Remote Sensing of Primary Production

Dear Colleagues,

Primary productivity, which refers to the creation of new organic matter by plant communities through the process of photosynthesis, is the fundamental determinant of both the structure and functioning of terrestrial biomes. The accurate estimation of primary productivity offers opportunities to better understand vegetation dynamics, patterns of biodiversity, potential agricultural yield, and global climatic changes.

Remote sensing observations from different platforms (drone, airborne, and spaceborne) provide substantial information for vegetation structure and physiological traits monitoring at various spatial resolutions, and remote-sensing-based methods become the mainstem to obtain large-scale primary productivity. The traditional techniques mainly include vegetation-index-based methods, light use efficiency models, and process-based models, which have been extensively applied in various ecosystems. In addition, in recent years, the remote sensing of solar-induced chlorophyll fluorescence (SIF) is becoming a rapidly advancing front in terrestrial primary productivity estimates, and machine learning techniques also achieved successful applications in this field. Although significant progress has been made, there are also uncertainties in terrestrial primary productivity estimation, especially over mountainous areas. Therefore, the development of state-of-the-art strategies and innovation-driven techniques is encouraged to integrate observations from space–air–ground platforms with models to achieve improved estimates of primary productivity.

As a result, this Special Issue aims to present the latest advances on remote sensing estimation and applications of ecosystem primary productivity. Topics of interest include, but are not limited to:

• Applications of new-generation and high-resolution remote sensing data in primary productivity;
• Remote sensing retrieval of vegetation structure (e.g., leaf area index, clumping index, height) and physiological parameters (e.g., leaf chlorophyll content, maximum photosynthetic carboxylation rate);
• Advancing terrestrial ecosystem models for vegetation productivity and biomass;
• Machine learning for long-term and high-resolution primary productivity products;
• Remote sensing of solar-induced fluorescence and vegetation photosynthesis;
• Retrieval of biophysical parameters, primary productivity, and biomass in mountain ecosystems;
• Interactions between ecosystem productivity and climate change at regional or global scales;
• The variation and response of primary productivity in typical ecosystems and zones;
• Vegetation mapping and classification, vegetation growth, phenology, and recovery monitoring;
• Novel vegetation remote sensing data processing methods: reconstruction, temporal filtering, downscaling, and data fusion.

Dr. Xiaobin Guan
Dr. Xing Li
Dr. Zhaoying Zhang
Dr. Xinyao 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 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-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.