Transcript What is Remote Sensing?

What is Remote Sensing?
Defining Remote Sensing




Remote sensing = collection of data about features
or phenomena of the earth surface (and near
surface) without being in direct contact
Lack of contact with features or phenomena
Sensors utilize electromagnetic radiation (EMR)
Collection of data
Analysis of data collected
Sensing

Data are collected by sensor


Passive – collection of reflected or emitted electromagnetic
radiation
Active – Generates signal and collects backscatter from
interaction with terrain

Imaging & Non-Imaging

Photographic vs. Non-Photographic
Distance – How remote is remote?

Platforms for sensors operate at multiple levels





Cranes
Balloons
Aircraft
Satellite
Permit near-surface to global scale data collection
Remote sensing:
the collection of
information
about an object without
being in direct physical
contact with the object.
Remote Sensing vs. Aerial Photography



Remote sensing is performed using a variety of sensors and
platforms that may operate in multiple parts of the EMR
spectrum
Aerial photography is performed using film-based cameras that
sense only in UV, visible, and NIR spectrum and are operated on
aircraft
Aerial photography is a subset of remote sensing
Image vs. Air Photo Interpretation



Images can be produced by most remote sensing
systems
Air photos are produced by aerial photographic
camera systems
Air photo interpretation is a subset of image
interpretation
Science vs. Art

Science




RS is a tool for scientific analyses
Draws on multiple scientific disciplines
Probabilistic
Art


Interpretation combines scientific knowledge with
experience and knowledge of the world
Interpretation skill is primarily learned through practice
Simplified Information Flow





Passive systems – detect naturally upwelling radiation
Flow: Source  Surface  Sensor
Source, the sun, illuminates surface
Surface reflects/emits radiation
Sensor detects reflected radiation within its field of
view (FOV).



Photographic systems – detected radiation exposes film
Non-photographic – detected radiation generates electrical
signal
Interpretation – manual or machine
Complexities in Information Flow

Variation in illumination




Sun angle
Clouds
Aerosol concentrations, other scattering
Variation in surface properties/coverage


Soil moisture, vegetation growth/conditions, surface
roughness affect reflectance properties
Reflectance properties are dependent on solar angles, ratio
of diffuse and direct, viewing angle
Complexities of Information Flow (cont.)

Sensor/platform variation






Attitude
Altitude
Orbit
Film/wavelength sensitivities
Calibration or Optics
Processing/interpretation variation


Film or digital processing
Repeatability of interpretation results
In situ vs. Remote Sensing

Both attempt to observe/measure phenomena

In situ



Physical contact
Instruments for direct measure
May be source of error



Interaction with phenomena
Sampling method
Ground reference vs. “ground truth”
In situ or remote sensing?
Ground Measurement
In Support of Remote
Sensing Measurement
Ground spectroradiometer
measurement of soybeans
Ground ceptometer leaf-areaindex (LAI) measurement
Advantages of Remote Sensing


Different perspective
Obtain data for large areas





In single acquisition – efficient
Synoptic
Systematic
Obtain data for inaccessible areas
No effect/interaction with phenomena of interest
Disadvantages of Remote Sensing

Accuracy and Consistency

Artifacts



Noise
Generalization
Processing

Scale-related effects

High initial outlays for equipment and training
Data Collection - Sensors

Cameras (film based)


Video Systems




Video cameras, Return Beam Vidicon
Imaging Radiometers


Metric, Strip, Panoramic, Multi-spectral
Digital frame, Scanners, Pushbroom, Hyperspectral
Passive Microwave
Radar
Operational vs. State-of-the-art
Data Collection - Imagery


Panchromatic (monochrome or B&W) – sensitive
across broad visible wavelengths
Color – may provide added discrimination




Color film
Color composites
Thermal – in region 3 microns to 1 mm, sensitive to
temperature
Microwave – all weather capability
Three-way Interaction Model Between the Mapping Sciences
as Used in the Physical, Biological, and Social Sciences
Jensen, 2000
Art vs. Science

Image interpretation is not exact science

Interpretations tend to be probabilistic not exact

Successful interpretation depends on



Training and experience
Systematic and disciplined approach using knowledge of remote
sensing, application area and location
Inherent talents
Image Interpretation - Defined
Act of examining images for the purpose of
identifying and measuring objects and
phenomena, and judging their significance
Image Interpretation (II) Tasks

In order of increasing sophistication...





