Affordable Access

deepdyve-link
Publisher Website

Potential of Space-Borne PolInSAR for Forest Canopy Height Estimation Over India-A Case Study Using Fully Polarimetric L-, C-, and X-Band SAR Data

Authors
  • KHATI, U
  • SINGH, G
  • KUMAR, S
Publication Date
Dec 03, 2018
Identifiers
DOI: 10.1002/2014GL060622
OAI: oai:dsapce.library.iitb.ac.in:100/22642
Source
DSpace at IIT Bombay
Keywords
License
Unknown
External links

Abstract

This paper aims to demonstrate the potential of space-borne datasets for forest height estimation over Indian tropical forests. Fully polarimetric space-borne SAR interferometry (PolInSAR) data is acquired at the L-, C-, and X-band frequencies. The X-band data are acquired in two modes-single pass and repeat pass. The datasets are compensated for decorrelation due to SNR and varying spatial baselines. The remaining major decorrelation is the volumetric decorrelation, which is modeled using random volume over ground model to estimate the PolInSAR height for all the three frequencies. The modified Three-stage inversion algorithm is utilized for forest stand height estimation. The effect of forest biomass on height inversion accuracy is assessed. Furthermore, a first-order estimate of the absolute temporal decorrelation is demonstrated for the repeat-pass space-borne PolInSAR datasets. Extensive field validation campaigns are carried out in the tropical forest ranges. The forest height is inverted using data at all the three frequencies and validated with field measured values. The zero-temporal baseline bistatic TerraSAR-X/TanDEM-X and the L-band ALOS-2/PALSAR-2 result in a good height inversion with r(2) and RMSE of 0.77 and 1.86 m (X-band) and 0.75 and 1.94 m (L-band), respectively. Furthermore, a comparison of estimated height of ALOS-2/PALSAR-2, TerraSAR-X, and RadarSAT-2 has been done with respect to the estimated height of TerraSAR-X/TanDEM-X. It is observed that RMSEof height inversion with respect to TerraSAR-X/TanDEM-X height is found to be 5.4 m, 7.6 m, and 12.8mfor ALOS-2/PALSAR2, RadarSAT-2, and TerraSAR-X, respectively.

Report this publication

Statistics

Seen <100 times