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

Assessing the use of multiseason quickbird imagery for mapping invasive species in a Lake Erie coastal marsh

QuickBird multispectral satellite images taken in September 2002 (peak biomass) and April 2003 (pre-growing season) were used to map emergent wetland vegetation communities, particularly invasive Phragmites australis and Typha spp., within a diked wetland at the western end of Lake Erie. An unsupervised classification was performed on a nine-layer image stack consisting of all four spectral bands from both dates plus a September Normalized Difference Vegetation Index image. The resulting eight cover classes distinguished three monodominant genera (Phragmites australis, Typha spp., Nelumbo lutea), three multigenera plant communities (wet meadow, other non persistent emergents, woody vegetation), and two unvegetated cover types (water, bare soil). Field validation at 196 data points yielded an overall classification accuracy of 62%, with producer's accuracy for the eight individual classes ranging from 41% to 91% and user's accuracy from 17% to 90%. Three-fourths of areas designated as Phragmites were correctly mapped, but 14% were found to be cattail (Typha) during field validation. Lotus (Nelumbo lutea) beds were accurately mapped on multiseason imagery (producer's accuracy = 91%); these beds had not yet emerged above water in April, but were fully developed in September. Other types of non persistent vegetation were confused with managed areas in which vegetation had been cut and burned to control invasive Phragmites. Multiseason QuickBird imagery is promising for distinguishing certain wetland plant species, but should be used with caution in highly managed areas where vegetation changes may reflect human alterations rather than phenological change

Inventory and Ventilation Efficiency of Nonnative and Native Phragmites australis (Common Reed) in Tidal Wetlands of the Chesapeake Bay

Nonnative Phragmites is among the most invasive plants in the U.S. Atlantic coast tidal wetlands, whereas the native Phragmites has declined. Native and nonnative patches growing side by side provided an ideal setting for studying mechanisms that enable nonnative Phragmites to be a successful invader. We conducted an inventory followed by genetic analysis and compared differences in growth patterns and ventilation efficiency between adjacent native and nonnative Phragmites stands. Genetic analysis of 212 patches revealed that only 14 were native suggesting that very few native Phragmites populations existed in the study area. Shoot density decreased towards the periphery of native patches, but not in nonnative patches. Ventilation efficiency was 300 % higher per unit area for nonnative than native Phragmites, likely resulting in increased oxidation of the rhizosphere and invasive behavior of nonnative Phragmites. Management of nonnative Phragmites stands should include mechanisms that inhibit pressurized ventilation of shoots