An Automatic Mosaicking Algorithm for the Generation of a Large-Scale Forest Height Map Using Spaceborne Repeat-Pass InSAR Correlation Magnitude

Yang Lei,Paul Siqueira

doi:10.3390/rs70505639

Abstract

This paper describes an automatic mosaicking algorithm for creating large-scale mosaic maps of forest height. In contrast to existing mosaicking approaches through using SAR backscatter power and/or InSAR phase, this paper utilizes the forest height estimates that are inverted from spaceborne repeat-pass cross-pol InSAR correlation magnitude. By using repeat-pass InSAR correlation measurements that are dominated by temporal decorrelation, it has been shown that a simplified inversion approach can be utilized to create a height-sensitive measure over the whole interferometric scene, where two scene-wide fitting parameters are able to characterize the mean behavior of the random motion and dielectric changes of the volume scatterers within the scene. In order to combine these single-scene results into a mosaic, a matrix formulation is used with nonlinear least squares and observations in adjacent-scene overlap areas to create a self-consistent estimate of forest height over the larger region. This automated mosaicking method has the benefit of suppressing the global fitting error and, thus, mitigating the “wallpapering” problem in the manual mosaicking process. The algorithm is validated over the U.S. state of Maine by using InSAR correlation magnitude data from ALOS/PALSAR and comparing the inverted forest height with Laser Vegetation Imaging Sensor (LVIS) height and National Biomass and Carbon Dataset (NBCD) basal area weighted (BAW) height. This paper serves as a companion work to previously demonstrated results, the combination of which is meant to be an observational prototype for NASA’s DESDynI-R (now called NISAR) and JAXA’s ALOS-2 satellite missions.

Highlights

Large-scale mosaics of biophysical parameters are important for monitoring global carbon storage, as well as forest degradation
When combined with field inventory and optical data, the SRTM InSAR phase data has been utilized to generate national mosaic maps of both biomass and forest height for the United States, which are provided by the National Biomass and Carbon Dataset (NBCD)
We investigate the solution for a three-scene mosaicking problem that serves as a simplified scenario and, generalize the matrix formulation for multiple overlapping scenes

Summary

Introduction

Large-scale mosaics of biophysical parameters (such as biomass and forest height) are important for monitoring global carbon storage, as well as forest degradation. For this purpose, spaceborne missions have the vantage point from space and are efficient platforms for remote sensing data collection. The. Shuttle Radar Topography Mission (SRTM), which carried a C-band synthetic aperture radar (SAR). When combined with field inventory and optical data, the SRTM InSAR phase data has been utilized to generate national mosaic maps of both biomass and forest height for the United States, which are provided by the National Biomass and Carbon Dataset (NBCD). In addition to this data, JAXA’s L-band JERS-1 (from 1992 to 1998; [3]) and ALOS/PALSAR (2006 to 2011; [4,5]) have collected a large amount of SAR image data over the past decade

Methods

Results

Discussion

Conclusion