Detection
Identification
Measurement
Problem-Solving
Not necessarily performed sequentially or in all
cases
II Tasks - Detection



Lowest order
Presence/absence of object or phenomena
Examples: buildings, water, roads and vegetation
IIMore
Tasks
- Identification
advanced than detection




Labeling or typing of the object/phenomena
Tends to occur simultaneously with detection
Examples: houses, pond, highway, grass/trees
II Quantification
Tasks - Measurement
of objects / phenomena



Direct physical measurement from the imagery
Examples


Inventories (count)
Length, area and height of objects




IIMost
Tasks
– Problem
Solving
complex
task
Uses information acquired in first three tasks to put
objects in assemblages or associations needed for
higher-level identification
With experience, recognition becomes more
automatic and tasks become less distinct
Example: residential housing density
Interpreter Requirements - Cognition


Concerned with how interpreter derives information from the
image data
Varies from individual to individual


Reasons for differences/inconsistencies among interpreters
Cognitive processes are concerned with perceptual evaluation of
elements of interpretation and how they are used in
interpretation process
Resolution & Discrimination Germane to Task

Resolution


Discrimination



The ability of a remote sensing system to distinguish between
signals that are radiometricall/spectrally/spatially near or similar
The ability to distinguish an object from its background
Function of spatial, spectral, and radiometric resolution
Germane to task

What is required for the particular assessment/task
Resolution

Four components of resolution

Spatial

Spectral

Radiometric

Temporal
Spatial Resolution




Indication of how well a sensor records spatial detail
Refers to the size of the smallest possible feature that can be
detected as distinct from its surroundings
Aerial Camera: function of of platform altitude and film and
optical characteristics
Non-film sensor: function of platform altitude and instantaneous
field of view (IFOV)
Lower (coarser)
spatial resolution
Higher (finer)
spatial resolution
Spatial
Resolution
Jensen, 2000
Spectral Resolution


The width of the specific EMR wavelength band(s) to
which sensor is sensitive
Broadband


Few, relatively broad bands
Hyper-spectral

Many, relatively narrow bands
Spectral
Resolution
Jensen, 2000
Airborne Visible
Infrared Imaging
Spectrometer
(AVIRIS) Datacube of
Sullivan’s Island
Obtained on October
26, 1998
Color-infrared color
composite on top
of the datacube was
created using three
of the 224 bands
at 10 nm
nominal bandwidth.
Jensen, 2000
Radiometric Resolution


Ability of a sensor to distinguish between objects of
similar reflectance
Measured in terms of the number of energy levels
discriminated





2n, where n = number of ‘bits’ (precision level)
Example: 8 bit data = 28 = 256 levels of grey
256 levels = 0-255 range
0 = black, 255 = white
Affects ability to measure surface properties
1 - bit
2 - bit
8 - bit
Temporal Resolution

The ability to obtain repeat coverage for an area

Timing is critical for some applications



Aircraft



Crop cycles (planting, maximum greenness, harvest)
Catastrophic events
Potentially high
Actually (in practice) lower than satellites
Satellite



Fixed orbit
Systematic collection
Pointable sensors
Temporal Resolution
Landsat Data Acquisition
June 1, 2001
June 17, 2002
July 3, 2003
16 days
Jensen, 2000
Discrimination

Ability to distinguish object from its background and involves
basic tasks of image interpretation:

Detection, identification, measurement, and analysis

As complexity of task increases, so do resolution requirements

Key: target to background contrast

Function of all 4 resolution elements

Example: vegetation type, soil/rock type, building type
Electromagnetic Radiation
(EMR): Properties, Sources
and Atmospheric Interactions
EMR as Information Link

Link between surface and sensor
Sun
Sensor
Surface

Energy
Transfer
(cont)
Radiation


Energy transferred between objects in the form of electromagnetic
waves/particles (light)
Can occur in a vacuum (w/o a medium)
EMR Properties

Wave Theory




EMR => continuous wave
Energy transfer through media (vacuum, air, water, etc.)
Properties
Quantum (Particle) Theory



EMR => packets of energy
Photons or quanta
Interaction of energy with matter
Wave Theory

Explains energy transfer as a wave

Energy radiates in accordance with basic wave theory

Travels through space at speed of light
at
3 x 108 ms-1 (meters per second)
Electromagnetic
Wave
Two components or fields
E = electrical wave
M = magnetic wave
http://www.colorado.edu/physics/2000/waves_particles/
Quantum Theory


Wave theory doesn’t account for all properties of
EMR
Interaction of EMR with matter (atoms)



Absorption
Emission
EMR is transferred in discrete packets (particles)

Photons (quanta)
Wavelength & Frequency
Near Infrared
Green
Microwave
Wavelength and Frequency

