Analysis of GEDI Elevation Data Accuracy for Inland Waterbodies Altimetry

The Global Ecosystem Dynamics Investigation (GEDI) Light Detection And Ranging (LiDAR) altimetry mission was recently launched to the International Space Station with a capability of providing billions of high-quality measurements of vertical structures globally. This study assesses the accuracy of the GEDI LiDAR altimetry estimation of lake water levels. The difference between GEDI’s elevation estimates to in-situ hydrological gauge water levels was determined for eight natural lakes in Switzerland. The elevation accuracy of GEDI was assessed as a function of each lake, acquisition date, and the laser used for acquisition (beam). The GEDI elevation estimates exhibit an overall good agreement with in-situ water levels with a mean elevation bias of 0.61 cm and a standard deviation (std) of 22.3 cm and could be lowered to 8.5 cm when accounting for instrumental and environmental factors. Over the eight studied lakes, the bias between GEDI elevations and in-situ data ranged from −13.8 cm to +9.8 cm with a standard deviation of the mean difference ranging from 14.5 to 31.6 cm. Results also show that the acquisition date affects the precision of the GEDI elevation estimates. GEDI data acquired in the mornings or late at night had lower bias in comparison to acquisitions during daytime or over weekends. Even though GEDI is equipped with three identical laser units, a systematic bias was found based on the laser units used in the acquisitions. Considering the eight studied lakes, the beams with the highest elevation differences compared to in-situ data were beams 1 and 6 (standard deviations of −10.2 and +18.1 cm, respectively). In contrast, the beams with the smallest mean elevation difference to in-situ data were beams 5 and 7 (−1.7 and −2.5 cm, respectively). The remaining beams (2, 3, 4, and 8) showed a mean difference between −7.4 and +4.4 cm. The standard deviation of the mean difference, however, was similar across all beams and ranged from 17.2 and 22.9 cm. This study highlights the importance of GEDI data for estimating water levels in lakes with good accuracy and has potentials in advancing our understanding of the hydrological significance of lakes especially in data scarce regions of the world.

[1]  C. Shum,et al.  Satellite radar altimetry for monitoring small rivers and lakes in Indonesia , 2014 .

[2]  B. D. Beckley,et al.  Investigating the Performance of the Jason-2/OSTM Radar Altimeter over Lakes and Reservoirs , 2010 .

[3]  P. Döll,et al.  Development and validation of a global database of lakes, reservoirs and wetlands , 2004 .

[4]  D. Oesch,et al.  Multi‐scale thermal pattern monitoring of a large lake (Lake Geneva) using a multi‐sensor approach , 2008 .

[5]  Felipe J. Colón-González,et al.  Multimodel assessment of water scarcity under climate change , 2013, Proceedings of the National Academy of Sciences.

[6]  A. Cazenave,et al.  SOLS: A lake database to monitor in the Near Real Time water level and storage variations from remote sensing data , 2011 .

[7]  Bob E. Schutz,et al.  A Survey of ICESat Coastal Altimetry Applications: Continental Coast, Open Ocean Island, and Inland River , 2008 .

[8]  C. Prigent,et al.  Surface freshwater storage and dynamics in the Amazon basin during the 2005 exceptional drought , 2012 .

[9]  H. Zwally,et al.  Overview of the ICESat Mission , 2005 .

[10]  Min Xu,et al.  Analysis of Sentinel-3 SAR altimetry waveform retracking algorithms for deriving temporally consistent water levels over ice-covered lakes , 2020 .

[11]  Nicolas Baghdadi,et al.  Viability Statistics of GLAS/ICESat Data Acquired Over Tropical Forests , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[12]  F. Frappart,et al.  Influence of recent climatic events on the surface water storage of the Tonle Sap Lake. , 2018, The Science of the total environment.

[13]  U. Lemmin,et al.  Summertime winds and direct cyclonic circulation: observations from Lake Geneva , 1996 .

[14]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[15]  Frédéric Frappart,et al.  Evolution of the Performances of Radar Altimetry Missions from ERS-2 to Sentinel-3A over the Inner Niger Delta , 2018, Remote. Sens..

[16]  Peter Bauer-Gottwein,et al.  CryoSat-2 radar altimetry for monitoring freshwater resources of China , 2017 .

[17]  Frédéric Frappart,et al.  Hydrological Applications of Satellite AltimetryRivers, Lakes, Man-Made Reservoirs, Inundated Areas , 2017 .

[18]  S. Kanae,et al.  Global flood risk under climate change , 2013 .

[19]  J. Crétaux,et al.  Global surveys of reservoirs and lakes from satellites and regional application to the Syrdarya river basin , 2015 .

[20]  Fernando Niño,et al.  Monitoring Water Levels and Discharges Using Radar Altimetry in an Ungauged River Basin: The Case of the Ogooué , 2018, Remote. Sens..

[21]  Charles J Vörösmarty,et al.  Widespread decline in hydrological monitoring threatens Pan-Arctic Research , 2002 .

[22]  C. Birkett,et al.  The contribution of TOPEX/POSEIDON to the global monitoring of climatically sensitive lakes , 1995 .

[23]  Nicolas Baghdadi,et al.  The Relevance of GLAS/ICESat Elevation Data for the Monitoring of River Networks , 2011, Remote. Sens..

[24]  Di Long,et al.  Validation and application of water levels derived from Sentinel-3A for the Brahmaputra River , 2019, Science China Technological Sciences.

[25]  Nicolas Baghdadi,et al.  Testing Different Methods of Forest Height and Aboveground Biomass Estimations From ICESat/GLAS Data in Eucalyptus Plantations in Brazil , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[26]  C. Donlon,et al.  The Global Monitoring for Environment and Security (GMES) Sentinel-3 mission , 2012 .

[27]  Ole Baltazar Andersen,et al.  The performance and potentials of the CryoSat-2 SAR and SARIn modes for lake level estimation , 2017 .

[28]  Christian Gratzke All That Matters. , 2017, European urology focus.

[29]  Nicolas Baghdadi,et al.  Improving the assessment of ICESat water altimetry accuracy accounting for autocorrelation , 2011 .

[30]  Frédérique Seyler,et al.  Continental surface waters from satellite altimetry , 2006 .

[31]  Scott J. Goetz,et al.  The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography , 2020, Science of Remote Sensing.

[32]  Frédéric Frappart,et al.  Satellite radar altimetry water elevations performance over a 200 m wide river: Evaluation over the Garonne River , 2017 .

[33]  Bradley Doorn,et al.  From Research to Operations: The USDA Global Reservoir and Lake Monitor , 2011 .