GEOG2013A - Methods, Models and GIS

Data Acquisition in GIS

Introduction

Data input is time-consuming and costly in GIS.
Data sharing promotes standardization and metadata generation.

Data Sources

Land, manual surveys, satellites, computerized registers, digital maps, analog maps, files, and other data.

Methods of Data Acquisition

Primary Methods: Data from the object itself (more exact, up-to-date, but expensive).
Secondary Methods: Data from existing sources (analog or digital).

Data Collection Process

Planning: User requirements, resources, project plan.
Collecting: Data acquisition, redrafting, hardware/software setup.
Editing/Improvement: Data validation, error correction, quality improvement.
Evaluation: Project success/failures assessment.

Data Types & Acquisition Methods

Geometrical Data: Surveying, satellite positioning, photogrammetry, remote sensing.
Attribute Data: Measurements, remote sensing, interviews, social networking.
Secondary Methods: Manual digitizing, scanning, existing databases, scientific reports.

Surveys

Primary data capture via direct measurement.
GIS represents and analyzes points, lines, areas from surveys.
Surveys can be quantitative (GPS, total station, laser scanning) or qualitative (census, opinion polls).

Quantitative Data Capture

Focuses on numbers and frequencies, statistically analyzed.
Modern land surveyors use total stations, satellite receivers, laser scanners, drones.
GNSS (Global Navigation Satellite Systems) acquire accurate position data.
Examples: American GPS, Russian GLONASS, European Galileo, Indian IRNSS, Japanese QZSS, Chinese BeiDou.

Qualitative Data Capture

Provides deeper description and meaning.
GIS links quantitative (position) with qualitative (description) data.
Examples: photographs, interviews, perceptions, newspaper reports, sound bites linked via GPS or aerial photos.

Remote Sensing

Acquiring information without physical contact.
Involves sensing, recording, analyzing reflected or emitted energy.
Used in geography, land surveying, Earth sciences, military, commercial, and humanitarian applications.

Remote Sensing Steps

A: Energy Source or Illumination
B: Radiation and the Atmosphere
C: Interaction with the Target
D: Recording of Energy by the Sensor
E: Transmission, Reception, and Processing
F: Interpretation and Analysis
G: Application

Energy Source and EMR

Requires an energy source, typically electromagnetic radiation (EMR).
EMR has electrical (E) and magnetic (M) fields, traveling at the speed of light $c = 3 \times 10^8 m.s^{-1}$ .

Characteristics of EMR Waves

Wavelength ( $\lambda$ ): Length of one wave cycle (μm-m).
Frequency: Cycles per second (Hertz).
Amplitude: Height of each peak.
Wavelength changes depending on the medium; frequency is constant at the source.

Wavelength and Frequency Relationship

Formula: $c = \lambda f$ , where c = speed of light, $\lambda$ = wavelength, f = frequency.
Inverse relationship: shorter wavelength = higher frequency, and vice versa.

Energy and Wavelength

The shorter the wavelength, the more energy it contains, and vice versa.
$E = hf$ (E ≈ Q = energy of a quantum), $E = \frac{hc}{\lambda}$
Shorter wavelengths are easier to detect, longer wavelengths require larger sensor area or longer viewing time.

Electromagnetic Spectrum (EMS)

Ranges from gamma rays to radio waves.
Useful regions for remote sensing exist throughout the spectrum.
Division of EMS:
- Gamma rays: <0.03 nm
- X-rays: 0.03 – 300 nm
- UV radiation: 0.30 – 0.38 μm
- Visible light: 0.38 – 0.72 μm
- Near IR: 0.72 – 1.30 μm
- Mid IR: 1.30 – 3.00 μm
- Far IR / Thermal IR: 7.0 – 1000 μm
- Microwave radiation: 1 mm – 30 cm
- Radio: >30 cm

Radiation and the Atmosphere

Atmosphere affects radiation via scattering and absorption.
Scattering redirects radiation from its path.

