Satellite-Based Time Series of Chlorophyll in Chilko Lake, British Columbia, Canada (original) (raw)
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2014 IEEE Geoscience and Remote Sensing Symposium, 2014
Chilko Lake sockeye constitute one of the largest salmon stocks in the Pacific Northwest, for which Fisheries and Oceans Canada has maintained a 55-year record, including partitioned freshwater and marine survival. The lake was also the site of fertilization experiments in the 1970s-1990s. This paper examined the use of spaceborne data from MERIS and LANDSAT collected over the Chilko Lake watershed for the purpose of generating long time series of lake chlorophyll and water temperature, testing and validating standard chlorophyll algorithms against in situ measurements, comparing Sockeye survival with lake variables, and assessing the state of glaciers in the watershed.
The Cryosphere, 2011
Supraglacial lakes form from meltwater on the Greenland ice sheet in topographic depressions on the surface, affecting both surface and sub-glacial processes. As the reflectance in the visible and near-infrared regions of a column of water is modulated by its height, retrieval techniques using spaceborne remote sensing data (e.g. Landsat, MODIS) have been proposed in the literature for the detection of lakes and estimation of their volume. These techniques require basic assumptions on the spectral properties of the water as well as the bottom of the lake, among other things. In this study, we report results obtained from the analysis of concurrent in-situ multi-spectral and depth measurements collected over a supraglacial lake during early July 2010 in West Greenland (Lake Olivia, 69 • 36 35 N, 49 • 29 40 W) and aim to assess some of the underlying hypotheses in remote sensing based bathymetric approaches. In particular, we focus our attention on the analysis of the lake bottom albedo and of the water attenuation coefficient. The analysis of in-situ data (collected by means of a remotely controlled boat equipped with a GPS, a sonar and a spectrometer) highlights the exponential trend of the water-leaving reflectance with lake depth. The values of the attenuation factor obtained from in-situ data are compared with those computed using approaches proposed in the literature. Also, the values of the lake bottom albedo from in-situ measurements are compared with those obtained from the analysis of reflectance of shallow waters. Finally, we quantify the error between in-situ measured and satellite-estimated lake depth values for the lake under study.
Monitoring lakes in high-latitude areas can provide a better understanding of freshwater systems sensitivity and accrete knowledge on climate change impacts. Phytoplankton are sensitive to various conditions: warmer temperatures, earlier ice-melt and changing nutrient sources. Satellite imagery can monitor algae biomass over large areas. The detection of chlorophyll a (chl-a) concentrations in small lakes is hindered by the low spatial resolution of conventional ocean colour satellites. The short time-series of the newest generation of space-borne sensors (e.g. Sentinel-2) is a bottleneck for assessing long-term trends. Although previous studies have evaluated the use of high-resolution sensors for assessing lakes' chl-a, it is still unclear how the spatial and temporal variability of chl-a concentration affect the performance of satellite estimates. We discuss the suitability of Landsat (LT) 30-m resolution imagery to assess lakes' chl-a concentrations under varying trophic...
Expanding understanding of optical variability in Lake Superior with a 4-year dataset
Earth System Science Data
Lake Superior is one of the largest freshwater lakes on our planet, but few optical observations have been made to allow for the development and validation of visible spectral satellite remote sensing products. The dataset described here focuses on coincidently observing inherent and apparent optical properties along with biogeochemical parameters. Specifically, we observe remote sensing reflectance, absorption, scattering, backscattering, attenuation, chlorophyll concentration, and suspended particulate matter over the ice-free months of 2013–2016. The dataset substantially increases the optical knowledge of the lake. In addition to visible spectral satellite algorithm development, the dataset is valuable for characterizing the variable light field, particle, phytoplankton, and colored dissolved organic matter distributions, and helpful in food web and carbon cycle investigations. The compiled data can be freely accessed at <a href="https://seabass.gsfc.nasa.gov/archi...
