Advance surveying lab (CE-605) - Unit 2 Short Notes

I. Advanced Total Station & Its Applications

A. Fundamentals & Components

• Electronic Distance Measurement (EDM) Principle:

  • Phase Method: Measures phase shift of a modulated carrier wave. High precision (mm). Used in modern total stations.

  • Pulse Method: Measures time-of-flight of a short pulse. Lower precision (cm to m). Used in long-range/reflectorless instruments.

• Core Components:

  • Telescope: For sighting target (prism/reflectorless).

  • EDM Unit: Emits/ receives infrared or laser signal.

  • Electronic Angle Measurement (EAM): Glass/ metal circles with electro-optical encoding (e.g., absolute, incremental).

  • Microprocessor & Memory: Computes coordinates, stores data (jobs/files).

  • On-board Software: For calculations (area, resection, road design).

• Types:

  • Conventional: Manual sighting, operator controls.

  • Robotic/Motorized: Motorized drives, remote control, can track moving prism.

B. Setup, Calibration & Error Sources

• Field Setup: Tripod → Optical/Laser plummet centering → Plate level (coarse) → Tubular bubble level (fine) → Focus eyepiece & objective.

• Key Calibrations:

  • Vertical Axis Index (II Error): Vertical circle index error. Check with Face Left & Face Right vertical angle to a point.

  • Horizontal Axis Index (ADM/ Collimation Error): Telescope not perpendicular to vertical axis. Check with Face Left & Face Right horizontal angle to a point.

  • Line of Sight (LOS) / Trunnion Axis Error: Telescope line of sight not perpendicular to horizontal axis. Check with trunnion bubble.

  • EDM Constant & Scale Factor: Corrects systematic distance error. Calibrated using known baseline.

  • Compensator: Dual-axis tilt sensor calibration.

• Error Sources:

  • Instrumental: Eccentricity (circle centering), collimation, horizontal axis not level.

  • Natural: Atmospheric refraction, Earth curvature (negligible for typical TS distances).

  • Personal: Centering over point, reading/ recording errors, target centering.

C. Measurement Modes & Operations

• Angle Measurement:

  • Horizontal/Vertical angles measured in Face I (Left) & Face II (Right).

  • Mean Angle: θ_avg = (θ_FL + (θ_FR ± 180°)) / 2 (sign depends on instrument convention).

• Distance Measurement Modes:

  • Slope Distance (SD): Direct EDM reading along line of sight.

  • Horizontal Distance (HD): HD = SD * cos(Vertical Angle)

  • Vertical Distance (VD): VD = SD * sin(Vertical Angle)

  • Reflectorless (RL): Uses high-power laser. Range shorter, accuracy lower, affected by surface/light.

• Traversing & Resection:

  • Resection (Free Station): Setup on unknown point by measuring to known points. Computes instrument coordinates & orientation.

  • Coordinate Measurement: Directly outputs Northing (N), Easting (E), Elevation (Z).

• Data Recording:

  • Electronic Field Book (Data Collector): Job/File structure, point codes/attributes (e.g., TREE, BM), note-taking.

D. Specialized Surveying Techniques

• Mining Survey:

  • Volume Calculation: Grid method (V = Σ(h_i * A_grid)), cross-section method, contour method.

  • Underground: Gyro-theodolite for azimuth orientation, transfer of surface coordinates via traverses.

• Deformation Monitoring:

  • Precise, repeat angle & distance measurements to targets on structure (dam, building).

  • Stability Analysis: Compare successive epochs. Compute displacements & their statistical significance.

• Setting Out:

  • Input design coordinates (N,E,Z) into TS. Instrument calculates azimuth, distance, and vertical angle to set out point.

• Topographic Survey:

  • Efficient detail point collection using codes/attributes for later GIS import.

[!TIP] Exam Focus: Be prepared to derive formulas for HD/VD from SD and VA. Understand the difference between reflectorless and prism-based errors. Know resection limitations (angle geometry).

II. Adjustment of Surveying Observations

A. Fundamental Concepts

• Need: Observations contain errors; network is usually over-determined (more observations than unknowns). Adjustment finds Most Probable Values (MPVs).

• Key Terms:

  • Observations (L): Measured quantities (angles, distances).

  • Parameters (X): Unknown coordinates to be estimated.

  • Residuals (V): V = L_corrected - L_observed. Sum of weighted residuals = 0.

  • Weights (P): Inverse of variance (P = 1/σ²). Express observation precision.

• Laws of Error: Errors follow normal distribution. Arithmetic mean of repeated observations is MPV.

B. Methods of Adjustment

• Method of Correlates / Condition Equations:

  • Form equations where sum of observed quantities equals sum of computed quantities (e.g., sum of angles in triangle = 180° + ω).

  • ΣL + ΣV = f(X) → ΣV = -w (misclosure). Solve for V using condition equations.

• Method of Least Squares:

  • Fundamental Principle: Minimize Σ(P * V²).

  • Indirect (Observation) Equations: V = AX - L

    • A: Design matrix (partial derivatives of obs w.r.t. params).

    • X: Vector of unknown parameters.