Factors Affecting Scattering

Wavelength of radiation.
Abundance of particles or gases.
Distance radiation travels through the atmosphere.

Types of Scattering

Rayleigh Scattering: Small particles compared to wavelength; shorter wavelengths scatter more (blue sky).
Mie Scattering: Particles similar size to wavelength; affects longer wavelengths (red/brown sky at sunrise/sunset).
Non-selective Scattering: Particles much larger than wavelength; all wavelengths scattered equally (white clouds).

Absorption

Atmospheric molecules absorb energy at specific wavelengths.
Ozone, carbon dioxide, and water vapor are primary absorbers.
Ozone absorbs UV radiation.

Implications for Sensor Design

Gases absorb electromagnetic energy in specific spectral regions.
Atmospheric windows are spectral areas unaffected by absorption.
Visible spectrum aligns with both an atmospheric window and peak solar energy.
Heat energy from Earth corresponds to a window around 10 μm (thermal IR), and beyond 1 mm (microwave).

Interaction with the Target

Radiation can be absorbed (A), transmitted (T), or reflected (R).
$I = A + T + R$ (I = Incident energy).
Proportions depend on wavelength, material, and condition.

Reflection Types

Specular Reflection: Smooth surface, energy directed in a single direction.
Diffuse Reflection: Rough surface, energy reflected uniformly in all directions.

Spectral Response Curve

Characterizes reflectance/emittance over various wavelengths.
Distinguishes image features by comparing responses across wavelength ranges.

Recording of Energy by the Sensor

Sensor: Detects reflected, emitted, or scattered energy (e.g., MODIS, OLCI/SLSTR).
Platform: Vehicle carrying a sensor (e.g., Aqua, Sentinel 3).

Orbits

Geostationary Orbits: High altitude (36,000 km), continuous observation over specific areas.
Near-Polar Orbits: North-south, Earth's rotation allows coverage of most of the surface; often sun-synchronous for consistent illumination.

Swath

Area imaged on the Earth's surface by a sensor.
Varies from tens to hundreds of kilometers wide.

Resolution

Spatial Resolution: Smallest detectable feature size, depends on Instantaneous Field of View (IFOV).
Spectral Resolution: Ability to define fine wavelength intervals; multi-spectral and hyperspectral sensors.
Radiometric Resolution: Ability to discriminate slight energy differences, measured in binary values (2ⁿ).
Temporal Resolution: Ability to image the same area at the same viewing angle repeatedly; depends on satellite/sensor capabilities, swath overlap, latitude, and sensor pointing ability.

Secondary Data Capture

Creating vector and raster files from maps, photographs, and other hardcopy sources.
Raster data via scanning, vector data via digitizing, photogrammetry, and COGO.
Georeferencing is crucial.

Raster Data Capture

Quality depends on source material, scanner, and preparation.
Automated digitizing vs. manual digitizing: cost-benefit analysis needed.

Vector Data Capture

Vectorization: Converting raster to vector data.
- Heads-up digitizing: On-screen digitizing.
- Photogrammetry: Measurements from photographs.
- COGO data entry.
Georeferencing is important.

Editing

Correcting errors from original data and encoding processes.
Continuous data quality management.

Editing Attribute Data

Spotting errors through manual comparison.
Checking for impossible values, extreme values, and internal consistency.

Editing Spatial Data

Identifying and correcting errors in vector or raster data.
Errors include missing entities, duplicate entities, mislocated entities, missing labels, duplicate labels, digitizing artifacts, and noise.

Georeferencing and Geocoding

Georeferencing: Fixing feature locations within a coordinate system; transforming real-world measurements to a flat map surface.
Geocoding: Assigning geographic locations to spatial objects.

Georeferencing Raster Data

Raster-to-world relationships, transforming raster grid coordinates to map coordinates.
Image-to-map rectification and image-to-image registration.

Geocoding Applications

Turning addresses into maps, locating incidents, establishing home locations of credit card holders.