USING SATELLITE DATA TO SUPPORT THE MONITORING AND ADMINISTRATION OF LAKES
The Danish national monitoring program seeks for new solutions for cost-effective monitoring of the more than 600 lakes (> 5 ha) in Denmark. Current monitoring builds solely upon in situ sampling, but only ca. 15% of the lakes can be annually covered with this approach. In this study we show the potential of Landsat 8-derived chlorophyll a (chl-a) estimates to expand conventional monitoring -spatially and temporally. A statistical model was applied on a time series of Landsat 8 data covering April-October 2013. Satellite-based chl-a concentrations were then compared to in situ sampled data. To make this information accessible to the Danish environmental administration it will be integrated into an administration tool together with traditional survey data for decision-making and cost-efficient monitoring of Danish freshwaters under the EU Water Framework Directive.
A refined mapping of Arctic lakes using Landsat imagery
Effective mapping of water bodies at regional scales is a challenge with respect to the description and monitoring of hydrological, climatic, and landscape processes. In a region as sensitive to climate change as the Arctic, inaccurate representation of lake cover has probably led to underestimation of the role of lakes as landscape constituents and thus of their contribution to biochemical cycles. To estimate lake cover reliably (and perhaps also its change through time), the scientific community necessitates techniques for mapping water bodies using satellite sensors that include rich historical data sets and have sufficiently fine spatial resolution. Here we applied a density-slicing detection technique to 617 cloud-free Landsat images for the summer months 2006-2011. We developed a comprehensive database of Arctic lakes with a detection accuracy of 80% and examined spatial patterns of lake distribution in relation to landscape properties. We mapped about 3,500,000 lakes; these cover nearly 6% of the Arctic land surface (about 400,000 km 2 ) and are typically small (<0.1 km 2 ). Lake density and lake fraction analyses show that lakes are most common in lowland permafrost areas with tundra vegetation. The method described here can also be used to map and monitor lake cover at regional to hemispheric scales and to monitor changes in lake cover over time.
Remote Sensing of Environment, 2007
There is a critical need for spatially and temporally extensive information on the trophic status of lakes to assist in scientifically sound forest management decisions. To meet this need, this study examined the utility of Landsat TM imagery in deriving indicators of trophic status in remote and relatively undisturbed lakes on the Boreal Plain of northern Alberta. Based on data collected during a survey of lakes in 2001, normalized exoatmospheric reflectance values of the red band explained 68, 82, and 47% of the variance in chlorophyll a, turbidity, and Secchi disk depth, respectively. To understand the natural variation in trophic status in the lakes, we applied the linear regression equations to images collected during late summer (i.e., August) for 18 out of 20 years from 1984 to 2003 and performed a two-way analysis of variance to decompose the total variation into space, time, and space × time interaction factors. We found that temporal factors accounted for 10% and spatial factors accounted for 50% of the total variation in trophic status, with a minimum of 10 years and 20 lakes needed to reach stability in the contributions of these factors. This study suggests that regional factors that are external to the lake explained the majority (60%) of the variation in trophic status of the lakes.
Remote Sensing, 2016
The importance of lakes and reservoirs leads to the high need for monitoring lake water quality both at local and global scales. The aim of the study was to test suitability of Sentinel-2 Multispectral Imager's (MSI) data for mapping different lake water quality parameters. In situ data of chlorophyll a (Chl a), water color, colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC) from nine small and two large lakes were compared with band ratio algorithms derived from Sentinel-2 Level-1C and atmospherically corrected (Sen2cor) Level-2A images. The height of the 705 nm peak was used for estimating Chl a. The suitability of the commonly used green to red band ratio was tested for estimating the CDOM, DOC and water color. Concurrent reflectance measurements were not available. Therefore, we were not able to validate the performance of Sen2cor atmospheric correction available in the Sentinel-2 Toolbox. The shape and magnitude of water reflectance were consistent with our field measurements from previous years. However, the atmospheric correction reduced the correlation between the band ratio algorithms and water quality parameters indicating the need in better atmospheric correction. We were able to show that there is good correlation between band ratio algorithms calculated from Sentinel-2 MSI data and lake water parameters like Chl a (R 2 = 0.83), CDOM (R 2 = 0.72) and DOC (R 2 = 0.92) concentrations as well as water color (R 2 = 0.52). The in situ dataset was limited in number, but covered a reasonably wide range of optical water properties. These preliminary results allow us to assume that Sentinel-2 will be a valuable tool for lake monitoring and research, especially taking into account that the data will be available routinely for many years, the imagery will be frequent, and free of charge.