Exploring the Urban Heat Island and Its Mechanisms Based on Satellite and AI
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 704
Special Issue Editors
Interests: remote sensing; biomass; urban heat island; air pollution
Interests: remote sensing; inland water; coastal water; atmospheric aerosols; atmospheric correction; satellite imagery
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; aerosol optical depth; air pollution estimation; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Urban Heat Island (UHI) effects, i.e., where urban areas experience significantly higher temperatures than their rural surroundings, pose serious challenges to public health, energy consumption, and urban sustainability. With rapid urbanization and climate change intensifying these effects, understanding the spatial and temporal dynamics of UHI has become a critical research priority. Remote sensing technologies, particularly satellite-based observations, offer powerful tools for monitoring land surface temperatures, vegetation cover, and urban morphology. Meanwhile, artificial intelligence (AI) and machine learning techniques are revolutionizing the analysis of complex geospatial data, enabling the more accurate modeling and prediction of UHI phenomena.
This Special Issue aims to collate cutting-edge research that leverages satellite remote sensing and AI to explore the mechanisms, impacts, and mitigation strategies of Urban Heat Islands. It aligns closely with the scope of Remote Sensing, emphasizing the integration of advanced Earth observation technologies with intelligent data analytics to address pressing environmental and urban challenges.
We welcome contributions in areas including, but not limited to, the following:
- Satellite-based detection and mapping of UHI;
- AI-driven modeling and prediction of UHI dynamics;
- Multi-source data fusion for urban thermal environment analysis;
- Temporal and spatial variability of UHI across different climates and urban forms;
- UHI mitigation strategies and their evaluation using remote sensing;
- Urban planning and policy implications derived from UHI studies.
You may choose our Joint Special Issue in Climate.
Prof. Dr. Charles Man Sing Wong
Dr. Majid Nazeer
Dr. Xin-Yu Yu
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.
Keywords
- urban heat island (UHI)
- satellite remote sensing
- artificial intelligence (AI)
- land surface temperature
- urban climate
- thermal infrared imaging
- data fusion
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