Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …

Land cover change detection (LCCD) with remote sensing images is an important
application of Earth observation data because it provides insights into environmental health …

Data science models, although successful in a number of commercial domains, have had
limited applicability in scientific problems involving complex physical phenomena. Theory …

Deep learning has substantially pushed forward remote sensing image change detection
through extracting discriminative hierarchical features. However, as the increasingly high …

Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …

Geosciences is a field of great societal relevance that requires solutions to several urgent
problems facing our humanity and the planet. As geosciences enters the era of big data …

Nowadays, modern earth observation programs produce huge volumes of satellite images
time series that can be useful to monitor geographical areas through time. How to efficiently …

Given the growing use of Artificial intelligence (AI) and machine learning (ML) methods
across all aspects of environmental sciences, it is imperative that we initiate a discussion …

Land cover information is essential in European Union spatial management, particularly that
of invasive species, natural habitats, urbanization, and deforestation; therefore, the need for …

In their applications, both deep learning techniques and object-based image analysis (OBIA)
have shown better performance separately than conventional methods on change detection …