Characterization of complex fluvial systems using remote sensing of spatial and temporal water level variations in the Amazon, Congo, and Brahmaputra Rivers

2010 ◽  
Vol 35 (3) ◽  
pp. 294-304 ◽  
Author(s):  
Hahn Chul Jung ◽  
James Hamski ◽  
Michael Durand ◽  
Doug Alsdorf ◽  
Faisal Hossain ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Level ◽  
Fluvial Systems ◽  
Water Level Variations

scholarly journals Mapping Substrate Types and Compositions in Shallow Streams

2019 ◽  
Vol 11 (3) ◽  
pp. 262 ◽  
Author(s):  
Milad Niroumand-Jadidi ◽  
Nima Pahlevan ◽  
Alfonso Vitti
Keyword(s):  
Remote Sensing ◽  
Water Column ◽  
Aquatic Vegetation ◽  
Image Data ◽  
Correction Method ◽  
Habitat Modeling ◽  
Fluvial Systems ◽  
Reflectance Data ◽  
Edge Band

Remote sensing of riverbed compositions could enable advances in hydro-morphological and habitat modeling. Substrate mapping in fluvial systems has not received as much attention as in nearshore, optically shallow inland, and coastal waters. As finer spatial-resolution image data become more available, a need emerges to expand research on the remote sensing of riverbed composition. For instance, research to date has primarily been based on spectral reflectance data from above the water surface without accounting for attenuation by the water-column. This study analyzes the impacts of water-column correction for substrate mapping in shallow fluvial systems (depth < 1 m). To do so, we performed three different experiments: (a) analyzing spectroscopic measurements in a hydraulic laboratory setting, (b) simulating water-leaving radiances under various optical scenarios, and (c) evaluating the potential to map bottom composition from a WorldView-3 (WV3) image of a river in Northern Italy. Following the retrieval of depth and diffuse attenuation coefficient ( K d ), bottom reflectances were estimated using a water-column correction method. The results indicated significant enhancements in streambed maps based on bottom reflectances relative to maps produced from above-water spectra. Accounting for deep-water reflectance, embedded in the water-column correction, was demonstrated to have the greatest impact on the retrieval of bottom reflectance in NIR bands, when the water column is relatively thick (>0.5 m) and/or when the water is turbid. We also found that the WV3’s red-edge band (i.e., 724 nm) considerably improved the characterization of submerged aquatic vegetation (SAV) densities from either above-water or retrieved bottom spectra. This study further demonstrated the feasibility of mapping SAV density classes from a WV3 image of the Sarca River in Italy by retrieving the bottom reflectances.

scholarly journals Remote Sensing Methods for the Biophysical Characterization of Protected Areas Globally: Challenges and Opportunities

2021 ◽  
Vol 10 (6) ◽  
pp. 384
Author(s):  
Javier Martínez-López ◽  
Bastian Bertzky ◽  
Simon Willcock ◽  
Marine Robuchon ◽  
María Almagro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Large Scale ◽  
Anthropogenic Activities ◽  
Global Scale ◽  
Area Network ◽  
Biophysical Characterization ◽  
Challenges And Opportunities ◽  
Scale Characterization

Protected areas (PAs) are a key strategy to reverse global biodiversity declines, but they are under increasing pressure from anthropogenic activities and concomitant effects. Thus, the heterogeneous landscapes within PAs, containing a number of different habitats and ecosystem types, are in various degrees of disturbance. Characterizing habitats and ecosystems within the global protected area network requires large-scale monitoring over long time scales. This study reviews methods for the biophysical characterization of terrestrial PAs at a global scale by means of remote sensing (RS) and provides further recommendations. To this end, we first discuss the importance of taking into account the structural and functional attributes, as well as integrating a broad spectrum of variables, to account for the different ecosystem and habitat types within PAs, considering examples at local and regional scales. We then discuss potential variables, challenges and limitations of existing global environmental stratifications, as well as the biophysical characterization of PAs, and finally offer some recommendations. Computational and interoperability issues are also discussed, as well as the potential of cloud-based platforms linked to earth observations to support large-scale characterization of PAs. Using RS to characterize PAs globally is a crucial approach to help ensure sustainable development, but it requires further work before such studies are able to inform large-scale conservation actions. This study proposes 14 recommendations in order to improve existing initiatives to biophysically characterize PAs at a global scale.

Water level estimation by remote sensing for the 2008 flooding of the Kosi River

2014 ◽  
Vol 35 (2) ◽  
pp. 424-440 ◽  
Author(s):  
Rajesh Kumar Pandey ◽  
Jean-François Crétaux ◽  
Muriel Bergé-Nguyen ◽  
Virendra Mani Tiwari ◽  
Vanessa Drolon ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Level
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