    • L: Vector of observations.

  • Normal Equations: AᵀPA X = AᵀPL

  • Solution: X̂ = (AᵀPA)⁻¹ AᵀPL (MPVs of parameters).

  • Residuals: V̂ = AX̂ - L

• Application:

  • Level Net: Adjust height differences.

  • Traverse: Adjust coordinates & azimuth. Use observation equations for angles & distances.

  • Triangulation/Trilateration: Adjust angles or sides.

C. Statistical Analysis of Results

• Standard Errors:

  • Unit Weight Standard Error: σ₀ = √(VᵀPV / (n - u)) where n=obs, u=params.

  • Observation Standard Error: σ_i = σ₀ / √P_i

  • Adjusted Parameter Error: σ_X = σ₀ * √(diagonal elements of (AᵀPA)⁻¹)

• Post-Adjustment Checks:

  • Residual Analysis: Check size, signs (no systematic pattern), distribution.

  • Global Test (Chi-square): χ²_calc = VᵀPV. Compare with χ²_table(n-u, α). Reject if χ²_calc > χ²_table (model/weights wrong).

• Interpretation:

  • Error Ellipse: For a point, defines region where true position lies with given probability. Major/minor axes from variance-covariance matrix.

  • Reliability: Ability to detect blunders. Measures like internal reliability (minimal detectable bias).

[!TIP] Common Pitfall: Forgetting to use weights in normal equations when observations have different precisions. Remember σ₀ is computed after adjustment to check model fit.

III. Global Navigation Satellite Systems (GNSS) Surveying

A. GNSS Fundamentals

• Constellations: GPS (USA), GLONASS (Russia), Galileo (EU), BeiDou (China).

• Segments:

  • Space: Satellites transmitting signals.

  • Control: Ground stations monitoring & uploading data.

  • User: Receivers.

• Signals:

  • C/A Code: Coarse/Acquisition, civilian, ~3m accuracy.

  • P(Y)-Code: Precise, military, encrypted.

  • Carrier Phase: Very precise (mm-cm), requires ambiguity resolution.

• Coordinates & Time:

  • WGS-84: Global Cartesian/Geodetic system.

  • ITRF: International Terrestrial Reference Frame (more precise, ties to Earth's crust).

  • GPS Time: Continuous, no leap seconds. UTC: GPS Time - leap seconds.

B. Measurement Techniques & Modes

• RTK vs. PPK: RTK = Real-time via radio/network link. PPK = Post-Processed Kinematic (store data, process later).

• Network RTK: Uses a network of reference stations (VRS, MAC, FKP) to generate virtual base corrections.

C. Field Procedures & Data Processing

1. Setup: Measure antenna height precisely (to ARP - Antenna Reference Point). Record metadata (point ID, receiver type).

2. Session Planning: Check PDOP (Position Dilution of Precision) < 4-6 ideal. Plan observation duration (static: 1-4+ hrs; kinematic: continuous).

3. Processing Steps:

   • Download RINEX data.

   • Convert to software format.

   • Select processing mode (static/kinematic).

   • Process baselines (rover to base).

   • Network adjustment (if multiple baselines).

4. RTK Workflow: Initialize (solve integer ambiguities) → Float (cm, low reliability) → Fixed (mm-cm, high reliability). Limited by baseline length (<20-30 km typical).

D. Sources of Error & Mitigation

[!TIP] Key Concept: RTK initialization is critical. "Fix" requires sufficient satellites & good geometry. "Float" solution is less reliable. Always check PDOP and number of satellites in the field.

IV. Geographic Information Systems (GIS) & Data Integration

A. GIS Concepts for Surveyors

• Components: Hardware (PC, GPS), Software (QGIS, ArcGIS), Data (spatial + attribute), People, Procedures.

• Data Models:

  • Vector: Points (0D), Lines/Polygons (1D/2D). Topology: Rules (e.g., no gaps, nodes must match). Essential for network analysis.

  • Raster: Grid cells (pixels). Used for imagery, DEMs.

• Coordinate Systems: Geographic (Lat/Lon, WGS-84) vs. Projected (UTM, State Plane). On-the-fly reprojection allows mixing.

B. Survey Data in GIS

• Import/Export Formats:

  • Text/CSV: Simple (E,N,Z,Code).

  • DXF/DWG: CAD drawings (lines, points).

  • Shapefile (.shp): Common GIS vector format (point, line, polygon + .dbf attribute table).

  • Geodatabase (.gdb): Advanced, relational (feature classes, domains).

• Attribute Data: Non-spatial info linked to feature (e.g., Point_ID, Feature_Type, Owner, Date_Surveyed). Key for querying & analysis.

C. Field-to-GIS Workflow

1. Planning: Define feature classes (e.g., Boundary_Pin, Tree, Building_Footprint) and attributes in the field. Use consistent coding scheme on data collector.

2. Collection: Survey points with codes. Record attributes in notes or directly on controller.

3. Transfer & Integration:

   • Export from TS/GNSS controller (often as .csv or .dxf).

   • Import into GIS.

   • Join spatial data (coordinates) with attribute table (using point ID).

