Water Quality Chl-a Inversion Based on Spatio-Temporal Fusion and Convolutional Neural Network
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Water Quality Chl-a Inversion Based on Spatio-Temporal Fusion and Convolutional Neural Network
Authors
Keywords
-
Journal
Remote Sensing
Volume 14, Issue 5, Pages 1267
Publisher
MDPI AG
Online
2022-03-07
DOI
10.3390/rs14051267
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Monitoring terrain elevation of intertidal wetlands by utilising the spatial-temporal fusion of multi-source satellite data: A case study in the Yangtze (Changjiang) Estuary
- (2021) Wenli Gao et al. GEOMORPHOLOGY
- Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale
- (2021) Ahmed Samir Abowarda et al. REMOTE SENSING OF ENVIRONMENT
- Deep Learning with WASI Simulation Data for Estimating Chlorophyll a Concentration of Inland Water Bodies
- (2021) Philipp M. Maier et al. Remote Sensing
- Research on Inversion Mechanism of Chlorophyll—A Concentration in Water Bodies Using a Convolutional Neural Network Model
- (2021) Yun Xue et al. Water
- Retrieval model for total nitrogen concentration based on UAV hyper spectral remote sensing data and machine learning algorithms – A case study in the Miyun Reservoir, China
- (2021) Jiang Qun'ou et al. ECOLOGICAL INDICATORS
- Remote Sensing-Based Analysis of Spatial and Temporal Water Colour Variations in Baiyangdian Lake after the Establishment of the Xiong’an New Area
- (2021) Yelong Zhao et al. Remote Sensing
- Inversion of Chlorophyll-a Concentration in Donghu Lake Based on Machine Learning Algorithm
- (2021) Xiaodong Tang et al. Water
- Comparing deep learning with several typical methods in prediction of assessing chlorophyll-a by remote sensing: a case study in Taihu Lake, China
- (2021) Xiaolan Zhao et al. Water Science and Technology-Water Supply
- A novel multi-source data fusion method based on Bayesian inference for accurate estimation of chlorophyll-a concentration over eutrophic lakes
- (2021) Cheng Chen et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Modeling tree canopy height using machine learning over mixed vegetation landscapes
- (2021) Hui Wang et al. International Journal of Applied Earth Observation and Geoinformation
- Multisensor fusion of remotely sensed vegetation indices using space‐time dynamic linear models
- (2021) Margaret C Johnson et al. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS
- A decadal (2008–2017) daily evapotranspiration data set of 1 km spatial resolution and spatial completeness across the North China Plain using TSEB and data fusion
- (2021) Caijin Zhang et al. REMOTE SENSING OF ENVIRONMENT
- Remote sensing of sun-induced chlorophyll-a fluorescence in inland and coastal waters: Current state and future prospects
- (2021) Remika S. Gupana et al. REMOTE SENSING OF ENVIRONMENT
- Quantification of chlorophyll-a in typical lakes across China using Sentinel-2 MSI imagery with machine learning algorithm
- (2021) Sijia Li et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Different storm responses of organic carbon transported to Lake Taihu by the eutrophic Tiaoxi River, China
- (2021) Dong Liu et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Reconstruction of arctic SST data and generation of multi-source satellite fusion products with high temporal and spatial resolutions
- (2021) Yuheng Li et al. Remote Sensing Letters
- High concentrations of dissolved biogenic methane associated with cyanobacterial blooms in East African lake surface water
- (2021) Stefano Fazi et al. Communications Biology
- Chlorophyll-a Retrieval From Sentinel-2 Images Using Convolutional Neural Network Regression
- (2021) Erchan Aptoula et al. IEEE Geoscience and Remote Sensing Letters
- Water clarity changes in Lake Taihu over 36 years based on Landsat TM and OLI observations
- (2021) Ziyao Yin et al. International Journal of Applied Earth Observation and Geoinformation
- Feasibility of the Spatiotemporal Fusion Model in Monitoring Ebinur Lake’s Suspended Particulate Matter under the Missing-Data Scenario
- (2021) Changjiang Liu et al. Remote Sensing
- Impact of upstream landslide on perialpine lake ecosystem: An assessment using multi-temporal satellite data
- (2020) Paolo Villa et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Measuring the Urban Land Surface Temperature Variations Under Zhengzhou City Expansion Using Landsat-Like Data
- (2020) Haibo Yang et al. Remote Sensing
- Remote estimation of chlorophyll a concentrations over a wide range of optical conditions based on water classification from VIIRS observations
- (2020) Guangjia Jiang et al. REMOTE SENSING OF ENVIRONMENT
- Water remote sensing eutrophication inversion algorithm based on multilayer convolutional neural network
- (2020) Feng Lei et al. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
