Extracting Coastal Water Depths from Multi-Temporal Sentinel-2 Images Using Convolutional Neural Networks

Satellite-Derived Bathymetry (SDB) can be calculated using analytical or empirical approaches. Analytical approaches require several water properties and assumptions, which might not be known. Empirical approaches rely on the linear relationship between reflectances and in-situ depths, but the relationship may not be entirely linear due to...

Satellite-derived bathymetry using convolutional neural networks and multispectral sentinel-2 images

Satellite-Derived Bathymetry (SDB) has been used in many applications related to coastal management. SDB can efficiently fill data gaps obtained from traditional measurements with echo sounding. However, it still requires numerous training data, which is not available in many areas. Furthermore, the accuracy problem still arises considering...

Computational modelling of terrains

The book Computational modelling of terrains presents an overview of algorithms and methodologies to reconstruct, manipulate, and extract information from terrains.<br/><br/>It covers different representations of terrains (eg TINs, rasters, point clouds, contour lines) and presents techniques to handle large datasets.

Population Estimation Using a 3D City Model: A Multi-Scale Country-Wide Study in the Netherlands

The remote estimation of a region’s population has for decades been a key application of geographic information science in demography. Most studies have used 2D data (maps, satellite imagery) to estimate population avoiding field surveys and questionnaires. As the availability of semantic 3D city models is constantly increasing, we investigate...