Data describing aircraft position and attitude are essential to computing return positions from ranging data collected during airborne laser scanning (ALS) campaigns. However, these data are often excluded from the products delivered to the client and their recovery after the contract is complete can require negotiations with the data provider, may involve additional costs, or even be infeasible. This paper presents a rigorous, fully automated, novel method for recovering aircraft positions using only the point cloud. The study used ALS data from five acquisitions in the US Pacific Northwest region states of Oregon and Washington and validated derived aircraft positions using the smoothed best estimate of trajectory (SBET) provided for the acquisitions. The computational requirements of the method are reduced and precision is improved by relying on subsets of multiple-return pulses, common in forested areas, with widely separated first and last returns positioned at opposite sides of the aircraft to calculate their intersection, or closest point of approach. To provide a continuous trajectory, a cubic spline is fit to the intersection points. While it varies by acquisition and parameter settings, the error in the computed aircraft position seldom exceeded a few meters. This level of error is acceptable for most applications. To facilitate use and encourage modifications to the algorithm, the authors provide a code that can be applied to data from most ALS acquisitions.
In Phase III of the North American Forest Dynamics (NAFD) study an automatic workflow has been developed for evaluating forest disturbance history using Landsat observations. It has four major components: an automated approach for image selection and preprocessing, the vegetation change tracker (VCT) forest disturbance analysis, post-processing, and validation. This approach has been applied to the conterminous US (CONUS) to produce a comprehensive analysis of US forest disturbance history using the NASA Earth Exchange (NEX) cloud computing system. The resultant NAFD-NEX product includes 25 annual forest disturbance maps for 1986-2010 and two time-integrated maps to provide spatial-temporal synoptic view of disturbances over this time period. These maps were derived based on 24,000+ scenes selected from 350,000+ available Landsat images at 30-m resolution, and were validated using a visual assessment of Landsat time-series images in combination with high-resolution and other ancillary data sources over samples selected using a probability based sampling method. The validation revealed no major biases in the NAFD-NEX maps for disturbance events that resulted in at least 20% canopy cover loss. The average user's and producer's accuracies for the disturbance class were 53.6% and 53.3%, respectively, with the individual year's user's accuracy varying from 42.8% to 73.6% and producer's accuracy from 39.0% to 84.8% over the 25-year period. The NAFD-NEX disturbance maps are available from a web portal of the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL-DAAC) at https://doi. org/10.3334/ORNLDAAC/1290.
Evidence of shifting dominance among major forest disturbance agent classes regionally to globally has been emerging in the literature. For example, climate-related stress and secondary stressors on forests (e.g., insect and disease, fire) have dramatically increased since the turn of the century globally, while harvest rates in the western US and elsewhere have declined. For shifts to be quantified, accurate historical forest disturbance estimates are required as a baseline for examining current trends. We report annual disturbance rates (with uncertainties) in the aggregate and by major change causal agent class for the conterminous US and five geographic subregions between 1985 and 2012. Results are based on human interpretations of Landsat time series from a probability sample of 7200 plots (30 m) distributed throughout the study area. Forest disturbance information was recorded with a Landsat time series visualization and data collection tool that incorporates ancillary high-resolution data. National rates of disturbance varied between 1.5% and 4.5% of forest area per year, with trends being strongly affected by shifting dominance among specific disturbance agent influences at the regional scale. Throughout the time series, national harvest disturbance rates varied between one and two percent, and were largely a function of harvest in the more heavily forested regions of the US (Mountain West, Northeast, and Southeast). During the first part of the time series, national disturbance rates largely reflected trends in harvest disturbance. Beginning in the mid-90s, forest decline-related disturbances associated with diminishing forest health (e.g., physiological stress leading to tree canopy cover loss, increases in tree mortality above background levels), especially in the Mountain West and Lowland West regions of the US, increased dramatically. Consequently, national disturbance rates greatly increased by 2000, and remained high for much of the decade. Decline-related disturbance rates reached as high as 8% per year in the western regions during the early-2000s. Although low compared to harvest and decline, fire disturbance rates also increased in the early- to mid-2000s. We segmented annual decline-related disturbance rates to distinguish between newly impacted areas and areas undergoing gradual but consistent decline over multiple years. We also translated Landsat reflectance change into tree canopy cover change information for greater relevance to ecosystem modelers and forest managers, who can derive better understanding of forest-climate interactions and better adapt management strategies to changing climate regimes. Similar studies could be carried out for other countries where there are sufficient Landsat data and historic temporal snapshots of high-resolution imagery.
The Rocky Mountain Research Station works with National Forest planning teams to understand and maximize an important resource: forest data collected by the Forest Service’s Forest Inventory and Analysis (FIA) program. The program’s website, found at https://www.fia.fs.fed. us, provides a variety of tools that allow users to download standard reports and create custom queries that can be used to improve the efficiency of their planning process. By integrating or putting FIA data to work, National Forest planners are able to meet the 2012 Planning Rule’s requirements for monitoring and using the best available science. For example, National Forest planning teams can use FIA data to better understand forest characteristics and conditions using readily available data and FIA analysis skills. Additional information on FIA resources for the Interior West region can be found at https://www.fs.usda.gov/rmrs/ interior-west-forest-inventory-analysis-fia. Other resources for National Forest plan revision teams include riparian and groundwater-dependent ecosystems assessments and a nationwide toolset of National Forest Climate Change Maps.
