Algal Bloom Forecasting using Remote Sensing with Spatially and Temporally Sparse Satellite Data

Title

Algal Bloom Forecasting using Remote Sensing with Spatially and Temporally Sparse Satellite Data

 Author

de Gruyl, Einar (TU Delft Electrical Engineering, Mathematics and Computer Science)

Contributor

van Gemert, J.C. (mentor) ORCID 0000-0002-6913-0482
Lengyel, A. (mentor) ORCID 0000-0002-2982-2003
Bruintjes, R. (mentor) ORCID 0000-0002-9798-0214
Langendoen, K.G. (graduation committee) ORCID 0000-0003-4996-3695

 Degree granting institution

Delft University of Technology

 Programme

Computer Science and Engineering

 Project

CSE3000 Research Project

 Date

2023-01-31

 Abstract

This research presents a method for forecasting algal blooms using remote sensing with spatially and temporally sparse satellite data. The method involves the use of multiple interpolation methods to interpolate the sparse input data. The approach is shown to be effective in predicting algal blooms in areas where data is sparse, and the results demonstrate the potential for using this method to improve the forecasting and management of harmful algal blooms.

 Subject

Chlorophyll-a
Forecasting
Remote Sensing

 To reference this document use:

http://resolver.tudelft.nl/uuid:c9d5aaac-0477-4ca9-9c78-06c3abb8946e

 Coordinates

-33.09307,-57.31049

 Part of collection

Student theses

 Document type

bachelor thesis

 Rights

© 2023 Einar de Gruyl
Files
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