The ATL08 as a height reference for the global digital elevation models

ABSTRACT

High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications. The Ice, Cloud, and Land elevation Satellite 2 (ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights, but it has not been fully evaluated. Hence, this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and TanDEM-X (TDX) DEMs over vegetated mountainous areas. We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy. Then, the results were evaluated against a reference airborne LiDAR digital terrain model (DTM), by selecting 10,000 points over the entire area and comparing the accuracy of ASTER, SRTM, and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER, SRTM, and TDX DEMs assessed by the ATL08 strong beams, weak beams, and all beams. We also detected the impact of the terrain aspect, slope, and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty. Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%; while the weak beams accuracy was enhanced by 74.05%. Furthermore, slope strongly influenced ATL08 height errors and height uncertainty; especially on the weak beams. The errors induced by the slope significantly decreased when the uncertainty levels were reduced to <20 m. The evaluations of ASTER, SRTM, and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams. These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions.

KEYWORDS:

• ATL08
• digital elevation model (DEM)
• digital terrain model (DTM)
• slope
• land cover
• terrain
• validation
• ICESat-2

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All the data used in this study are for free and publicly available. The ATL08 data, ASTER DEM, and SRTM DEM were provided by The National Aeronautics and Space Administration through this link https://doi.org/10.1080/10095020.2022.2087108. While, the TDX DEM was provided by the German Aerospace Center (DLR) through this link https://doi.org/10.1080/10095020.2022.2087108. The validation data is available through The OpenTopography website through this link https://doi.org/10.1080/10095020.2022.2087108.

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China under grant of 42090012, in part by the project supported by the Open Fund of Hubei Luojia Laboratory (220100009), in part by 03 special research and 5G project of Jiangxi province in China (20212ABC03A09); Zhuhai industry university research cooperation project of China (ZH22017001210098PWC);Sichuan Science and Technology Program (2022YFN0031), and Zhizhuo Research Fund on Spatial-Temporal Artificial Intelligence (Grant No. ZZJJ202202).

Notes on contributors

Nahed Osama

Nahed Osama received her MSC degree from Wuhan University. She is currently a PhD scholar at LIESMARS, Wuhan University. Her research interests are photogrammetry and remote sensing, information extraction, land observations and analysis.

Zhenfeng Shao

Zhenfeng Shao received his PhD degree from Wuhan University. He is a full professor at LIESMARS, Wuhan University. His research interests include urban remote sensing, impervious surfaces, information extraction, environmental monitoring, big data, image classification, deep learning.

Yue Ma

Yue Ma is an associate professor at school of electronic information, Wuhan University. His research interests are Optics, Oceanography, and Remote Sensing.

Jianguo Yan

Jianguo Yan received his PhD degree from Wuhan University. He is a professor at LIESMARS, Wuhan University. His research interests include Satellite geodesy, Planetary spacecraft precise orbit determination, Planet gravity field recovery, and Planet interior structure research.

Yewen Fan

Yewen Fan is an associate professor at LIEMSARS, Wuhan University. His research interests are GIS applications.

Shaimaa Magdy Habib

Shaimaa Magdy Habib received her MSC degree from Cairo university, Egypt. She is a research assistant at the National Authority for Remote Sensing and Space sciences (NARSS), Egypt. Her research interests are remote sensing and GIS, and their applications in renewable energy.

Mohamed Freeshah

Mohamed Freeshah received a PhD degree from Wuhan University. He is currently a post-doctor fellow at SGG, Wuhan University. His research interests include Interdisciplinary studies in Earth system science.