G-LiHT Digital Terrain Model V001

Accurately surveyed coordinate location used to maintain survey control during acquistion of various products for Kentucky's Aerial Photography and Elevation Data programhttps://ky.box.com/v/kymartian-gcp-phase3

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) mission utilizes 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 Digital Terrain Model Keyhole Markup Language (KML) data product (GLDTMK) is to provide LiDAR-derived bare earth elevation, aspect and slope on the EGM96 Geopotential Model. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and the collection will continue to grow as aerial campaigns are flown and processed. GLDTMK data are processed as a Google Earth overlay KML file at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the digital terrain with a color map applied in JPEG format.

This group includes the following items:  1. Hampton Roads Elevation Certificate Building Footprints: includes only building footprints where final elevation certificates are available, with elevations reported in the vertical datum provided on the elevation certificate (NGVD 29 or NAVD 88).   2. Hampton Roads Elevation Certificate Parcels: includes only parcels where final elevation certificates are available, with elevations reported in the vertical datum provided on the elevation certificate (NGVD 29 or NAVD 88).  Elevation certificates were collected from the following 12 localities: Chesapeake, Franklin, Gloucester County, Hampton, James City County, Newport News, Norfolk, Portsmouth, Southampton County, Suffolk, Virginia Beach, and York County. Localities included in the current inventory were able to provide digital elevation certificate copies. This inventory is not complete for the region, and elevation certificates will continue to be added to the database when available. The elevation certificate database was developed by HRPDC staff with support from the Center for Geospatial, Science, Education, and Analytics at Old Dominion University (ODU). We would like to acknowledge Manuel Solano (ODU) for his contributions to the Gloucester County and City of Norfolk elevation certificate data development. Building footprints are courtesy the VGIN statewide building footprints layer and locality GIS departments. Building attributes and parcels are courtesy of the Hampton Roads Regional Parcels layer and locality GIS departments. Current flood zones are courtesy of the FEMA National Flood Hazard Layer, with base flood elevations reported in NAVD 1988 where available. A complete list of attribute descriptions is available here.  Created 2/8/2019Updated 10/10/2020

Dates of Images: Post-Event: May 22, 2026 Pre-Event: May 7, 2026 Date of Next Image: Unknown Summary: These pre-fire and post-fire images pair were analyzed for normalized burn ratio (NBR). The input images were generated from the Harmonized Landsat Sentinel-2 (HLS) dataset at 30m resolution. NBR is defined mathematically as (NIR – SWIR)/(NIR + SWIR) where NIR is near-infrared and SWIR is short-wave infrared. dNBR is computed by the difference between the pre-fire NBR and the post-fire NBR. More information on dNBR can be found here: https://un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/in-detail/normalized-burn-ratio. dNBR data may be computed while the fire is in progress. This is intentionally done to prioritize rapid data availability for proactive disaster response but means data can change over the course of the fire. Ground slopes were calculated using the slope algorithm in QGIS. This algorithm determined ground slopes in degrees by analyzing USGS 1/3 arcsecond (i.e. roughly 10m) digital elevation rasters in the NAD27 / UTM zone 13N projection. To produce the dNBR and ground slope exceedance map, dNBR data was filtered for values greater than 0.4 and ground slope data was filtered for areas greater than or equal to 23 degrees. These thresholds were defined by NASA subject matter expertise to indicate critical levels for enhanced debris flow risk where both are in exceedance. The locations where both dNBR and slope thresholds were exceeded were initially identified in a binary raster and then vectorized to polygons using 8-neighbor feature selection (data represented here). Suggested Use: dNBR is commonly used as a proxy to identify fire-affected areas. Higher dNBR value are statistically correlated with greater burn severity, where negative dNBR values may represent a re-greening of or growth of vegetation in between pre and post-vegetation. The use of this dNBR product as a quantitative metric of burn severity at the time of posting this dataset should be strongly caveated. This is due to several dNBR limitations: The spectral band selections used for dNBR calculations, and the implication of changes observed following fire in those wavelengths, primarily pertain to how vegetation spectral signatures change in NIR and SWIR wavelengths following charring. Because of this, dNBR will not accurately describe burned surfaces that are not vegetation (e.g. human built infrastructure), and the interpretation of dNBR values may vary widely based on the type of vegetation burned. This dataset has not been validated by independent burn severity assessments. The degree to which dNBR is accurately determined depends on careful selection of pre and post event imagery. An effort was made to use the highest quality imagery (i.e. cloud free) with representative conditions for each scene; however, it is unknown at the time of this posting how selection of different pre/post image pairs could affect the derived dNBR values. Satellite/Sensor: NASA Disasters/MSFC, USGS, ESA Copernicus Resolution: 10 meters Credits: NASA Disasters Program, USGS, ESA Copernicus Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202605_FIRE_CA/sentinel2_dnbr_slopeExceedance/MapServer/WMSServer

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) 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 LiDAR Point Cloud data product (GLLIDARPC) is to provide high-density individual LiDAR return data, including 3D coordinates, classified ground returns, Above Ground Level (AGL) heights, and LiDAR apparent reflectance. GLLIDARPC data are processed as a LAS Version 1.1 binary format specified by the American Society for Photogrammetry and Remote Sensing (ASPRS). The point cloud includes a density of more than 10 points per square meter. A low resolution browse is also provided showing the LiDAR Point Cloud as an Inverse Data Weighted (IDW) interpolation in PNG format.

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) 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.