Satellite Imagery in the Study of Lake Baykal Surface Temperatures

Mogilev, N. Yu.; Gnatovskiy, R. Yu.

doi:10.2747/0749-3878.40.1.41

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…Many studies have used satellite imagery to document the SWT of lakes, including the Great Lakes (Li et al, 2001;Plattner et al, 2006), Great Slave and Great Bear Lakes (Bussieres & Schertzer, 2003), Lake Tahoe (Hook et al, 2003;Steissberg et al, 2005), Lake Baikal (Bolgrien et al, 1995;Mogilev & Gnatovsky, 2003), various high-elevation European lakes (Oesch et al, 2005), Wisconsin lakes (Becker & Daw, 2005), Salton Sea (Cardona et al, 2008), and the hypersaline Lake Eyre in Australia (Barton & Takashima, 1986). Reinart and Reinhold (2008) used MODIS thermal imagery to study Swedish lakes between 2001 and 2003.…”

Section: Introductionmentioning

confidence: 99%

MODIS-derived surface temperature of the Great Salt Lake

Crosman

Horel

2009

Remote Sensing of Environment

132

116

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Section: Introductionmentioning

confidence: 99%

MODIS-derived surface temperature of the Great Salt Lake

Crosman

Horel

2009

Remote Sensing of Environment

132

116

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“…Over the past three decades, satellite-derived estimates of lake WST have been sporadically developed for a number of large lakes around the world (e.g., Bolgrien et al 1995;Li et al 2001;Bussieres and Schertzer 2003;Mogilev and Gnatovskiy 2003;Plattner et al 2006). These include studies of saline and endorheic lakes, such as the Salton Sea (Cardona et al 2008), Dead Sea (Nehorai et al 2009), Lake Eyre (Barton and Takashima 1986), and the GSL (Crosman and Horel 2009).…”

Section: Introductionmentioning

confidence: 98%

Techniques for Using MODIS Data to Remotely Sense Lake Water Surface Temperatures

Grim

Knievel

Crosman

2013

Journal of Atmospheric and Oceanic Technology

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This study describes a stepwise methodology used to provide daily high-spatial-resolution water surface temperatures from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data for use nearly in real time for the Great Salt Lake (GSL). Land surface temperature (LST) is obtained each day and then goes through the following series of steps: land masking, quality control based on other concurrent datasets, bias correction, quality control based on LSTs from recent overpasses, temporal compositing, spatial hole filling, and spatial smoothing. Although the techniques described herein were calibrated for use on the GSL, they can also be applied to any other inland body of water large enough to be resolved by MODIS, as long as several months of in situ water temperature observations are available for calibration. For each of the buoy verification datasets, these techniques resulted in mean absolute errors for the final MODIS product that were at least 62% more accurate than those from the operational Real-Time Global analysis. The MODIS product provides realistic cross-lake temperature gradients that are representative of those directly observed from individual MODIS overpasses and is also able to replicate the temporal oscillations seen in the buoy datasets over periods of a few days or more. The increased accuracy, representative temperature gradients, and ability to resolve temperature changes over periods down to a few days can be vital for providing proper surface boundary conditions for input into numerical weather models.

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