GIS week 6 Flashcards
(27 cards)
What is remote sensing data, and how is it collected?
Techniques for collecting environmental data from a distance without coming into direct contact with the objects of interest.
Record the magnitude of electromagnetic energy flux that is reflected or emitted from the objects on the Earth’s surface or within the atmosphere (normally imagery).
Airplanes, satellites, and UAVs equipped with sensors.
What are key applications of remote sensing?
Urban monitoring and disaster management - floods, wildfires, dust storms, landslides, and earthquakes.
Climate change trends - greenhouse gases and air pollution.
Agriculture - crop health, yield estimation and precision farming.
Forestry management - tracking deforestation and assessing biodiversity.
Water resource management – monitoring the quality and quantity of lakes, rivers, wetland areas and oceans.
Archaeological studies.
Environmental conservation.
Land use and infrastructure planning
What is electromagnetic radiation (EMR), and what are its key properties?
EMR travels at the speed of light, waves consist of electric and magnetic fields.
The distance between wave peaks is the wavelength, measured in micrometres (µm).
What is the electromagnetic spectrum?
The electromagnetic spectrum is the range of all EMR wavelengths, from gamma rays to radio waves, used in remote sensing to study Earth’s features.
How does EMR interact with matter in remote sensing?
The Sun is the most important natural source of EMR for remote sensing.
When EMR from the Sun strikes an object, the energy may be transmitted, absorbed, reflected or scattered.
Remote sensors observe Earth features mainly by detecting EMR reflected or emitted from them.
Different objects reflect, absorb, transmit or emit EMR in different proportions.
How does EMR interact with the atmosphere, and what are atmospheric windows?
EMR interacts with particles and gases in the atmosphere through scattering and absorption.
Scattering deflects the radiation from its path (can severely reduce the information content of remote sensing data)
Absorption causes molecules in the atmosphere to absorb energy at various wavelengths (ozone, carbon dioxide, and water vapour are atmospheric constituents which absorb EMR)
Atmospheric windows (EMR spectral regions that are relatively, though not completely, unaffected by absorption and scattering.)
How does EMR interact with surface features?
Three forms of interaction: absorption, transmission and reflection.
The amount of interaction depends on the wavelength of the energy, the material and condition of the feature.
Remote sensing is concerned with the radiation reflected from targets.
Spectral reflectance: the portion of the incoming radiation that is reflected.
Spectral reflectance curve: a graph of the spectral reflectance of an object as a function of wavelength
What is a spectral reflectance curve in remote sensing?
A graph showing how much radiation an object reflects across wavelengths, crucial for identifying materials like vegetation, water, or soil.
What are aerial photographs in remote sensing, and what are their features?
Images from satellites, aircraft, or UAVs in colour (RGB) or greyscale, optimising spatial detail over spectral information.
What are digital multispectral images, and how is radiometric resolution defined?
Images captured in multiple spectral bands, with radiometric resolution (e.g., 8-bit = 256 values) defining the range of pixel values that can be stored.
What are key features of Landsat and Sentinel satellites for remote sensing?
They capture different spectral bands. Commercial satellites may achieve 30–50 cm resolution
non-commercial satellites, 10–100s m (spatial resolution).
Temporal resolution varies:
weather satellites (5–10 min),
Sentinel-2 (3–5 days),
Landsat (32 days).
What is spatial resolution in remote sensing, and how do Landsat and Sentinel compare?
Spatial resolution is the size of the smallest feature that a sensor can detect. Landsat: 15–60 m; Sentinel: 10–60 m.
Higher resolution = more detail and clarity but larger data size
What is radiometric resolution in remote sensing?
The ability of a sensor to discriminate slight differences in energy intensity; defined by bit depth (e.g., 8-bit = 256 levels).
What is spectral resolution in remote sensing, and how do Landsat and Sentinel compare?
Spectral resolution is the number and width of the spectral bands that a sensor can record.
Each band corresponds to a range of wavelengths of the electromagnetic spectrum.
Different bands can reveal different information about the surface features, vegetation, water, or atmosphere.
Higher spectral resolution means more bands and more diversity, but also more complexity and noise.
Landsat sensors have 8-11 bands, covering the visible, near-infrared, shortwave infrared, and thermal infrared regions.
Sentinel sensors have 13 to 25 bands, covering the visible, near infrared, shortwave infrared, and microwave regions.
What are the spectral bands used in Sentinel satellites?
Sentinel records bands in the visible, near-infrared, shortwave infrared, and microwave regions for diverse applications.
What are the spectral bands used in Landsat satellites?
Landsat captures bands in the visible, near-infrared, shortwave infrared, and thermal infrared regions.
What is the Landsat orbit system used for remote sensing?
Landsat satellites follow a sun-synchronous orbit to provide consistent global imaging.
What is geometric preprocessing in remote sensing?
-remove geometric distortions caused by sensor-Earth geometry variations.
-georeference the image to a particular projected map coordinate system.
What is radiometric preprocessing in remote sensing?
correct an image for sensor response properties and viewing geometry.
correct an image for atmospheric effects and scene illumination
restore an image to accurately represent the radiance measured by the sensor.
What are the main image enhancement techniques in remote sensing?
Band combination (increasing the amount of information that can be visually interpreted.)
Pan-sharpening (increasing the spatial resolution of a multispectral image with a higher-resolution panchromatic image.)
Contrast stretching (enlarging the tonal distinction between different features.)
Spatial filtering (enhancing or suppressing specific spatial details)
What is pan-sharpening in remote sensing?
Combining multispectral and panchromatic images to produce an image with higher both spectral and spatial resolution.
What is contrast stretching in remote sensing?
Expands tonal range to enhance differences between features.
What are band combinations in remote sensing, and what are they used for?
Natural Colour (B4, B3, B2) imagery.
Color Infrared (B8, B4, B3) healthy and unhealthy vegetation.
Short-Wave Infrared (B12, B8A, B4) vegetation, bare soil and urban areas.
Agriculture (B11, B8, B2) health of crops.
Geology (B12, B11, B2) faults, rock types, mineral deposits.
Bathymetric (B4, B3, B1) coastal studies, sediment suspension in water.
Vegetation Index (B8-B4)/(B8+B4) dense canopy, urban and water features.
Moisture Index (B8A-B11)/(B8A+B11) identifying water stress in plants, wetter vegetation has higher values. Lower moisture index values suggest plants are under stress from insufficient moisture (drought areas).
What is the Normalised Burn Ratio (NBR) in remote sensing?
NBR an index highlighting differences in the way healthy green vegetation and burnt vegetation reflect light.
calculated using NIR (B8) and SWIR (B12) bands to highlight differences in reflectance between green and burnt vegetation. NBR = (NIR - SWIR) / (NIR + SWIR).
returns values between -1 and 1
healthy green vegetation= high NBR
burnt vegetation, dry, brown vegetations or bare soil= low NBR
