Estimation of Forest Height Using Spaceborne Repeat-Pass L-Band InSAR Correlation Magnitude over the US State of Maine
Estimation of Forest Height Using Spaceborne Repeat-Pass L-Band InSAR Correlation Magnitude over the US State of Maine
Y. Lei,P. Siqueira
TLDR
A novel, simple and efficient approach to estimate forestheight over a wide region utilizing spaceborne repeat-pass InSAR correlation magnitudedata at L-band and serving as an alternative and complementary tool for other PolInSAR inversiontechniques when full-polarization data may not be available.
Abstract
Yang Lei and Paul Siqueira Department of Electrical and Computer Engineering, University of Massachusetts Amherst,151 Holdsworth Way, Amherst, MA 01003, USA; E-Mail: [email protected] Author to whom correspondence should be addressed; E-Mail: [email protected];Tel.: +1-413-577-0623; Fax: +1-413-545-4652.External Editors: Nicolas Baghdadi and Prasad S. ThenkabailReceived: 27 July 2014; in revised form: 10 October 2014 / Accepted: 11 October 2014 /Published: 24 October 2014Abstract: This paper describes a novel, simple and efficient approach to estimate forestheight over a wide region utilizing spaceborne repeat-pass InSAR correlation magnitudedata at L-band. We start from a semi-empirical modification of the RVoG model thatcharacterizes repeat-pass InSAR correlation with large temporal baselines (e.g., 46 daysfor ALOS) by taking account of the temporal change effect of dielectric fluctuation andrandom motion of scatterers. By assuming (1) the temporal change parameters andforest backscatter profile/extinction coefficient follow some mean behavior across eachinteferogram; (2) there is minimal ground scattering contribution for HV-polarization; and(3) the vertical wavenumber is small, a simplified inversion approach is developed to linkthe observed HV-polarized InSAR correlation magnitude to forest height and validatedusing ALOS/PALSAR repeat-pass observations against LVIS lidar heights over the HowlandResearch Forest in central Maine, US (with RMSE <4 m at a resolution of 32 hectares).The model parameters derived from this supervised regression are used as the basis forpropagating the estimates of forest height to available interferometric pairs for the entirestate of Maine, thus creating a state-mosaic map of forest height. The present approachdescribed here serves as an alternative and complementary tool for other PolInSAR inversiontechniques when full-polarization data may not be available. This work is also meant to be anobservational prototype for NASA’s DESDynI-R (now called NISAR) and JAXA’s ALOS-2satellite missions.
