
Evan Beren BrooksVirginia Tech | VT · Department of Forest Resources and Environmental Conservation
Evan Beren Brooks
Ph.D.
About
20
Publications
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948
Citations
Education
August 2010 - May 2013
August 2008 - May 2010
January 2005 - May 2008
Publications
Publications (20)
The forest carbon sink of the United States offsets emissions in other sectors. Recently passed US laws include important climate legislation for wildfire reduction, forest restoration, and forest planting. In this study, we examine how wildfire reduction strategies and planting might alter the forest carbon sink. Our results suggest that wildfire...
Disturbances including fire, insect and disease outbreaks,
and drought are ubiquitous in forests and rangelands,
and many disturbance events are parts of the natural dynamics
of forest and rangeland ecosystems. This chapter is a new
addition to the Resources Planning Act (RPA) Assessment
and summarizes disturbance trends in the recent past and...
Freshwaters are important, interconnected, and imperiled. Aquatic ecosystems, including freshwater fishes, are closely tied to the terrestrial ecosystems they are embedded within, yet available spatially explicit datasets have been underutilized to determine associations between freshwater fishes and forested areas. Here, we determined the spatial...
National Forest Inventories (NFI) are designed to produce unbiased estimates of forest parameters at a variety of scales. These parameters include means and totals of current forest area and volume, as well as components of change such as means and totals of growth and harvest removals. Over the last several decades, there has been a steadily incre...
The southeastern United States is unique in terms of both the intensity and scale of forest management, which includes substantial thinning and other forms of harvesting. Because thinning is not a land use transition, and the disturbance signal is relatively subtle compared to a clear cut, there is a dearth of studies that attempt to detect thinnin...
Future land use projections are needed to inform long-term planning and policy. However, most projections require downscaling into spatially explicit projection rasters for ecosystem service analyses. Empirical demand-allocation algorithms input coarse-level transition quotas and convert cells across the raster, based on a modeled probability surfa...
The goal of this study was to evaluate whether harmonic regression coefficients derived using all available cloud-free observations in a given Landsat pixel for a three-year period can be used to estimate tree canopy cover (TCC), and whether models developed using harmonic regression coefficients as predictor variables are better than models develo...
One way of analyzing satellite images for land use and land cover change (LULCC) is time series analysis (TSA). Most of the many TSA based LULCC algorithms proposed in the remote sensing community perform well on datasets for which they were designed, but their performance on randomly chosen datasets from across the globe has not been studied. A po...
The continued development of algorithms using multitemporal Landsat data creates opportunities to develop and adapt imputation algorithms to improve the quality of that data as part of preprocessing. One example is de-striping Enhanced Thematic Mapper Plus (ETM+, Landsat 7) images acquired after the Scan Line Corrector failure in 2003. In this stud...
Ecological forecasting of forest productivity involves integrating observations into a process‐based model and propagating the dominant components of uncertainty to generate probability distributions for future states and fluxes. Here, we develop a forecast for the biomass change in loblolly pine (Pinus taeda) forests of the southeastern United Sta...
The relationship between forests and changing global climate is of major importance to forest landowners and policymakers. In this study, we apply an empirical growth and yield model for loblolly pine (Pinus taeda) to the southeastern United States in an effort to predict the impacts of changing climate and ambient CO2 concentrations on loblolly pi...
The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover. Performance among algorithms varies acr...
Remote detection of forest disturbance remains a key area of interest for scientists and land managers. Subtle disturbances such as drought, disease, insect activity, and thinning harvests have a significant impact on carbon budgeting and forest productivity, but current change detection algorithms struggle to accurately identify them, especially o...
Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion...
Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms. Many of these algorithms take advantage...
Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion...
The use of satellite-derived classification maps to improve post-stratified forest parameter estimates is well established. When reducing the variance of post-stratification estimates for forest change parameters such as forest growth, it is logical to use a change-related strata map. At the stand level, a time series of Landsat images is ideally s...
Forest change information is critical in forest planning, ecosystem modeling, and in updating forest condition maps. The Landsat satellite platform has provided consistent observations of the world's ecosystems since 1972. A number of innovative change detection algorithms have been developed to use the Landsat archive to identify and characterize...
One challenge to implementing spectral change detection algorithms using multitemporal Landsat data is that key dates and periods are often missing from the record due to weather disturbances and lapses in continuous coverage. This paper presents a method that utilizes residuals from harmonic regression over years of Landsat data, in conjunction wi...
With the advent of free Landsat data stretching back decades, there has been a surge of interest in utilizing remotely sensed data in multitemporal analysis for estimation of biophysical parameters. Such analysis is confounded by cloud cover and other image-specific problems, which result in missing data at various aperiodic times of the year. Whil...