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REMOTE SENSING OF NATURAL RESOURCES

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Preprocessing RS data is a function of the application and sensor type: ... Because a camera lens has a 'fish-eye' effect, the farther from nadir you go the ... – PowerPoint PPT presentation

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Title: REMOTE SENSING OF NATURAL RESOURCES


1
Preprocessing RS Data And Ground Truth
2
Preprocessing
  • Many corrections that need to be made before RS
    can be analyzed.
  • Preprocessing RS data is a function of the
    application and sensor type
  • Satellite-Airborne-Handheld
  • Imaging Non Imaging
  • Some satellite data is delivered ready to go.

3
Preprocessing
  • Preprocessing can be extensive
  • Atmospheric Mixed Pixels
  • Radiometric Georegistration
  • Elevation Off-Nadir

4
The Digital Value
  • So what shape is the raw data in?
  • Essentially the raw data represents the amount
    of energy received by the sensor in any one
    band. This is only radiant energy and referred
    to as a digital value (DV).

An electron will move into the conduction band
with applied energy. The amount of energy in the
conduction band is recorded as a DV.
e-
e-
e-
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5
The Atmosphere
  • The raw DV is often converted to energy or
    percent reflectance.
  • It is an important because atmospheric
    conditions can significantly affect the amount
    of energy received at the sensor.
  • Corrections are done in many ways
  • Atmospheric Models Image Based Algorithms
  • Reflectance Calculations

6
The Atmosphere
  • ATMOSPHERIC MODELING
  • Attempts to model atmospheric scattering and
    converts DV into energy values
  • Often used on satellite and highly calibrated
    airborne systems.
  • Requires
  • Altitude Elevation Aerosol Distribution
  • Visibility Water Vapor Sensor
    Configurations

7
The Atmosphere
REFLECTANCE CALCULATIONS Reflectance
Radiance/Irradiance
8
The Atmosphere
REFLECTANCE CALCULATIONS In airborne systems,
reflectance may be estimated using ground control
points of known reflectance Painted
Tarps Asphalt Concrete
9
The Atmosphere
REFLECTANCE CALCULATIONS Handheld Units are
slightly different
10
The Atmosphere
Image Based Algorithms Designed to calculate the
average reflectance in an image. The average
reflectance is assumed to approximate a flat
field in each band. Each pixel in the image is
divided by the average reflectance.
11
The Atmosphere
Image Based Algorithms Just like the vegetation
ratios, the ratio between pixel reflectance and
average scene reflectance will reduce atmospheric
effects. Caution Use only over large areas
with representative amounts of water, urban,
vegetation.
12
Off- Nadir
  • Nadir is the center most point directly beneath
    the sensor.
  • Because a camera lens has a fish-eye effect,
    the farther from nadir you go the pixels become
    distorted.
  • Off-Nadir affects are particularly important
    with airborne images.

13
Pixels at Nadir (pt.1) 1 m2 Pt. 2 1.02
m2 Pt. 2 1.05 m2 Pt. 2 1.22 m2
1524 m
X1
X2
X3
1
2
3
4
14
Radiometric Corrections
  • Sometimes satellite systems are radiometrically
    calibrated.
  • This means each DV can be converted to an
    energy value.

15
Radiometric Corrections
  • These are NOT atmospherically corrected! The
    energy values calculate energy at the sensor
    only. They are not calibrated for atmospheric
    attenuation/contribution.

16
Georegistration
  • For many applications it will be important to
    locate the image on the surface of the earth.
  • Georegistration is simply assigned coordinates
    to an image.

17
Georegistration
Registered DOQQ
Unregistered RS Image
18
Georegistration
Registered DOQQ
Unregistered RS Image
19
Georegistration
The computer resamples the image. Coordinates
are assigned coordinates based on selected points
in each reference image. GIGO Applies!
Geo registered RS Image
20
Elevation Corrections
  • Ground elevation can cause distortions in an
    image.
  • Digital Elevation Models can be used to account
    for this distortion
  • The resulting image is referred to as a digital
    ortho quadrangle.

21
Elevation Corrections
  • Digital Elevation Models (DEM) can also be
    applied to imagery to show terrain elevation.

22
Elevation Corrections
23
Mixed Pixels
  • A mixed pixel is a pixel composed of more than
    one attribute.
  • It is highly dependent on spatial resolution.

24
Mixed Pixels
  • How do you handle mixed pixels?
  • Vegetation Indices
  • Ground Truth

25
Ground Truthing
  • How do we know whats on the ground?
  • How accurate are our interpretations of the RS
    data?
  • How are other site-specific factors affecting
    those interpretations?

26
Ground Truthing
  • Examples
  • Ground Control Points for the
    Georegistration Windshield Surveys
  • Yield
  • Soil Samples

27
Ground Truthing
  • This is a critical component in designing an RS
    acquisition. You must consider what kinds of
    data will be necessary beforehand.
  • Ground Truthing will be a function of
  • Total Coverage Area
  • Frequency
  • The Question Asked

28
Ground Truthing
  • Example
  • Fire ants are a nuisance and a pest. The GA EPD
    wants to know where fire ants are likely to be
    and target pest control efforts accordingly.
    They would like to use satellite imagery as a
    tool and have asked for your help. What kinds of
    ground truth would be useful?
  • Hint We cannot actually detect the mound
    itself.

29
Ground Truthing
  • Mounds will not always be evident, but are
    usually found in open areas such as lawns,
    pastures, along roadsides and unused cropland.
    Mounds are rarely found in frequently cultivated
    areas. This species could easily be confused with
    the common coastal brown ant and as well as
    some local native ants.

30
Ground Truthing
  • Using modelling and satellite imagery to assist
    fire ant eradication
  • The Queensland Government is now employing
    satellite imagery to find areas of land
    unsuitable for fire ants in a bid to eradicate
    fire ants in the State's south-east and protect
    the rest of Australia from this dangerous exotic
    pest.
  • The Fire Ant Control Centre has been working in
    collaboration with a postgraduate researcher from
    the University of Queensland, Robert George, to
    develop a model to predict preferred habitats and
    likely spread-patterns of fire ants. Using
    satellite imagery, this research has been able to
    identify the land types not suitable to fire ants
    in what is called the Fire Ant Habitat
    Identification System.
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