Generation of Large-Scale Moderate-Resolution Forest Height Mosaic With Spaceborne Repeat-Pass SAR Interferometry and Lidar
Abstract
This paper provides an overview of the scattering model, inversion approach, and validation of the application results for creating large-scale moderate-resolution (hectare-level) mosaics of forest height through using spaceborne repeat-pass SAR interferometry and lidar. By incorporating several improvements to the forest height inversion and mosaicking approach, the height estimation accuracy along with the robustness of this approach have been considerably enhanced from its originally reported accuracy of RMSE of 3–4 m at a 20-hectare aggregated pixel size to RMSE of 3–4 m on the order of 3–6 hectares. Furthermore, practical data processing schemes are provided in detail. Extensive validation results are demonstrated which include: 1) a forest height mosaic (total area of 11.6 million hectares) is generated for the U.S. states of Maine and New Hampshire using Japanese Aerospace Exploration Agency's (JAXA) ALOS-1 InSAR correlation data and a small airborne lidar strip (44 000 hectares); 2) the mosaic height estimates are further compared with the available airborne lidar data and field measurements over both flat and mountainous areas; and 3) feasibility of using modern repeat-pass InSAR satellites with short repeat interval is also examined by using JAXA's ALOS-2 data. This simple and efficient approach is a potential observational prototype with much smaller error budget for the future spaceborne repeat-pass L-band InSAR systems with small spatial baseline and moderate/large temporal baseline (such as NISAR) in combination with lidar (such as GEDI) on the application of large-scale forest height/biomass mapping. It also serves as a complementary tool to the spaceborne single-pass InSAR systems using InSAR/PolInSAR methods when full-pol data are not available and/or when the underlying topography slope causes problems for these approaches.
Additional Information
© 2018 IEEE. Manuscript received December 5, 2017; revised April 30, 2018 and June 21, 2018; accepted July 14, 2018. Date of publication August 17, 2018; date of current version January 21, 2019. This work was supported in part by the National Aeronautics and Space Administration (NASA) Headquarters through the NASA Earth and Space Science Fellowship Program, a grant for the development of NISAR Ecosystems Applications under NASA grant number NNX16AK59G and in part by the NASA Postdoctoral Program at the Jet Propulsion Laboratory, California Institute of Technology, administered by Universities Space Research Association under contract with NASA. The authors would like to thank P. Agram and M. Lavalle from the ISCE Developer Team at JPL for the valuable discussions and generous support on InSAR processing of ALOS and ALOS-2 data using JPL's ISCE software package. They would like to thank T. Whelen at the University of Massachusetts Amherst for developing the python version of the FSH software, S. Hagen at Applied GeoSolutions for the support of using the lidar2dems software, as well as the anonymous reviewers for the valuable and professional suggestions. They would also like to thank Japanese Aerospace Exploration Agency (JAXA) for the ALOS-1/-2 data acquisitions as well as the Kyoto and Carbon (K&C) initiative.Additional details
- Eprint ID
- 92914
- Resolver ID
- CaltechAUTHORS:20190214-074012255
- NASA Earth and Space Science Fellowship
- NNX16AK59G
- NASA
- NASA/JPL/Caltech
- Created
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2019-02-14Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field