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139 Terms

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Electromagnetic Radiation Interactions

EM energy can be reflected, transmitted (refracted), or absorbed.These interactions occur with matter at various frequencies, affecting how electromagnetic waves propagate and interact with different materials.

<p>EM energy can be reflected, transmitted (refracted), or absorbed.These interactions occur with matter at various frequencies, affecting how electromagnetic waves propagate and interact with different materials. </p>
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Law of Reflection

The principle that states reflection follows specific angles of incidence (\thetai) and reflection (\thetar), where \thetai = \thetar.

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Transmission and Refraction

Transmission involves refraction due to a change in the velocity of EM energy when passing between media of different densities.

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Absorption

The process of converting energy to heat, which may be re-emitted as thermal radiation.

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<p>Wave Properties and Label Diagram </p>

Wave Properties and Label Diagram

A wave transfers energy without transferring matter, characterized by crests and troughs. The diagram illustrating wave properties should label crests, troughs, wavelength, and amplitude.

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Amplitude

Controls the energy level of the wave, measured as the vertical distance from the equilibrium to the crest.

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Wavelength

Defines the position of the wave in the electromagnetic spectrum (\lambda), measured as the distance between two successive crests.

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Atmospheric Windows

Regions of the atmosphere that selectively absorb EM radiation, allowing high transmission in specific bands.

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Visible and Thermal IR

Major atmospheric windows that sensor systems are designed to operate within to minimize signal loss.

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Sensor Resolution Trade-offs

Balance between spatial resolution (pixel size) and spectral resolution (number of bands) in sensor technology.

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MODIS

A sensor with low spatial resolution (250m to 1km) and high spectral resolution (36 bands).

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Sentinel-2

A sensor providing a balance between spatial (10m to 60m) and spectral resolution (13 bands).

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Planet

A sensor known for high spatial resolution (3m) but low spectral resolution (typically 4 to 8 bands).

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Vegetation Spectral Curves

Reflectance patterns indicating chlorophyll absorption and reflectivity in various wavelengths.

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Green Peak

Occurs at approximately 0.55µm in the vegetation spectral curve, where light is reflected more than in the blue or red bands.

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Red Edge

A sharp change in reflectance near 0.7µm, indicating the transition from chlorophyll absorption to leaf structure scattering.

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NIR Reflectance

High reflectance in the near-infrared region (NIR) triggered by the internal cellular structure (spongy mesophyll) of leaves.

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SWIR Absorption

Controlled by water content in vegetation; higher water content leads to deeper absorption features in the Short-Wave Infrared region.

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Remote Sensing Workflow

  1. Energy Source (Sun/Sensor)

  2. Atmosphere (Scattering/Absorption)

  3. Surface Interaction (Reflection)

  4. Sensor Recording (Data capture)

  5. Interpretation (Analysis)

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Radar Geometry

Describes the active side-looking microwave system parameters including azimuth and range.

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Slant Range vs Ground Range

Slant Range is the direct line-of-sight distance from the sensor to the target; Ground Range is the horizontal distance on the terrain.

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Incidence Angle

The angle between the radar beam and the surface normal, which significantly controls backscatter intensity.

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DEM Hydrology

Digital Elevation Model representing elevation and water flow dynamics across a landscape.

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Flow Direction

Defines the movement of water downslope in the landscape, often using the D8 algorithm (8 cardinal directions).

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Flow Accumulation

Identifies areas of converging flow by counting how many upslope cells drain into a single cell.

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Threshold

Technique used to extract stream channels by selecting cells with a flow accumulation value above a specific limit.

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LiDAR Waveform

Represents the intensity of laser pulses over time.

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Canopy Height Calculation

Derived by subtracting the ground return elevation from the first return elevation in a LiDAR point cloud or waveform.

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Airborne LiDAR

Characterized by a small laser footprint and high point density (30 pts/m^2), ideal for detailed forest mapping.

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Spaceborne LiDAR

Features a large footprint (70m for GEDI) and sparse coverage, but provides global sampling of forest structure.

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Biomass Mapping

Utilizes height data from LiDAR to estimate the total organic matter in an area, crucial for carbon cycle studies.

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Can you define the four types of resolution in EO remote sensing?

The four types of resolution in Earth Observation remote sensing are spatial resolution, spectral resolution, temporal resolution, and radiometric resolution. Spatial resolution refers to the size of the smallest object that can be detected. Spectral resolution indicates the number of wavelengths or spectral bands captured. Temporal resolution measures the frequency of data collection over time. Radiometric resolution describes the sensitivity to detect variations in energy values.

<p>The four types of resolution in Earth Observation remote sensing are spatial resolution, spectral resolution, temporal resolution, and radiometric resolution. Spatial resolution refers to the size of the smallest object that can be detected. Spectral resolution indicates the number of wavelengths or spectral bands captured. Temporal resolution measures the frequency of data collection over time. Radiometric resolution describes the sensitivity to detect variations in energy values. </p>
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what are the 3 stages from DN to AT-surface Reflactance?

