Types of data supported in LAS datasets

There are two major data sources to LAS datasets: lidar data stored in LAS files and surface constraints stored in shapefiles or feature classes.

Lidar

Lidar (light detection and ranging) is an optical remote-sensing technique that uses laser light to densely sample the surface of the earth producing highly accurate x,y,z measurements.

General characteristics of lidar include:

• Lidar point clouds stored in LAS format
• Not surface specific
• Sampled to required nominal point spacing, varying from 1 to 15 feet (approximately 0.3 to 5 meters) depending on application
• Often, but not always, filtered to bare earth points
• Every point contains attributes that are stored with the x,y,z data
• Large quantities of point data

A LAS dataset is designed and optimized to support LAS files from an airborne lidar collection. The LAS dataset can support lidar data in LAS format from a terrestrial collection, however, they should only be displayed as points. With an airborne collection you can visualize the LAS dataset in ArcMap, ArcScene, and ArcCatalog as points or as a triangulated surface.

Surface constraints

Surface constraints are surface features stored in either geodatabase feature classes or shapefiles, which are usually derived from some sort of remote sensing technique like photogrammetry.

Photogrammetrically derived breaklines:

• Surface-specific breaks in slope along linear features
• Natural landforms (for example, ridges and valleys)
• Terrain features resulting from earthworks (for example, bulldozed)
• Lake shorelines, creeks, river shorelines
• Edge of road pavement
• Delineation of void areas (usually obscured by vegetation)
• Minimal attribution
• Typically moderate quantities

GPS Points:

• Irregularly spaced
• May or may not represent surface-specific peaks and pits
• Used for control, QA, and benchmarking other data
• Property boundary control points
• Potentially significant attribution per point
• Typically small quantities

Surface constraint type	Feature class	Z-value source in the feature class	Thematic data type examples
Points (x,y,z locations)	Point feature class	Shape geometry; x,y,z per vertex or Attribute column holding one z-value per shape	Spot heights Survey points GPS points
	Polygon feature class	Shape geometry; x,y,z per vertex or Attribute column holding one z-value per shape	Shoreline delineation
Breaklines (hard or soft)	Line feature class	Shape geometry; x,y,z per vertex Attribute column holding one z-value per shape No height source; z-values interpolated for each feature from the surface before being added	Contours Edge of pavement Water lines (streams, rivers, canals, and shorelines)
	Polygon feature class	Shape geometry; x,y,z per vertex Attribute column holding one z-value per shape (such as a shoreline) No height source; z-values interpolated for each feature from the surface before being added	Lake shoreline
Clipping polygons (hard or soft)	Polygon feature class	Shape geometry; x,y,z per vertex Attribute column holding one z-value per shape (such as a shoreline) No height source; z-values interpolated for each feature from the surface before being added	Study area boundary
Erase polygons (hard or soft)	Polygon feature class	Shape geometry; x,y,z per vertex Attribute column holding one z-value per shape No height source; z-values interpolated for each feature from the surface before being added	Lake shoreline Obscured areas (dense forest canopy)
Replace polygons (hard or soft)	Polygon feature class	Shape geometry; x,y,z per vertex Attribute column holding one z-value for all vertices in each shape	Water bodies