Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

ECHIDNA LIDAR Campaigns: Forest Canopy Imagery and Field Data, U.S.A., 2007-2009

Metadata Updated: December 6, 2023

This data set contains forest canopy scan data from the Echidna? Validation Instrument (EVI) and field measurements data from three campaigns conducted in the United States: 2007 New England Campaign; 2008 Sierra National Forest Campaign; and 2009 New England Campaign. The New England field sites were located in Harvard Forest (Massachusetts), Howland Research Forest (Maine), and the Bartlett Experimental Forest (New Hampshire).The objective of the research was to evaluate the ability of the EVI ground-based, scanning near-infrared lidar to retrieve stem diameter, stem count density, stand height, leaf area index, foliage profile, foliage area volume density, and other useful forest structural parameters rapidly and accurately.The EVI scan data are Andrieu Transpose (AT) Projection images in ENVI .img and .hdr file pairs. There are 28 images from the 2007 New England Campaign, 30 images from the 2008 Sierra National Forest Campaign, and 54 images from the 2009 New England Campaign. There are range-weighted mean preview image files (.jpg format) for each AT Projection image.Manual measurements of tree structural properties were made during each campaign at EVI scan locations. The field measurements are provided in one file for each campaign (.csv format). Parameters include species identification, DBH, tree height, crown base, etc. organized by field plot. There is also a data file (.csv format) which compares EVI derived measurements to the field measured data (DBH, stem density, basal area, biomass, and LAI) from the 2007 New England Campaign.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date May 30, 2023
Metadata Updated Date December 6, 2023

Metadata Source

Harvested from NASA Data.json

Graphic Preview

Browse Image

Additional Metadata

Resource Type Dataset
Metadata Created Date May 30, 2023
Metadata Updated Date December 6, 2023
Publisher ORNL_DAAC
Maintainer
Identifier C2556025141-ORNL_CLOUD
Data First Published 2022-11-29
Language en-US
Data Last Modified 2023-06-12
Category NACP, geospatial
Public Access Level public
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://data.nasa.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Citation Strahler, A.H., C. Schaaf, C. Woodcock, D. Jupp, D. Culvenor, G. Newnham, R.O. Dubayah, T. Yao, F. Zhao, and X. Yang. 2010. ECHIDNA LIDAR Campaigns: Forest Canopy Imagery and Field Data, U.S.A., 2007-2009. ORNL DAAC, Oak Ridge, Tennessee, USA. http://dx.doi.org/10.3334/ORNLDAAC/1045
Graphic Preview Description Browse Image
Graphic Preview File https://daac.ornl.gov/graphics/browse/project/square/nacp_logo_square.png
Harvest Object Id 945f3bb0-fbf1-416a-b920-f9853cf8c4f1
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL https://doi.org/10.3334/ORNLDAAC/1045
Metadata Type geospatial
Old Spatial -119.25 36.96 -68.72 45.21
Program Code 026:001
Source Datajson Identifier True
Source Hash 4eb03f8dee84845b9e1136b2d6c47e49ce96bec076ed71fdb15c9522bc610042
Source Schema Version 1.1
Spatial
Temporal 2007-08-01T00:00:00Z/2009-08-05T23:59:59Z

Didn't find what you're looking for? Suggest a dataset here.