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:Remote sensing:

the collection of the collection of information information about an object without about an object without being in direct physical being in direct physical contact with the object.contact with the object.

the collection of the collection of information information about an object without about an object without being in direct physical being in direct physical contact with the object.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”

Ground spectroradiometer measurement of soybeans

Ground spectroradiometer measurement of soybeans

Ground ceptometer leaf-area-index (LAI) measurement

Ground ceptometer leaf-area-index (LAI) measurement

Ground MeasurementIn Support of Remote Sensing Measurement

Ground MeasurementIn Support of Remote Sensing Measurement

In situ or remote sensing?

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) Metric, Strip, Panoramic, Multi-spectral

Video Systems Video cameras, Return Beam Vidicon

Imaging Radiometers 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

Jensen, 2000Jensen, 2000

Three-way Interaction Model Between the Mapping SciencesThree-way Interaction Model Between the Mapping Sciencesas Used in the Physical, Biological, and Social Sciencesas Used in the Physical, Biological, and Social Sciences

Three-way Interaction Model Between the Mapping SciencesThree-way Interaction Model Between the Mapping Sciencesas Used in the Physical, Biological, and Social Sciencesas Used in the Physical, Biological, and Social Sciences

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

II Tasks - Identification More advanced than detection Labeling or typing of the object/phenomena Tends to occur simultaneously with detection Examples: houses, pond, highway, grass/trees

II Tasks - Measurement Quantification of objects / phenomena Direct physical measurement from the

imagery Examples

Inventories (count) Length, area and height of objects

II Tasks – Problem Solving Most 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 The ability of a remote sensing system to distinguish

between signals that are radiometricall/spectrally/spatially near or similar

Discrimination 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 Spatial ResolutionResolution

Spatial Spatial ResolutionResolution

Jensen, 2000Jensen, 2000

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

Spectral Spectral ResolutionResolution

Spectral Spectral ResolutionResolution

Jensen, 2000Jensen, 2000

Airborne Visible Infrared Imaging

Spectrometer (AVIRIS) Datacube of Sullivan’s Island

Obtained on October 26, 1998

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, 2000Jensen, 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

2 - bit

8 - bit

1 - bit

Temporal Resolution The ability to obtain repeat coverage for an

area

Timing is critical for some applications Crop cycles (planting, maximum greenness, harvest) Catastrophic events

Aircraft Potentially high Actually (in practice) lower than satellites

Satellite Fixed orbit Systematic collection Pointable sensors

TemporalTemporal ResolutionResolutionTemporalTemporal ResolutionResolution

June 1, 2001June 1, 2001June 1, 2001June 1, 2001 June 17, 2002June 17, 2002June 17, 2002June 17, 2002 July 3, 2003July 3, 2003July 3, 2003July 3, 2003

Landsat Data AcquisitionLandsat Data AcquisitionLandsat Data AcquisitionLandsat Data Acquisition

16 days16 days16 days16 days

Jensen, 2000Jensen, 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

Surface

Sensor

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 WaveTwo components or fields

E = electrical waveM = 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

Microwave

Green

Near Infrared

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 =x

where: c = speed of light (3 x 108 m/s) = wavelengthv = frequency

therefore: = c/ and = c/

EMR SpectrumShort , High , High Q Long , Low , Low Q

Wavelength and Frequency - Example

Energy of Green Light

= 0.5 m = 0.5 x 10-6 m = 5 x 10-7 m

= C/ = (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

= 3000 m = 3 x 10-3 m

= C/ = (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 (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:

Spectral absorptance: = absorbed / i

Spectral transmittance = transmitted / i

Spectral reflectance: = reflected / i

i

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 clouds

Gas Molecules 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*0.3 – 1.1 m UV, visible, reflected IR (near)1.5 – 1.8 m Reflected IR (shortwave)2.0 – 2.4m Reflected IR (shortwave)3.0 – 5.0 m Thermal IR8.0 – 14.0 m Thermal IR10.5 – 12.5 m Thermal IR> 0.6 cm Microwave

*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 Imaging Spectrometer Data of Healthy Green Vegetation in the San Luis Valley of Colorado Obtained on September 3, 1993 San Luis Valley of Colorado Obtained on September 3, 1993

Using AVIRIS Using AVIRIS

Imaging Spectrometer Data of Healthy Green Vegetation in the Imaging Spectrometer Data of Healthy Green Vegetation in the San Luis Valley of Colorado Obtained on September 3, 1993 San Luis Valley of Colorado Obtained on September 3, 1993

Using AVIRIS Using AVIRIS

Jensen, 2000Jensen, 2000224 channels each 10 nm wide with 20 x 20 m pixels224 channels each 10 nm wide with 20 x 20 m pixels224 channels each 10 nm wide with 20 x 20 m pixels224 channels each 10 nm wide with 20 x 20 m pixels

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 PP

Nadir

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 PhotoFlat 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 Horizontal Distance (HD) Flat Terrain Photo-coordinates for

each location Apply the Pythagorean

Theorem

Multiply ‘c’ by scale factor (SF) to find distance

(x1,y1)

(x2,y2)(x1-x2)

(y1-y2)

if RF = 1:10,000 = SF = 10,000

a2 + b2 = c2

(x2-x1)2 + (y2-y1)2 = c2

(x2-x1)2 + (y2-y1)2 = c

c

Relief Displacement - Definition

Stereoscopic Viewing Provides 3rd dimension to air photo interpretation

Identify 3-D form of an object (volcano, building, etc.)

Stereopairs 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

Apparent change in relative positions of stationary objects Caused by change in viewing position Example – looking out car window (side)

Parallax – Air Photo 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 PhotosHigh 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

StereoModel

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