Treesearch

DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived height information provides a powerful tool to make fine scale inference about height related forest attributes. Predictions can also be aggregated to sub-stand, stand, or strata levels. Remote-sensing derived forest attributes...

Forested ecosystems are shaped by climate, soil and biotic interactions, resulting in constrained spatial distribution of species and biomes. Tolerance traits of species determine their fundamental ecological niche, while biotic interactions narrow tree distributions to the realized niche. In particular, shade, drought and waterlogging tolerances have been well-characterized at the species level in the Northern hemisphere tree species. Species distribution models explore fundamental niches and current geographic distributions with respect to environmental factors, but their ability to...

The state of Oregon recently invested in exploring options for increasing the extent of forest restoration activity. This initiative aims to reduce the incidence, effects, and expense of catastrophic fire events and restore economic stability to rural communities by enhancing the supply of raw materials for wood processing facilities and wood-based, renewable energy producers, particularly in the comparatively xeric, eastern two-thirds of the State. Collaborating with PNW-FIA and Portland State University, the Oregon Department of Forestry evaluated current levels of fire hazard as...

In many forest inventories, statistical models are employed to predict values for attributes that are difficult and/or time-consuming to measure. In some applications, models are applied across a large geographic area, which assumes the relationship between the response variable and predictors is ubiquitously invariable within the area. The extent to which this assumption holds for a tree height prediction model was evaluated at regional, ecoprovince, and ecosection spatial scales in the Northeastern United States. Two nonlinear regression models were tested, a spatially-ambiguous model...

Understanding changes in land use and land cover over space and time provides an important means to evaluate complex interactions between human and biophysical systems, to project future conditions, and to design mitigation and adaptive management strategies. Assessing and monitoring landscape change is evolving into a foundational element of climate change adaptation, ecological restoration, and resource sustainability. Landscape change data are core to Forest Service functions including: land management planning, restoration analysis, carbon accounting, greenhouse gas emission reporting,...

The USDA Forest Service is evaluating the status of current landscape change maps and assessing gaps in their information content. These activities have been occurring under the auspices of the Landscape Change Monitoring System (LCMS) project, which is a joint effort between USFS Research, USFS Remote Sensing Applications Center (RSAC), USGS Earth Resources Observation and Science (EROS) Center, and academic partners. One of the early needs identified was a system that facilitated the visual comparison of several change maps in a common visualization framework. The application presented...

Analysis of remeasurement data from 1079 Forest Inventory and Analysis (FIA) plots revealed multi-scale change occurring in the temperate rainforests of southeast Alaska. In the western half of the region, including Prince William Sound, aboveground live tree biomass and carbon are increasing at a rate of 8 ( ± 2 ) percent per decade, driven by an increase in Sitka spruce. In the Alexander Archipelago, western red cedar is increasing, as is overall biomass on gentler slopes and in higher latitudes. These increases, which occurred during a warmer period of the Pacific Decadal Oscillation,...

In California, the Forest Inventory and Analysis (FIA) plots within large fires were visited one year after the fire occurred resulting in a time series of measurements before and after fire. During this additional plot visit, the standard inventory measurements were augmented for these burned plots to assess fire effects. One example of the additional measurements is the post fire index (PFI), which is a fire severity classification based on post-fire crown observations. Stands that showed presence or no evidence of residual green crowns were assigned to PFI classes Alive and Dead...

Forest inventory datasets offer unprecedented opportunities to model forest dynamics under evolving environmental conditions but they are analytically challenging due to irregular sampling time intervals of the same plot, across the years. We propose here a novel method to model dynamic changes in forest biomass and basal area using forest inventory data. Our methodology involves the following steps: 1) parameterize transition matrices for biomass using Gibbs sampling, 2) incorporate dynamic disturbance and forest growth scenarios and 3) simulate transient dynamics and stationary states...

REDD+, Reduction of Emissions from Deforestation and Forest Degradation is a United Nations initiative targeted to combat atmospheric carbon dioxide and global warming by providing monetary incentives to developing countries to preserve their forested land as effective carbon sinks. In order for these countries to receive this monetary benefit, they must develop and implement forest monitoring, reporting and validation (MRV) programs that effectively quantify the amount and change of “forested” land, the “health” of the forests, and estimate the amount of carbon in these forests. The USFS...