L-Band SAR Backscatter Related to Forest Cover, Height and Aboveground Biomass at Multiple Spatial Scales across Denmark

Neha Joshi,Edward Mitchard,Johannes Schumacher,Sassan Saatchi,Rasmus Fensholt,Vivian Johannsen

doi:10.3390/rs70404442

Neha Joshi, Edward Mitchard + Show 4 more

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https://doi.org/10.3390/rs70404442

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Abstract

Mapping forest aboveground biomass (AGB) using satellite data is an important task, particularly for reporting of carbon stocks and changes under climate change legislation. It is known that AGB can be mapped using synthetic aperture radar (SAR), but relationships between AGB and radar backscatter may be confounded by variations in biophysical forest structure (density, height or cover fraction) and differences in the resolution of satellite and ground data. Here, we attempt to quantify the effect of these factors by relating L-band ALOS PALSAR HV backscatter and unique country-wide LiDAR-derived maps of vegetation penetrability, height and AGB over Denmark at different spatial scales (50 m to 500 m). Trends in the relations indicate that, first, AGB retrieval accuracy from SAR improves most in mapping at 100-m scale instead of 50 m, and improvements are negligible beyond 250 m. Relative errors (bias and root mean squared error) decrease particularly for high AGB values (\(>\)110 Mg ha\(^{-1}\)) at coarse scales, and hence, coarse-scale mapping (\(\ge\)150 m) may be most suited for areas with high AGB. Second, SAR backscatter and a LiDAR-derived measure of fractional forest cover were found to have a strong linear relation (R\(^2\) = 0.79 at 250-m scale). In areas of high fractional forest cover, there is a slight decline in backscatter as AGB increases, indicating signal attenuation. The two results demonstrate that accounting for spatial scale and variations in forest structure, such as cover fraction, will greatly benefit establishing adequate plot-sizes for SAR calibration and the accuracy of derived AGB maps.

Highlights

Explicit measures of aboveground forest biomass (AGB) are important for understanding the terrestrial carbon cycle and have been largely addressed in the context of global environmental change [1,2]
Our study demonstrates the suitability of a two-step approach, in which radar images are calibrated against a higher-resolution light detection and ranging (LiDAR) product, itself calibrated with ground measurements of aboveground biomass (AGB) [14]
We have provided a characterization of the relations between cross-polarized ALOS

Summary

Introduction

Explicit measures of aboveground forest biomass (AGB) are important for understanding the terrestrial carbon cycle and have been largely addressed in the context of global environmental change [1,2]. Existing national, continental and global maps produced using Earth observation data still face challenges in presenting the spatial distribution of biomass with high accuracy [6,7,8]. This may constrain evaluating the effectiveness of policies targeted towards forest carbon conservation. Large-scale mapping of aboveground carbon stocks has benefited from the wide-coverage remote sensing satellite data, calibrated with ground measurements of AGB based on field inventories, e.g., [9,10,11]. Small field plots may be associated with larger sampling errors due to local spatial variability of AGB, as well as geo-location mismatches with satellite imagery [14,15]

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