A5026864044- Remote Sensing and LiDAR Applications
- Forest ecology and management
- Forest Ecology and Biodiversity Studies
- Forest Management and Policy
- Remote Sensing in Agriculture
- Fire effects on ecosystems
- Wildlife-Road Interactions and Conservation
- Land Use and Ecosystem Services
Minnesota Department of Natural Resources
2016-2022
University of Minnesota
2016-2018
Michigan Technological University
2014-2016
Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast site-specific models. We integrated inventory plot with spatial predictors from Landsat time-series imagery LiDAR strip samples at four sites across the eastern USA—Minnesota (MN), Maine (ME), Pennsylvania-New Jersey (PANJ) South Carolina...
The publicly accessible archive of Landsat imagery and increasing regional-scale LiDAR acquisitions offer an opportunity to periodically estimate aboveground forest biomass (AGB) from 1990 the present align with reporting needs National Greenhouse Gas Inventories (NGHGIs). This study integrated time-series data, a state-wide dataset, recent cycle national inventory (NFI) records in Minnesota, USA, obtain spatially explicit AGB across large region space time back baseline used by US NGHGI....
The conventional approach to LiDAR-based forest inventory modeling depends on field sample data from fixed-radius plots (FRP). Because FRP sampling is cost intensive, combining variable-radius plot (VRP) and LiDAR has the potential improve efficiency. overarching goal of this study was evaluate integration VRP data. using different basal-area factors (BAF) were colocated in 6 conifer stands near Alberta, Michigan, United States. A suite metrics developed for 24 resolutions at each location,...
The ability to harmonize data sources with varying temporal, spatial, and ecosystem measurements (e.g. forest structure soil organic carbon) for creation of terrestrial carbon baselines is paramount refining the monitoring stocks stock changes. In this study, we developed examined short- (5 years) long-term (30 performance matrix models incorporating light detection ranging (LiDAR) strip samples time-series Landsat surface reflectance high-level products, field inventory predict aboveground...
Aboveground biomass (AGB) estimates for regional-scale forest planning have become cost-effective with the free access to satellite data from sensors such as Landsat and MODIS. However, accuracy of AGB predictions based on passive optical depends spatial resolution extent target area fine (small pixels) are associated smaller coverage longer repeat cycles compared coarse data. This study evaluated various resolutions Landsat-derived predictors regional models at three different sites in...
Abstract Tree cavities are an essential habitat component for wildlife species across diverse taxa, from insects to large mammals. Many of these imperiled by loss cavities. Further, conservation action is hindered limited information on the spatial distribution cavities, largely due difficulties in developing useful models their presence or abundance. Accurately predicting fine‐scale, landscape‐wide, important features would greatly benefit measures. In this study, we evaluated efficacy...
AbstractAbstract. This paper summarizes the output of an imputation model that simultaneously estimates multiple operational-scale forest inventory attributes in Laurentian mixed type United States. The was constrained by national privacy protocols and temporal uncertainties feature reference data. Estimates were most accurate at county level more variable across smaller spatial extents. Model development validation highlighted performance reliability influenced our approach using publicly...
We used LiDAR metrics and satellite imagery to examine regeneration on forested sites disturbed via harvest or natural means over a 44-year period. tested the effectiveness of older low-density elevation data in producing information related existing levels above ground biomass (AGB). To accomplish this, we paired with time series wetness greenness indices derived from Landsat model changes AGB for experiencing different agents change. Current was determined high-density acquired northern...