Research graph
References from Retrieval of Water Quality Parameters of Lake Taihu Based on Sentinel-2 Imagery. Local targets link to admitted publications; unresolved targets remain external evidence.
Changes of nutrients and phytoplankton chlorophyll-a in a large shallow lake, Taihu, China: An 8-year investigation
10.1023/b:hydr.0000008604.09751.01 · 2003 · External reference
Eutrophication in Peel Inlet—I. The problem-defining behavior and a mathematical model for the phosphorus scenario
10.1016/0043-1354(80)90039-1 · 1980 · External reference
10.3389/fenvs.2025.1549301
10.3389/fenvs.2025.1549301 · External reference
10.3390/w15173110
10.3390/w15173110 · External reference
Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer
10.1080/01431160500075857 · 2005 · External reference
Deep learning-based remote sensing retrieval of inland water quality: A review
2025 · External reference
Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms
10.1007/s11356-022-23431-9 · 2023 · External reference
Water quality variations in the lower Yangtze River based on GA-RF model from GF-1, Landsat-8, and Sentinel-2 images
10.1109/jstars.2025.3526207 · 2025 · External reference
Tempo-spatial dynamics of water quality and its response to river flow in estuary of Taihu Lake based on GOCI imagery
10.1007/s11356-017-0305-7 · 2017 · External reference
10.3390/w12113124
10.3390/w12113124 · External reference
Remote sensing inversion of water quality parameters in the Yellow River Delta
10.1016/j.ecolind.2023.110914 · 2023 · External reference
10.3390/rs16244793
10.3390/rs16244793 · External reference
10.3390/rs17020267
10.3390/rs17020267 · External reference
Development of remote sensing algorithm for total phosphorus concentration in eutrophic lakes: Conventional or machine learning?
10.1016/j.watres.2022.118213 · 2022 · External reference
Extreme climate anomalies enhancing cyanobacterial blooms in eutrophic Lake Taihu, China
10.1029/2020wr029371 · 2021 · External reference
Satellite retrievals of water quality for diverse inland waters from Sentinel-2 images: An example from Zhejiang Province, China
2024 · External reference
10.1117/12.2067123
10.1117/12.2067123 · External reference
Machine learning and deep learning
10.1007/s12525-021-00475-2 · 2021 · External reference
10.1145/2939672.2939785
10.1145/2939672.2939785 · External reference
A scalable tree boosting system: XG boost
2020 · External reference
10.1007/978-3-642-34062-8_32
10.1007/978-3-642-34062-8_32 · External reference
Random forest algorithm for soil fertility prediction and grading using machine learning
10.35940/ijitee.l3609.119119 · 2019 · External reference
Random Forest Algorithm Overview
10.58496/bjml/2024/007 · 2024 · External reference
10.1109/icaica54878.2022.9844516
10.1109/icaica54878.2022.9844516 · External reference
10.1007/978-3-642-34041-3_27
10.1007/978-3-642-34041-3_27 · External reference
Prediction of lake chlorophyll concentration using the BP neural network and Sentinel-2 images based on time features
10.2166/wst.2023.019 · 2023 · External reference
Brief introduction of back propagation (BP) neural network algorithm and its improvement
2012 · External reference
Multi-factor modeling of chlorophyll-a in South China’s subtropical reservoirs using long-term monitoring data for quantitative analysis
10.1016/j.envres.2026.124149 · 2026 · External reference
Unresolved reference
External reference
Comparison of different machine learning algorithms for predicting maize grain yield using UAV-based hyperspectral images
2023 · External reference
Detecting Associations Based on the Multi-Variable Maximum Information Coefficient
10.1109/access.2021.3070925 · 2021 · External reference
Detecting novel associations in large data sets
10.1126/science.1205438 · 2011 · External reference
An improved algorithm for the maximal information coefficient and its application
10.1098/rsos.201424 · 2021 · External reference
EEG feature selection method based on maximum information coefficient and quantum particle swarm
10.1038/s41598-023-41682-5 · 2023 · External reference
Long-term variations of phosphorus concentration and capacity in Lake Taihu, 2005–2018: Implications for future phosphorus reduction target management
2020 · External reference
10.3390/ijerph15112355
10.3390/ijerph15112355 · External reference
Light scattering properties and their relation to the biogeochemical composition of turbid productive waters: A case study of Lake Taihu
