Analyzing the Accuracy of Satellite-Derived DEMs Using High-Resolution Terrestrial LiDAR

The accurate estimation of Digital Elevation Models (DEMs) derived from satellite data is critical for numerous environmental applications. This study evaluates the accuracy and reliability of two satellite-derived elevation models, the ALOS World 3D and SRTM DEMs, specifically for their application in hydrological modeling. A comparative analysis with Terrestrial Laser Scanning (TLS) measurements assessed the agreement between these datasets. Multiple linear regression models were utilized to evaluate the relationships between the datasets and provide detailed insights into their accuracy and biases. The results indicate significant correlations between satellite DEMs and TLS measurements, with adjusted R-square values of 0.8478 for ALOS and 0.955 for the SRTM. To quantify the average difference, root mean square error (RMSE) values were calculated as 10.43 m for ALOS and 5.65 m for the SRTM. Additionally, slope and aspect analyses were performed to highlight terrain characteristics across the DEMs. Slope analysis showed a statistically significant negative correlation between SRTM and TLS slopes (R2 = 0.16, p < 4.47 × 10−10 indicating a weak relationship, while no significant correlation was observed between ALOS and TLS slopes. Aspect analysis showed significant positive correlations for both ALOS and the SRTM with TLS aspect, capturing 30.21% of the variance. These findings demonstrate the accuracy of satellite-derived elevation models in representing terrain features relative to high-resolution terrestrial data.

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Publication Details

Journal
Land
Published
2024-12-13
DOI
https://doi.org/10.3390/land13122171
Citations
3
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.62
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article

Analyzing the Accuracy of Satellite-Derived DEMs Using High-Resolution Terrestrial LiDAR

Mihai Daniel Niță, Ashraf A. Mohamed, Mohamed Islam Keskes
3 citations
Land
Remote Sensing and LiDAR Applications
0.62
article

Analyzing the Accuracy of Satellite-Derived DEMs Using High-Resolution Terrestrial LiDAR

Mihai Daniel Niță, Ashraf A. Mohamed, Mohamed Islam Keskes
article en
3 citations

Abstract

The accurate estimation of Digital Elevation Models (DEMs) derived from satellite data is critical for numerous environmental applications. This study evaluates the accuracy and reliability of two satellite-derived elevation models, the ALOS World 3D and SRTM DEMs, specifically for their application in hydrological modeling. A comparative analysis with Terrestrial Laser Scanning (TLS) measurements assessed the agreement between these datasets. Multiple linear regression models were utilized to evaluate the relationships between the datasets and provide detailed insights into their accuracy and biases. The results indicate significant correlations between satellite DEMs and TLS measurements, with adjusted R-square values of 0.8478 for ALOS and 0.955 for the SRTM. To quantify the average difference, root mean square error (RMSE) values were calculated as 10.43 m for ALOS and 5.65 m for the SRTM. Additionally, slope and aspect analyses were performed to highlight terrain characteristics across the DEMs. Slope analysis showed a statistically significant negative correlation between SRTM and TLS slopes (R2 = 0.16, p < 4.47 × 10−10 indicating a weak relationship, while no significant correlation was observed between ALOS and TLS slopes. Aspect analysis showed significant positive correlations for both ALOS and the SRTM with TLS aspect, capturing 30.21% of the variance. These findings demonstrate the accuracy of satellite-derived elevation models in representing terrain features relative to high-resolution terrestrial data.

LandVol. 13(12)
Transylvania University of Brașov (RO)
Openalex Percentile: Top 34%
Remote Sensing and LiDAR Applications
0.62
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Analyzing the Accuracy of Satellite-Derived DEMs Using High-Resolution Terrestrial LiDAR — Mihai Daniel Niță, Ashraf A. Mohamed, et al. · Land (2024) | TGRS Research Map | TGRS