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Validation of ICESat-2 Surface Water Level Product ATL13 with Near Real Time Gauge Data

Published in Hydrology (Volume 8, Issue 2)
Received: 23 July 2020     Accepted: 3 August 2020     Published: 13 August 2020
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Abstract

The NASA’s Ice, Cloud, and land Elevation Satellite (ICESat) mission uses laser altimetry measurements to determine the elevations at point levels of Earth. ICESat-2, which is a successor to the ICESat-1 satellite mission is a continuation of this series and carries a sensor namely Advanced Topographic Laser Altimeter System (ATLAS). The key advancement of ICESat-2 is that it generates individual laser foot prints of nearly 14 m (in diameter) on the Earth’s surface, with each footprint separated by only 70 cm, a much higher resolution and sampling than the earlier mission. ATLAS works under the concept of multi-beam approach containing three pairs of strong and weak beams that produce data products containing global geolocated photon data and height data from land-ice, sea-ice, land/terrain, canopy, ocean surface, and inland water-bodies. From the Level 2 master product called ATL03 numerous sub-data product are generated and are made available to the public through the National Snow and Ice Data Center. One of the products namely ATL13 is a specialized geophysical data product that gives along-track and near-shore water surface height distribution within the water masks. In this article, results after validating ATL13 data product with 46 observations made with near real-time gauged data for 15 reservoirs/water bodies have been presented. The maximum uncertainty observed for this data product is at centimeter-level. A significant observation made from this study is that the heights of surface water level computed from strong beams (gt1r, gt2r, and gt3r) and weak beams (gt1l, gt2l, and gt3l) are occasionally having a variation of 5 to 10 centimeters relatively.

Published in Hydrology (Volume 8, Issue 2)
DOI 10.11648/j.hyd.20200802.11
Page(s) 19-25
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Surface Water Level, ICESat-2, ATL13, Laser Altimetry, Photon

References
[1] Markus, T., Neumann, T., Martino, A., Abdalati, W., Brunt, K., Csatho, B., and Jasinski, M., “The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2): science requirements, concept, and implementation”. Remote Sensing of Environment, 2017, 190, pp. 260-273.
[2] Brown, M. E., Arias, S. D., Neumann, T., Jasinski, M. F., Posey, P., Babonis, G., and Markus, T., “Applications for ICESat-2 Data: From NASA's Early Adopter Program”. IEEE Geoscience and Remote Sensing Magazine, 2016, 4 (4), pp. 24-37.
[3] Alsdorf, D. E., Rodríguez, E. and Lettenmaier, D. P., “Measuring surface water from space”. Reviews of Geophysics, 2007, 45 (2).
[4] Jasinski, M. F., J. D. Stoll, D. Hancock, J. Robbins, J. Nattala, J. Morison, B. M. Jones, M. E. Ondrusek, T. M. Pavelsky, C. Parrish, and the ICESat-2 Science Team., “ATLAS/ICESat-2 L3A Inland Water Surface Height, Version 3.” Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/ATLAS/ATL13.003.
[5] Dandabathula, G., Verma, M., Satyanarayana, P., and Rao, S. S., “Evaluation of ICESat-2 ATL08 Data Product: Performance Assessment in Inland Water”. European Journal of Environment and Earth Sciences, 2020, 1 (3).
[6] Zhang, G., Chen, W., and Xie, H., “Tibetan Plateau's lake level and volume changes from NASA's ICESat/ICESat-2 and Landsat Missions”. Geophysical Research Letters, 2019, 46 (22), pp. 13107-13118.
[7] Yuan, C., Gong, P., and Bai, Y. “Performance Assessment of ICESat-2 Laser Altimeter Data for Water-Level Measurement over Lakes and Reservoirs in China”. Remote Sensing, 2020, 12 (5), 770.
[8] OpenAltimetry, “Open Altimetry: Advanced discovery, processing, and visualization services for ICESat and ICESat-2 altimeter data. (https://openaltimetry.org/).
[9] PDO, “Handbook for Hydrometeorological Observaitons. Planning and Development Organisation”. Central Water Commission. 2020.
[10] CDSO, “Guidelines for Instrumentation of Large Dams. Central Dam Safety Organization, Central Water Commission. Doc. No. CDSO_GUD_DS_02_v1.0. 2018.
[11] CWC Portal, “Central Water Commission”, (http://cwc.gov.in/reservoir-storage).
[12] Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O. “Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature communications, 2016, 7 (1), 1-11.
[13] Neumann, T., Brenner, A., Hancock, D., Robbins, J., Saba, J., Harbeck, K., and Gibbons, A., “Ice, Cloud, and land Elevation Satellite–2 (ICESat-2) Project: Algorithm Theoretical Basis Document (ATBD) for Global Geolocated Photons (ATL03)”. National Aeronautics and Space Administration, Goddard Space Flight Center. 2019.
[14] Morison, J., Hancock, D., Dickinson, S., Robbins, J., Roberts, L., Kwok, R., Palm, S., Smith, B., Jasinski, M., Plant, B. and Urban, T., “Algorithm Theoretical Basis Document (ATBD) for Ocean Surface Height”. National Aeronautics and Space Administration, Goddard Space Flight Center. 2019.
[15] Li, Y., Gao, H., Jasinski, M. F., Zhang, S. and Stoll, J. D., “Deriving high-resolution reservoir bathymetry from ICESat-2 prototype photon-counting lidar and Landsat imagery”. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57 (10), pp. 7883-7893.
Cite This Article
  • APA Style

