Remote Sensing

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Remote Sensing

• Remote Sensing is the science and art of
  obtaining information about an object, area or
  phenomenon through the analysis of data acquired
  by a device that is not in contact with object,
  area or phenomenon.
• - T.M.Lillesand R.W. Kiefer, 1999

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Process of Remote Sensing

• Energy source
• Atmosphere
• Earth Features
• Sensors
• Data Processing
• Analysis and Applications

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Energy sources and Radiation Principles

• Electromagnetic Theory Wave Model
• Electromagnetic Energy
• E hv
• Where v the electromagnetic wave's frequenc
• h Planck's constant 6.625x10-34 Joule-Seconds

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Planck Radiation Law

• The primary law governing blackbody radiation is
  the Planck Radiation Law, which governs the
  intensity of radiation emitted by unit surface
  area into a fixed direction (solid angle) from
  the blackbody as a function of wavelength for a
  fixed temperature. The Planck Law can be
  expressed through the following equation.
• The behavior is illustrated in the figure shown
  above. The Planck Law gives a distribution that
  peaks at a certain wavelength, the peak shifts to
  shorter wavelengths for higher temperatures, and
  the area under the curve grows rapidly with
  increasing temperature.

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The Wien and Stefan-Boltzmann Laws

• The behavior of blackbody radiation is described
  by the Planck Law, but we can derive from the
  Planck Law two other radiation laws that are very
  useful. The Wien Displacement Law, and the
  Stefan-Boltzmann Law are illustrated in the
  following equations.
• The Wien Law gives the wavelength of the peak of
  the radiation distribution, while the
  Stefan-Boltzmann Law gives the total energy being
  emitted at all wavelengths by the blackbody
  (which is the area under the Planck Law curve).
  Thus, the Wien Law explains the shift of the peak
  to shorter wavelengths as the temperature
  increases, while the Stefan-Boltzmann Law
  explains the growth in the height of the curve as
  the temperature increases. Notice that this
  growth is very abrupt, since it varies as the
  fourth power of the temperature.

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Electromagnetic Spectrum
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Energy Interactions in the Atmosphere

• Radiation used for Remote Sensing reaches earths
  surface after going through the atmosphere of the
  earth. Gases and particles in the atmosphere
  affect the radiation.
• These effects are caused by Atmospheric
  Scattering and Absorption.

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Scattering

• Scattering of Electromagnetic Radiation
• Scattering of electromagnetic radiation is
  caused by the interaction of radiation with
  matter resulting in the reradiation of part of
  the energy to other directions not along the path
  of the incidint radiation. Scattering effectively
  removes energy from the incident beam. Unlike
  absorption, this energy is not lost, but is
  redistributed to other directions. Both the
  gaseous and aerosol components of the atmosphere
  cause scattering in the atmosphere.
• Scattering by gaseous molecules
• The law of scattering by air molecules was
  discovered by Rayleigh in 1871, and hence this
  scattering is named Rayleigh Scattering. Rayleigh
  scattering occurs when the size of the particle
  responsible for the scattering event is much
  smaller than the wavelength of the radiation. The
  scattered light intensity is inversely
  proportional to the fourth power of the
  wavelength. Hence, blue light is scattered more
  than red light. This phenomenon explains why the
  sky is blue and why the setting sun is red. The
  scattered light intensity in Rayleigh scattering
  for unpolarized light is proportional to (1
  cos2 s) where s is the scattering angle, i.e. the
  angle between the directions of the incident and
  scattered rays.
• Scattering by Aerosols
• Scattering by aerosol particles depends on the
  shapes, sizes and the materials of the particles.
  If the size of the particle is similar to or
  larger than the radiation wavelength, the
  scattering is named Mie Scattering. The
  scattering intensity and its angular distribution
  may be calculated numerically for a spherical
  particle. However, for irregular particles, the
  calculation can become very complicated. In
  general, the scattered radiation in Mie
  scattering is mainly confined within a small
  angle about the forward direction. The radiation
  is said to be very strongly forward scattered.

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Atmospheric Absorption

• Absorption by Gaseous Molecules
• The energy of a gaseous molecule can exist in
  various forms
• Translational Energy Energy due to translational
  motion of the centre of mass of the molecule. The
  average translational kinetic energy of a
  molecule is equal to kT/2 where k is the
  Boltzmann's constant and T is the absolute
  temperature of the gas.
• Rotational Energy Energy due to rotation of the
  molecule about an axis through its centre of
  mass.
• Vibrational Energy Energy due to vibration of
  the component atoms of a molecule about their
  equilibrium positions. This vibration is
  associated with stretching of chemical bonds
  between the atoms.
• Electronic Energy Energy due to the energy
  states of the electrons of the molecule.
• The last three forms are quantized, i.e. the
  energy can change only in discrete amount, known
  as the transitional energy. A photon of
  electromagnetic radiation can be absorbed by a
  molecule when its frequency matches one of the
  available transitional energies.
• Ultraviolet Absorption
• Absorption of ultraviolet (UV) in the atmosphere
  is chiefly due to electronic transitions of the
  atomic and molecular oxygen and nitrogen. Due to
  the ultraviolet absorption, some of the oxygen
  and nitrogen molecules in the upper atmosphere
  undergo photochemical dissociation to become
  atomic oxygen and nitrogen. These atoms play an
  important role in the absorption of solar
  ultraviolet radiation in the thermosphere. The
  photochemical dissociation of oxygen is also
  responsible for the formation of the ozone layer
  in the stratosphere.

