Multi-source Remote Sensing Data in Hydrology and Geophysical Processes

Dear Colleagues,

Remote sensing technologies have revolutionized the way we observe and understand the Earth's surface and its dynamic processes and satellite, airborne, and ground-based remote sensing platforms offer the ability to collect spatially extensive, temporally frequent, and multispectral data over large geographic areas. These datasets provide valuable information on a wide range of hydrological and geophysical variables, including precipitation, soil moisture, surface water dynamics, land cover/land use, topography, and geophysical properties. In the fields of hydrology and geophysics, the integration of multi-source remote sensing data has emerged as a powerful tool for advancing our understanding of complex environmental phenomena and informing sustainable resource management practices.

Research focused on the integration of multi-source remote sensing data in hydrology and geophysical processes is critical for advancing our understanding of Earth's dynamic systems and addressing pressing societal and environmental challenges. By leveraging the wealth of information provided by remote sensing technologies, researchers can contribute to improved water resource management, enhanced disaster resilience, and informed decision-making for sustainable development. This fits well with the scope of the journal.

We invite contributions covering a wide range of topics related to the integration of multi-source remote sensing data in hydrology and geophysical processes including, but not limited to:

• The integration of satellite, airborne, and ground-based remote sensing data for hydrological modelling and analysis;
• Applications of multi-source remote sensing data in surface water and groundwater monitoring, assessment, and management;
• The utilization of remote sensing techniques for studying soil moisture dynamics, land surface processes, and land–atmosphere interactions;
• Remote sensing-based approaches to monitoring and modelling hydrological extremes such as floods, droughts, and landslides;
• The fusion of remote sensing data with in situ observations and numerical models to improve the understanding of geophysical processes;
• Innovative methods for the retrieval and assimilation of multi-source remote sensing data for hydrological and geophysical models;
• Remote sensing-based studies on the impacts of climate change and land use/land cover change on hydrological and geophysical processes;
• Applications of advanced remote sensing technologies (e.g., SAR, LiDAR, hyperspectral imaging) in hydrology and geophysics;
• The integration of remote sensing data with machine learning and data-driven approaches for the enhanced understanding and prediction of processes;
• Case studies and applications showcasing the practical implications of multi-source remote sensing data in hydrological and geophysical research and management.

Prof. Dr. Shiqiang Zhang
Dr. Yun Chen
Dr. Qiudong Zhao
Dr. Chang Huang
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.

• hydrologic variables
• data fusion
• surface water
• glaciers
• snow cover
• hydrological process
• flood monitoring