Mapping of the water quality of Lake Erken, Sweden, from Imaging Spectrometry and Landsat Thematic Mapper

Östlund, Catherine; Flink, Peter; Strömbeck, Niklas; Pierson, Don; Lindell, Tommy

doi:10.1016/s0048-9697(00)00683-5

Cited by 83 publications

(32 citation statements)

References 26 publications

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“…Remote sensing is the proven technology which can be visualized spatially and temporally and related methods can be used in establishing various water quality parameters was widely studied. [3][4][5][6][7][8]. Remote sensing has the ability to comprehend the changes in the past, estimate present impacts and gauge the future for effectual planning.…”

Section: Introductionmentioning

confidence: 99%

“…In inland surface waters the spatial resolution should be high for the estimation of quality constituents but is limited by high spectral resolution of the hyperspectral imagery. Thus, Lake water quality monitoring can be improved by the usage of field spectro-radiometer along with using satellite imagery [12,13,3] or the water quality can directly be derived from spectro-radiometer signatures from the field [14] overcoming the tedious conventional procedures. The large number of contiguous spectral bands of the hyperspectral imagery provides more prominent and accurate modeling of water quality parameters like Chl-a, TSS, SD, Turbidity etc., by Dekker et al [15].…”

Section: Introductionmentioning

confidence: 99%

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Hyper-spectral Remote Sensing of Water Quality Parameters in Lakes: A Case Study of Hyderabad City, Telangana State, India

Sailaja

Babu

Reddy

2017

IRA-JTE

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hyper-spectral Remote Sensing of Water Quality Parameters in Lakes: A Case Study of Hyderabad City, Telangana State, India

Sailaja

Babu

Reddy

2017

IRA-JTE

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“…Odermatt et al [12] have provided a comprehensive overview of water constituent retrieval algorithms and have found that the regression models for Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-5 Thematic Mapper (TM) images had a weaker performance compared with the NIR-red algorithms using MERIS and Moderate-resolution Imaging Spectroradiometer (MODIS) images. Moreover, high spatial resolution of remote sensing data is also required to detect changes in the distribution of complex coastal water and inland water [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

An Improved Unmixing-Based Fusion Method: Potential Application to Remote Monitoring of Inland Waters

Guo

Zhu

et al. 2015

Remote Sensing

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Although remote sensing technology has been widely used to monitor inland water bodies; the lack of suitable data with high spatial and spectral resolution has severely obstructed its practical development. The objective of this study is to improve the unmixing-based fusion (UBF) method to produce fused images that maintain both spectral and spatial information from the original images. Images from Environmental Satellite 1 (HJ1) and Medium Resolution Imaging Spectrometer (MERIS) were used in this study to validate the method. An improved UBF (IUBF) algorithm is established by selecting a proper HJ1-CCD image band for each MERIS band and thereafter applying an unsupervised classification method in each sliding window. Viewing in the visual sense-the radiance and the spectrum-the results show that the improved method effectively yields images with the spatial resolution of the HJ1-CCD image and the spectrum resolution of the MERIS image. When validated using two datasets; the ERGAS index (Relative Dimensionless Global Error) indicates that IUBF is more robust than UBF. Finally, the fused data were applied to evaluate the chlorophyll a concentrations (Cchla) in Taihu Lake. The result shows that the Cchla map obtained by IUBF fusion captures more detailed information than that of MERIS.

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“…Although traditional water quality monitoring methods can be precise, they are usually costly and time consuming (Östlund et al 2001;Wang and Ma 2001;Gan et al 2004), but above all, it is not possible to obtain from them the spatial overview required for global assessment and monitoring of water quality . Therefore, in order to monitor the environmental state and pollution of such bodies of water, a viable and economical approach must be based on satellite data (Gan et al 2004;Ekercin 2007).…”

Section: Introductionmentioning

confidence: 99%

Selection of appropriate sampling stations in a lake through mapping

Karabörk

2009

Environ Monit Assess

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Much valuable information is obtained from water quality measurements and monitoring of lakes around the world. A powerful tool is the use of mapping techniques, as it offers potential use in water quality research. Both remote sensing techniques and traditional water quality monitoring are required to collect data at sampling stations. This study suggests another approach to determine the most appropriate distribution of sampling stations in water reservoirs that will be mapped for water quality parameters. Tests were conducted for the proposed approach for Secchi disc depth (SDD), chlorophyll-a, turbidity and suspended solids parameters in Lake Beysehir, Turkey. Results of analysis are available for a total of 30 sampling stations in August 2006. Ten sampling stations were used to model Lake Beysehir while the others were used for validation of the model. Sampling stations that offered the best representation of the lake for each parameter were determined. Then, the best representative sampling stations for all parameters in the study were determined. Moreover, in order to confirm the accuracy of these re-determined sampling stations, modelling was performed on the results of the analysis of June 2006, and it was found that the values obtained from the re-determined sampling stations were acceptable.

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Mapping of the water quality of Lake Erken, Sweden, from Imaging Spectrometry and Landsat Thematic Mapper

Cited by 83 publications

References 26 publications

Hyper-spectral Remote Sensing of Water Quality Parameters in Lakes: A Case Study of Hyderabad City, Telangana State, India

Hyper-spectral Remote Sensing of Water Quality Parameters in Lakes: A Case Study of Hyderabad City, Telangana State, India

An Improved Unmixing-Based Fusion Method: Potential Application to Remote Monitoring of Inland Waters

Selection of appropriate sampling stations in a lake through mapping

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