What is Photogrammetry and Remote Sensing? Core Concepts for Surveying Exams

Preparing for technical recruitment examinations like the Survey of Pakistan (SoP), provincial public service commissions, or technical board certifications can feel overwhelming. Many candidates struggle when transitioning from basic field surveying (like Total Station or Levelling) to advanced spatial technology questions covering Photogrammetry and Remote Sensing.

Questions on electromagnetic spectrum bands, aerial overlap calculations, pixel resolutions, and sensor classifications frequently appear in objective tests and interview panels. Missing these core theoretical concepts is one of the most common reasons candidates lose easy marks.

This comprehensive guide breaks down Photogrammetry and Remote Sensing into clear, easy-to-understand concepts complete with core formulas, comparison tables, practical examples, and essential exam troubleshooting tips.

1. What is Photogrammetry?

Photogrammetry is the science and technology of obtaining reliable information about physical objects and the environment through the process of recording, measuring, and interpreting photographic images.

In simple terms: It is the art of turning 2D flat photographs into accurate 3D maps and spatial measurements.

+------------------------+      Camera Capture      +------------------------+
| 3D Real-World Terrain  | -----------------------> | 2D Aerial Photograph   |
+------------------------+                          +------------------------+
                                                                |
                                                            Mathematical
                                                            Reconstruction
                                                                |
                                                                v
                                                    +------------------------+
                                                    | 3D Spatial Vector Map  |
                                                    +------------------------+

Core Types of Photogrammetry

1. Aerial Photogrammetry: The camera is mounted on an aircraft, satellite, or Unmanned Aerial Vehicle (UAV/Drone) pointing vertically downward toward the ground.
2. Terrestrial (Close-Range) Photogrammetry: The camera is stationary on the ground or hand-held to map building facades, monuments, or structural engineering projects.

Essential Photogrammetry Concepts for Exams

A. Scale of a Vertical Aerial Photograph

The scale ($S$) of a vertical aerial photograph depends on the focal length of the camera lens ($f$) and the flying height above the ground ($H – h$).

$$\text{Scale } (S) = \frac{f}{H – h}$$

• $f$ = Focal length of the camera lens (in meters or mm)
• $H$ = Flying height of the aircraft above Mean Sea Level (MSL)
• $h$ = Elevation of the ground terrain above MSL

B. End Lap and Side Lap (Stereoscopic Coverage)

To reconstruct 3D imagery (stereoscopic viewing), consecutive images must overlap:

• End Lap (Forward Overlap): Overlap along the flight direction, typically kept at 60% to 65%.
• Side Lap (Lateral Overlap): Overlap between adjacent parallel flight paths, typically kept at 20% to 30%.

C. Relief Displacement ($d$)

Due to perspective projection, points at higher elevations appear shifted outward from the center of the photo (Isocenter/Nadir point).

$$d = \frac{r \cdot h}{H}$$

• $r$ = Radial distance from the principal point on the photograph
• $h$ = Height of the object above the datum
• $H$ = Flying height above the base of the object

2. What is Remote Sensing?

Remote Sensing is the science of gathering information about an object, area, or phenomenon from a distance without coming into direct physical contact with it.

While photogrammetry focuses primarily on geometric measurements and mapping boundaries, remote sensing focuses on identifying land cover features (vegetation, water bodies, urban structures, soil types) based on how they reflect or emit energy.

[ Energy Source (Sun) ] ───(Radiation)───> [ Target / Earth Feature ]
                                                      │
                                             (Reflected/Emitted)
                                                      │
                                                      v
                                            [ Sensor / Satellite ]

Passive vs. Active Remote Sensing

Feature	Passive Remote Sensing	Active Remote Sensing
Energy Source	Uses natural solar radiation (Sunlight) or naturally emitted heat.	Generates its own artificial energy signal toward the target.
Operational Time	Daylight only (for optical sensors).	Day and Night (24/7 capability).
Weather Dependency	Blocked by thick cloud cover and fog.	Can penetrate clouds, rain, and smoke (e.g., Radar/Microwave).
Primary Examples	Landsat, Sentinel-2, MODIS, Aerial Cameras.	LiDAR, RADAR (Sentinel-1), Sonar.

