Lake and reservoir volume variability from satellite imagery data: An assessment of the usability of high-resolution digital elevation models to extract water levels

Recent research suggested that the digital elevation models can be considered, as an alternative to the altimetry data. However, the water prohibits the ability of monitoring the construction the waterbed, due to the loss of the returning signal. The elevation models have therefore a flat surface, which prohibits the extraction of the water...

A machine learning assessment of multi-resolution remote sensing data for Natura 2000 dune habitat classification

Coastal dunes habitats are in the transition zone of marine and terrestrial ecosystems and therefore have high biodiversity in terms of animal and vegetation species. These species provide important ecosystem services to the human kind. Due to the development and operation of Maasvlakte 2, an increase of nitrogen emission is expected in the...

Estimating Total Suspended Matter in Low to Extremely High Level Turbid River Surface Waters using a WISP-3 Hyperspectral Radiometer and Sentinel-2 Optical Imagery: A case study conducted on the Brantas River Basin, East-Java, Indonesia

This research focuses on using Sentinel-2 optical imagery to provide a means of high-resolution monitoring and evaluation of changes in Total Suspended Matter (TSM) concentration in the Brantas river basin. In situ spectral measurements as well as laboratory results show an extremely turbid nature of the Brantas River surface water. Current...

Comparing thresholding with machine learning classifiers for mapping complex water

Small reservoirs play an important role in mining, industries, and agriculture, but storage levels or stage changes are very dynamic. Accurate and up-to-date maps of surface water storage and distribution are invaluable for informing decisions relating to water security, flood monitoring, and water resources management. Satellite remote...