Surface Radiative Transfer: Modeling, Inversion, and Applications

Dear Colleagues,

Surface radiative transfer models are an essential foundation for the development of remote sensing. They play a crucial role not only in radiation balance but also in supporting the water and carbon cycles. Currently, these models are applied in vegetation monitoring, climate change studies, weather forecasting, and disaster early warning systems. In recent years, advancements in remote sensing hardware and observation methods have introduced new characteristics in spectral, spatial, temporal, and angular dimensions. Notable developments include transitions from multispectral to hyperspectral remote sensing, from medium and low resolution to high resolution, and from traditional remote sensing processing to onboard real-time processing. Radiative transfer models have significantly contributed to supporting and advancing remote sensing research. They underpin the validation and development of new remote sensing technologies, particularly in transitioning from homogeneous to heterogeneous remote sensing modeling and from single-band to multi-band simulations. Additionally, they facilitate the application of remote sensing data across various industries, including, but not limited to, agricultural yield estimation, weather forecasting, drought monitoring, and urban planning. Furthermore, with the widespread development of machine learning and deep learning, radiative transfer models can provide physical constraints for empirical models and supply research samples. Exploring the integration of physical models and empirical models is currently a significant research direction.

This Special Issue aims to explore the latest advancements and applications of surface radiative transfer models in remote sensing. It seeks to gather innovative research and case studies that highlight the significance of these models in understanding and addressing critical environmental issues. By examining the integration of new remote sensing technologies, machine learning, and deep learning techniques, this Special Issue will offer a comprehensive overview of how surface radiative transfer models contribute to various fields, including vegetation monitoring, climate change, weather forecasting, disaster early warning, and urban planning.

Articles may address, but are not limited to, the following topics:

• Radiative transfer model;
• 3D modeling;
• Machine learning model;
• Deep learning model;
• Water balance;
• Weather forecasting;
• Drought monitoring;
• Vegetation monitoring;
• Climate change;
• High-resolution remote sensing;
• Onboard real-time processing;
• Heterogeneous modeling;
• Agricultural yield estimation;
• Urban planning.

Dr. Zunjian Bian
Dr. Xiangyang Liu
Dr. Yazhen Jiang
Dr. Jianbo Qi
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.

• radiative transfer model
• 1D/3D modeling
• land surface temperature
• agriculture application
• drought monitoring