Speaker
Description
Sweden covers approximately 450,000 km2, almost 60% consisting of forests. More than 95% of the forests are intensively managed, thus representing a major source of income besides being a substantial carbon sink. Forest resources in Sweden have been quantified since 1923 with on ground surveys at inventory plots. Currently, the national forest inventory (NFI) consists of field plots that are being visited with a 5-years cycle and a number of field plots that are visited once. In total, 12,000 inventory plots are surveyed yearly. The forest field inventory allows for a broad assessment of forest resources; to capture the spatial distribution of these resource, the use of remote sensing has been fostered in Sweden already in the early days. In particular, spaceborne remote sensing was acknowledged to achieve detailed and complete coverage of the whole country in a reasonable amount of time and at reasonable costs compared to on ground surveys. Since 2000, optical imagery has been used to generate country-wide estimates of forest variables on a 5-years basis. A non-parametric approach is used to combine plot data from the national forest inventory and optical bands to estimate a number of forest variables, including stem volume and above-ground biomass. Besides the indirect relationship between optical reflectances and biomass, the mapping reflects the necessity of stitching estimates from images acquired under different viewing geometries and atmospheric conditions resulting in seams and unnatural biomass spatial distributions. More recently, elevation information from laser waveforms and SAR interferometric phase at X-band has been used together with NFI inventory data to generate two country-wide datasets of biomass estimates. In order to achieve full coverage, several years of acquisitions and detailed planning of the acquisitions were necessary, which translates in high costs of operation. Because of its relatively weak sensitivity to biomass and, until recently, sparse availability, the SAR backscatter from spaceborne missions has not been used as widely. Nonetheless, there is an increasing attention paid by space agencies to achieve full and repeated coverage with spaceborne SAR missions and there is evidence that the estimation of biomass based on SAR backscatter appears reasonable when based on multi-temporal observations.
In this paper, we present a number of datasets with biomass estimates for Sweden based on Envisat ASAR and Sentinel-1 (C-band), ALOS PALSAR and ALOS-2 PALSAR-2 (L-band). Each biomass dataset is accompanied by per-pixel estimates of the standard error. All datasets share the same retrieval framework, namely the BIOMASAR algorithm, and the same strategy for validation based on the forest inventory plots of the NFI. Here, we discuss the impact of amount and specifications of the SAR data on the retrieval, the impact of the modelling framework on the retrieval, the validity of the SAR-based estimates and, finally, the usefulness and the limitations of the datasets in a user's context.
