Airborne multi-temporal L-band polarimetric SAR data for biomass estimation in semi-arid forests

• Published in: Remote sensing of environment Vol. 145; pp. 93 - 104
• Main Authors: Tanase, Mihai A., Panciera, Rocco, Lowell, Kim, Tian, Siyuan, Hacker, Jorg M., Walker, Jeffrey P.
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 05-04-2014; Elsevier
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Earth sciences; Earth, ocean, space; Exact sciences and technology; Forest biomass; Forest variability; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; L-band radar; Multi-temporal; Polarimetric decomposition; Random forest; Teledetection and vegetation maps; Random forest; Multi-temporal; Forest biomass; L-band radar; Polarimetric decomposition; Forest variability; components; Forest(graph); mathematical models; Parametric system; aggregation; cycles; decomposition; Modeling; Semi arid zone; Imaging; Synthetic aperture radar; Estimation error; biomass; density; Estimation; L band; Acquisition; Independent variable; Lidar; radar methods; Multidate observation
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2014.01.024

Using the airborne Polarimetric L-band Imaging Synthetic aperture radar (PLIS) the impact of high revisit cycle and full polarimetric acquisitions on biomass retrieval was investigated by means of backscatter-based multi-temporal methods. Parametric and non-parametric models were used to relate reference biomass levels obtained from field plot measurements and high point density lidar data to backscatter intensities or polarimetric target decomposition components. Single-date retrieval using multiple independent variables provided lower estimation errors when compared to models using one independent variable with errors decreasing by 2% to 15%. The multi-temporal aggregation of daily biomass estimates did not improve the overall retrieval accuracy but provided more reliable estimates with respect to single-date methods. Backscatter intensities improved estimation accuracies up to 10% compared to polarimetric target decomposition components. Using all four polarizations increased the estimation accuracy marginally (2%) when compared to a dual-polarized system. The biomass estimation error was considerably reduced (up to 30%) only by decreasing the spatial resolution and was related to decreasing forest variability with increasing pixel size. These results indicate that, at least in semi-arid areas, future L-band missions would not significantly improve biomass estimation accuracy using backscatter-based modeling approaches despite their better spatial resolution, higher revisit cycles and the availability of fully polarimetric information.
•The potential of upcoming L-band missions for biomass retrieval was investigated.•Polarimetry showed similar sensitivity to biomass levels as backscatter intensity.•Multi-temporal methods were more reliable when compared to single-date methods.•Significant improvements of biomass estimates were possible by increasing plot size.