcase innovative research on the following topics:

(1) Urban Climate Change: Research that examines how multi-source RS data, e.g., aerial and satellite optical, hyperspectral, LiDAR, and SAR images, as well as in situ measurement, can be utilized to monitor and model urban climate patterns, including temperature variations, precipitation changes, and extreme weather events, is welcome. Studies on spatial statistical analysis, which can help to identify hotspots of vulnerability and assess the effectiveness of urban planning strategies in mitigating climate impacts, are also welcome.

(2) Urban Heat Islands: Studies that use aforementioned multi-source RS data to map and analyze urban heat islands at different spatial and temporal scales are welcome. Research on the correlation between land cover/land use, 3D urban geometry, and surface temperature, as well as the application of spatial statistical models to predict heat island intensity and develop cooling strategies, is also highly encouraged.

(3) Geohazards: We encourage studies that examine the potential of remote sensing technologies such as DInSAR and PSInSAR using aforementioned multi-source RS data for the early detection, monitoring, and risk assessment of geohazards (e.g., landslides, land subsidence, and earthquakes) in urban areas. Contributions that integrate spatial statistical analysis to identify hazard-prone zones and evaluate the impact of urban development on geological stability are also welcome.

(4) Flood Disasters: Studies using optical, hyperspectral, LiDAR, and SAR data for flood mapping, flood risk assessment, and floodplain management are encouraged. Research that employs spatial statistical methods to analyze the relationship between urban expansion, land cover changes, and flood frequency/severity are of particular interest

(5) Biodiversity Conservation: Studies on how aforementioned multi-source RS data and spatial analysis can support urban biodiversity conservation efforts are welcome. This research could include mapping and monitoring urban green spaces, identifying habitat connectivity, and assessing the impact of urbanization on species distribution and ecosystem services.

We seek high-quality, original research papers, review articles, and case studies demonstrating the capacity of multi-source remote sensing and spatial statistical tools in these domains. Submissions should highlight the innovative use of data and methodology, providing clear and actionable insights for urban planners and policymakers. We expect the authors to contribute to increasing understanding of urban–environment interactions.

Dr. Hao Zhang
Dr. Ashraf Dewan
Dr. Rui Zhou
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 250 words) can be sent to the Editorial Office for assessment.

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.