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Estimating Ground Level and Canopy Top Elevation With Airborne Microwave Profiling Radar.

Authors :
Feng, Ziyi
Chen, Yuwei
Hyyppa, Juha
Hakala, Teemu
Zhou, Hui
Wang, Yunshen
Karjalainen, Mika
Source :
IEEE Transactions on Geoscience & Remote Sensing. Apr2018, Vol. 56 Issue 4, p2283-2294. 12p.
Publication Year :
2018

Abstract

This paper presents the estimation of the ground elevation and canopy top elevation from the data collected by an airborne frequency-modulated continuous waveform profiling radar, Tomoradar. The estimated ground and canopy top elevations are critical for the derivation of reference information for the satellite-borne microwave radar data and the modeling of interaction between microwave radar signal and foliage. The methods of estimating the ground elevation and canopy top elevation from profiling radar are introduced, and the accuracy was evaluated via digital terrain model and Velodyne VLP-16 LiDAR integrated with the Tomoradar. To our knowledge, the ranging radar and the LiDAR data were simultaneously collected for the first time. The evaluation proved that the root-mean-square error (RMSE) of ground level estimation of the developed profiling radar can reach up to 0.33 m. When comparing the estimated canopy top peak elevation between the profile radar data and the LiDAR data, it was found that the side lobes of Tomoradar antenna system may produce undesired canopy backscatters when the size of the canopy gap is comparable to the footprint size of the main lobe, resulting in a higher canopy top elevation measurement from Tomoradar than that from LiDAR. The RMSE of the estimated canopy top peak elevation between two data sets was 0.32 m in the best case and 0.852 m on average. Moreover, the RMSE of point-to-point comparing the entire canopy tops elevation estimated from the data of two active remote sensing systems is 0.799 m after excluding the outliers. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01962892
Volume :
56
Issue :
4
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
129949271
Full Text :
https://doi.org/10.1109/TGRS.2017.2778024