Literature DB >> 23430067

Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region, New Zealand.

Brendan J Hicks1, Glen A Stichbury, Lars K Brabyn, Mathew G Allan, Salman Ashraf.   

Abstract

Cost-effective monitoring is necessary for all investigations of lake ecosystem responses to perturbations and long-term change. Satellite imagery offers the opportunity to extend low-cost monitoring and to examine spatial and temporal variability in water clarity data. We have developed automated procedures using Landsat imagery to estimate total suspended sediments (TSS), turbidity (TURB) in nephlometric turbidity units (NTU) and Secchi disc transparency (SDT) in 34 shallow lakes in the Waikato region, New Zealand, over a 10-year time span. Fifty-three Landsat 7 Enhanced Thematic Mapper Plus images captured between January 2000 and March 2009 were used for the analysis, six of which were captured within 24 h of physical in situ measurements for each of 10 shallow lakes. This gave 32-36 usable data points for the regressions between surface reflectance signatures and in situ measurements, which yielded r (2) values ranging from 0.67 to 0.94 for the three water clarity variables. Using these regressions, a series of Arc Macro Language scripts were developed to automate image preparation and water clarity analysis. Minimum and maximum in situ measurements corresponding to the six images were 2 and 344 mg/L for TSS, 75 and 275 NTU for TURB, and 0.05 and 3.04 m for SDT. Remotely sensed water clarity estimates showed good agreement with temporal patterns and trends in monitored lakes and we have extended water clarity datasets to previously unmonitored lakes. High spatial variability of TSS and water clarity within some lakes was apparent, highlighting the importance of localised inputs and processes affecting lake clarity. Moreover, remote sensing can give a whole lake view of water quality, which is very difficult to achieve by in situ point measurements.

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Year:  2013        PMID: 23430067     DOI: 10.1007/s10661-013-3098-2

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  5 in total

1.  Detecting chlorophyll, Secchi disk depth and surface temperature in a sub-alpine lake using Landsat imagery.

Authors:  C Giardino; M Pepe; P A Brivio; P Ghezzi; E Zilioli
Journal:  Sci Total Environ       Date:  2001-03-14       Impact factor: 7.963

2.  Application of Landsat imagery to regional-scale assessments of lake clarity.

Authors:  Steven M Kloiber; Patrick L Brezonik; Marvin E Bauer
Journal:  Water Res       Date:  2002-10       Impact factor: 11.236

3.  A semi-operative approach to lake water quality retrieval from remote sensing data.

Authors:  J Pulliainen; K Kallio; K Eloheimo; S Koponen; H Servomaa; T Hannonen; S Tauriainen; M Hallikainen
Journal:  Sci Total Environ       Date:  2001-03-14       Impact factor: 7.963

4.  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

5.  Water quality assessment at Omerli Dam using remote sensing techniques.

Authors:  Erhan Alparslan; Cihangir Aydöner; Vildan Tufekci; Hüseyin Tüfekci
Journal:  Environ Monit Assess       Date:  2007-03-08       Impact factor: 2.513

  5 in total
  1 in total

1.  Monitoring water quality in a hypereutrophic reservoir using Landsat ETM+ and OLI sensors: how transferable are the water quality algorithms?

Authors:  Eliza S Deutsch; Ibrahim Alameddine; Mutasem El-Fadel
Journal:  Environ Monit Assess       Date:  2018-02-15       Impact factor: 2.513

  1 in total

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