Context and objectives
Recent improvements in optical remote sensing through the launch of high quality decametre and metre scale sensors, i.e. the Operational Land Imagers on board Landsat 8/9 (2013/2022) and the MultiSpectral Instrument on board of Sentinel-2A/B (2015/2017) and their planned successor missions, as well as commercial cubesat imagers such as those on PlanetScope/Dove, has increased interest in remote sensing of narrow and small water bodies. At short spatial length scales the high resolution imagery is impacted by adjacency effects, which may dominate the signal. The RAdCor project aims to develop a generic and fast correction algorithm for these effects, and make it available in the open source ACOLITE processor.
Project outcome
Expected scientific results
The scientific results will be the availability of an adjacency correction algorithm, and improved remote sensing reflectance retrievals over narrow and small inland water bodies. These improved reflectance retrievals will lead to improved remote sensing derived products such as pigment concentration and water turbidity. Additional scientific results are expected from the application of this method to the previous research initiated during the PONDER and HYPERMAQ projects, targeting the Spuikom coastal lagoon.
Societal (including environmental) relevance
The monitoring of all inland water bodies is a daunting task, and prohibitively expensive to regularly do in situ (e.g. the Vlaamse milieumaatschappij only samples every lake only every 4 years). Through the use of remote sensing this monitoring frequency could be increased. The occurrence of algal blooms can for example impact human and animal health.
Products and services
The main product will be an open source adjacency correction algorithm integrated in ACOLITE, and adjacency corrected products for lakes sampled in PONDER and HYPERMAQ projects.
Additionally there will be products made available to early adopters external to the project who are working on inland water remote sensing.
Potential users
Remote sensing experts working in inland waters, water quality monitoring agencies.
| Project leader(s): | IRSNB/KBIN - Directorate Natural Environment - Ecosystems data processing and modelling | |||
| Belgian partner(s) |
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