Validation and Inter-Comparison of Land Cover and Land Use Data

Dear Colleagues,

The generation of land cover and land use data remains an evolving field in providing essential information for many policy and scientific applications, such as climate modeling, biodiversity, ecosystem assessment, food security, and environmental modeling. Data are being generated using different approaches and novel technologies (i.e., remote sensing, crowdsourcing, sensor webs, surveying, etc.) with increasing levels of detail and accuracy in space, time, and thematic attributes. While datasets are derived from various initiatives and with different strategies for using input data, methodologies, and standards, they often lack comparability and (accuracy) assessments of their strengths and weaknesses for certain users and applications. Approaches for validation and inter-comparison remain vital in a field that is dynamic and is responding to both the opportunities from novel technologies and increasing demands from a growing user community. The ambitions in science and practice are to address (for example) more detailed spatial scales (i.e., global land monitoring from Landsat-type data), more consistent land change using a longer-time series (i.e., via big-data approaches), integration of different data sources (i.e., remote sensing and crowdsourcing), and increasingly a focus on land use (rather than land cover only). These areas of interest require robust approaches and studies for accuracy-driven comparisons and assessments of data and methods and the incorporation of user needs to synthesize the full potential of new technologies for applications. In that context, we would like to invite you to submit articles about your recent research with respect to the following topics:

(1)   Methodologies for validation and inter-comparison: theory and practice
(2)   Accuracy-driven inter-comparison of land cover and land use datasets (including regional and global case studies)
(3)   Integration of land cover and land use data from different observation sources including crowdsourced data
(4)   Comparison of large-area estimates for land change
(5)   Generation and analysis of reference/validation datasets
(6)   Monitoring land cover and land use (change): novel concepts and methods
(7)   Approaches and experiences dealing with conflating information
(8)   User needs and implications for land monitoring, intercomparison and accuracy assessments
(9)   Review articles covering one or more of these topics are also welcome.

Prof. Dr. Martin Herold
Dr. Linda See
Guest Editors

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