Introduction to Photogrammetry GEOM 3071

Upon successful completion of this course, the student will be able to:

Introduction to Remote Sensing

• List different type of sensor data.
• Describe fundamental concepts of remote sensing and data models.
• Select appropriate raster data for survey projects.

Remote Sensing Platforms

• Recognize appropriate platforms and sensors to capture data relevant to specific projects.
• Identify the data requirements for the specific project.
• Demonstrate airborne mission-planning.

Passive Remote Sensing: Image Processing and Manipulation

• Discuss and review the right sensor/data to meet the survey requirements.
• Explain the role of resolution in data quality captured by cameras and scanners.
• Memorize basic image corrections.
• State the mathematical models relating sensor space to object space.
• Solve calculations to determine print scale and size.
• Select appropriate DEM for orthoimage generation.

Passive Remote Sensing: Image Analysis and Interpretation

• Implement and compare visual and digital imager interpretation.
• Demonstrate common image analyses and interpretation techniques.

Passive Remote Sensing: Applications

• Compare the various vegetation indices.

Information From Optical and Range Data: Photogrammetric Computer Vision

• Apply the concepts of optical data for spatial data collection (3D position) and the 2/3D object reconstruction from optical and range measurements.
• Interpret the mathematical photogrammetric theory and procedures of photogrammetric triangulation (indirect, integrated sensor, direct, orientations).
• Recognize the camera calibration parameters required for a photogrammetric project.
• Calculate approximate coordinate precision from aerial imagery.

Data Visualization and Mapping

• Define graphics (e.g., maps and other forms of geographic visualizations) to explain, interpret, and assess information.

Data Acquisition and Manipulation

• List different GIS data acquisition approaches and data sources.
• Recognize appropriate tools and techniques to acquire and maintain high-quality data.

Geospatial Data Analysis & Analytical Modeling

• Examine appropriate spatial analysis methods to support decision-making.

Digital Elevation Modeling (DEM)

• List mathematical approaches and techniques for terrain surface interpolations and reconstruction.
• State terrain/surface parameters, visualization, generalization, accuracy, and quality control.
• Demonstrate data-acquisition methods for DEM applications.
• Evaluate DTM applications and terrain analysis.

Effective as of Fall 2024