Possible Inaccuracy of Canopy Height Model Estimation for Dense and Sparse Boreal Forest with Tandem-X DSM and ALOS Palsar DEM Fusion, Case Study from the Baikal Lake Region, Russia

Чимитдоржиев, Т. Н.; Дмитриев, А. В.; Kirbizhekova, Irina; Sherkhoeva, Alena; Baltukhaev, A.K.; Dagurov, P. N.

doi:10.1109/igarss.2019.8900058

Cited by 1 publication

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, it can be considered, in almost all extensions, a measure of ground elevation. This conclusion is supported > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 14 by recent works such as that by Chimitdorzhiev, et al [38], who found an error in canopy height, concluding that radar interferometric measurements underestimate the actual forest height by an average value of 5.5 m for high coverage and by 2-4 m for medium coverage. On the other hand, Gonzalez and Rizzoli [57] summarized the global relative height accuracy of the global TanDEM-X DEM for all continents and cover types.…”

Section: Discussionmentioning

confidence: 66%

See 1 more Smart Citation

GEDI Elevation Accuracy Assessment: A Case Study of Southwest Spain

Quiros

Polo

Fragoso-Campon

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Information about forest structures is becoming crucial to Earth's global carbon cycle, forest habitats and biodiversity. The Global Ecosystem Dynamics Investigation (GEDI) provides 25-m diameter footprints of the surface for 3D structure measurements. The main goal of this study is to compare 12 031 footprints of GEDI data with other airborne and spaceborne Digital Elevation Models (DEMs) for Southwest Spain. Ground elevation differences (ELM) are analyzed by comparing GEDI measurements with ALS LiDAR-and TanDEM-X-derived DEMs. The vertical structure (RH100) is compared to the ALS LiDAR measurement. Ten zones are analyzed, considering different degrees of coverage and slopes. We achieved an RMSE of 6.13 m for the ELM when comparing GEDI and LiDAR data and an RMSE of 7.14 m when comparing GEDI and TanDEM-X data. For some of the studied areas, these values were considerably smaller, with RMSE values even lower than 1 m. For the RH100 metric, an RMSE of 3.56 m was achieved when comparing GEDI and LiDAR data, but again with a minimum value of 2.09 m for one zone. The results show a clear relation to coverage and slope, especially for the latter. This work also evaluates the positional uncertainty of GEDI footprints, shifting them ±10 and ±5 m along and across the track of the satellite orbit and their intermediate angular positions. The outcomes reveal a strong tendency to obtain better results in the ELM when setting the footprint to 270° and displacing it within 10 m of its positional uncertainty in comparison with the LiDAR and TanDEM-X data.

show abstract

Section: Discussionmentioning

confidence: 66%

“…It is used mainly for flood detection [36] and other hydrological purposes [37]. However, works have also used the model to obtain canopy height models for forested 1 https://earthdata.nasa.gov/ areas [38].…”

Section: Introductionmentioning

confidence: 99%