Height of the top of canopy above bare earth (Canopy Height Model (CHM)); data are mosaicked over AOP footprint; mosaicked onto a spatially uniform grid at 1 m spatial resolution in 1 km by 1 km tiles. Data are provided in geotiff format.

This dataset provides 30 m gridded estimates of aboveground biomass density (AGBD), forest canopy height, and tree canopy coverage for the New England Region of the U.S., including the state of Maine, Vermont, New Hampshire, Massachusetts, Connecticut, and Rhode Island, for the nominal year 2015. It is based on inputs from 1 m resolution Leaf-off LiDAR data collected from 2010 through 2015, high-resolution leaf-on agricultural imagery, and FIA plot-level measurements. Canopy height and tree cover were derived directly from LiDAR data while AGBD was estimated by statistical models that link remote sensing data and FIA plots at the pixel level. Error in AGBD was calculated at the 90% confidence interval. This approach can directly contribute to the formation of a cohesive forest carbon accounting system at national and even international levels, especially via future integrations with NASA's spaceborne LiDAR missions.

Tree crown geometry and height, especially when coupled with remotely sensed data, can aid in the characterization of tree and forest structure. In this study, we collected crown geometry data (tree height, crown radius, and crown depth) in order to develop mixed-effects model allometric equations. We leveraged the already existing Center for Tropical Forest Science (CTFS) and Smithsonian Institute’s Forest Global Earth Observatory (ForestGEO) MegaPlot on Prospect Hill at Harvard Forest, Massachusetts to apply allometric equations. In total, we sampled 374 trees across 14 species. Developed allometry was applied to 2014 CTFS-ForestGEO census data to develop allometric canopy height models, which were compared to a lidar canopy height model acquired by NASA’s G-LiHT.

This dataset provides 30-m resolution maps of estimated forest aboveground biomass (AGB) in the state of Maryland between 1984-2016. This dataset was produced by a novel forest carbon monitoring system which utilizes high resolution remote sensing of contemporary tree cover and canopy height as powerful constraints within a process-based ecosystem model to reconstruct the spatial and temporal dynamics in AGB while considering impacts of spatially and temporally transient meteorology, elevated CO2 and disturbance. This dataset reports AGB in unit of kg C/m2.

This forest carbon monitoring system was built on a process-based ecosystem model called Ecosystem Demography (ED) (Hurtt et al 1998; Moorcroft et al 2001; Ma et al 2022), which can simulate plant dynamics including growth, mortality, and reproduction; carbon dynamics within the simulated plants; and dynamics of carbon pools in forest ecosystems.

This forest carbon monitoring system ingests transient meteorology from Daymet (Thornton et al 2016) and MERRA2 (Gelaro et al. 2017) and CO2 concentrations from NOAA, remote sensing of forest change from the North American Forest Dynamics (NAFD), contemporary tree cover and canopy height from airborne lidar (e.g. Tang et al. 2021) and aerial imagery from National Agriculture Imagery Program (NAIP). More details about the system development can be found in Hurtt et al. 2022.

This data is currently utilized in the State of Maryland’s Greenhouse Gas Inventory and is scheduled to be updated at least triennially as part of updates to the State’s inventory. This data is also serves as the basis for calculations within the University of Maryland Peer-Reviewed Offset Protocol for Maryland Reforestation/Afforestation Projects.

For questions and support please contact lma6@umd.edu, rachlamb@umd.edu and gchurtt@umd.edu.

Reference

Hurtt, G.C., P.R. Moorcroft, S.W. Pacala, and S.A. Levin. 1998 Terrestrial models and global change: challenges for the future. Global Change Biology 4:581-590. https://doi.org/10.1046/j.1365-2486.1998.t01-1-00203.x

Hurtt et al 2022. Beyond Forest Carbon Monitoring: Integrating High-Resolution Remote Sensing and Ecosystem Modeling for Geospatial Assessment and Attribution of Changes in Forest Carbon Stocks Over Maryland, USA (in prep).

Ma, L., G. Hurtt, L. Ott, R. Sahajpal, J. Fisk, R. Lamb, H. Tang, S. Flanagan, L. Chini, A. Chatterjee, and J. Sullivan. 2022a. Global evaluation of the Ecosystem Demography model (ED v3.0). Geoscientific Model Development 15:1971–1994. https://doi.org/10.5194/gmd-15-1971-2022

Moorcroft, P. R., G.C. Hurtt. and S.W. Pacala, 2001 A method for scaling vegetation dynamics: the ecosystem demography model (ED) Ecol. Monogr. 71 557–86. https://doi.org/10.1890/0012-9615(2001)071[0557:AMFSVD]2.0.CO;2

Tang, H., L. Ma, A.J. Lister, J. O'Neil-Dunne, J. Lu, R. Lamb, R.O. Dubayah, and G.C. Hurtt. 2021. LiDAR Derived Biomass, Canopy Height, and Cover for New England Region, USA, 2015. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1854.

Dr. Pieter Tans, NOAA/GML (gml.noaa.gov/ccgg/trends/) and Dr. Ralph Keeling, Scripps Institution of Oceanography (scrippsco2.ucsd.edu/).

This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations, which have been re-surveyed at different times.

The Harvard Forest plot is dominated by eastern hemlock and northern hardwood species, and will make an excellent comparison with several other hardwood plots in North America and China at similar latitudes. This plot is part of a global array of large-scale plots established by ForestGEO, which recently expanded sampling efforts into temperate forests to explore ecosystem processes beyond population dynamics and biodiversity. The Harvard Forest was designed to include a continuous, expansive, and varied natural forest landscape that will yield opportunities for the study of forest dynamics and demography while capturing a large amount of existing science infrastructure (e.g., eddy flux towers, gauged sections of a small watershed, existing smaller permanent plots) that will enable the integrated study of ecosystem processes (e.g., biogeochemistry, hydrology, carbon dynamics) and forest dynamics .

The project scanned all trees in the permanent sample plot (PSP) spanning a range of soil fertility and productivity gradients (24 x 1 ha PSPs in total). The aim of the weighing trees with lasers project is to test if current allometric relationships are invariant across continents or whether they differ significantly and require continental-level models; quantify the impact of assumptions of tree shape and wood density on tropical forest allometry; test hypotheses relating to pan-tropical differences in observed AGB (Above Ground Biomass) from satellite and field data. It also aims to apply new knowledge to assessing retrieval accuracy of forthcoming ESA BIOMASS and NASA GEDI (Global Ecosystem Dynamics Investigation Lidar) missions and providing calibration datasets; In addition to testing the capability of low-cost instruments to augment TLS data, including: UAVs (unmanned aerial vehicle) for mapping cover and canopy height; low-cost lidar instruments to assess biomass rapidly, at lower accuracy.

A first-surface topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 60 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by NASA at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of 3 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 60 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by NASA at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of 3 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 60 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by NASA at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of 3 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

Estimates of reference height (Zm) and characteristic height (Zc) at three plant populations (x) for absorption of solar radiation in a corn canopy at Deerfield, MA.