[HTML][HTML] Advancing cyanobacteria biomass estimation from hyperspectral observations: Demonstrations with HICO and PRISMA imagery

RE O'Shea, N Pahlevan, B Smith, M Bresciani… - Remote Sensing of …, 2021 - Elsevier
Retrieval of the phycocyanin concentration (PC), a characteristic pigment of, and proxy for,
cyanobacteria biomass, from hyperspectral satellite remote sensing measurements is …

Estimating soil salinity in Pingluo County of China using QuickBird data and soil reflectance spectra

A Sidike, S Zhao, Y Wen - … Journal of Applied Earth Observation and …, 2014 - Elsevier
Soil salinization is a worldwide environmental problem with severe economic and social
consequences. In this paper, estimating the soil salinity of Pingluo County, China by a partial …

Remote estimation of phycocyanin concentration in inland waters based on optical classification

L Lyu, K Song, Z Wen, G Liu, C Fang, Y Shang… - Science of The Total …, 2023 - Elsevier
In recent years, under the dual pressure of climate change and human activities, the
cyanobacteria blooms in inland waters have become a threat to global aquatic ecosystems …

Using machine learning algorithms with in situ hyperspectral reflectance data to assess comprehensive water quality of urban rivers

J Cai, J Chen, X Dou, Q Xing - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Remotely sensed hyperspectral data can support more effective water quality monitoring.
Nevertheless, the variability and complexity of urban river water make it hard to retrieve …

Digital mapping of soil organic carbon density using newly developed bare soil spectral indices and deep neural network

Q Liu, L He, L Guo, M Wang, D Deng, P Lv, R Wang… - Catena, 2022 - Elsevier
Soil organic carbon density (SOCD) is an important parameter of agricultural soils and is
useful for the improvement of environment and agricultural production. Proximal and remote …

Enhancing tomato leaf nitrogen analysis through portable NIR spectrometers combined with machine learning and chemometrics

D Abderrahim, S Taoufiq, I Bouchaib… - … and Intelligent Laboratory …, 2023 - Elsevier
Plant-Nitrogen is a vital element that significantly influences plant growth, fruit quality, and
yield. However, excessive Nitrogen (N) fertilizer application can have adverse effects on …

Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning–based gamma test variable selection and empirical wavelet transform

S Heddam, ZM Yaseen, MW Falah, L Goliatt… - … Science and Pollution …, 2022 - Springer
This study aims to evaluate the usefulness and effectiveness of four machine learning (ML)
models for modelling cyanobacteria blue-green algae (CBGA) at two rivers located in the …

[HTML][HTML] Monitoring phycocyanin concentrations in high-latitude inland lakes using Sentinel-3 OLCI data: The case of Lake Hulun, China

X Wang, C Fang, K Song, L Lyu, Y Li, F Lai, Y Lyu… - Ecological …, 2023 - Elsevier
With the intensification of global warming, eutrophication in lakes at high latitudes of China
has become increasingly severe, with the harm of blue-green algae blooms also on the rise …

[HTML][HTML] Hyperspectral sensing for turbid water quality monitoring in freshwater rivers: empirical relationship between reflectance and turbidity and total solids

JL Wu, CR Ho, CC Huang, AL Srivastav, JH Tzeng… - Sensors, 2014 - mdpi.com
Total suspended solid (TSS) is an important water quality parameter. This study was
conducted to test the feasibility of the band combination of hyperspectral sensing for inland …

Impact of spectral resolution on quantifying cyanobacteria in lakes and reservoirs: A machine-learning assessment

K Zolfaghari, N Pahlevan, C Binding… - … on Geoscience and …, 2021 - ieeexplore.ieee.org
Cyanobacterial harmful algal blooms are an increasing threat to coastal and inland waters.
These blooms can be detected using optical radiometers due to the presence of …