Multi-Source Remote Sensing and Modeling for Agro-Hydrological and Ecological Assessment

Dear Colleagues,

Recent advancements in remote sensing technologies have brought new opportunities to enhance the monitoring, modeling and management of hydrological processes and ecological systems, particularly at agricultural, regional and basin scales. The integration of multi-source remote sensing datasets, including optical, radar, LiDAR, thermal, microwave sensors and airborne and UAV platforms, enables more accurate, spatially explicit, and temporally consistent analysis of soil–water–vegetation interaction, land–atmosphere interactions, agro-ecosystem dynamics, water availability, and the impacts of climate change and anthropogenic activities.

This Special Issue aims to bring together cutting-edge research that leverages multi-source remote sensing data to enhance agro-hydrological and ecological assessments. We invite contributions that explore the applications of satellite-derived products, UAV-based observations, and crop, hydrological and ecological model simulations to improve our understanding of regional water resources, sustainable irrigation and agriculture, ecological resilience and ecosystem services. We encourage interdisciplinary studies that integrate hydrology, irrigation, agronomy, ecology, geospatial analysis, and artificial intelligence/machine learning techniques to address integrated solutions to water, land, and ecosystem management challenges.

Potential Topics Include (but are not limited to):

• Multi-source remote sensing (e.g., MODIS, Sentinel, Landsat, SMAP, GPM, LiDAR, UAV) applications for agro-hydrological and ecological modeling
• Remote-sensing-based estimation of evapotranspiration, irrigation demand and use, soil moisture, precipitation, and runoff
• Assessment of drought, flood, and water stress using multi-sensor data
• Machine learning and data assimilation or fusion techniques for regional-scale hydrological and ecological analysis
• Land use/land cover change impacts on agricultural productivity, hydrology, and ecosystem services
• Monitoring wetland dynamics, surface water extent, irrigated area mapping, and groundwater interactions using remote sensing
• Remote sensing for ecosystem health assessment, crop water use and condition monitoring, vegetation dynamics, and habitat modeling
• Integration of climate projections and remote sensing for scenario-based agro-ecological planning and water resource assessments
• Validation and uncertainty analysis of remote sensing-derived agro-hydrological and ecological products

Dr. Yared Bayissa
Dr. Abebe D. Chukalla
Prof. Dr. David Costa
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.