Evaluation and improvement of the vertical accuracy of the global open DEM under forest environment
Existing multi-source Digital Elevation Models (DEMs) still have uncertainties in estimating understory terrain. The study aims to use Goddard’s LiDAR, Hyperspectral & Thermal Imager (G-LiHT) as validation data to investigate the accuracy of L2A-level Products of the Global Ecosystem Dynamics In...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2453024 |
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| author | Jiapeng Huang Xiaozhu Yang |
| author_facet | Jiapeng Huang Xiaozhu Yang |
| author_sort | Jiapeng Huang |
| collection | DOAJ |
| description | Existing multi-source Digital Elevation Models (DEMs) still have uncertainties in estimating understory terrain. The study aims to use Goddard’s LiDAR, Hyperspectral & Thermal Imager (G-LiHT) as validation data to investigate the accuracy of L2A-level Products of the Global Ecosystem Dynamics Investigation (GEDI02_A) and six open-source DEMs in estimating understory terrain across six research areas. This study will quantify the influence of canopy height, canopy coverage, and leaf area index on estimation accuracy, and improve the accuracy of DEMs. The research findings indicate that the accuracy of GEDI02_A is the highest, with Root Mean Square Error (RMSE)=6.20m. Next, the Federal Railway Authority of Germany’s DEM (FABDEM) with RMSE = 8.46 m. Canopy height exhibits a higher correlation with the estimated accuracy of forest understory terrain. Finally, optimizing FABDEM based on the mathematical interpolation method using GEDI02_A reduces the RMSE from 8.46 m to 6.83 m. Slope ranging from 0-3% demonstrates the most significant improvement. |
| format | Article |
| id | doaj-art-79ac03f05a764a5d93c5349eb55c3c90 |
| institution | Kabale University |
| issn | 1010-6049 1752-0762 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geocarto International |
| spelling | doaj-art-79ac03f05a764a5d93c5349eb55c3c902025-01-20T11:41:03ZengTaylor & Francis GroupGeocarto International1010-60491752-07622025-12-0140110.1080/10106049.2025.2453024Evaluation and improvement of the vertical accuracy of the global open DEM under forest environmentJiapeng Huang0Xiaozhu Yang1School of Geomatics, Liaoning Technical University, Fuxin, ChinaSchool of Geomatics, Liaoning Technical University, Fuxin, ChinaExisting multi-source Digital Elevation Models (DEMs) still have uncertainties in estimating understory terrain. The study aims to use Goddard’s LiDAR, Hyperspectral & Thermal Imager (G-LiHT) as validation data to investigate the accuracy of L2A-level Products of the Global Ecosystem Dynamics Investigation (GEDI02_A) and six open-source DEMs in estimating understory terrain across six research areas. This study will quantify the influence of canopy height, canopy coverage, and leaf area index on estimation accuracy, and improve the accuracy of DEMs. The research findings indicate that the accuracy of GEDI02_A is the highest, with Root Mean Square Error (RMSE)=6.20m. Next, the Federal Railway Authority of Germany’s DEM (FABDEM) with RMSE = 8.46 m. Canopy height exhibits a higher correlation with the estimated accuracy of forest understory terrain. Finally, optimizing FABDEM based on the mathematical interpolation method using GEDI02_A reduces the RMSE from 8.46 m to 6.83 m. Slope ranging from 0-3% demonstrates the most significant improvement.https://www.tandfonline.com/doi/10.1080/10106049.2025.2453024Understory terrainGEDIdigital elevation modelsvertical accuracy assessmentimprovement |
| spellingShingle | Jiapeng Huang Xiaozhu Yang Evaluation and improvement of the vertical accuracy of the global open DEM under forest environment Geocarto International Understory terrain GEDI digital elevation models vertical accuracy assessment improvement |
| title | Evaluation and improvement of the vertical accuracy of the global open DEM under forest environment |
| title_full | Evaluation and improvement of the vertical accuracy of the global open DEM under forest environment |
| title_fullStr | Evaluation and improvement of the vertical accuracy of the global open DEM under forest environment |
| title_full_unstemmed | Evaluation and improvement of the vertical accuracy of the global open DEM under forest environment |
| title_short | Evaluation and improvement of the vertical accuracy of the global open DEM under forest environment |
| title_sort | evaluation and improvement of the vertical accuracy of the global open dem under forest environment |
| topic | Understory terrain GEDI digital elevation models vertical accuracy assessment improvement |
| url | https://www.tandfonline.com/doi/10.1080/10106049.2025.2453024 |
| work_keys_str_mv | AT jiapenghuang evaluationandimprovementoftheverticalaccuracyoftheglobalopendemunderforestenvironment AT xiaozhuyang evaluationandimprovementoftheverticalaccuracyoftheglobalopendemunderforestenvironment |