1. Stage 1 (DN to At-Sensor Radiance): Converts raw DNDN values into physical units of spectral radiance.

  1. Stage 2 (Radiance to TOA Reflectance): Normalises radiance data for illumination variations (EarthEarth-SunSun distance, solar angle) to compare images from different dates. Result is Top of Atmosphere (TOATOA) reflectance (values between 00 and 11).

  2. Stage 3 (Atmospheric Correction): Removes atmospheric effects (scattering, absorption by water vapour, etc.) to get the true At-Surface (Bottom of Atmosphere) reflectance.

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Can you name one approach for atmospherically correcting optical satellite imagery?

One approach for atmospherically correcting optical satellite imagery is the use of the Dark Object Subtraction (DOS) method, which removes atmospheric effects by identifying and correcting for the darkest pixels in the image.

Another one is Empirical line calibration and finally Physical atmospheric modelling.

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<p>label this diagram of a radar: include Range vector, Local incidence angle, flight path, illumination angle, range factor, slant range, incidence range, earth normal vector, near range, far range, ground range, azimuth, nadir, altitude , swath range and swath width</p>

label this diagram of a radar: include Range vector, Local incidence angle, flight path, illumination angle, range factor, slant range, incidence range, earth normal vector, near range, far range, ground range, azimuth, nadir, altitude , swath range and swath width

correct labels -

<p>correct labels - </p>
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How do we retrieve hydrological information from a DEM?

Hydrological information from a Digital Elevation Model (DEM) is retrieved by analyzing the terrain to delineate watersheds, identifying flow directions, and calculating flow accumulation, which helps in modeling water movement and drainage patterns.

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Describe how we can calculate a channel network?

A channel network can be calculated by using a Digital Elevation Model (DEM) to analyze the terrain, applying methods like flow direction and flow accumulation analyses, which identify interconnected pathways that allow water to flow.

1.Fill sinks

2.Flow direction (Dinf)

3.Flow accumulation

4.Threshold on flow accumulation to identify stream network

<p>A channel network can be calculated by using a Digital Elevation Model (DEM) to analyze the terrain, applying methods like flow direction and flow accumulation analyses, which identify interconnected pathways that allow water to flow.  </p><p><span><span>1.</span><strong><span>Fill sinks</span></strong></span></p><p><span><span>2.</span><strong><span>Flow direction (</span></strong></span><span style="font-family: &quot;Aptos Narrow&quot;;"><strong><span>Dinf)</span></strong></span></p><p><span><span>3.</span><strong><span>Flow accumulation</span></strong></span></p><p><span><span>4.</span><strong><span>Threshold on flow accumulation to identify stream network</span></strong></span></p>
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What are the primary differences between airborne and spaceborne LiDAR

Airborne LiDAR operates from aircraft and typically captures high-resolution data over smaller areas, while spaceborne LiDAR uses satellites to gather data over larger regions with lower resolution. This results in differences in applications, precision, and scale between the two methods.

<p>Airborne LiDAR operates from aircraft and typically captures high-resolution data over smaller areas, while spaceborne LiDAR uses satellites to gather data over larger regions with lower resolution. This results in differences in applications, precision, and scale between the two methods. </p>
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How would you analyse spatial patterns in the following datasets?

Location of diseased trees in a forest

Smoking rates across counties in the UK

Spatial patterns in these datasets can be analyzed using methods like spatial autocorrelation, kernel density estimation, and hot spot analysis. These techniques help identify clusters, trends, and relationships within the geographic distribution of the data. These analyses reveal spatial clustering, correlations, and variations in patterns, informing management strategies and public health initiatives.

<p>Spatial patterns in these datasets can be analyzed using methods like spatial autocorrelation, kernel density estimation, and hot spot analysis. These techniques help identify clusters, trends, and relationships within the geographic distribution of the data. These analyses reveal spatial clustering, correlations, and variations in patterns, informing management strategies and public health initiatives. </p>
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Ellipsoid

coordinate systems describe how spatial locations are represented in terms of numerical values, defining the position of points in a given space using systems like Cartesian, polar, or geographic coordinates.

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Datum

A reference point or surface from which measurements are made in geospatial data, crucial for establishing the position of locations in relation to the Earth's surface.

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Projection

A method for representing the curved surface of the Earth on a flat map, involving transformations of geographic coordinates to map coordinates.

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Geoid

A model of the Earth's shape that accounts for variations in gravitational field, representing the mean sea level across the globe. It serves as a reference surface for measuring elevations and depths.

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Mean sea level

the reference surface used to define the geoid, representing the average height of the ocean's surface under the influence of Earth's gravity and rotation.

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Float

A data type that stores real numbers with decimal values.

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Integer

A data type that stores whole numbers with no decimal places.

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Spectral Regions

Ranges of wavelengths associated with specific colors or types of light.

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Blue Light

The spectral region from approximately 450 to 500 nm.