Relationship is inverse

High frequency associated with short wavelengths and high energy

Low frequency associated with long wavelengths and low energy
c=lx
where:
c = speed of light (3 x 108 m/s)
l = wavelength
v = frequency
therefore:
 = c/l
and
l = c/
EMR Spectrum
Short l, High , High Q
Long l, Low , Low Q

Wavelength and Frequency Example
Energy of Green Light
l = 0.5 mm = 0.5 x 10-6 m = 5 x 10-7 m
 = C/l = (3 x 108 m/s) / (5 x 10-7 m) = 0.6 x 1015 Hz
= 6 x 1014 Hz
Q = h = 6.626 x 10-34 Js x 6 x 1014 cycles/s
= 39.756 x 10-20 J

Energy of Microwave
l = 3000 mm = 3 x 10-3 m
 = C/l = (3 x 108 m/s) / (3 x 10-3 m) = 1 x 1011 Hz
Q = hf = 6.626 x 10-34 Js x 1 x 1011 cycles/s
= 6.626 x 10-23 J
Partitioning of Energy at Surface

Radiant flux at the surface is partitioned among:

Absorption

Transmission

Reflection
Radiation Budget Equation

Radiant Flux (F) incident at a surface = 1 + 2 + 3

1) Amount of energy absorbed by the surface

2) Amount of energy reflected from the surface

3) Amount of energy transmitted through the surface
Radiation Budget Equation (cont.)

Dimensionless ratios:
al = Fabsorbed / Fil

Spectral absorptance:

Spectral transmittance: tl = Ftransmitted / Fil

Spectral reflectance:

rl = Freflected / Fil
al + tl + rl = Fil = 1
Radiation Budget Equation (cont.)

Proportion of energy absorbed/transmitted/reflected
will vary from target-to-target




Material type
Material condition
For a given target, proportion absorbed, transmitted,
and reflected energy will vary with wavelength
Ability to distinguish between targets

Atmospheric
Interactions
Energy detected by sensor is a function of



Atmospheric influences
Surface properties
Atmosphere will affect EMR in three ways



Absorption
Transmission
Scattering
Constituents in the
Atmosphere

Responsible for absorption and scattering

Water droplets/ice crystals


Gas Molecules


clouds
CO2, water vapor, ozone
Aerosols


particles suspended in the atmosphere
smoke, dust, sea salt, chemical pollutants
Atmospheric Windows

Portions of the spectrum that transmit radiant energy
effectively
Wavelength Window
Radiation Type
1.5 – 1.8 mm
2.0 – 2.4 mm
3.0 – 5.0 mm
8.0 – 14.0 mm
10.5 – 12.5 mm
> 0.6 cm
UV, visible, reflected IR (near)
Reflected IR (shortwave)
Reflected IR (shortwave)
Thermal IR
Thermal IR
Thermal IR
Microwave
*0.3 – 1.1 mm
*scattering may limit transmission for UV and shorter visible wavelengths
Scattering Effects

Scatter can occur anywhere in information flow:
Sun -> Surface -> Sensor

Reduces direct illumination from sun and creates
diffuse illumination

Creates noise and reduces contrast in image

May add to or reduce signal received by sensor

Filters may be used to reduce effects of haze and
scatter
Radiation Budget Equation (cont.)

Proportion of energy absorbed/transmitted/reflected
will vary from target-to-target




Material type
Material condition
For a given target, proportion absorbed, transmitted,
and reflected energy will vary with wavelength
Ability to distinguish between targets
Types of Reflection (cont.)
Uniform
reflection
Smooth
surface
Rough
surface
Spectral Signature Concept


Describes spectral reflectance of a target at different
wavelengths of EMR
Spectral reflectance curve - graphs reflectance
response as a function of wavelength

Key to separating and identifying objects

Selection of optimum wavelength bands
More Spectral Reflectance Curves
Imaging Spectrometer Data of Healthy Green Vegetation in the
San Luis Valley of Colorado Obtained on September 3, 1993
Using AVIRIS
224 channels each 10 nm wide with 20 x 20 m pixels
Jensen, 2000
Air Photo Geometry and
Stereo Viewing

Photographic Elements
Fiducials

Minimum of four markers on photo



A) Placed on center of each side of photo AND/OR
B) Placed in photo corners
Intersection of lines drawn between opposite fiducials marks the
image principal point
A
B
Photographic Elements

Principal Point (PP)


Center point of the image
Used for finding center of photographic and aligning
imagery for stereo viewing
Photographic Elements

Nadir


The point directly below
the aircraft
If the image is truly
vertical, then the
principal point is the
image of the nadir point
Nadir
PP
Basic Photo Geometry

Height (H)



Altitude of the platform (and camera system) above the
terrain
AGL = Above ground level
ASL = Above sea level
H
Basic Photo Geometry (cont)

