Remote Sensing for Building Extraction and Large-Scale Urban Mapping
A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Urban Remote Sensing".
Deadline for manuscript submissions: 28 February 2027 | Viewed by 175
Editors
Interests: remote sensing images; building extraction; large vision-language models; semantic segmentation, and change detection
Interests: deep learning; machine learning; computer vision; remote sensing image processing; image restoration; low-rank modeling; multimodal data fusion; remote sensing image understanding
Interests: GeoAI; AI4EO; multimodal remote sensing; change detection; disaster response; height estimation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Rapid urbanization and the increasing demand for timely geospatial information have made accurate building extraction and large-scale urban mapping essential for urban planning, infrastructure management, disaster risk assessment, population estimation, environmental monitoring, and sustainable development. Recent advances in very-high-resolution optical imagery, synthetic aperture radar, LiDAR, unmanned aerial vehicle data, cloud computing, and artificial intelligence have substantially improved the automated characterization of complex urban environments. Nevertheless, challenges remain in cross-region generalization, multi-source data fusion, fine-boundary delineation, dense and heterogeneous urban scenes, limited annotations, computational efficiency, uncertainty assessment, and the production of consistent mapping results over large areas. This Special Issue aims to present recent methodological and applied advances in remote sensing for building extraction and large-scale urban mapping. It welcomes studies that improve the accuracy, robustness, scalability, interpretability, and transferability of urban mapping approaches. The topic is closely aligned with the scope of Remote Sensing because it addresses the acquisition, processing, analysis, and application of remotely sensed data for Earth observation and geospatial information generation. Original research articles, review papers, technical notes, and communications are invited.
Suggested topics include, but are not limited to:
- Building detection, segmentation, and footprint extraction;
- Large-scale and high-resolution urban land-cover mapping;
- Deep learning, foundation models, and vision–language models for urban remote sensing;
- Multi-temporal building and urban change detection;
- Three-dimensional building reconstruction and urban morphology analysis;
- Applications in urban planning, disaster management, environmental assessment, and sustainable cities.
Dr. Jiepan Li
Prof. Dr. Wei He
Dr. Hongruixuan Chen
Dr. Ting Hu
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-anonymized 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
- building extraction
- large-scale urban mapping
- change detection
- high-resolution imagery
- remote sensing
- deep learning
- sustainable urban development
- three-dimensional reconstruction
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