Special Issue "Optical Remote Sensing Applications in Urban Areas"
Deadline for manuscript submissions: 31 July 2021.
Interests: geomatics, remote sensing, and the analysis of optical and synthetic aperture radar Earth observations through artificial intelligence and machine learning approaches for urban and agro-environmental applications
Urban areas have been the center of human settlement and civilization. They also play essential roles in various aspects of human life, including economic, political, cultural, and educational activities. On the other hand, these areas are physically and geographically complex systems and phenomena due to the presence and integration of various elements such as residential, industrial, infrastructure, road networks, green spaces, and water bodies. As such, these phenomena are the study subject of experts and researchers in different fields, from social to physical sciences and engineering. In particular, the physical characteristics of an urban area are essential for various applications in geography, sustainable development, urban planning, and civil engineering. Geospatial information, with different levels of details at local and regional scales, can provide a valuable source of information to reach the ultimate objectives of urban studies.
Remote sensing technology and techniques are among the most effective observation and analysis tools for provision of the geospatial information about urban land complexes. From the beginning of the remote sensing era, aerial photography has provided unprecedented views of the urban area. In addition, Earth observation (EO) systems, such as Landsat satellites, have acquired unique and valuable spatial, spectral, and temporal information of surfaces of the planet, including urban areas. This collection of EOs has progressively continued and been improved by new operational spaceborne, airborne, and drone imagery, as well as optical, lidar, thermal, and radar data sources. In addition, technology revolutions related to open data and informatics resources, big data, and cloud computing platforms bring both opportunities and challenges for the user and the academic community in urban studies.
The main objective of this Special Issue (SI) of the Remote Sensing journal is to promote recent thematic research and development applications and state-of-the-art outcomes and results based on optical Earth observations. For this SI, we invite researchers with different expertise and interest to consider this opportunity and submit their papers on both applications and methodologies on “Optical Remote Sensing for Urban Area.”
Dr. Saeid Homayouni
Dr. Ying Zhang
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 papers will be 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 2400 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.
- Spatiotemporal analysis of urban land
- Urban natural/manmade hazards
- Land-cover mapping
- Land-cover land-use changes (LCLUC) and modeling
- Urban feature detection and extraction
- Urbanization impacts and sustainable development
- Change detection
- Green space monitoring
- 3D mapping and modeling from remote sensing data
- Big data
- Data mining
- Image processing
- Machine and deep learning
- Object-based image analysis