Building Extraction from Remote Sensing Images
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: closed (26 April 2024) | Viewed by 718
Special Issue Editors
Interests: LIDAR; RADAR/SAR; building detection; 3D reconstruction; image analysis; point cloud processing; machine learning; earth observation; capacity building orest remote sensing building extraction; 2D/3D change detection; data fusion; time-series image analysis; semantic 3D point cloud segmentation; computer vision
Special Issues, Collections and Topics in MDPI journals
Interests: forest remote sensing building extraction; 2D/3D change detection; data fusion; time-series image analysis; semantic 3D point cloud segmentation; computer vision; 3D reconstruction
Special Issues, Collections and Topics in MDPI journals
Interests: photogrammetric engineering; remote sensing mapping; low-cost unmanned mobile mapping systems; indoor/outdoor navigation and mapping; sensor integration; 3D modelling using optical and lidar data; high resolution imagery; spatial data co-registration; spatial awareness and intelligence; GIS; risk assessment; disaster management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Building extraction from remotely sensed images is an essential task for a wide range of applications, including urban planning, disaster management, navigation, the updating of spatial databases, and environmental monitoring. Remote sensing images provide a cost-effective and efficient way to map and monitor large areas. The availability of high-resolution satellite imagery has made building extraction more accurate and reliable than ever before. This Special Issue aims to showcase the latest advances in building extraction from remotely sensed images from satellites, airborne platforms, or UAVs. The papers in this issue aim to cover a wide range of topics on building detection and extraction from imagery, including:
- Advanced AI models: Deep learning models have revolutionized many fields of computer vision, and building extraction is no exception. This issue features several papers that propose new AI models for building detection and extraction, with improved accuracy and efficiency over traditional methods, and a special focus on weakly supervised learning and domain adaptation techniques.
- Semantic and instantaneous image segmentation: Semantic segmentation is the task of assigning each pixel in an image to a semantic class, such as building, road, or vegetation. Semantic segmentation and instantaneous segmentation, where individual buildings are identified, are key steps in building extraction, and this issue expects to feature several papers that propose new semantic and instance segmentation methods specifically designed for remotely sensed images.
- 2D/3D change detection: Change detection is the task of identifying changes in an image over time. Change detection is important for building extraction as it can be used to track the growth and development of urban areas, as well as to identify damage caused by natural disasters. This issue anticipates to feature several papers that propose new change detection methods for remote sensing images.
- Disaster monitoring: Disaster monitoring is one of the most important applications of building extraction from remote sensing images. New methods for using remote sensing images to monitor disasters such as earthquakes, floods, and wildfires, specifically focusing on buildings, are welcome in this Special Issue.
The papers in this Special Issue are expected to demonstrate the significant progress that has been made in building extraction from remotely sensed images in recent years. The new methods proposed in these papers offer the potential to improve the accuracy, efficiency, and reliability of building extraction for a wide range of applications. Reviews, original articles, or technical notes are welcome.
Dr. Nusret Demir
Dr. Jiaojiao Tian
Prof. Dr. Costas Armenakis
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
- building detection
- building extraction
- semantic segmentation for buildings
- change detection on buildings
- data fusion for the building detection/extraction
