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Landsat and limnologically derived water quality data: A perspective
A Howman1, D Grobler, P Kempster
1Hydrological Research Institute, Private Bag X313, 0001, Pretoria.
Environmental Monitoring and Assessment
|November 19, 2013
Summary
This study shows that using Landsat satellite data can accurately estimate median chlorophyll concentrations in reservoirs. This remote sensing approach provides a broader spatial understanding of chlorophyll distribution compared to traditional fixed station sampling.
Area of Science:
- Environmental Science
- Remote Sensing
- Water Quality Monitoring
Background:
- Fixed station sampling is conventional for reservoir water quality but may not represent ambient conditions.
- Chlorophyll concentrations, crucial for water quality, exhibit patchy spatial distributions, challenging fixed-site monitoring.
- This study addresses the limitations of fixed station sampling for water quality variables like chlorophyll.
Purpose of the Study:
- To investigate the use of Landsat reflectance data for estimating median chlorophyll concentrations in Roodeplaat Dam.
- To compare chlorophyll estimates derived from satellite data with those from traditional fixed station sampling.
- To assess the spatial distribution information provided by Landsat-derived chlorophyll data.
Main Methods:
- A linear polynomial regression model was developed to estimate chlorophyll from Landsat reflectance data.
- The model was calibrated using two approaches: individual calibration with data from seven fixed stations during a satellite overflight, and a generalized calibration using pooled data from five overflights.
- Water quality data from fixed stations were collected concurrently with satellite overflights.
Main Results:
- Median chlorophyll concentrations estimated from Landsat data were comparable to those from fixed station data.
- Landsat-derived estimates revealed a considerably larger range of chlorophyll concentrations than fixed station data.
- Landsat data provided valuable insights into the spatial distribution of chlorophyll within the reservoir.
Conclusions:
- Landsat reflectance data offer a viable and effective method for estimating median chlorophyll concentrations in reservoirs.
- Remote sensing with Landsat provides a more comprehensive spatial overview of chlorophyll distribution than fixed station sampling.
- This approach enhances water quality monitoring by capturing spatial variability often missed by traditional methods.
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