Remote Sensing of Land Surfaces: Observation, Modeling, and Data Assimilation
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 699
Special Issue Editors
Interests: satellite remote sensing; data assimilation; weather forecasting
Special Issues, Collections and Topics in MDPI journals
Interests: satellite data assimilation; remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The land surface is a key component of the Earth system and it plays a critical role in various environmental processes. The accurate monitoring and analysis of land surface parameters, such as soil moisture, vegetation cover, land use, and surface temperature, are essential for numerous applications, including climate modeling, agricultural management, disaster response, and ecological conservation.
In recent years, the field of remote sensing has experienced significant advancements, profoundly enhancing the ability to observe, model, and understand the land surface. For example, satellite, airborne, and ground-based sensors, etc., can provide comprehensive, high-resolution, and continuous data across wide areas, as well as capture the dynamic and heterogeneous nature of land surfaces. At the same time, integrating remote sensing observations with modeling and data assimilation further enhances the ability to interpret and utilize land surface information. Combining observational data with numerical models provides accurate and coherent representations of land surface processes, which is also important for improving predictive models and resource management.
This Special Issue aims to showcase the latest research on the observation, modeling, and data assimilation of land surface process using remote sensing technologies, hopefully benefitting researchers, practitioners, and policymakers interested in this topic. All original research articles, review papers, technical notes, and case studies on this topic are welcomed.
Prof. Dr. Yansong Bao
Dr. Fu Wang
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 surface process
- data assimilation
- remote sensing
- land cover
- soil moisture
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