In the last six years, we have developed DeepObjectв„ў, which uses deep learning to detect objects from imagery and 3-D point clouds. The Intelligent Photogrammetry can identify errors in DSM generated from UAV images and correct them therefore, providing a very competitive DEM generation capability for UAV images. DEM production from UAV images using our Intelligent Photogrammetry can achieve state-of-the-art accuracy. This issue was resolved with 3DGroundPointModel based on machine learning, achieving RMSE 2.40 meter and meeting the desired DEM accuracy requirement of 2 to 3 meters using stereo satellite images. The most time consuming component of DEM production is dense forestry areas, and in this case study, the forestry height is up to 19 meters causing the ground to be nearly invisible.

This case study indicates that Intelligent Photogrammetry can reduce the DEM production cost by more than 50%. For this case study, the city of San Diego was used to generate DEM from Intelligent Photogrammetry to achieve Root Mean Square Error (RMSE) of 0.95 meters from stereo satellite images. Intelligent Photogrammetry, based on machine learning, can handle different cases by adding training samples. Traditional handcrafted bare earth algorithms for DSM to DEM transformation cannot deal with so many different cases for general purpose application and big data. The main cost of DEM production using DSM generated from satellite images in difficult terrain is the transformation from DSM to DEM. The last model classifies 3-D points into thirteen categories, which are then used to generate DEM in difficult terrain such as dense forestry areas, where the ground is mostly unseen.

3DGroundPointModel The first four models detect above ground 3-D objects and then remove them from DSM to generate DEM. The following sets of 3-D models have been trained based on the different DSM types: 1. There are various types of DSM, each containing different post spacing and accuracy.

By applying machine learning to Digital Photogrammetry, our Intelligent Photogrammetry can significantly reduce the cost of DEM production from Digital Surface Models (DSM), which are generated from satellite images, aerial images, Unmanned Aerial Vehicle (UAV) images, sparse LiDAR 3-D point clouds, and dense LiDAR 3-D point clouds. Digital Elevation Model (DEM) production is one of the most time consuming tasks in digital photogrammetry.

Digital terrain model no background