TY - JOUR
T1 - Inferring elevation variation of lakes and reservoirs from areal extents
T2 - Calibrating with altimeter and in situ data
AU - Nguy-Robertson, Anthony
AU - May, Jack
AU - Dartevelle, Sebastien
AU - Birkett, Charon
AU - Lucero, Eileen
AU - Russo, Tess
AU - Griffin, Sean
AU - Miller, Justin
AU - Tetrault, Robert
AU - Zentner, Matthew
N1 - Publisher Copyright:
© 2018
PY - 2018/1
Y1 - 2018/1
N2 - Water security is a major national security issue that can impact food and energy production and sometimes political stability in countries all over the globe. Monitoring water supplies is critical for identifying potential crises before they begin. As a means to estimate lake and reservoir storage for sites without reliable in situ water stage data, this study defines correlations between satellite-based reservoir elevation and aerial extents. Water body levels from altimeter water levels (i.e. TOPEX/Poseidon, Jason series) were correlated with areal extents observed in historic multispectral (i.e. MODIS and Landsat TM/ETM + /OLI) imagery for 18 sites globally. Water levels measured using in situ observations were used to validate the relationships between water level, altimetry data, and surface area for six of the sites. Altimeters were generally more accurate (RMSE: 0.40–0.49 m) for estimating lake elevations in Iraq and Afghanistan than the modeled elevation data using multispectral sensor areal extents: Landsat (RMSE: 0.25–1.5 m) and MODIS (RMSE 0.53–3.0 m). Correlations between altimeter data and Landsat imagery processed with Google Earth Engine confirmed similar relationships exists for a broader range of lakes without reported in situ data across the globe (RMSE: 0.24–1.6 m). Both sensor types have limitations. Altimeters have fixed orbits, which limits geographical coverage, though multispectral sensors are sensitive to atmospheric conditions. Thus, while altimetry is still preferred to an aerial extent model, lake surface area derived with Google Earth Engine can be used as a reasonable proxy for lake storage, expanding the number of observable lakes beyond the current constellation of altimeters and in situ gauges.
AB - Water security is a major national security issue that can impact food and energy production and sometimes political stability in countries all over the globe. Monitoring water supplies is critical for identifying potential crises before they begin. As a means to estimate lake and reservoir storage for sites without reliable in situ water stage data, this study defines correlations between satellite-based reservoir elevation and aerial extents. Water body levels from altimeter water levels (i.e. TOPEX/Poseidon, Jason series) were correlated with areal extents observed in historic multispectral (i.e. MODIS and Landsat TM/ETM + /OLI) imagery for 18 sites globally. Water levels measured using in situ observations were used to validate the relationships between water level, altimetry data, and surface area for six of the sites. Altimeters were generally more accurate (RMSE: 0.40–0.49 m) for estimating lake elevations in Iraq and Afghanistan than the modeled elevation data using multispectral sensor areal extents: Landsat (RMSE: 0.25–1.5 m) and MODIS (RMSE 0.53–3.0 m). Correlations between altimeter data and Landsat imagery processed with Google Earth Engine confirmed similar relationships exists for a broader range of lakes without reported in situ data across the globe (RMSE: 0.24–1.6 m). Both sensor types have limitations. Altimeters have fixed orbits, which limits geographical coverage, though multispectral sensors are sensitive to atmospheric conditions. Thus, while altimetry is still preferred to an aerial extent model, lake surface area derived with Google Earth Engine can be used as a reasonable proxy for lake storage, expanding the number of observable lakes beyond the current constellation of altimeters and in situ gauges.
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U2 - 10.1016/j.rsase.2018.01.001
DO - 10.1016/j.rsase.2018.01.001
M3 - Article
AN - SCOPUS:85044856463
SN - 2352-9385
VL - 9
SP - 116
EP - 125
JO - Remote Sensing Applications: Society and Environment
JF - Remote Sensing Applications: Society and Environment
ER -