Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons
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 12...
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Published in | The Science of the total environment Vol. 268; no. 1; pp. 59 - 77 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Netherlands
Elsevier B.V
14.03.2001
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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 μg 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
R
2 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,
R
2 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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AbstractList | 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 μg 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
R
2 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,
R
2 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. 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. 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 mu g l super(-1), turbidity 0.4-26 FNU, total suspended solids 0.7-32 mg l super(-1), absorption coefficient of aquatic humus at 400 nm 1.2-14 m super(-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 R super(2) 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, R super(2) 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. Airborne spectrometer, limnological, and optical measurements were carried out in southern Finland in August 1996, May and August 1997, and August 1998, and the best empirical algorithms for the retrieval of water quality from airborne spectrometer data were determined. Both airborne imaging spectrometer for applications radiances and atmospherically corrected reflectances were used. The results revealed that chlorophyll a, total suspended solids, turbidity, aquatic humus, and secchi disk transparency could be detected by airborne remote sensing. The empirical parameters of the retrieval algorithms differed in May and August, due to differences in the proportion of optically active substances and in the specific inherent optical properties. The use of atmospherically corrected reflectances rather than radiances improved only the estimation of total suspended solids and turbidity. |
Author | Kutser, T. Pyhälahti, T. Pulliainen, J. Koponen, S. Vepsäläinen, J. Kallio, K. Hannonen, T. |
Author_xml | – sequence: 1 givenname: K. surname: Kallio fullname: Kallio, K. email: kari.y.kallio@vyh.fi organization: Finnish Environment Institute, P.O. Box 140, 00251 Helsinki, Finland – sequence: 2 givenname: T. surname: Kutser fullname: Kutser, T. organization: Estonian Marine Institute, 1 Paldiski Road, EE-0001 Tallinn, Estonia – sequence: 3 givenname: T. surname: Hannonen fullname: Hannonen, T. organization: Finnish Environment Institute, P.O. Box 140, 00251 Helsinki, Finland – sequence: 4 givenname: S. surname: Koponen fullname: Koponen, S. organization: Laboratory of Space Technology, Helsinki University of Technology, PL 3000, 02015 TKK, Helsinki, Finland – sequence: 5 givenname: J. surname: Pulliainen fullname: Pulliainen, J. organization: Laboratory of Space Technology, Helsinki University of Technology, PL 3000, 02015 TKK, Helsinki, Finland – sequence: 6 givenname: J. surname: Vepsäläinen fullname: Vepsäläinen, J. organization: Finnish Environment Institute, P.O. Box 140, 00251 Helsinki, Finland – sequence: 7 givenname: T. surname: Pyhälahti fullname: Pyhälahti, T. organization: Finnish Environment Institute, P.O. Box 140, 00251 Helsinki, Finland |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/11315747$$D View this record in MEDLINE/PubMed |
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Pozdnyakov, Kondratyev, Bukata, Jerome (BIB37) 1998; 19 Virta (10.1016/S0048-9697(00)00685-9_BIB45) 1999; 48 Kutser (10.1016/S0048-9697(00)00685-9_BIB30) 1998; 3 Kondratyev (10.1016/S0048-9697(00)00685-9_BIB25) 1998; 19 Mäkisara (10.1016/S0048-9697(00)00685-9_BIB34) 1998; 1894 10.1016/S0048-9697(00)00685-9_BIB27 10.1016/S0048-9697(00)00685-9_BIB28 Quibell (10.1016/S0048-9697(00)00685-9_BIB39) 1991; 12 Gitelson (10.1016/S0048-9697(00)00685-9_BIB9) 1992; 13 10.1016/S0048-9697(00)00685-9_BIB7 Fraser (10.1016/S0048-9697(00)00685-9_BIB8) 1998; 19 10.1016/S0048-9697(00)00685-9_BIB20 10.1016/S0048-9697(00)00685-9_BIB42 10.1016/S0048-9697(00)00685-9_BIB6 Hoogenboom (10.1016/S0048-9697(00)00685-9_BIB14) 1998; 24 10.1016/S0048-9697(00)00685-9_BIB23 10.1016/S0048-9697(00)00685-9_BIB24 Schalles (10.1016/S0048-9697(00)00685-9_BIB41) 1998; 34 10.1016/S0048-9697(00)00685-9_BIB43 Gitelson (10.1016/S0048-9697(00)00685-9_BIB10) 1993; 14 10.1016/S0048-9697(00)00685-9_BIB22 Raatikainen (10.1016/S0048-9697(00)00685-9_BIB40) 1988; 102 Kortelainen (10.1016/S0048-9697(00)00685-9_BIB26) 1993; 50 10.1016/S0048-9697(00)00685-9_BIB4 Yacobi (10.1016/S0048-9697(00)00685-9_BIB46) 1995; 17 10.1016/S0048-9697(00)00685-9_BIB3 10.1016/S0048-9697(00)00685-9_BIB1 Pulliainen (10.1016/S0048-9697(00)00685-9_BIB38) 2001; 268 Vertucci (10.1016/S0048-9697(00)00685-9_BIB44) 1989; 34 10.1016/S0048-9697(00)00685-9_BIB16 10.1016/S0048-9697(00)00685-9_BIB17 10.1016/S0048-9697(00)00685-9_BIB36 10.1016/S0048-9697(00)00685-9_BIB15 Dekker (10.1016/S0048-9697(00)00685-9_BIB5) 1992; 233 Hamilton (10.1016/S0048-9697(00)00685-9_BIB11) 1993; 44 10.1016/S0048-9697(00)00685-9_BIB18 10.1016/S0048-9697(00)00685-9_BIB19 Kallio (10.1016/S0048-9697(00)00685-9_BIB21) 1999; 48 De Haan (10.1016/S0048-9697(00)00685-9_BIB2) 1996; 96/16 Han (10.1016/S0048-9697(00)00685-9_BIB12) 1994; 15 10.1016/S0048-9697(00)00685-9_BIB31 Kutser (10.1016/S0048-9697(00)00685-9_BIB29) 1995; 16 Hoogenboom (10.1016/S0048-9697(00)00685-9_BIB13) 1998; 65 10.1016/S0048-9697(00)00685-9_BIB35 10.1016/S0048-9697(00)00685-9_BIB32 Millie (10.1016/S0048-9697(00)00685-9_BIB33) 1992; 28 Pozdnyakov (10.1016/S0048-9697(00)00685-9_BIB37) 1998; 19 |
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Snippet | The suitability of the AISA airborne imaging spectrometer for monitoring lake water quality was tested in four surveys carried out in southern Finland in... Airborne spectrometer, limnological, and optical measurements were carried out in southern Finland in August 1996, May and August 1997, and August 1998, and... |
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SubjectTerms | Airborne imaging spectrometer for applications Airborne spectrometer Algorithms Chlorophyll - analysis Chlorophyll A Data Collection Environmental Monitoring - methods Humic Substances - analysis Hyperspectral Lakes Optical properties Particle Size Seasons Sensitivity and Specificity Spacecraft Spectrophotometry - methods Water Pollution - analysis Water quality |
Title | Retrieval of water quality from airborne imaging spectrometry of various lake types in different seasons |
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