   • Georeference if using scanned maps/imagery.

4. Basic GIS Ops: Query (select all trees > 10m height), Buffer (create 10m setback around building), Overlay (intersect soil map with parcel), Map Layout (create final survey plan).

[!TIP] Critical: Attribute integrity is as important as spatial accuracy. Garbage-in, garbage-out. Define clear coding rules before fieldwork.

V. Remote Sensing & Photogrammetry for Surveying

A. Principles & Platforms

• EM Spectrum: Surveying uses visible, near-IR (vegetation), microwave (Radar).

• Platforms:

  • Satellite: Landsat (30m), Sentinel (10m), WorldView (0.3m).

  • Aerial: Manned aircraft, film/digital.

  • UAV/Drone: Revolutionary for surveying. Low altitude, high resolution, flexible.

• Sensors:

  • Passive: Detect reflected sunlight (Multispectral: few bands; Hyperspectral: many narrow bands).

  • Active: Emit own energy (LiDAR: laser; Radar: microwave).

B. Photogrammetry & UAV Surveying

• Aerial Photogrammetry: Requires high endlap (60-80%) & sidelap (30-60%) for stereo pairing & coverage.

• UAV Surveying Workflow:

  1. Mission Planning: Use software (Pix4D, DroneDeploy). Set altitude (controls GSD - Ground Sample Distance), flight lines, overlap.

  2. Ground Control Points (GCPs): Crucial for accuracy. Survey-grade GNSS measured points (4+ corners, interior) with known coordinates. Placed in clear, stable locations.

  3. Data Acquisition: Automated flight. Ensure good lighting, minimal wind.

  4. Data Processing (SfM - Structure from Motion):

     • Align photos → Sparse point cloud.

     • Densify → Dense point cloud.

     • Generate DSM (Digital Surface Model - includes objects) & DEM/DTM (Digital Terrain Model - bare earth).

     • Create orthomosaic (georeferenced, distortion-corrected image map).

     • Output: Point cloud (.las), orthophoto (.tif), contours, 3D mesh.

C. LiDAR Surveying

• Principle: Measure time-of-flight of laser pulse: Distance = (Speed of Light * Time) / 2.

• Returns: Discrete (first/last/only returns). Full-waveform (entire return signal, more info).

• Platforms:

  • ALS: Airborne, large area.

  • TLS: Terrestrial, static scan of objects/bldgs.

  • MLS: Mobile (vehicle-mounted), corridors.

• Output & Classification: Dense 3D point cloud. Points classified as Ground, Vegetation, Building, Power Line, etc.

• Applications: High-accuracy DEM/DTM, forestry (canopy height), urban 3D modeling, as-built surveys, utility corridor mapping.

[!TIP] UAV vs. LiDAR: UAV photogrammetry (SfM) is cheaper, provides true color, but struggles under vegetation. LiDAR penetrates vegetation to get ground, is more expensive, provides direct 3D points (no matching). Often used together.

VI. Integrated Surveying Projects & Modern Applications

A. Combining Technologies

• Hybrid Networks: Use GNSS to establish high-precision, long-range control network. Use Total Station for dense, high-accuracy detail surveys in constrained areas (under tree cover, near buildings).

• GIS as Hub: Central repository for all data:

  • GNSS control points.

  • TS detail (points, lines, codes).

  • Remote sensing (orthophoto, LiDAR DEM).

  • Legacy cadastral maps (scanned, georeferenced).

  • Enables comprehensive analysis & map production.

B. Application-Specific Surveying

• Cadastral Surveying:

  • GNSS (RTK) for boundary corners (open areas).

  • TS for precise boundary definition under trees/obstructions.

  • GIS Integration: Parcel fabric, spatial join with ownership records.

• Engineering/Construction:

  • Setting Out: TS/GNSS for stakeout.

  • Machine Control: GNSS/TS on earthmoving equipment for automated grading.

  • As-Built Surveys: TLS/UAV for 3D capture of completed work vs. design model.

• Hydrographic Surveying:

  • Echo Sounder (single/multi-beam) for depth.

  • GNSS for position & tide correction (via geoid model).

  • Integration produces bathymetric chart.

C. Quality Assurance/Quality Control (QA/QC)

• Field Checks:

  • Redundancy: Close traverse, measure angles/distances both ways.

  • Independent Measurements: Check critical points with different method/instrument.

  • Residuals: In traverse, misclosure should be within tolerance (√(n) * precision).

• Data Validation:

  • Software checks (coordinate geometry, attribute domains).

  • Visual inspection of point cloud/orthophoto for blunders.

• Documentation:

  • Field Notes: Sketches, point IDs, codes, conditions.

  • Metadata: Who, what, when, where, how, accuracy.

  • Processing Logs: Software versions, settings, parameters.

  • Final Report: Methodology, results, accuracy statistics, deliverables.

[!TIP] Modern Practice: QA/QC is continuous, not just at end. Field checks during survey prevent costly rework. Metadata is legally required for geospatial data. Always know the specified accuracy (e.g., "1 cm + 1 ppm") and verify it's achieved.