    Giribabu Dandabathula, Sitiraju Srinivasa Rao. (2020). Validation of ICESat-2 Surface Water Level Product ATL13 with Near Real Time Gauge Data. Hydrology, 8(2), 19-25. https://doi.org/10.11648/j.hyd.20200802.11

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    ACS Style

    Giribabu Dandabathula; Sitiraju Srinivasa Rao. Validation of ICESat-2 Surface Water Level Product ATL13 with Near Real Time Gauge Data. Hydrology. 2020, 8(2), 19-25. doi: 10.11648/j.hyd.20200802.11

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    AMA Style

    Giribabu Dandabathula, Sitiraju Srinivasa Rao. Validation of ICESat-2 Surface Water Level Product ATL13 with Near Real Time Gauge Data. Hydrology. 2020;8(2):19-25. doi: 10.11648/j.hyd.20200802.11

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  • @article{10.11648/j.hyd.20200802.11,
      author = {Giribabu Dandabathula and Sitiraju Srinivasa Rao},
      title = {Validation of ICESat-2 Surface Water Level Product ATL13 with Near Real Time Gauge Data},
      journal = {Hydrology},
      volume = {8},
      number = {2},
      pages = {19-25},
      doi = {10.11648/j.hyd.20200802.11},
      url = {https://doi.org/10.11648/j.hyd.20200802.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hyd.20200802.11},
      abstract = {The NASA’s Ice, Cloud, and land Elevation Satellite (ICESat) mission uses laser altimetry measurements to determine the elevations at point levels of Earth. ICESat-2, which is a successor to the ICESat-1 satellite mission is a continuation of this series and carries a sensor namely Advanced Topographic Laser Altimeter System (ATLAS). The key advancement of ICESat-2 is that it generates individual laser foot prints of nearly 14 m (in diameter) on the Earth’s surface, with each footprint separated by only 70 cm, a much higher resolution and sampling than the earlier mission. ATLAS works under the concept of multi-beam approach containing three pairs of strong and weak beams that produce data products containing global geolocated photon data and height data from land-ice, sea-ice, land/terrain, canopy, ocean surface, and inland water-bodies. From the Level 2 master product called ATL03 numerous sub-data product are generated and are made available to the public through the National Snow and Ice Data Center. One of the products namely ATL13 is a specialized geophysical data product that gives along-track and near-shore water surface height distribution within the water masks. In this article, results after validating ATL13 data product with 46 observations made with near real-time gauged data for 15 reservoirs/water bodies have been presented. The maximum uncertainty observed for this data product is at centimeter-level. A significant observation made from this study is that the heights of surface water level computed from strong beams (gt1r, gt2r, and gt3r) and weak beams (gt1l, gt2l, and gt3l) are occasionally having a variation of 5 to 10 centimeters relatively.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - Validation of ICESat-2 Surface Water Level Product ATL13 with Near Real Time Gauge Data
    AU  - Giribabu Dandabathula
    AU  - Sitiraju Srinivasa Rao
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    PY  - 2020
    N1  - https://doi.org/10.11648/j.hyd.20200802.11
    DO  - 10.11648/j.hyd.20200802.11
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    PB  - Science Publishing Group
    SN  - 2330-7617
    UR  - https://doi.org/10.11648/j.hyd.20200802.11
    AB  - The NASA’s Ice, Cloud, and land Elevation Satellite (ICESat) mission uses laser altimetry measurements to determine the elevations at point levels of Earth. ICESat-2, which is a successor to the ICESat-1 satellite mission is a continuation of this series and carries a sensor namely Advanced Topographic Laser Altimeter System (ATLAS). The key advancement of ICESat-2 is that it generates individual laser foot prints of nearly 14 m (in diameter) on the Earth’s surface, with each footprint separated by only 70 cm, a much higher resolution and sampling than the earlier mission. ATLAS works under the concept of multi-beam approach containing three pairs of strong and weak beams that produce data products containing global geolocated photon data and height data from land-ice, sea-ice, land/terrain, canopy, ocean surface, and inland water-bodies. From the Level 2 master product called ATL03 numerous sub-data product are generated and are made available to the public through the National Snow and Ice Data Center. One of the products namely ATL13 is a specialized geophysical data product that gives along-track and near-shore water surface height distribution within the water masks. In this article, results after validating ATL13 data product with 46 observations made with near real-time gauged data for 15 reservoirs/water bodies have been presented. The maximum uncertainty observed for this data product is at centimeter-level. A significant observation made from this study is that the heights of surface water level computed from strong beams (gt1r, gt2r, and gt3r) and weak beams (gt1l, gt2l, and gt3l) are occasionally having a variation of 5 to 10 centimeters relatively.
    VL  - 8
    IS  - 2
    ER  - 

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Author Information
  • Regional Remote Sensing Centre-West, National Remote Sensing Centre, Indian Space Research Organization, Jodhpur, Rajasthan, India

  • Regional Remote Sensing Centre-West, National Remote Sensing Centre, Indian Space Research Organization, Jodhpur, Rajasthan, India

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