Mapping Land Productivity Dynamics with Time-Series of Remote Sensing Images

Dear Colleagues,

Land is our shared, essential resource. It maintains healthy ecosystems and supports the flora and fauna; it is the foundation of our society and it is also a source for economic growth. Yet, it is under intense pressure, far beyond the limit of sustainable development for our planet. Food demand is increasing globally, whereas climate change and extreme events are critically impacting the functioning of all ecosystems on Earth. To satisfy the ever-growing demands for land resources, intensive use of lands manifests in the over-exploitation of ecosystems, which may cause the irreversible loss of ecosystem functions, in many cases leading to land degradation. A comprehensive understanding of all interactions between the biosphere, the climate, the biogeochemical cycle, and socio-economic impacts requires one to properly linking the related drivers of land productivity dynamics.

Land productivity dynamics should be monitored and mapped over time and space and mapped on a large scale using high-repeat frequency and spatially continuous observation approaches. These approaches have to be supported by quantitative, robust, reliable, and comparable methods to supply a standardized framework for land degradation studies. Earth Observation sensors, techniques, methods, and approaches are now advanced enough to support policy makers with sound, quantitative, and comparable assessments. Remote sensing-derived land productivity parameters have a strong added value in completing the mapping of the condition and degradation of ecosystems. They capture the spatial patterns of vegetation dynamics repetitively over vast areas; they are directly related to key aspects of vegetation dynamism such as seasonality, productivity, and inter-annual variation; and they provide an integrated measure of ecosystem responses to climatic factors, to extreme events, as well as to anthropogenic disturbances.

This Special Issue aims at presenting the latest advances in EO-based research for monitoring land productivity dynamics and related land degradation patterns. We welcome papers discussing challenges and opportunities in mapping land productivity dynamics and related land degradation over case studies. Emphasis is put on those interdisciplinary approaches, which link Earth Observation-derived land productivity, and other vegetation remote sensing-related paramaters to climatic and socio-economic drivers of land degradation. Articles covering but not limited to recent research on the following topics are invited to this Special Issue:

• Remote Sensing data and methods for estimating land productivity dynamics (e.g., biophysical variables, Gross Primary Production, and above-ground biomass);
• Integration of RS-derived land productivity data with in situ data and other expert knowledge;
• Approaches to monitoring land degradation using Remote Sensing-derived land productivity;
• Research demonstrating new use of EO-based land productivity dynamics for assessing of, and accounting for sustainable land use and/or change in ecosystem functioning;
• Apporaches to facilitate reporting on land degradation addressing international targets or conventions (such as the SDGs, the UNCCD, the UNFCCC, etc.);
• Methods using high and very high resolution satellite images such as the Sentinel systems;
• Advanced processing methods to process time series of land porductivity dynamics such as Artificial Intelligence, cloud computing environments, and big data cubes.

We are looking forward to high-quality submissions on the topic of monitoring land productivity dynamics and to an exciting and fruitful collaboration with the research community in these critical times of increasing global environmental crises.

Dr. Eva Ivits
Dr. Stephanie Horion
Dr. Roel Van Hoolst
Guest Editors

Manuscript Submission Information

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