Advances and Challenges in Ultra-High-Resolution Land Cover and Land Use Classification
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 30 December 2024 | Viewed by 1034
Special Issue Editors
Interests: forest; GIS; Copernicus; remote sensing; machine learning; land cover; vegetation mapping
Special Issues, Collections and Topics in MDPI journals
Interests: geomatics; GNSS; mapping; earth observations; remote sensing; geographic information system; spatial analysis; image analysis; UAV; artificial intelligence; low-cost sensors; sensors integrations; data fusion
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Land cover and land use (LCLU) classification has witnessed significant advancements in recent decades, propelled by the widespread availability of high-resolution optical imagery and from satellite and unmanned aerial vehicles (UAVs). Land cover classification at spatial resolutions finer than 10 cm is commonly referred to as ultra-high-resolution (UHR), distinguishing it from very-high-resolution (VHR) classifications, which denote resolutions less than 1 m. The utilization of specific classification algorithms, diverse processing platforms, and increasingly powerful computational resources has further enhanced the capabilities of LCLU classification. Integrating very-high-resolution imagery has notably transformed LCLU analysis, presenting new opportunities and challenges.
In particular, challenges arise from significant inter-class variability, where pixels with markedly different digital numbers belong to the same class and spectrally similar but semantically distant classes. Various techniques have been employed to address these complexities, including object-based image analysis (OBIA) and incorporating texture-related information or object relationships with surrounding elements (spatial relations).
This Special Issue of Remote Sensing aims to compile contributions focused on generating land cover and land use maps using ultra-high-resolution and very-high-resolution optical data derived from both UAVs and satellites, along with their integration, including model transfer and model upscaling/downscaling. Submissions related to diverse geographic areas, specific semantic classifications, methodologies for minimizing errors associated with UHR and VHR resolution, and applications in complex scenarios are encouraged.
Dr. Elena Belcore
Prof. Dr. Marco Piras
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
- land cover
- land use
- ultra-high-resolution (UHR)
- very-high-resolution (VHR)
- classification algorithms
- OBIA
- texture analysis
- spatial components
- UAV
- satellite satellite–UAV data fusion
- model upscaling
- model downscaling
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.
