Forest height and structure from airborne lidar (G-LiHT)
What it measures. Detailed measurements of forest height and structure, including ground, tree, and shrub heights and densities, delivered as more than 80 layers at 13-meter detail.
How it's made. Collected by NASA's airborne G-LiHT system, which combines lidar, hyperspectral, and thermal sensors, and processed into raster map layers over surveyed flight areas.
How & where you'd use it. Helps map forest structure and composition for ecosystem and carbon studies across North American forests.
What's measured
Coverage & cadence
- Time span2011-06-30 → ongoing
- Measured byG-LiHT (Headwall, Riegl Airborne Lidar)
- Processing levelLevel 3
- Spatial extent-170, 10, -50, 73
- FormatsGeoTIFF
- StatusACTIVE
What you can do with it
- Track deforestation, fire scars and land-cover change
- Monitor crop and vegetation health (NDVI/EVI)
- Map how built-up vs. green an area is over time
Official description
Goddard’s LiDAR, Hyperspectral, and Thermal Imager ([G-LiHT](https://gliht.gsfc.nasa.gov/)) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Metrics data product (GLMETRICS) is to provide extensive lidar height and density metrics and return statistics in more than 80 science data set layers. Included in the product are mean, standard deviation, and percentile information for ground, tree, and shrub data. Some flights also contain Canopy Height Model (CHM) and Digital Terrain Model (DTM) returns. The total number of metrics layers varies by flight or campaign. GLMETRICS data are processed as a raster data product (GeoTIFF) at a 13 meter spatial resolution over locally defined areas. Known Issues * Science Data Layers do not currently reflect valid Fill Value, No Data Value, Valid Range, or Scaling Factor. These will be updated when more information is available.
Get the data
import earthaccess
earthaccess.login(strategy="netrc") # free Earthdata Login
results = earthaccess.search_data(
short_name="GLMETRICS",
version="001",
bounding_box=(-122.5, 37.2, -121.8, 37.9), # your area (W,S,E,N)
temporal=("2024-01-01", "2024-12-31"), # your dates
)
files = earthaccess.open(results) # stream straight from LPCLOUDBrowsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.