Three Important Lidar Data Products: CHM, DEM, DSM Digital Surface Model (DSM), Digital Elevation Models (DEM) and the Canopy Height Model (CHM) are the most common raster format lidar derived data products. This CHM is created by subtracting the DTM from the DSM. This includes the actual heights of trees, builds and any other objects on the earth’s surface. Canopy Height Model (CHM): the height or residual distance between the ground and the top of the of objects above the ground.Digital Surface Model (or DSM): top of the surface (imagine draping a sheet over the canopy of a forest.Digital Terrain Model (or DTM): ground elevation.In this lesson, you will import and work with 3 of the most common lidar derived data products in Python: However, often people work with lidar data in raster format given it’s smaller in size and thus easier to work with. If the data are discrete return, Lidar point clouds are most commonly derived data product from a lidar system. Describe the key differences between the CHM, DEM, DSM.Īs you learned in the previous lesson, LiDAR or Light Detection and Ranging is an active remote sensing system that can be used to measure vegetation height across wide areas.
Chapter 4: Intro to Raster Data in Python.SECTION 3 INTRODUCTION TO RASTER DATA IN PYTHON.Chapter 3: Processing Spatial Vector Data in Python.SECTION 2 INTRO TO SPATIAL VECTOR DATA IN PYTHON.Chapter 1.5: Flood Returns Period Analysis in Python.
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