3. The Electromagnetic Spectrum (EMS) & Spectral Signatures

Sensors detect reflected or emitted radiation across different regions of the Electromagnetic Spectrum (EMS). Understanding spectral bands is critical for written test MCQs:

• Visible Region (0.4 µm – 0.7 µm): Blue, Green, and Red wavelengths visible to human eyes.
• Near-Infrared / NIR (0.7 µm – 1.1 µm): Crucial for health assessment of vegetation (healthy plants reflect high amounts of NIR radiation).
• Short-Wave Infrared / SWIR (1.1 µm – 3.0 µm): Used for monitoring soil moisture content and geological mapping.
• Thermal Infrared (8.0 µm – 14.0 µm): Used to detect surface temperature differences and urban heat islands.
• Microwave Region (1 mm – 1 m): Used in Active Radar systems (LiDAR/RADAR) to penetrate canopy cover and map terrain topography.

4. The 4 Types of Sensor Resolution

Exams often ask candidates to differentiate between sensor resolutions. Memorize these four fundamental definitions:

1. Spatial Resolution: The minimum ground area represented by a single pixel in an image (e.g., 30 meters on Landsat vs. 10 cm on high-resolution drones).
2. Spectral Resolution: The number and specific width of electromagnetic bands a sensor can record (e.g., Multispectral vs. Hyperspectral).
3. Radiometric Resolution: The sensitivity of a sensor to detect slight differences in brightness, expressed in bits ($2^n$, such as 8-bit = 256 gray levels vs. 16-bit = 65,536 levels).
4. Temporal Resolution: The frequency or re-visit time required for a satellite to capture an image of the exact same location on Earth.

5. Direct Comparison: Photogrammetry vs. Remote Sensing

Dimension	Photogrammetry	Remote Sensing
Primary Focus	High-precision 3D metric measurements, geometry, and contours.	Qualitative classification, land cover change, and environmental analysis.
Primary Output	Topographic maps, Orthomosaics, Digital Elevation Models (DEM/DSM).	Land Cover Maps, Vegetation Indices (NDVI), Soil Moisture Maps.
Key Instrument	Metric Aerial Cameras, UAVs, Stereoscopes, Total Stations.	Satellite Sensors (Landsat, Sentinel), LiDAR scanners, Multispectral Cameras.
Mathematical Basis	Central Projection, Photogrammetric Triangulation, Relief Displacement equations.	Spectral Reflectance Curves, Image Processing Algorithms, Band Ratios.

6. Real-World Applications in Pakistan

Connecting theoretical concepts to practical projects demonstrates advanced knowledge during interview rounds:

• Infrastructure Development: Route planning for motorway expansions, railways, and CPEC transport corridors using UAV orthomosaics.
• Cadastral & Land Registration: Modernizing urban property records using high-resolution drone mapping instead of traditional manual chaining.
• Water & Agricultural Management: Utilizing Sentinel-2 multispectral imagery to calculate Normalized Difference Vegetation Index (NDVI) for crop health assessment and flood inundation mapping along the Indus Basin.

Common Candidate Mistakes & Exam Preparation Tips

⚠️ Confusing Scale Formulas: Candidates often forget that flying height ($H$) is measured from Mean Sea Level, while ground elevation ($h$) must be subtracted from $H$. Always double-check units (convert feet to meters or vice versa) before solving scale calculations.

⚠️ Mixing Up End Lap vs. Side Lap: Always remember that End Lap (60-65%) is along the line of flight to ensure stereoscopic pairs, whereas Side Lap (20-30%) is perpendicular to the flight path to prevent coverage gaps between strips.

⚠️ Neglecting Spectral Signatures: Do not memorize band numbers blindly without knowing their spectral regions. Satellite band designations vary across sensors (e.g., Band 4 is Red on Landsat 8, but NIR on Landsat 7). Focus on the wavelength ranges instead.

Summary & Key Takeaway

Mastering Photogrammetry and Remote Sensing requires balancing mathematical spatial geometry with physical sensor concepts. Remember:

• Photogrammetry gives you precise 3D geometric dimensions and orthophotos.
• Remote Sensing provides spectral insights into environmental features and land use.

Focusing on scale formulas, overlap percentages, sensor resolutions, and real-world mapping applications will ensure you perform confidently in both written exams and professional interviews.