Remote Sensing in Vegetation Phenology
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".
Deadline for manuscript submissions: 28 November 2025 | Viewed by 14
Special Issue Editors
Interests: satellite time series analysis; change detection; vegetation phenology; wildfires; land degradation
Special Issues, Collections and Topics in MDPI journals
Interests: ecosystem dynamics monitoring; remote sensing of the environment; vegetation phenology; vegetation response to climate change
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Vegetation phenology is an essential variable that affects ecosystem functions and services. Satellite and near-surface remote sensing have contributed to various scientific findings regarding vegetation phenology and its interactions with the environment across multiple spatiotemporal scales. Significant progress in the remote sensing of vegetation phenology has been made in recent decades, partially benefiting from the progress in sensors and time series data-processing algorithms. However, challenges remain in the theory, methodology, and applications in the remote sensing of vegetation phenology. Various essential issues need to be further investigated. For example, what does satellite-observed vegetation phenology really represent in a heterogeneous landscape? How do we explain the relationships between vegetation phenology across spatial scales? And how do we better characterize vegetation phenology in evergreen or dryland ecosystems with weak or irregular seasonal signals in remote sensing time series?
This Special Issue aims to provide a platform for sharing recent advances and various perspectives in the remote sensing of vegetation phenology.
Research, technical notes, and review articles including (but not limited to) the following topics are welcome:
- Detection of vegetation phenology with multiple sensors/land surface parameters/products.
- Novel algorithms for reconstructing high-quality remote sensing time series and detecting vegetation phenology metrics.
- Development of vegetation phenology products.
- Scale/mixed-pixel issues in the remote sensing of vegetation phenology.
- Near-real-time prediction of vegetation phenology.
- Flowering phenology for specific species.
- Spatio-temporal dynamics in vegetation phenology and its response to environmental changes.
- Vegetation phenology feedbacks to the environment.
- Applications of vegetation phenology in the management of agriculture, forestry, and rangeland systems.
- Applications of vegetation phenology in land surface information extraction and analysis (e.g., land cover/ species mapping, wildfire prediction).
Dr. Chao Ding
Dr. Qiaoyun Xie
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
- vegetation phenology
- time series analysis
- multi-source remote sensing
- UAV
- deep learning
- climate warming
- drought
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