Literature DB >> 11315747

Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons.

K Kallio1, T Kutser, T Hannonen, S Koponen, J Pulliainen, J Vepsäläinen, T Pyhälahti.   

Abstract

The suitability of the AISA airborne imaging spectrometer for monitoring lake water quality was tested in four surveys carried out in southern Finland in 1996-1998. Altogether, 11 lakes were surveyed and the total number of stations with concurrent remote sensing and limnological measurements was 127. The ranges of the water quality variables were: the sum of chlorophyll a and phaeophytin a 1-100 microg l(-1), turbidity 0.4-26 FNU, total suspended solids 0.7-32 mg l(-1), absorption coefficient of aquatic humus at 400 nm 1.2-14 m(-1) and secchi disc transparency 0.4-7 m. For the retrieval analyses, 24 AISA channels in the 450-786 nm range with a channel width of 6-14 nm were used. The agreement between estimated and observed water quality variables was generally good and R2 for the best algorithms was in the range of 0.72-0.90 over the whole dataset. The channels used for May were, in most cases, the same as those for August, but the empirical parameters of the algorithms were different. After seasonal grouping, R2 varied from 0.84 to 0.95. The use of apparent reflectance instead of radiance improved the estimation of water quality in the case of total suspended solids and turbidity. In the most humic lake, the empirical algorithms tested were suitable only for the interpretation of total suspended solids and turbidity.

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Year:  2001        PMID: 11315747     DOI: 10.1016/s0048-9697(00)00685-9

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  7 in total

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2.  A feasible method to assess inaccuracy caused by patchiness in water quality monitoring.

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Authors:  Richard Beck; Min Xu; Shengan Zhan; Richard Johansen; Hongxing Liu; Susanna Tong; Bo Yang; Song Shu; Qiusheng Wu; Shujie Wang; Kevin Berling; Andrew Murray; Erich Emery; Molly Reif; Joseph Harwood; Jade Young; Christopher Nietch; Dana Macke; Mark Martin; Garrett Stillings; Richard Stumpf; Haibin Su; Zhaoxia Ye; Yan Huang
Journal:  J Great Lakes Res       Date:  2019-06-01       Impact factor: 2.480

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Journal:  Environ Sci Pollut Res Int       Date:  2017-09-24       Impact factor: 4.223

5.  Landsat ETM+ images in the estimation of seasonal lake water quality in boreal river basins.

Authors:  Kari Kallio; Jenni Attila; Pekka Härmä; Sampsa Koponen; Jouni Pulliainen; Ulla-Maija Hyytiäinen; Timo Pyhälahti
Journal:  Environ Manage       Date:  2008-05-29       Impact factor: 3.266

6.  Assessment of chlorophyll-a concentration and trophic state for Lake Chagan using Landsat TM and field spectral data.

Authors:  Hongtao Duan; Yuanzhi Zhang; Bai Zhang; Kaishan Song; Zongming Wang
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7.  Validation and Comparison of Water Quality Products in Baltic Lakes Using Sentinel-2 MSI and Sentinel-3 OLCI Data.

Authors:  Tuuli Soomets; Kristi Uudeberg; Dainis Jakovels; Agris Brauns; Matiss Zagars; Tiit Kutser
Journal:  Sensors (Basel)       Date:  2020-01-29       Impact factor: 3.576

  7 in total

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