Exploiting Growing Stock Volume Maps for Large Scale Forest Resource Assessment: Cross-Comparisons of ASAR- and PALSAR-Based GSV Estimates with Forest Inventory in Central Siberia

Abstract

Growing stock volume is an important biophysical parameter describing the state and dynamics of the Boreal zone. Validation of growing stock volume (GSV) maps based on satellite remote sensing is challenging due to the lack of consistent ground reference data. The monitoring and assessment of the remote Russian forest resources of Siberia can only be done by integrating remote sensing techniques and interdisciplinary collaboration. In this paper, we assess the information content of GSV estimates in Central Siberian forests obtained at 25 m from ALOS-PALSAR and 1 km from ENVISAT-ASAR backscatter data. The estimates have been cross-compared with respect to forest inventory data showing 34% relative RMSE for the ASAR-based GSV retrievals and 39.4% for the PALSAR-based estimates of GSV. Fragmentation analyses using a MODIS-based land cover dataset revealed an increase of retrieval error with increasing fragmentation of the landscape. Cross-comparisons of multiple SAR-based GSV estimates helped to detect OPEN ACCESSForests 2014, 5 1754 inconsistencies in the forest inventory data and can support an update of outdated forest inventory stands.

Estimation of Above-Ground Biomass over Boreal Forests in Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data

“…Data collection for the FRA 2020 has begun in 2018, even though in many countries up-to-date quantitative estimates on the AGB are not available. For example, in the Russian Federation, which has the largest forest area in the world, some forest regions have not been recorded for more than 25 years [7]. At the same time, due to more frequent fires and illegal logging, (which is estimated to make up approximately 20% of all logging activity in Russia), according to the World Bank and the World Wide Fund for Nature (WWF) [8], the AGB experiences dynamic change within a given period of time.…”

“…For the boreal forests, a biomass (AGB or GSV) estimation error of approximately 20% was calculated for forest stands greater than 10 ha [40,[54][55][56][57] or approximately 40% for a spatial resolution of 25 m [7,22]. Current studies using X-band interferometric SAR height information derived over highly managed forest, reported an estimation error of 16% [20].…”

Radar Time Series for Land Cover and Forest Mapping

“…Change is shown for the zoom region as color composites with (b1) Red-2007, Green-2008, Blue-2009and (b2) Red-2008, Green-2009, Blue-2010. The data were made available through the ALOS Kyoto and Carbon Initiative of JAXA inventory errors of 34-39 %, as has been investigated stand-wise in Hüttich et al (2014b). It can be concluded, that the freely available PALSAR mosaics are an applicable tool for up-to-date forest monitoring -even considering varying accuracies.…”

Can We Use Forest Inventory Mapping as a Coarse Filter in Ecosystem Based Management in the Black Spruce Boreal Forest?

“…From an ecosystem based management standpoint, mapping tools have limitations due to the lack of accuracy that may be inadequate for conservation planning [39] and the use of better tools such as remote sensing [40], including LiDAR [41] or Radar [42] should be promoted. As the detection of the severity of an event that took place decades or even centuries previous via remote sensing is unlikely, studies should focus on finding a physical proxy that would remain within the forest.…”