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Drone-Photogrammetry-Data-Processing

Overview

This repository contains the documentation and visual outputs for the Open-Ended Lab (OEL) on Drone Photogrammetry Data Processing. Completed as part of the CV-202L – Advanced Surveying Lab course, this project demonstrates the full workflow of processing drone-based photogrammetry data, from raw imagery to final geospatial products.

Repository Structure

The public repository is organized into the following directories:

  • /report: Contains the comprehensive project report (.docx).
  • /screenshots: Contains .png images capturing various stages of the processing workflow, including the DEM, dense cloud, mesh, and tie points.

Data Availability Note: The primary spatial dataset files — including Contours (.qgz, .gpkg, .pdf), DEM (.tiff, .tiff.aux.xml), and Orthomosaic (KMZ and TIFF formats) — are not included in this public repository due to file hosting limits. If you require access to these GIS datasets for review or research, please send me a direct message to obtain them.

Dataset & Software

  • Dataset Location: A hilly and mountainous area near Bajaur, Khyber Pakhtunkhwa.
  • Data Type: High-resolution nadir and oblique imagery captured by a UAV, supplemented with Ground Control Points (GCPs) to improve spatial accuracy.
  • Photogrammetry Engine: Agisoft Metashape Professional.
  • GIS Software: QGIS (Open Source GIS).

Methodology

The project workflow was divided into two main phases using industry-standard geomatics software:

1. Photogrammetric Workflow (Agisoft Metashape)

  • Photo Alignment: Images were aligned to create a sparse point cloud (tie points).
  • Dense Reconstruction: A dense point cloud was generated using multi-view stereo (MVS) techniques to reconstruct the 3D scene.
  • DEM Construction: A Digital Elevation Model was built by interpolating terrain elevation data from the dense point cloud, utilizing the WGS 84 coordinate reference system.
  • Orthomosaic Generation: A geometrically corrected, seamless aerial image mosaic was rendered.
  • Export: The DEM was exported in GeoTIFF format for further GIS analysis.

2. Contour Mapping (QGIS)

  • Data Import: The exported DEM GeoTIFF was loaded into QGIS.
  • Contour Extraction: Topographic contour lines were generated across the terrain surface.
  • Intervals: Minor contours were set at 10 m intervals, and major contours were set at 20 m intervals.
  • Styling & Layout: Major contours were labeled with elevation data and styled with heavier line weights, culminating in a print-ready map layout.

Results & Deliverables

The successful execution of this workflow yielded several key geospatial deliverables[cite: 2]:

  • A Dense Point Cloud representing the 3D geometry of the surveyed region[cite: 2].
  • A Digital Elevation Model capturing elevation changes ranging from 830 m to 1050 m[cite: 2].
  • A georeferenced, true-scale Orthomosaic[cite: 2].
  • A detailed Contour Map highlighting the topography of the linear valley and surrounding ridges[cite: 2].

Project Team

  • Umar Gohar Ali
  • Saad Syed
  • Saifur Rahman
  • Shehreyar Ahmad
  • Muhammad Kamal

Submitted to Engr. Tausif Junaid Khan on May 11, 2026, for the GIK Institute of Engineering Sciences and Technology.

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This repository contains the documentation and visual outputs of Drone Photogrammetry Data Processing

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