Spatial and temporal distribution analysis of dominant algae in Lake Taihu based on ocean and land color instrument data DOI Creative Commons

Yuxin Zhu,

Yunmei Li, Shun Bi

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 155, P. 110959 - 110959

Published: Sept. 27, 2023

The proliferation of algal blooms can lead to environmental issues. phytoplankton responsible for these are diverse. Different species bloom-forming algae have distinct characteristics and hazards, therefore need different treatment methods. An accurate quick determination the spatial temporal distribution is crucial lake ecological restoration. Based on differences in remote sensing reflectance (Rrs) various typical eutrophic lakes (including Microcystis aeruginosa, Aphanizomenon sp., Pseudanabaena sp. Cyanobacteria Chlorella Scenedesmus quadricauda Chlorophytes), difference index distinguishing were developed differentiate species. A validation, using an independent dataset from indoor experiment in-situ-measured satellite-image-derived Rrs, showed that algorithm provide reliable results (overall accuracies 81.97%, 81.25%, 60.42%, respectively). According Ocean Land Color Instrument images Lake Taihu period 2016 2020, was dominant algae, followed by Aphanizomenon. dominance two types Chlorophytes less pronounced. proportion as highest summer, while peaked winter. varied slightly throughout year, In terms distribution, patterns spring autumn relatively similar. approximately 80% dominated Microcystis. winter, more prevalent along southeastern shore Taihu. construction application this model a technical support prediction prevention inland lakes.

Language: Английский

Remote sensing for mapping algal blooms in freshwater lakes: a review DOI
Sílvia Beatriz Alves Rolim, Bijeesh Kozhikkodan Veettil,

Antônio Pedro Vieiro

et al.

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(8), P. 19602 - 19616

Published: Jan. 16, 2023

Language: Английский

Citations

34
Cyanotoxins, biosynthetic gene clusters, and factors modulating cyanotoxin biosynthesis DOI

Fahim Bashir,

Arif Bashir,

Noureddine Bouaı̈cha

et al.

World Journal of Microbiology and Biotechnology, Journal Year: 2023, Volume and Issue: 39(9)

Published: July 3, 2023

Language: Английский

Citations

23
Application of Remote Sensing Technology in Water Quality Monitoring: From Traditional Approaches to Artificial Intelligence DOI

Yuan Sun,

Denghui Wang, P. R. Li

et al.

Water Research, Journal Year: 2024, Volume and Issue: 267, P. 122546 - 122546

Published: Sept. 30, 2024

Language: Английский

Citations

10
Remote sensing of cyanobacterial harmful algal blooms: Current trends and future directions DOI
Abhishek Kumar, Chintan Maniyar,

Isabella R. Fiorentino

et al.

Progress in Environmental Geography, Journal Year: 2025, Volume and Issue: 4(1), P. 131 - 150

Published: March 1, 2025

Cyanobacterial harmful algal blooms (CyanoHABs) pose significant threats to aquatic ecosystems, public health, and economic sustainability worldwide. This progress report explores recent advancements in CyanoHAB detection, quantification, monitoring using multi-sensor remote sensing approaches, artificial intelligence (AI) applications, their integration with health impact studies. We presented the capabilities of various satellite sensors CyanoHABs across different spatial temporal scales, discussing multiple data sources overcome individual sensor limitations. The highlights promise AI, particularly machine learning (ML) techniques, improving detection forecasting, demonstrating how ML methods consistently outperformed traditional algorithms estimating phycocyanin concentrations, a key indicator CyanoHABs.We examined development cloud-based applications for real-time awareness. Furthermore, we explored impacts on humans animals, emphasizing role mitigating these effects. implications CyanoHAB-related issues are discussed, along potential integrating epidemiological Overall, this underscores importance cross-disciplinary, integrated approaches that combine cutting-edge technologies, advanced assessments address complex challenges posed by inland waters.

