336 publications from this institution
Several upcoming satellite missions have core science requirements to produce data for accurate forest aboveground biomass mapping. Largely because of these mission datasets, the number of available biomass products is expected to greatly increase over the coming decade. Despite the recognized importance of biomass mapping for a wide range of science, policy and management applications, there remains no community accepted standard for satellite-based biomass map validation. The Committee on Earth Observing Satellites (CEOS) is developing a protocol to fill this need in advance of the next generation of biomass-relevant satellites, and this paper presents a review of biomass validation practices from a CEOS perspective. We outline the wide range of anticipated user requirements for product accuracy assessment and provide recommendations for the validation of biomass products. These recommendations include the collection of new, high-quality in situ data and the use of airborne lidar biomass maps as tools toward transparent multi-resolution validation. Adoption of community-vetted validation standards and practices will facilitate the uptake of the next generation of biomass products.
Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.
The data products consist of two layers that include estimates of<br> 1. growing stock volume (GSV, unit: m3/ha) for the year 2014 (raster data set)<br> Definition: volume of all living trees more than 6 cm in diameter at breast height measured over bark from ground to a top stem diameter of 0 cm. Excludes: branches, twigs, foliage, flowers, seeds, stump and roots.<br> 2. per-pixel of growing stock volume uncertainty expressed as standard error in m3/ha (raster data set) The maps have a spatial resolution of 3.2 arc sec (ca 0.5 ha for Russia). The GSV estimates were obtained by calibration of two remote sensing-based maps with ca 8000 ground plots from the National Forest Inventory:<br> • The global GlobBiomass map of GSV (Santoro, 2018; Santoro et al., 2020) is based on synthetic aperture radar (SAR) observations acquired around the year 2010 and has a spatial resolution of 100m, units m³ ha<sup>-1</sup>.<br> • The global Climate Change Initiative (CCI) Biomass map of AGB (Santoro and Cartus, 2019) is also based on SAR data, acquired in 2017 and has a spatial resolution of 100m, units t ha<sup>-1</sup>. The methodology, input data and software are published here: Schepaschenko, D., Moltchanova, E., Fedorov, S. <em>et al.</em> Russian forest sequesters substantially more carbon than previously reported. <em>Sci Rep</em> <strong>11, </strong>12825 (2021). https://doi.org/10.1038/s41598-021-92152-9