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Mapping Freshwater Chlorophyll-a Concentrations at a Regional Scale Integrating Multi-Sensor Satellite Observations with Google Earth Engine.
- Source :
-
Remote Sensing . Oct2020, Vol. 12 Issue 20, p3278. 1p. - Publication Year :
- 2020
-
Abstract
- Monitoring harmful algal blooms (HABs) in freshwater over regional scales has been implemented through mapping chlorophyll-a (Chl-a) concentrations using multi-sensor satellite remote sensing data. Cloud-free satellite measurements and a sufficient number of matched-up ground samples are critical for constructing a predictive model for Chl-a concentration. This paper presents a methodological framework for automatically pairing surface reflectance values from multi-sensor satellite observations with ground water quality samples in time and space to form match-up points, using the Google Earth Engine cloud computing platform. A support vector machine model was then trained using the match-up points, and the prediction accuracy of the model was evaluated and compared with traditional image processing results. This research demonstrates that the integration of multi-sensor satellite observations through Google Earth Engine enables accurate and fast Chl-a prediction at a large regional scale over multiple years. The challenges and limitations of using and calibrating multi-sensor satellite image data and current and potential solutions are discussed. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 12
- Issue :
- 20
- Database :
- Academic Search Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 146966948
- Full Text :
- https://doi.org/10.3390/rs12203278