Language: Английский

Citations

1
Effects of spectral variability due to sediment and bottom characteristics on remote sensing for suspended sediment in shallow rivers DOI
Siyoon Kwon, Hyoseob Noh, Il Won Seo

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 878, P. 163125 - 163125

Published: March 28, 2023

Language: Английский

Citations

19
Chlorophyll-a Detection Algorithms at Different Depths Using In Situ, Meteorological, and Remote Sensing Data in a Chilean Lake DOI Creative Commons
Lien Rodríguez‐López, Denisse Álvarez, David Francisco Bustos Usta

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(4), P. 647 - 647

Published: Feb. 9, 2024

In this study, we employ in situ, meteorological, and remote sensing data to estimate chlorophyll-a concentration at different depths a South American freshwater ecosystem, focusing specifically on lake southern Chile known as Lake Maihue. For our analysis, explored four scenarios using three deep learning traditional statistical models. These involved field (Scenario 1), meteorological variables 2), satellite (Scenarios 3.1 3.2) predict levels Maihue (0, 15, 30 m). Our choice of models included SARIMAX, DGLM, LSTM, all which showed promising performance predicting concentrations lake. Validation metrics for these indicated their effectiveness chlorophyll levels, serve valuable indicators the presence algae water body. The coefficient determination values ranged from 0.30 0.98, with DGLM model showing most favorable statistics tested. It is worth noting that LSTM yielded comparatively lower metrics, mainly due limitations available training data. employed, use machine data, have great potential application lakes rest world similar characteristics. addition, results constitute fundamental resource decision-makers protection conservation quality.

Language: Английский

Citations

6
Spatiotemporal Expansion of Algal Blooms in Coastal China Seas DOI
Kai Zeng,

Elamurugu Alias Gokul,

Haifeng Gu

et al.

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(29), P. 13076 - 13086

Published: May 23, 2024

The coastal seas of China are increasingly threatened by algal blooms, yet their comprehensive spatiotemporal mapping and understanding underlying drivers remain challenging due to high turbidity heterogeneous water conditions. We developed a singular value decomposition-based algorithm map these blooms using two decades MODIS-Aqua satellite data, spanning from 2003 2022. Our findings indicate significant activity along the Chinese coastline, impacting an average annual area approximately 1.8 × 10

Language: Английский

Citations

6
China’s ongoing rural to urban transformation benefits the population but is not evenly spread DOI Creative Commons
Xin Chen, Le Yu, Yaoyao Li

et al.

Communications Earth & Environment, Journal Year: 2024, Volume and Issue: 5(1)

Published: Aug. 4, 2024

China prioritizes a coordinated and sustainable shift from rural to urban areas, termed rural-urban transformation. This involves land, population, industry urbanization. Here we explore the spatiotemporal dynamics of transformation patterns in China, focusing on degree integrated coupling between three tracks. To conduct our investigation, utilized urbanization cube theory, satellite-derived gridded datasets, self-organizing map. Our findings show that eastern has higher levels compared western China. There been an overall increase China's We identified six typical across Over time, 53.58% prefectures improved patterns, 3.44% degraded, 42.98% (mainly China) remained unchanged. More importantly, highlight increasing reduced inequities well-being. The rural-to-urban integrates changes land use, development reduces well-being is more evident East but not West according analysis combines satellite data, statistical analysis, machine learning.

Language: Английский

Citations

6
Synergistic retrieval of mangrove vital functional traits using field hyperspectral and satellite data DOI Creative Commons
Bolin Fu, Yan Wu, Shurong Zhang

et al.

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2024, Volume and Issue: 131, P. 103963 - 103963

Published: June 13, 2024

Language: Английский

Citations

5
Examining the Effects of Soil and Water Conservation Measures on Patterns and Magnitudes of Vegetation Cover Change in a Subtropical Region Using Time Series Landsat Imagery DOI Creative Commons
Xiaoyu Sun, Guiying Li,

Qinquan Wu

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(4), P. 714 - 714

Published: Feb. 18, 2024

Soil and water erosion has long been regarded as a serious environmental problem in the world. Thus, research on reducing soil received continuous attention. Different conservation measures such restoring low-function forests, closing hillsides for afforestation, planting trees grass, constructing terraces slope land have implemented controlling problems promoting vegetation cover change. One important task is to understand effects of different problems. However, directly conducting evaluation reduction difficult. solution evaluate patterns magnitudes change due implementing these measures. Therefore, this selected Changting County, Fujian Province case study examine based time series Landsat images field survey data. between 1986 2021 were used produce data using Google Earth Engine. Sentinel-2 acquired 2010 separately develop maps random forest method. The spatial distribution was linked annual cover. results showed significant bare lands increase pine forests. coverage increased from 42% 79% region compared with an 73% 87% non-conservation during same period. Of measures, magnitude 0.44 forests afforestation 0.65 multiple control This provides new insights terms understanding taking proper scientific decisionmaking controls. strategy method are valuable other regions roles through employing remote sensing technologies.

Language: Английский

Citations

4