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Challenges for chlorophyll-a remote sensing in a highly variable turbidity estuary, an implementation with Sentinel-2
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A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques.
A global approach for chlorophyll-a retrieval across optically complex inland waters based on optical water types
Assessing the effectiveness of Landsat 8 chlorophyll a retrieval algorithms for regional freshwater monitoring.
Automatic Mapping and Monitoring of Marine Water Quality Parameters in Hong Kong Using Sentinel-2 Image Time-Series and Google Earth Engine Cloud Computing
Challenges for chlorophyll-a remote sensing in a highly variable turbidity estuary, an implementation with Sentinel-2
Chlorophyll-a and total suspended solids retrieval and mapping using Sentinel-2A and machine learning for inland waters
Comparing deep learning with several typical methods in prediction of assessing chlorophyll-a by remote sensing: a case study in Taihu Lake, China
Comparison of Landsat 8 and Landsat 7 for regional measurements of CDOM and water clarity in lakes
Estimating Chlorophyll-a of Inland Water Bodies in Greece Based on Landsat Data
Estimation of Chlorophyll-a Concentrations in Lanalhue Lake Using Sentinel-2 MSI Satellite Images
Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine
Land–Lake Linkage and Remote Sensing Application in Water Quality Monitoring in Lake Okeechobee, Florida, USA
Monitoring Water Quality of Valle de Bravo Reservoir, Mexico, Using Entire Lifespan of MERIS Data and Machine Learning Approaches
Multi-Reservoir Water Quality Mapping from Remote Sensing Using Spatial Regression
Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types
Preliminary examination of influence of Chlorophyll, Total Suspended Material, and Turbidity on Satellite Derived-Bathymetry estimation in coastal turbid water
Retrieving Inland Reservoir Water Quality Parameters Using Landsat 8-9 OLI and Sentinel-2 MSI Sensors with Empirical Multivariate Regression
Sea water quality monitoring using remote sensing techniques: a case study in Tangier-Ksar Sghir coastline.
Selecting the Best Band Ratio to Estimate Chlorophyll-a Concentration in a Tropical Freshwater Lake Using Sentinel 2A Images from a Case Study of Lake Ba Be (Northern Vietnam)
Spatiotemporal Dynamics of Water Quality Indicators in Koka Reservoir, Ethiopia
Paper Details
Paper Name:
Challenges for chlorophyll-a remote sensing in a highly variable turbidity estuary, an implementation with Sentinel-2
Authors:
F. Maciel,S. Haakonsson,Lucia Ponce de León,S. Bonilla,F. Pedocchi
Journal:
Geocarto International
Date:
2022
URL:
https://app.readcube.com/library/eeeabbd4-b0f2-4d1d-af2b-b1d02dd21a9d/item/498dc93f-1c88-49bc-98ff-c7405695ee03
DOI:
10.1080/10106049.2022.2160017
Add Data
Sample (n)
Parameter
Model/Algorithm
Formula
r^2
RMSE
Study Area
Satellite
Reference
Formula Details
Sample (n)
Parameter
Model/Algorithm
Formula
r^2
RMSE
Study Area
Satellite
Reference
43
Chl-a
Linear Regression
chl-a = 214.07(3BI) + 17.53
0.959999978542328
6.40000009536743
Punta del Tigre
Sentinel-2
Formula 2 - 3BI
43
Chl-a
Linear Regression
chl-a = 762.6(NDCI)^2 + 207.4(NDCI) + 16.4(*)
0.980000019073486
4.90000009536743
Punta del Tigre
Sentinel-2
Formula 2 - NDCI
38
Chl-a
Linear Regression
chl-a = 3154.7(IDrozd)^4.86
0.769999980926514
17.7999992370605
Punta del Tigre
Sentinel-2
Formula 3 - IDrozd
43
Chl-a
Linear Regression
chl-a = 66067(B4)^2-1726.9(B4)+13.65(***)
0.959999978542328
7.19999980926514
Punta del Tigre
Sentinel-2
Formula 4 - SS(665)