Lecture 6 (GIS Data Collection) Flashcards
Data Collection
Adding geographic data into a GIS database.
- One of most expensive and time consuming GIS activities
-Many diverse sources
- Two broad types of collection
-> Data capture
– Two broad capture techniques (direct entry)
• Primary (direct measurement)
• Secondary (indirect derivation)
-> Data transfer
– importing the existing data from other sources into a GIS database
DATA MAINTENANCE IS MORE IMPORTANT AND COMPLEX THAN DATA COLLECTION
Data Collection Techniques
- Primary data sources are captured specifically by direct measurement.
- Secondary sources are reused or obtained from other systems.
SEE SLIDE
Primary Data Sources
Digital and analog format
Raster - Digital remote sensing images/ digital aerial photographs
Vector - GPS measurements/ Survey measurements
Secondary
Digital and analog format
Raster - scanned maps/ photographs/ DEMs from maps
Vector - USGS Topographic maps/ Toponymy (place-name) data sets from atlases
Primary way
Measure terrain directly/ Digital imagery collected with LiDar
Data Collection - Digitalizing
- Analog data must be digitized before adding to a GIS database.
- Analog-to-digital transformation
- > Scanning paper maps or photographs
- > Optical character recognition (OCR)
- > Text describing geographic object properties
- > Vectorization of selected features
SEE SLIDE
Data Collection Project Workflow
1) Planning (establish users’ requirements, gathering all resources), 2) Preparation (obtain existing data, hardware/ software), 3) Digitizing/ Transfer (Require most efforts, Survey data entry, scanning, photogrammetry), 4) Editing/ Improvement (Validate data, Correct errors, improve quality), 5) Evaluation (Identify if the project succeeded, or failed)
Primary Data Collection
Raster - Remote Sensing (Aerial Photography, Satellite Imagery) Vector - Ground Survey - GPS (Global Positioning System) - LiDAR (Light Detection and Ranging)
Raster Primary Data Capture
- Remote sensing – the most popular form
-> The measurement of physical, chemical, and
biological properties of the objects without direct
contact.
-> Information derived from the measurement of the amount of electromagnetic radiation reflected,
emitted, or scattered from objects.
-> Passive sensors (limitation: cloud effect)
• Rely on reflected solar radiation or emitted terrestrial radiation (by sun light)
-> Active sensors – synthetic aperture radar (SAR)
• Generate their own source of electromagnetic radiation
Raster Primary Data Capture
Remote Sensing - Satellite imagery -> Earth-orbiting satellites – collect information from parts of Earth surface at regular time intervals. - Aerial photography -> Fixed-wing aircraft -> Smaller area in great detail -> Suitable for detailed surveying and mapping projects
Raster Primary Data Capture - Remote Sensing (Four Key Aspects of Resolution)
- Spatial resolution – pixel size: The size of object to be resolved
- Spectral resolution
- > The parts of electromagnetic spectrum to be measured
- > Different objects emit and reflect different types and amounts of radiation (e.g., Landsat 8, 0.435 nm ~ 2.297 nm; 11 bands)
- > Single band (value range: 8 bit [0-255]) or multiband/multispectral
- Radiometric resolution- How finely the radiometric resolution a system can represent or distinguish differences of intensity, and is usually expressed as a number of bits (8 bit [0-255]).
- Temporal resolution – repeat cycle
- > Describe the frequency of images to be collected for the same area
ALL SENSORS NEED TO TRADE OFF BETWEEN THESE RESOLUTIONS, B/C OF STORAGE PROCESSING AND BANDWIDTH CONSIDERATION
GeoEye 1 (2008) and 2 (not currently scheduled to launch)
Geoeye2 : .34m spatial, spectral, radiometric, temporal
4 multispectral bands
SEE SLIDE
The resolution of the satellite image is 0.41 meter in panchromatic image and 1.65 m in multispectral imagery (Repeat cycle is between 2.1-8.3 days).
Worldview 2 - Satellite
8 multispectral bands 2.0m
Panchromatic (B&W): .5m
The resolution of the satellite image is .5 m
Vector Primary Data Capture
- Ground Survey - Shifting from measurement-based to coordinate-based
- GPS (Global Positioning System) - Receiving the orbit satellite signals to calculate the location through trilateral
- LiDAR - Light Detection and Ranging - Using scanned laser range-finder to produce accurate topographic surveys with great detail.
Vector Primary Data Capture
Surveying
- > Principle: 3D locations of objects determined by angle and distance measurements from known locations (benchmark point)
- > All points obtained from survey measurements, and their locations are relative to other points.
- > Time-consuming and expensive activity
- > Uses expensive field equipments and crews
- > Most accurate method for large scale, small areas
- > Provide the georeference points for other fine-scale images
Ex. Leica Total Station
Vector Primary Data Capture
GPS – Global Positioning System
- > Consist of a system of 24 satellites, orbiting the Earth every 12 hrs, at the elevation of 20,200km
- -> Transmitting radio pulses at precisely timed-interval
- > Four satellites to locate a three dimension (x,y,z)
- > Differential GPS (DGPS) used to improve accuracy
- —–> Combines GPS signals from satellite with correction signals via radio/telephone from base station
Pen Portable PC and GPS - Originally funded by the US Dept. of Defense • Navigation • Mapping • Surveying • Other applications needed precise positions EX. Kinematic GPS Surveying
Vector Primary Data Capture
LiDAR (Light Detection And Ranging)
-> Active sensor
-> Using lasers to measure distances to reflective surfaces
-> Point cloud: a massive collection of independent points (x, y, z)
-> Collect extremely large quantities of very detailed information
• 200,000 points per second
• Accuracy around 10 cm
Ex. Multiple Pulses in Air (MPiA) doubles pulse rate
Alliance for Integrated Spatial Technologies (SLIDES)
Secondary Geographic Data Capture
- Data collected from other purposes can be converted for use in GIS projects - Raster conversion -> Scanning - Vector conversion -> Digitizing/Vectorization -> Photogrammetry -> COGO – coordinate geometry
Raster Conversion
-> Scanning – convert hard-copy analog media into digital images by scanners
• Scanner – scan the line across the map to record the amount of light reflected from data sources
-> Sources:
• Maps, Aerial photographs, Documents, etc
Digitizing/ Vectorization
-> Process of converting raster data into vector data
-> Collection of vector objects from maps, photographs, image, etc.
• Primary sources
• Secondary raster data
Georeference/ Georegistration
-> Convert image coordinates into database coordinates by geometric transformation process/algorithms
• Photo image
• Coordinate database
• Three reference/control points
Image Rectification Using Ground Control Points (GCPs)
- Identify GCPs on image and reference
- Develop transformation equations
- Resample to determine digital number (DNs) for
corrected image pixels
1st Order Polynomial
2nd Order Polynomial
See SLIDE
Resampling
- Used to determine the pixel DN values to fill in the output matrix by sampling from original (distorted) image
- Nearest Neighbor
-> Uses closest pixel value
-> Discreet data
• Classes, land use - Bilinear Interpolation
-> Uses 4 closest neighbors
-> Continuous data, localized
• Elevation data - Cubic Convolution
-> Uses 16 closest neighbors
-> Continuous data, smoothest (IMAGES)
SEE SLIDEs (EXAMPLES)
Vector Secondary Data Capture - Digitizing/ Vectorization
Manual digitizing – vertices defining point, line, polygon
- > Point – screen cursor to record the location by clicking button
- > Stream-mode – partially automated collecting vertices ( .25 sec, .02in)
EX. Heads-Up Digitizing and Vectorization
