Integrating Remote Sensing, Machine Learning, and Process-Based Modelling for Monitoring Environmental and Agricultural Landscapes Under Climate Change

Dear Colleagues,

Environmental and agricultural landscapes are undergoing rapid change in response to climate variability, land-use intensification, ecosystem degradation, water scarcity, biodiversity loss, and increasing exposure to extreme events. Addressing these challenges requires monitoring and modelling approaches that can capture complex spatial and temporal processes while also producing information that supports practical management decisions.

Building on the research of the previous Special Issue "Integrating Remote Sensing, Machine Learning, and Process-Based Modelling for Monitoring Environmental and Agricultural Landscapes Under Climate Change", this renewed collection will focus on the integration of Earth observation and airborne technologies, artificial intelligence, machine learning, deep learning, process-based models, and biophysical modelling for the assessment and management of environmental and agricultural systems. Particular emphasis will be placed on approaches that move beyond observation alone by linking spatial data, predictive modelling, and decision-support frameworks to climate adaptation, sustainable production, ecosystem restoration, and natural-resource management.

We welcome original research articles, reviews, methodological papers, and case studies addressing topics including, but not limited to, the following:

• Multiscale environmental and agricultural monitoring using satellite, airborne, UAV, LiDAR, radar, thermal, and hyperspectral observations;
• Integration of remote sensing with process-based, biophysical, hydrological, crop, pasture, forestry, and ecosystem models;
• Machine learning, artificial intelligence, deep learning, geospatial AI, and foundation-model applications for environmental assessment and prediction;
• Data fusion involving multi-sensor, multi-platform, in situ, IoT, datalogger, and citizen-science observations;
• Monitoring of vegetation condition, biomass, productivity, soil moisture, water resources, carbon dynamics, biodiversity, habitat condition, and ecosystem health;
• Precision agriculture, pasture and rangeland management, forestry, regenerative agriculture, and climate-smart production systems;
• Detection and monitoring of land degradation, invasive species, drought, fire, flooding, soil erosion, and other landscape disturbances;
• Earth observation applications for landscape character assessment, ecosystem restoration, nature-based solutions, landscape rehydration, and climate resilience;
• Uncertainty analysis, model transferability, explainable AI, reproducibility, and operational implementation;
• Decision-support systems and spatial frameworks that translate scientific outputs into actionable strategies for policy, industry, land managers, and communities.

This Special Issue aims to demonstrate how integrated monitoring and modelling frameworks can improve understanding of environmental processes, strengthen predictive capability, and support timely and defensible management decisions. It will particularly highlight research that connects methodological innovation with real-world applications in sustainable land management, food and water security, carbon accounting, biodiversity conservation, disaster response, and climate adaptation.

Contributions from diverse regions, disciplines, and application contexts are encouraged, including studies undertaken in agricultural, forest, rangeland, coastal, urban, freshwater, and dryland environments.

Dr. Michael Gbenga Ogungbuyi
Dr. Dimitrios D. Alexakis
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-anonymized 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.