digital-surface-model

NZ elevation data freely available to use under an open license.

Process case studies on DEM uncertainty analysis at the Mont-Blanc massif and Northern Patagonian Icefield: Hugonnet et al. (2022).

Code for the paper - Comparison of Digital Building Height Models Extracted from AW3D, TanDEM-X, ASTER, and SRTM Digital Surface Models over Yangon City

Estimate the stereoscopic capacity (B/H) of pairs of images from the Pleiades or SPOT6-7 satellites

swisstopo geospatial Python utilities

This repository is associated with our research paper: A Dynamic Blind Zone Simulation and Analysis Model for Roadside LiDAR Sensor Deployment Considering the Full Roadway Terrain and Vehicle Dynamics

Projected sunlight intensities for arbitrary building elevations using satellite-derived LIDAR🌞🏡

Official GeoRay implementation: gauge-aware feed-forward satellite 3D reconstruction in the absolute geodetic frame with RPC-native geometry.

Preprocessed and split version of the SSBH remote sensing dataset for building height estimation, including RGB composites, height maps, and building masks with train/valid/test manifests and ready-to-train scripts.

Sample a 2.5D Digital Surface Model as a pointcloud.

Tutorial for creating DSM from LiDAR data in R

Python-based slippy map tile server that downloads USGS 3DEP LIDAR point clouds, processes them into DSMs and generates tiles. Intended to reveal hidden terrain features (building edges, cliffs) under vegetation in OpenStreetMap iD Editor

An open-source cFS-based framework for real-time photogrammetric mapping from simulated UAV imagery, generating georeferenced dense point clouds, DSMs, and incremental orthomosaics.

Controlled 4/8/9-view evaluation of EOGS for urban DSM reconstruction using WorldView-3 imagery and LiDAR reference data.

experiments with terrain

A high resolution Digital Elevation Model of Great Britain

Hands-on introductory lab activities for learning lidar and deriving gridded products (DEM, DSM, DTM, and CHM) in R. Designed for undergraduate students with no prior lidar or programming experience, the browser-based lessons guide learners through accessing public lidar data, processing point clouds, and interpreting terrain and canopy datasets.

SIH26175 · Offline single-view satellite RGB to evidence-calibrated DSM and interactive 3D terrain workstation.