[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Wang et al., 2022 - Google Patents

Developing remote sensing methods for monitoring water quality of alpine rivers on the Tibetan Plateau

Wang et al., 2022

View PDF
Document ID
18294202301703193860
Author
Wang S
Shen M
Liu W
Ma Y
Shi H
Zhang J
Liu D
Publication year
Publication venue
GIScience & Remote Sensing

External Links

Snippet

Water quality in alpine rivers on the Tibetan Plateau is a key indicator for eco-environment security in China, which, however, is difficult to be monitored over the plateau. In this study, several regression methods and physicals models based on hyperspectral satellite data and …
Continue reading at www.tandfonline.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3155Measuring in two spectral ranges, e.g. UV and visible
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/62Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64Fluorescence; Phosphorescence
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/75Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated
    • G01N21/77Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator
    • G01N21/78Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator producing a change of colour
    • G01N21/80Indicating pH value
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/84Systems specially adapted for particular applications
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01JMEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED, VISIBLE OR ULTRA-VIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J1/00Photometry, e.g. photographic exposure meter
    • G01J1/42Photometry, e.g. photographic exposure meter using electric radiation detectors
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01WMETEOROLOGY
    • G01W1/00Meteorology
    • G01W1/10Devices for predicting weather conditions
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/18Water
    • G01N33/1826Water organic contamination in water
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/18Water
    • G01N33/1886Water using probes, e.g. submersible probes, buoys

Similar Documents

Publication Publication Date Title
Rodríguez-López et al. Spectral analysis using LANDSAT images to monitor the chlorophyll-a concentration in Lake Laja in Chile
Lymburner et al. Landsat 8: Providing continuity and increased precision for measuring multi-decadal time series of total suspended matter
Brezonik et al. Factors affecting the measurement of CDOM by remote sensing of optically complex inland waters
Muster et al. Subpixel heterogeneity of ice-wedge polygonal tundra: a multi-scale analysis of land cover and evapotranspiration in the Lena River Delta, Siberia
Reinart et al. Mapping surface temperature in large lakes with MODIS data
Zhang et al. A Landsat 8 OLI-based, semianalytical model for estimating the total suspended matter concentration in the slightly turbid Xin’anjiang Reservoir (China)
Du et al. Tempo-spatial dynamics of water quality and its response to river flow in estuary of Taihu Lake based on GOCI imagery
Wang et al. Developing remote sensing methods for monitoring water quality of alpine rivers on the Tibetan Plateau
Yu et al. Assessment of total suspended sediment concentrations in Poyang Lake using HJ-1A/1B CCD imagery
Jiao et al. Estimation of chlorophyll‐a concentration in Lake Tai, China using in situ hyperspectral data
Liu et al. Satellite estimation of dissolved organic carbon in eutrophic Lake Taihu, China
Chen et al. A novel multi-source data fusion method based on Bayesian inference for accurate estimation of chlorophyll-a concentration over eutrophic lakes
Ma et al. Machine Learning Based Long‐Term Water Quality in the Turbid Pearl River Estuary, China
Gomes et al. Satellite estimates of euphotic zone and Secchi disk depths in a colored dissolved organic matter-dominated inland water
Duan et al. Estimation of chlorophyll‐a concentration and trophic states for inland lakes in Northeast China from Landsat TM data and field spectral measurements
Zhu et al. Landsat 8‐observed water quality and its coupled environmental factors for urban scenery lakes: A case study of West Lake
Tan et al. Using hyperspectral data to quantify water-quality parameters in the Wabash River and its tributaries, Indiana
Hochberg et al. Trends and variability in spectral diffuse attenuation of coral reef waters
Virdis et al. Remote sensing of tropical riverine water quality using sentinel-2 MSI and field observations
Wang et al. Detecting the spatial and temporal variability of chlorophyll-a concentration and total suspended solids in Apalachicola Bay, Florida using MODIS imagery
Kim et al. Application of airborne hyperspectral imagery to retrieve spatiotemporal CDOM distribution using machine learning in a reservoir
Zhu et al. Robust remote sensing retrieval of key eutrophication indicators in coastal waters based on explainable machine learning
Zheng et al. A semi-analytical model to estimate Chlorophyll-a spatial-temporal patterns from Orbita Hyperspectral image in inland eutrophic waters
Hu et al. Empirical ocean color algorithm for estimating particulate organic carbon in the South China Sea
Ciglenečki et al. Accumulation of organic matter in a mesotidal Mediterranean lagoon (Boughrara, Tunisia)