Next Article in Journal
Hidden Naive Bayes Indoor Fingerprinting Localization Based on Best-Discriminating AP Selection
Previous Article in Journal
Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach
Article

Forest Vertical Parameter Estimation Using PolInSAR Imagery Based on Radiometric Correction

by 1, 1,2,*, 1 and 3
1
Signal Processing Lab, Electronic and Information School, Wuhan University, Wuhan 430079, China
2
State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China
3
ATR Key Lab, National University of Defense Technology, Changsha 410073, China
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(10), 186; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100186
Received: 30 June 2016 / Revised: 21 September 2016 / Accepted: 28 September 2016 / Published: 10 October 2016
This work introduces an innovative radiometric terrain correction algorithm using PolInSAR imagery for improving forest vertical structure parameter estimation. The variance of radar backscattering caused by terrain undulation has been considered in this research by exploiting an iteration optimization procedure to improve the backscattering estimation for a Synthetic Aperture Radar (SAR) image. To eliminate the variance of backscatter coefficients caused by the local incident angle, a radiometric normalization algorithm has been investigated to compensate the influence of terrain on backscattering values, which hinders forest vertical parameter estimation. In vertical parameter estimation, species diversity and the spatial distribution of different vegetation have been modeled. Then, a combination of Fisher’s Alpha-Diversity model parameter estimation and the three-stage inversion method was designed for the vertical structure parameter. To demonstrate the efficiency of the proposed method in forest height estimation, the classical phase difference and three-stage inversion approach have been performed for the purpose of comparison. The proposed algorithm is tested on ALOS PALSAR (Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 (Radio Direction and Range Satellite 2) data sets for the Great Xing’an Mountain area and BioSAR (Biomass Synthetic Aperture Radar) 2007 data sets for the Remningstorp area. Height estimation results have also been validated using in-situ measurements. Experiments indicate the proposed method has the ability to compensate the influence of terrain undulation and improving the accuracy of forest vertical structure parameter estimation. View Full-Text
Keywords: PolInSAR; radiometric terrain correction; vertical structure; scattering mechanism; RVoG model (Random Volume-over-Ground model) PolInSAR; radiometric terrain correction; vertical structure; scattering mechanism; RVoG model (Random Volume-over-Ground model)
Show Figures

Figure 1

MDPI and ACS Style

Zhang, Y.; He, C.; Xu, X.; Chen, D. Forest Vertical Parameter Estimation Using PolInSAR Imagery Based on Radiometric Correction. ISPRS Int. J. Geo-Inf. 2016, 5, 186. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100186

AMA Style

Zhang Y, He C, Xu X, Chen D. Forest Vertical Parameter Estimation Using PolInSAR Imagery Based on Radiometric Correction. ISPRS International Journal of Geo-Information. 2016; 5(10):186. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100186

Chicago/Turabian Style

Zhang, Yu, Chu He, Xin Xu, and Dong Chen. 2016. "Forest Vertical Parameter Estimation Using PolInSAR Imagery Based on Radiometric Correction" ISPRS International Journal of Geo-Information 5, no. 10: 186. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi5100186

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop