LiDAR derived vector representation of forested and forest gap areas of PRWI. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.

LiDAR derived percent understory cover at PRWI. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.

LiDAR derived Canopy Height at PRWI at 2m resolution. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.

LiDAR derived Canopy Height at PRWI at 1m resolution. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.

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LiDAR derived percent understory cover of HAFE at 2m resolution. These data are part of a large data set describing the three-dimensional structure of vegetation in portions of four, primarily forested national parks: Prince William Forest Park, Catoctin Mountain Park, C&O Canal National Historical Park, and Harpers Ferry National Historical Park. All four parks are within the National Capital Region Inventory and Monitoring Network and contain forest monitoring plots that have been measured yearly since 2005. We acquired Light Detection and Ranging (LiDAR) surveys of these parks during leaf-on conditions in 2009 and 2010. From these data four primary products were generated: (1) digital elevation models (2-m resolution DEMs), (2) Canopy height models (at 1- and 2-m resolutions), (3) canopy gaps (defined as 2-m grid cells with canopies shorter than 3m), and (4) understory percent cover (2-m resolution). All data products are made available in standard GIS-compatible file formats and are intended to be used to understand spatial patterns in vegetation structure and as documentation of baseline conditions. Future assessments of vegetation structure using the same or similar methods would enable assessment of change in vegetation structure over time.

This data set provides a 30-year record of Landsat TM and ETM+ derived forest phenology and the results of tree ring analyses for annual wood production and nitrogen and carbon isotopic composition at 113 selected forested sites in the eastern United States. The sites are located in four national parks: Prince William Forest Park (PRWI), Harpers Ferry National Historical Park (HAFE), Catoctin Mountain Park (CATO), and Great Smoky Mountains National Park (GRSM). Phenology and tree ring data cover 1984-2013.

The Inventory and Monitoring (I&M) Division's Mid-Atlantic Network (MIDN) and Northeast Coastal and Barrier Network (NCBN) have identified forest vegetation, and several associated vital signs, as high priority for long-term monitoring. The MIDN and NCBN long-term forest monitoring protocol was adapted from methods developed by the U.S. Forest Service Forest Inventory and Analysis program and was developed in collaboration with other eastern forest I&M networks. The forest monitoring protocol assesses the status and trends in structure, function, and composition of forested ecosystems, along with the impacts of stressors such as white-tailed deer, invasive exotic plants, exotic pests and pathogens, and effects of acid deposition on forest soils. A set of Standard Operating Procedures are shared with the Northeast Temperate Network's forest vegetation monitoring protocol. The current protocol has been designed to sample 392 plots in forested areas of MIDN and NCBN parks. Plot locations are randomly chosen from a 250-m grid developed for both networks using a spatially balanced design (generalized random-tessellation stratified). Each plot consists of a 20 x 20 m square where all stems with a diameter at breast height (dbh) ≥10 cm are identified, measured, tagged, marked, mapped, and their condition assessed. Stems with a dbh ≥1 cm are identified and measured in each of three microplots. Percent cover of shrubs ≥30 cm tall are also recorded in each of three microplots. Percent cover of all vascular plant species is estimated by species in eight 1 m2 quadrats. Number of tree seedlings by height class are also counted and assessed for presence or absence of deer browse in the 1 m2 quadrats. Coarse woody debris is measured along three 15 m transects. Data collected are used to inform management decisions affecting forested systems in MIDN and NCBN parks. To view all protocol documents, please visit: https://irma.nps.gov/DataStore/Reference/Profile/2189099 This data package contains a cumulative record of all forest monitoring data collected at National Park units in the Mid-Atlantic Network (MIDN) and Northeast Coastal and Barrier Network (NCBN) through the most recent field season and is organized into twenty-six (25) datasets: AdditionalSpecies_MIDN_NCBN.csv contains data captured during a 15-minute search for species not observed during other protocol activities on the plot. CWD_MIDN_NCBN.csv contains data captured from Line intercept sampling of coarse woody debris (CWD) along three 15-m transects. EventObservers_MIDN_NCBN.csv contains a list of all observers for each sampling event. Events_MIDN_NCBN.csv contains a list of all sampling events. MicroplotSaplings_MIDN_NCBN.csv contains data for all saplings measured in microplots. MicroplotShrubs_MIDN_NCBN.csv contains data for all shrubs measured in microplots. Plots_MIDN_NCBN.csv contains data regarding forest sampling plots. QuadCharacter_MIDN_NCBN.csv contains data characterizing the substrate of 1-m2 quadrats using standard cover classes. QuadNotes_MIDN_NCBN.csv contains a list of annotations relating to the sampling of quadrats. QuadSeedlings_MIDN_NCBN.csv contains counts of tree seedlings by species and height category collected in quadrats. QuadSpecies_MIDN_NCBN.csv contains data for groundstory vascular plant species collected in 1-m2 quadrats using standard cover classes. SoilHeader_MIDN_NCBN.csv contains event data for soil sampling. SoilLab_MIDN_NCBN.csv contains soil lab results for all soil samples collected. SoilSample_MIDN_NCBN.csv contains sample details for soil sampling. StandDisturbances_MIDN_NCBN.csv contains plot disturbance data for each sampling event. StandForestFloor_MIDN_NCBN.csv contains plot forest floor cover for each sampling event. StandInfoPhotos_MIDN_NCBN.csv contains various plot level metrics for each sampling event. StandPlantCoverStrata_MIDN_NCBN.csv contains plot level plant cover strata for each sampling event. StandSlopes_MIDN_NCBN.csv

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