Focal Length (f)

Distance from focal point
(lens) to film plane at
back of camera
f
Target-to-Film Energy Path

Radiation reflected up from the surface and atmosphere

Rays converge at the focal point (lens)

Film is exposed at the back of the camera

Optical axis


Line from the focal point to the center of scene
For a perfectly vertical photo, the optical axis, principal point, and
nadir point will line up
Air Photo Geometry – Negative Reversal

Reversal



Geometric
Tonal
Contact Positive
Print
Scale – Vertical Air Photo
Flat Terrain

Similar to map scale


Length of feature on image : Length of feature on ground
Expressed as a dimensionless representative fraction (RF)


RF = 1:10,000 OR
1 / 10,000
Can be determined


Knowing actual length of feature visible in image
Knowing the height of the camera (H) above ground level (hAGL)
and the focal length (f) of the camera & using the concept of
‘similar triangles’
Calculate Scale
Scale – Note About ‘Height’

Height of Camera/Platform


Should be stated as height above the terrain, e.g., 200 meters
above ground level (AGL)
If height is stated in terms of height above mean sea level (H’),
then you must know height of terrain (h) and adjust denominator
of representative fraction accordingly
Height above terrain: H = H’ - h

Scale
Flat vs. Variable Terrain



If terrain is flat, then scale can be determined for the entire
image
If height of terrain varies, then scale will also vary across the
image
Depending on the amount of variation, an average terrain
value may be used

Computing
Flat
Terrain


Horizontal Distance (HD)
Photo-coordinates for each
location
Apply the Pythagorean
Theorem
(x1,y1)
(y1-y2)
a2 + b2 = c2
c
(x1-x2)
(x2-x1)2 + (y2-y1)2 = c2
2 + (y2-y1)
2 = c

Multiply
‘c’ by scale
factor
(x2-x1)
(SF) to find distance
if RF = 1:10,000 = SF = 10,000
(x2,y2)
Relief Displacement - Definition
Stereoscopic Viewing

Provides 3rd dimension to air photo interpretation


Stereopairs


Identify 3-D form of an object (volcano, building, etc.)
Overlapping vertical photographs
Stereoscopes


Used to create synthetic visual response
by forcing each eye to look at different
views of same terrain
Gives perception of depth (3-D)
Stereo Viewing

Parallax




Parallax – Air Photo


Apparent change in relative positions of stationary objects
Caused by change in viewing position
Example – looking out car window (side)
Caused by taking photographs of the same object from different positions --> relative displacement
Relative displacement

Forms the basis for 3-D viewing of successive overlapping photos
Stereoscopic Parallax
Types of Stereoscopes

Lens




Pair of magnifying lens that keep eyes working separately
Used with pre-aligned stereopairs called stereograms
Unable to view entire photo at one time
Mirror/Reflecting



Separates lines of sight using mirrors or prisms
Can also magnify
Less portable
Oblique Photographs - Geometry
Oblique Photos
High oblique
Low oblique
StereoPlotters


Various types
Three main components



1. Projection system that creates the terrain model
2. Viewing system so operator can see model
stereoscopically
3. Measuring and tracing system to record elevation and
trace features onto a map sheet
StereoPlotters


Reverse process of projecting rays from terrain thru camera lens
to film plane to create a terrain model
Orientation and position of the aerial camera is recreated by
adjusting projectors




Adjust for side-to-side movement (roll)
Adjust for up-down movement (pitch)
Adjust for orientation (yaw)
Traced using floating mark


Planimetrically by raising/lowering mark to maintain contact with
terrain
Contours by setting elevation and moving mark along terrain so
that contact is maintained
Stereo
Model
StereoPlotter
Orthophotography

Images corrected for tilt and relief displacement

Base of features will be shown in their true planimetric position

Feature distortion is not eliminated



e.g., tall buildings will still appear to “lean”
Perspective of the image is changed from point to parallel rays
orthogonal to the surface
Useful as base map
Digital Elevation Models



Regular array of terrain elevations
Normally stored as a grid of hexagonal pattern
Created using




Ground survey data
Cartographic digitization of contour data
Photogrammetric measurements
Other remote sensing approaches


Interferometric synthetic aperature radar (InSAR)
Scanning LIDAR
Photo Mosaics


Stitching together series of aerial photographs to
cover large areal extents
Uncontrolled




Photos are matched visually without ground control
Generally limited to center of images
Scale may not be constant
Unequal brightness between photos may make
interpretation difficult
Photo Mosaics

Controlled (relative to uncontrolled)



More rigorous
Photos have been rectified and precisely matched using
ground control
Greater accuracy, but greater cost