10.1364/ao.48.001979 · 2009 · External reference
A study of absorption characteristics of chromophoric dissolved organic matter and particles in Lake Taihu, China
10.1007/s10750-007-0724-4 · 2007 · External reference
Assessment of water constituents in highly turbid productive water by optimization bio-optical retrieval model after optical classification
10.1016/j.jhydrol.2014.09.007 · 2014 · External reference
Temporal-spatial distribution of nitrogen and phosphorus nutrients in Lake Taihu based on geostatistical analysis
2019 · External reference
10.3390/w13121704
10.3390/w13121704 · External reference
10.1007/s11783-023-1655-7
10.1007/s11783-023-1655-7 · External reference
Monitoring water quality using proximal remote sensing technology
10.1016/j.scitotenv.2021.149805 · 2022 · External reference
Widespread decrease of phosphorus and the potential driving mechanisms in Taihu basin’s lakes
2025 · External reference
Dynamics of cyanobacterial bloom and water quality in Lake Taihu under National Class III water quality achieved in 2024
2025 · External reference
Shallow lake limnology and control of eutrophication in Lake Taihu
2020 · External reference
Using Hyperion imagery to monitor the spatial and temporal distribution of colored dissolved organic matter in estuarine and coastal regions
10.1016/j.rse.2013.03.009 · 2013 · External reference
Variation and driving factors of nutrients and chlorophyll-a concentrations in northern region of Lake Taihu, China, 2005–2017
2018 · External reference
Spatial and temporal distribution of nitrogen species in sediment and interstitial waters of Taihu Lake
2010 · External reference
Mechanism research of the effects of water quality (nitrogen and phosphorus concentrations) and water volume on eutrophication of Lake Taihu
2022 · External reference
Stormwater runoff pollution loads from an urban catchment with rainy climate in China
10.1007/s11783-012-0447-2 · 2012 · External reference
Inversion model and daily variation of total phosphorus concentrations in Taihu lake based on GOCI data
2016 · External reference
10.1371/journal.pone.0127915
10.1371/journal.pone.0127915 · External reference
10.1007/978-3-642-34041-3_27
10.1007/978-3-642-34041-3_27 · ExternalCitation · doi-reference
10.1007/978-3-642-34062-8_32
10.1007/978-3-642-34062-8_32 · ExternalCitation · doi-reference
A study of absorption characteristics of chromophoric dissolved organic matter and particles in Lake Taihu, China
10.1007/s10750-007-0724-4 · ExternalCitation · doi-reference
Tempo-spatial dynamics of water quality and its response to river flow in estuary of Taihu Lake based on GOCI imagery
10.1007/s11356-017-0305-7 · ExternalCitation · doi-reference
Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms
10.1007/s11356-022-23431-9 · ExternalCitation · doi-reference
Stormwater runoff pollution loads from an urban catchment with rainy climate in China
10.1007/s11783-012-0447-2 · ExternalCitation · doi-reference
10.1007/s11783-023-1655-7
10.1007/s11783-023-1655-7 · ExternalCitation · doi-reference
Machine learning and deep learning
10.1007/s12525-021-00475-2 · ExternalCitation · doi-reference
Eutrophication in Peel Inlet—I. The problem-defining behavior and a mathematical model for the phosphorus scenario
10.1016/0043-1354(80)90039-1 · ExternalCitation · doi-reference
Remote sensing inversion of water quality parameters in the Yellow River Delta
10.1016/j.ecolind.2023.110914 · ExternalCitation · doi-reference
Multi-factor modeling of chlorophyll-a in South China’s subtropical reservoirs using long-term monitoring data for quantitative analysis
10.1016/j.envres.2026.124149 · ExternalCitation · doi-reference
Assessment of water constituents in highly turbid productive water by optimization bio-optical retrieval model after optical classification
10.1016/j.jhydrol.2014.09.007 · ExternalCitation · doi-reference
Using Hyperion imagery to monitor the spatial and temporal distribution of colored dissolved organic matter in estuarine and coastal regions
10.1016/j.rse.2013.03.009 · ExternalCitation · doi-reference
Monitoring water quality using proximal remote sensing technology
10.1016/j.scitotenv.2021.149805 · ExternalCitation · doi-reference
Development of remote sensing algorithm for total phosphorus concentration in eutrophic lakes: Conventional or machine learning?