Nine multipurpose silvicultural treatments, formulated as a synthesis of recently implemented prescriptions offered by forest managers, were simulated to evaluate their effectiveness at enhancing fire resistance. The Forest Vegetation Simulator was applied, within the BioSum Framework, on over 3,000 Forest Inventory and Analysis plots representing 5 million hectares of dry mixed conifer forests in eastern Washington and Oregon and California’s Sierra Nevada Mountains. We developed a composite fire-resistance score based on four fuel modification principals and metrics: fuel strata gap, canopy bulk density, proportion of basal area in resistant species, and predicted tree survival. The trajectories of stands with and without treatment were compared to evaluate effectiveness immediately post-treatment, and over the three decades that followed. Seventy percent of these forests could be effectively treated in the short term by at least one prescription. Pretreatment forest condition, particularly fire-resistant species abundance, strongly influenced short-term treatment success, and the post-treatment stand dynamics that limit treatment longevity. Treatment effectiveness endured only 10 or 20 years, depending on fire-resistant species abundance, owing to growing space for crown expansion generated by treatment plus regeneration and release and growth of understory tree strata.
Wildfires in southwestern US ponderosa pine (Pinus ponderosa Lawson & C. Lawson) forests have recently increased in size and severity, leaving large, contiguous patches of tree mortality, and raising concerns about post-fire recovery. Ponderosa pines are a dominant species in the Southwest and they evolved with low- to moderate-severity fire regimes. They are poorly adapted to regenerate after large, high-severity fires because they do not have serotinous cones, re-sprouting capabilities, or long-lived seed banks. Additionally, high-severity fires can favor competing understory plants or induce long-term changes to soil nutrient dynamics and surface fuel loads, potentially altering ponderosa pine regeneration niches. Furthermore, high-severity wildfires and the loss of ponderosa pines may alter fungal community composition, including pine-symbiotic ectomycorrhizal (EM) fungi and saprotrophic fungi, which are important for forest recovery and productivity. My research objectives were to understand the effects of fire severity > 10 years post-fire on: (1) the spatial patterns, and interactions of regenerating ponderosa pine and sprouting tree species, (2) ponderosa pine regeneration niches and seedling growth, and (3) fungal sporocarp and root tip EM community composition and colonization. My study sites for the first objective included large, 4-ha plots located in two types of high-severity (100% tree mortality) burn, either adjacent to residual live forest edges (edge plots) or > 200 m from any residual live trees (interior plots) in two Arizona wildfires, the 2000 Pumpkin and 2002 Rodeo-Chediski Fires.
Of California’s almost 100 million ac, about a third are forested (32 million ac). This report, including the accompanying tables, summarizes key findings from the 5,369 Forest Inventory and Analysis (FIA) plots measured in California’s forests during the period 2006–2015. Estimates are provided for forest area, ownership, species composition and distribution, size and age classes, volume, biomass, carbon, dead and downed wood, and understory vegetation. Starting in 2001, plots were measured on a 10-year cycle (10 percent of all plots measured annually). Thus, those plots measured in 2011–2015 represent completion of half of the remeasurement cycle; estimates of growth, mortality, and removals from remeasured plots are also included. The U.S. Forest Service manages about half of California’s forested land—48 percent. Fifty-two percent of California’s forests is categorized as timberland (unreserved forest land capable of producing ≥20 ft of wood per acre per year) predominantly consisting of the California mixed-conifer type. The most common forest type on the remaining 48 percent was western oak. Mean annual gross growth was 1.99 billion ft/year. Subtracting harvest removals (21 percent of growth values) and mortality (45 percent of growth values) still resulted in a positive net growth of 673 million ft/year. Of some of the commercially important tree species, damage was present in 17 to 27 percent of the trees, including Douglas-fir (17 percent), white fir (27 percent), ponderosa pine (20 percent), and redwood (17 percent). The two most prevalent nonnative species were both grasses—cheatgrass (estimated 277,000 ac of cover) and ripgut brome (234,000 ac). During the 10-year period, the years with the most forested acres with evidence of fire were 2008 and 2015. FIA plots will continue to be measured as stipulated by the 1998 Farm Bill. By the time the next FIA report for California is issued, a complete remeasurement cycle will have been completed.
The Pacific Northwest Research Station launched a Carbon Dynamics for Land and Watershed Stewardship research initiative in 2019. In this webinar, which took place January 21, 2020, working groups summarize their progress to date and talk about next steps and opportunities for additional scientists and stakeholders to contribute.
Methods to accurately estimate spatially explicit fuel consumption are needed because consumption relates directly to fire behavior, effects, and smoke emissions. Our objective was to quantify sparkleberry (Vaccinium arboretum Marshall) shrub fuels before and after six experimental prescribed fires at Fort Jackson in South Carolina. We used a novel approach to characterize shrubs non-destructively from three-dimensional (3D) point cloud data collected with a terrestrial laser scanner. The point cloud data were reduced to 0.001 m-3 voxels that were either occupied to indicate fuel presence or empty to indicate fuel absence. The density of occupied voxels was related significantly by a logarithmic function to 3D fuel bulk density samples that were destructively harvested (adjusted R2 = .32, P < .0001). Based on our findings, a survey-grade Global Navigation Satellite System may be necessary to accurately associate 3D point cloud data to 3D fuel bulk density measurements destructively collected in small (submeter) shrub plots. A recommendation for future research is to accurately geolocate and quantify the occupied volume of entire shrubs as 3D objects that can be used to train models to map shrub fuel bulk density from point cloud data binned to occupied 3D voxels.
The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.