Remote Sensing of Waikato Lakes
Allan, M. G. (2016). Remote Sensing of Waikato Lakes (ERI report). Hamilton, New Zealand: Environmental Research Institute, The University of Waikato.
Permanent Research Commons link: https://hdl.handle.net/10289/12821
This study explored and utilised existing remote sensing technology and algorithms to determine total suspended sediments (TSS) in lakes at a regional scale, producing a dataset quantifying spatial and temporal variability of remotely sensed TSS (including an experimental algorithm for chlorophyll a concentrations). The study processed Landsat 7 and 8 images from 1999 until the end of 2015. Statistical analysis included estimation of minimum, maximum, mean, range, and skewness of all Waikato lakes larger than 1 ha. The study demonstrated that the remote estimation of TSS within Waikato lakes is feasible and provides TSS estimations within the ranges of measured in situ TSS concentrations within most of the Waikato lakes except a small number of lakes with higher than expected estimated TSS concentrations (possible causes are identified including bottom reflection, and optical conditions not within the bounds of algorithm design). The study also demonstrated the ability of using remote sensing data to estimate and quantify variability of TSS over a large range of both within and between lakes. This spatial variation appeared to be driven by both geomorphic and abiotic factions, including turbid inflows and resuspension from the lakebed. The derived dataset maybe helpful to elucidate a better understanding of water quality variability and ultimately better understand implications for lake management. It is recommended that detailed in situ data be captured at the time of satellite overpass to further assess and improve the accuracy of the methods derived within the present study. The recent launch of Sentinel 2a (10 m resolution) will provide greater spatial and temporal coverage satellite imagery with a similar spectral resolution to Landsat 8 (30 m resolution) in the near future.
Environmental Research Institute, The University of Waikato
© 2016 copyright with the author.