Automated spectral transfer learning strategy for semi-supervised regression on Chlorophyll-a retrievals with Sentinel-2 imagery
Author:
Affiliation:
1. College of Electronic Science & Engineering, Jilin University, Changchun, People’s Republic of China
2. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, People’s Republic of China
Funder
Technological Research and Development Projects of Jilin
Land Observation Satellite Supporting Platform of National Civil Space Infrastructure Project
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2313856
Reference69 articles.
1. Retrieval of Chlorophyll a from Sentinel-2 MSI Data for the European Union Water Framework Directive Reporting Purposes
2. Chlorophyll-a Retrieval From Sentinel-2 Images Using Convolutional Neural Network Regression
3. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations
4. A DBSCAN-based framework to mine travel patterns from origin-destination matrices: Proof-of-concept on proxy static OD from Brisbane
5. Improved red-edge chlorophyll-a detection for Sentinel 2
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