Advanced Studies in Land Cover Change and Geographic Data Fusion

Dear Colleagues,

Land cover change tops research agendas in fields of remote sensing, geoinformatics, geography, ecology, and environmental science. Multi-source data are necessarily fused to enable accurate, high-resolution, and (near) real-time change monitoring and analyses. Spatial statistics in general and Bayesian inference in particular, especially accurate analytical approximation provided by INLA and SPDE, will have greater roles in these endeavors. This is because these new developments in Bayesian spatio-temporal statistical methods will be required to support multi- and cross-resolution data fusion, data and model integration, enhanced change monitoring and analyses, and uncertainty characterization. Spatio-temporal data assimilation will also find impetus for applications in land change analytics. Ultimately, the aforementioned methods and technical thrusts constitute the backbones of the emerging digital twins of the environment.

This Special Issue aims to publish papers which study the emerging important methodology and pursue technical advancements in change monitoring, spatio-temporal data fusion, data–model integration, change analyses, and uncertainty quantification and propagation. Topics of interest include, but are not limited to, the following:

• Land cover change typology;
• From change detection to change monitoring;
• Multi-source data technology and data streaming;
• Applied Bayesian statistics in geospatial domain;
• Data support and cross-resolution data modeling;
• Bayesian spatio-temporal data fusion;
• Bayesian downscaling;
• Land cover change as surface time series;
• Bayesian spatio-temporal data assimilation;
• New landscapes for machine learning;
• Uncertainty quantification and propagation;
• Statistical methodology towards building up digital twins of the environment;
• Case studies in natural resources and the environment.

Prof. Dr. Jingxiong Zhang
Dr. Ludovit Kovanic
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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.

• land cover change
• applied Bayesian statistics
• spatio-temporal data fusion
• remote sensing
• geoinformatics