Advances in Space Research, Journal Year: 2024, Volume and Issue: 74(1), P. 117 - 129
Published: March 28, 2024
Language: Английский
Advances in Space Research, Journal Year: 2024, Volume and Issue: 74(1), P. 117 - 129
Published: March 28, 2024
Language: Английский
Chemosphere, Journal Year: 2023, Volume and Issue: 343, P. 140198 - 140198
Published: Sept. 15, 2023
Language: Английский
Citations
15Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2023, Volume and Issue: 134, P. 103536 - 103536
Published: Dec. 19, 2023
Language: Английский
Citations
13Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 229 - 229
Published: Jan. 6, 2024
The spatiotemporal variations in suspended sediment concentration (SSC) the lower reaches of Yellow River exhibit significant variability and are influenced by reservoir operations. Understanding distribution characteristics SSC water holds crucial implications for environmental protection operation management. Based on daily-scale monitoring data from four hydrological stations River, this study established an remote sensing model applicable to Landsat series satellite data. independent variable model, Rrs(NIR)/(Rrs(G) + Rrs(R) Rrs(SWIR)), demonstrated sensitivity bodies with different values. Distinctive transport were observed across River. Spatially, values Sanmenxia Xiaolangdi reservoirs notably than those other river sections, averaging 1008.42 ± 602.83 mg/L 1177.89 627.95 mg/L, respectively. Over time, majority sections (96%) exhibited decreasing trends during 1984–2022, particularly downstream reservoir, average 4265.58 1101.77 1980s 1840.80 2255.15 2020s. Seasonal prominent, higher summer concentrations, 5536.43 2188.77 (2020s summer) 814.11 158.27 winter). Reductions 1984–2022 primarily occurred summer, weakening its seasonal Water discharge emerged as a critical factor influencing transport, increasing high-water-flow months. Following construction relationship between at underwent notable alterations. This enhances our understanding dynamics providing valuable insights utilizing long-term dynamic transport.
Language: Английский
Citations
5International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)
Published: March 11, 2024
Optical Water Type (OWT) analysis is crucial for comprehending water composition and quality, key factors in assessing quality over extensive areas. However, China's inland waters lack a standardized system such analysis. To quantitatively analyze the classification results, our study compared three K-means clustering methods, analyzing 1310 spectral data from various Chinese lakes reservoirs, thereby addressing this gap. The innovative split-merge method identified 13 distinct OWTs that more closely adhere to principles of minimizing intra-class distance maximizing inter-class distance. These were categorized into four groups: clear water, turbid eutrophic special type water. Additionally, we developed based on Spectral Angle Distance (SAD) evaluate capabilities 12 satellite sensors. results show Sentinel-3 OLCI (Ocean Land Color Instrument), MERIS (Medium Resolution Imaging Spectrometer), Sentinel-2 MSI (Multispectral Instrument) have best capabilities, making them well-suited large-scale monitoring OWT changes. Conversely, other sensors, as Sustainable Development Scientific Satellite-1 (SDGSAT-1), Landsat-8, GaoFen-6, GaoFen-1, GaoFen-2, Landsat-5, Landsat-7, Moderate Spectroradiometer (MODIS), HuanJing-1, necessitate consolidation types effective categorization, indicative their limited capabilities.
Language: Английский
Citations
5Advances in Space Research, Journal Year: 2024, Volume and Issue: 74(1), P. 117 - 129
Published: March 28, 2024
Language: Английский
Citations
5