The use of airborne laser scanning to develop a pixel-based stratification for a verified carbon offset project

Background The voluntary carbon market is a new and growing market that is increasingly important to consider in managing forestland. Monitoring, reporting, and verifying carbon stocks and fluxes at a project level is the single largest direct cost of a forest carbon offset project. There are now many methods for estimating forest stocks with high accuracy that use both Airborne Laser Scanning (ALS) and high-resolution optical remote sensing data. However, many of these methods are not appropriate for use under existing carbon offset standards and most have not been field tested. Results This paper presents a pixel-based forest stratification method that uses both ALS and optical remote sensing data to optimally partition the variability across an ~10,000 ha forest ownership in Mendocino County, CA, USA. This new stratification approach improved the accuracy of the forest inventory, reduced the cost of field-based inventory, and provides a powerful tool for future management planning. This approach also details a method of determining the optimum pixel size to best partition a forest. Conclusions The use of ALS and optical remote sensing data can help reduce the cost of field inventory and can help to locate areas that need the most intensive inventory effort. This pixel-based stratification method may provide a cost-effective approach to reducing inventory costs over larger areas when the remote sensing data acquisition costs can be kept low on a per acre basis

Forest Environmental Reporting Services

One of the forest environmental monitoring projects of the European Space Agency is implementing remote-sensing based services for national Kyoto Protocol reporting. Key players in this reporting for five European countries are actively involved. Their needs are mainly forest maps, land-use and land-use change maps. Prototypes are being implemented on twelve test sites before proceeding to a large-scale demonstration covering 500 000 km2

The potential of a bioeconomy to reduce Brazilian GHG emissions towards 2030:a CGE-based life cycle analysis

Brazil is one of the largest emitters of greenhouse gases in the world with most of its emissions coming from the land use, land use change, and forestry (LULUCF) sector. New commitments have been set by the Paris Agreement and are reflected in the country's Nationally Determined Contribution (NDC). The Brazilian NDC has three main pillars to reduce emissions: increasing the share of biomass in the total primary energy supply to 18%, reducing deforestation, and achieving 45% of renewable energy in the energy mix. It is important to enlarge the share of biomass in the Brazilian economy, but it is also important to assess the potential impacts on deforestation in order to set the right strategy eventually. This study is thus an effort to investigate the contributions of a biobased economy to reduce Brazilian emissions, considering the broader concept of the bioeconomy, using biomass for energy, chemicals, and materials. To satisfy the objectives of the project, especially those related to its interest in economy‐wide changes in feedstock (from fossil to biobased), computable general equilibrium modeling (CGE) was chosen as the basic methodology integrated with an economic input–output life cycle analysis (EIO‐LCA). Results show that the impacts of the bioeconomy scenarios are positive but not sufficiently high to reduce the estimated emissions drastically. Emissions by the energy sector produce the highest reductions (7.5%) but the 12% increase in the LULUCF sector offsets those reduction142265285FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP2013/50347–