- Plastic pollution impacts on marine carbon biogeochemistry
- (2020) Luisa Galgani et al. ENVIRONMENTAL POLLUTION
- A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes
- (2020) Zhigang Cao et al. REMOTE SENSING OF ENVIRONMENT
- Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2
- (2020) Milad Niroumand-Jadidi et al. Remote Sensing
- Improved Radiometric and Spatial Capabilities of the Coastal Zone Imager Onboard Chinese HY-1C Satellite for Inland Lakes
- (2020) Zhigang Cao et al. IEEE Geoscience and Remote Sensing Letters
- Water quality related to Conservation Reserve Program (CRP) and cropland areas: Evidence from multi-temporal remote sensing
- (2020) Dameng Yin et al. International Journal of Applied Earth Observation and Geoinformation
- A Machine Learning Approach to Estimate Surface Chlorophyll a Concentrations in Global Oceans From Satellite Measurements
- (2020) Chuanmin Hu et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Retrieving the Lake Trophic Level Index with Landsat-8 Image by Atmospheric Parameter and RBF: A Case Study of Lakes in Wuhan, China
- (2019) Yadong Zhou et al. Remote Sensing
- Performance of Landsat-8 and Sentinel-2 surface reflectance products for river remote sensing retrievals of chlorophyll-a and turbidity
- (2019) Catherine Kuhn et al. REMOTE SENSING OF ENVIRONMENT
- Water-Quality Classification of Inland Lakes Using Landsat8 Images by Convolutional Neural Networks
- (2019) Fangling Pu et al. Remote Sensing
- Projected Climatic and Hydrologic Changes to Lake Victoria Basin Rivers under Three RCP Emission Scenarios for 2015–2100 and Impacts on the Water Sector
- (2019) Lydia A. Olaka et al. Water
- A Comprehensive and Automated Fusion Method: The Enhanced Flexible Spatiotemporal DAta Fusion Model for Monitoring Dynamic Changes of Land Surface
- (2019) Shi et al. Applied Sciences-Basel
- Coupling remote sensing data with in-situ optical measurements to estimate suspended particulate matter under the Evros river influence (North-East Aegean sea, Greece)
- (2019) Athina Tsapanou et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Effect of Satellite Temporal Resolution on Long-Term Suspended Particulate Matter in Inland Lakes
- (2019) Zhigang Cao et al. Remote Sensing
- Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression
- (2018) Hone-Jay Chu et al. International Journal of Applied Earth Observation and Geoinformation
- Evaluation of atmospheric correction and high-resolution processing on SeaDAS-derived chlorophyll-a: an example from mid-latitude mesotrophic waters
- (2018) James M. Bramich et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Fusing Landsat and MODIS data to retrieve multispectral information from fire-affected areas over tropical savannah environments in the Brazilian Amazon
- (2018) Daniel Borini Alves et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Improved MODIS-Aqua Chlorophyll-a Retrievals in the Turbid Semi-Enclosed Ariake Bay, Japan
- (2018) Meng Meng Yang et al. Remote Sensing
- Remote estimation of colored dissolved organic matter and chlorophyll-a in Lake Huron using Sentinel-2 measurements
- (2017) Jiang Chen et al. Journal of Applied Remote Sensing
- Application of Landsat 8 imagery to regional-scale assessment of lake water quality
- (2016) Jacek Andrzej Urbanski et al. International Journal of Applied Earth Observation and Geoinformation
- Analysis and Inversion of the Nutritional Status of China’s Poyang Lake Using MODIS Data
- (2016) Jiang Hui et al. Journal of the Indian Society of Remote Sensing
- A flexible spatiotemporal method for fusing satellite images with different resolutions
- (2016) Xiaolin Zhu et al. REMOTE SENSING OF ENVIRONMENT
- Barriers to adopting satellite remote sensing for water quality management
- (2013) Blake A. Schaeffer et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Assessing the accuracy of blending Landsat–MODIS surface reflectances in two landscapes with contrasting spatial and temporal dynamics: A framework for algorithm selection
- (2013) Irina V. Emelyanova et al. REMOTE SENSING OF ENVIRONMENT
- An Enhanced Spatial and Temporal Data Fusion Model for Fusing Landsat and MODIS Surface Reflectance to Generate High Temporal Landsat-Like Data
- (2013) Wei Zhang et al. Remote Sensing
- An Improved Image Fusion Approach Based on Enhanced Spatial and Temporal the Adaptive Reflectance Fusion Model
- (2013) Dongjie Fu et al. Remote Sensing
- Remote sensing of water quality in an Australian tropical freshwater impoundment using matrix inversion and MERIS images
- (2011) Glenn Campbell et al. REMOTE SENSING OF ENVIRONMENT
- Cogs in the endless machine: Lakes, climate change and nutrient cycles: A review
- (2011) Brian Moss SCIENCE OF THE TOTAL ENVIRONMENT
Add your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started