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Red Light

The spectral region from approximately 650 to 680 nm.

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Shortwave Infrared (SWIR)

The spectral region from approximately 2000 to 2500 nm.

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Spatial Resolution

The amount of detail in an image, determining how small specific objects can be resolved.

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Thermal Infrared

Wavelengths longer than visible light that provide thermal images of surfaces.

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Red Edge

The sharp increase in vegetation reflectance between red and near-infrared wavelengths.

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UTM Zones

A global system divided into 60 zones, each spanning 6 degrees of longitude.

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Transverse Cylindrical Projection

A map projection that minimizes distortion in narrow north-south zones.

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Equal-area Cylindrical Projection

A projection that preserves area, suitable for measuring deforestation.

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LiDAR Footprint

The area on the ground illuminated by a single LiDAR laser pulse.

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Digital Terrain Model (DTM)

A representation of the ground surface created from ground returns in LiDAR.

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Linear Spectral Unmixing

A technique modeling pixel reflectance as a linear combination of spectral endmembers.

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Problem Solving Steps

Define the problem, collect data, analyze data, interpret results.

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Ripley’s K Function

A statistic to determine if point patterns are clustered, dispersed, or random.

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Real Aperture Radar

Radar relying on antenna size for resolution.

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Synthetic Aperture Radar (SAR)

Radar that synthesizes a large antenna using platform motion for higher resolution.

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Radar Cross-Section (σ)

The measure of strength of backscattered energy from a target.

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Orthorectification

Geometric correction of imagery to remove terrain-induced distortions.

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Atmospheric Scattering

The process that redistributes energy in the atmosphere.

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Atmospheric Absorption

The removal of energy at specific wavelengths due to atmospheric gases.

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Energy Transfer Model Components

Incoming solar radiation, atmospheric interactions, surface reflection, sensor radiance.

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Spectral Curve

A graphical representation of reflectance values across different wavelengths.

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Albedo

The proportion of solar radiation reflected by a surface.

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Sensor Altitude

The height of the sensor which affects atmospheric path length.

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Spectral Resolution

The ability to resolve different wavelengths in remotely sensed data.

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Temporal Resolution

The frequency at which data is captured or observed.

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Fixed-wing Drones

Drones known for long endurance and large coverage area.

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Rotary Drones

Drones characterized by vertical take-off and precise maneuverability.

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Field Spectroscopy Data

Ground truth data used for calibration and validation of remote sensing.

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GIS Buffer Operation

An operation that creates zones around spatial features at a specified distance.

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Surface Reflectance

The proportion of radiation reflected by a surface after removing atmospheric effects.

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Online Map Presentation

The design of maps for improved accessibility and understanding.

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Multi-Criteria Decision Analysis (MCDA)

A method for combining multiple criteria to aid decision-making.

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Dissolve Operation

A GIS operation that merges adjacent polygons with a common attribute.

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Spatial Join

An operation to transfer attributes between layers based on spatial relationships.

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Electromagnetic Energy

Energy radiated from the Sun that can be absorbed, reflected, transmitted, or scattered.

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Wave

A transfer of energy characterized by wavelength, frequency, amplitude, and polarization.

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Frequency

The number of wave cycles passing a point per second.

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Types of Resolution in EO Remote Sensing

Spatial, spectral, temporal, and radiometric resolution.

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Atmospheric Correction Approaches

Methods like Dark Object Subtraction or Empirical Line Calibration used to correct imagery.

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Radar in Vegetation Studies

Radar is useful as it can penetrate cloud cover and is sensitive to vegetation structure.

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Digital Elevation Models (DEMs)

Models that support hydrological analysis by providing topographic details.

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LiDAR for Biomass Estimation

LiDAR provides information on tree height and structure related to biomass.

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Combining Optical and Radar Data

Using both types of data for enhanced accuracy in mapping wetlands.

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What happens to electromagnetic energy from the Sun?

Electromagnetic energy from the Sun can be reflected, absorbed, transmitted, or scattered by the atmosphere and Earth’s surface.

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Define a wave in remote sensing.

A wave is a means of energy transfer characterised by wavelength, frequency, amplitude, and polarisation.

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Define frequency.

Frequency is the number of wave cycles passing a point per second, measured in Hertz (Hz).

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What are the four types of resolution in Earth Observation remote sensing?

Spatial resolution, spectral resolution, temporal resolution, and radiometric resolution.

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Explain spatial resolution.

Spatial resolution refers to the ground area represented by a single pixel in an image.

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Explain spectral resolution.

Spectral resolution describes a sensor’s ability to distinguish between different wavelengths of electromagnetic energy.

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How do we convert DN values to at-surface reflectance?

Stage 1: Convert DN to at-sensor radiance. Stage 2: Convert radiance to top-of-atmosphere reflectance. Stage 3: Apply atmospheric correction to obtain at-surface reflectance.

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What is atmospheric correction?

Atmospheric correction removes the effects of scattering and absorption by gases and aerosols to retrieve true surface reflectance.