10.1016/j.watres.2022.118213 · ExternalCitation · doi-reference
Changes of nutrients and phytoplankton chlorophyll-a in a large shallow lake, Taihu, China: An 8-year investigation
10.1023/b:hydr.0000008604.09751.01 · ExternalCitation · doi-reference
Extreme climate anomalies enhancing cyanobacterial blooms in eutrophic Lake Taihu, China
10.1029/2020wr029371 · ExternalCitation · doi-reference
EEG feature selection method based on maximum information coefficient and quantum particle swarm
10.1038/s41598-023-41682-5 · ExternalCitation · doi-reference
Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer
10.1080/01431160500075857 · ExternalCitation · doi-reference
An improved algorithm for the maximal information coefficient and its application
10.1098/rsos.201424 · ExternalCitation · doi-reference
Detecting Associations Based on the Multi-Variable Maximum Information Coefficient
10.1109/access.2021.3070925 · ExternalCitation · doi-reference
10.1109/icaica54878.2022.9844516
10.1109/icaica54878.2022.9844516 · ExternalCitation · doi-reference
Water quality variations in the lower Yangtze River based on GA-RF model from GF-1, Landsat-8, and Sentinel-2 images
10.1109/jstars.2025.3526207 · ExternalCitation · doi-reference
10.1117/12.2067123
10.1117/12.2067123 · ExternalCitation · doi-reference
Detecting novel associations in large data sets
10.1126/science.1205438 · ExternalCitation · doi-reference
10.1145/2939672.2939785
10.1145/2939672.2939785 · ExternalCitation · doi-reference
Light scattering properties and their relation to the biogeochemical composition of turbid productive waters: A case study of Lake Taihu
10.1364/ao.48.001979 · ExternalCitation · doi-reference
10.1371/journal.pone.0127915
10.1371/journal.pone.0127915 · ExternalCitation · doi-reference
Prediction of lake chlorophyll concentration using the BP neural network and Sentinel-2 images based on time features
10.2166/wst.2023.019 · ExternalCitation · doi-reference
10.3389/fenvs.2025.1549301
10.3389/fenvs.2025.1549301 · ExternalCitation · doi-reference
10.3390/ijerph15112355
10.3390/ijerph15112355 · ExternalCitation · doi-reference
10.3390/rs16244793
10.3390/rs16244793 · ExternalCitation · doi-reference
10.3390/rs17020267
10.3390/rs17020267 · ExternalCitation · doi-reference
10.3390/w12113124
10.3390/w12113124 · ExternalCitation · doi-reference
10.3390/w13121704
10.3390/w13121704 · ExternalCitation · doi-reference
10.3390/w15173110
10.3390/w15173110 · ExternalCitation · doi-reference
Random forest algorithm for soil fertility prediction and grading using machine learning
10.35940/ijitee.l3609.119119 · ExternalCitation · doi-reference
Random Forest Algorithm Overview
10.58496/bjml/2024/007 · ExternalCitation · doi-reference