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Atmospheric Absorption Cntd.

• Ozone Layers
• Ozone in the stratosphere absorbs about 99 of
  the harmful solar UV radiation shorter than 320
  nm. It is formed in three-body collisions of
  atomic oxygen (O) with molecular oxygen (O2) in
  the presence of a third atom or molecule. The
  ozone molecules also undergo photochemical
  dissociation to atomic O and molecular O2. When
  the formation and dissociation processes are in
  equilibrium, ozone exists at a constant
  concentration level. However, existence of
  certain atoms (such as atomic chlorine) will
  catalyse the dissociation of O3 back to O2 and
  the ozone concentration will decrease. It has
  been observed by measurement from space platforms
  that the ozone layers are depleting over time,
  causing a small increase in solar ultraviolet
  radiation reaching the earth. In recent years,
  increasing use of the flurocarbon compounds in
  aerosol sprays and refrigerant results in the
  release of atomic chlorine into the upper
  atmosphere due to photochemical dissociation of
  the fluorocarbon compounds, contributing to the
  depletion of the ozone layers.
• Visible Region
• There is little absorption of the
  electromagnetic radiation in the visible part of
  the spectrum.
• Infrared Absorption
• The absorption in the infrared (IR) region is
  mainly due to rotational and vibrational
  transitions of the molecules. The main
  atmospheric constituents responsible for infrared
  absorption are water vapour (H2O) and carbon
  dioxide (CO2) molecules. The water and carbon
  dioxide molecules have absorption bands centred
  at the wavelengths from near to long wave
  infrared (0.7 to 15 µm). In the far infrared
  region, most of the radiation is absorbed by the
  atmosphere.
• Microwave Region The atmosphere is practically
  transparent to the microwave radiation.

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Spectral Reflectance

• What is Spectral Reflectance?

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Active and Passive Remote Sensing

• Based on the energy source Remote Sensing is
  classified in to two major classes.
• Passive Remote Sensing
• Remote sensing systems which measure energy
  that is naturally available are called passive
  sensors. Passive sensors can only be used to
  detect energy when the naturally occurring energy
  is available. For all reflected energy, this can
  only take place during the time when the sun is
  illuminating the Earth. There is no reflected
  energy available from the sun at night. Energy
  that is naturally emitted (such as thermal
  infrared) can be detected day or night, as long
  as the amount of energy is large enough to be
  recorded.
• Active Remote Sensing
• Active Remote Sensing provides its own energy
  source for illumination. The sensor emits
  radiation which is directed toward the target to
  be investigated. The radiation reflected from
  that target is detected and measured by the
  sensor. Advantages for active sensors include the
  ability to obtain measurements anytime,
  regardless of the time of day or season. Active
  sensors can be used for examining wavelengths
  that are not sufficiently provided by the sun,
  such as microwaves, or to better control the way
  a target is illuminated. However, active systems
  require the generation of a fairly large amount
  of energy to adequately illuminate targets.

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Satellites
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Multi Spectral Data Collection- Pushbroom
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Multi Spectral Data Collection- Whiskbroom
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Satellites and Sensor Types

• Multi-Spectral Imaging using discrete detectors
  and scanning mirrors
• Landsat MSS, TM, ETM, GOES, AVHRR, SeaWIFS
  ATLAS
• Multi-Spectral Imaging using linear arrays
  (Pushbroom)
• SPOT1-4, IRS, Ikonos, Quick Bird, ASTER
• Image Spectrometry using Linear arrays
  (Whiskbroom)
• AVRIS,MODIS

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Process of Satellite Remote Sensing
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Satellite Data Format
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Landsat 7
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Landsat

• Landsat has a revisit period of 16 days.
• Due to cloud cover and other variables, Landsat
  does not record images continuously.
• The actual number of images recorded is a small
  percentage of the theoretical value.
• In addition, for this study, the satellites
  overpass date must have corresponded to a
  particular water level.
• These combined constraints resulted in a
  relatively small number of potentially useful
  images. These constraints apply to all of the
  remote sensing satellites employed in this study.
• Landsat scene cover 185 km X 185 km and cost
  6000.00 ( 0.57/km2).
• The Landsat image used for this project was taken
  on October 23, 1999.
• The average water level at the United States
  Geological Station (USGS) gauging station located
  in Lake Kissimmee was 51.98 above mean sea level
  (AMSL) on this date.

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Landsat TM Image June 29 1998
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Landsat Image
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SPOT

• The SPOT satellite has a scanner with images that
  cover a 60 km x 60 km area per scene.
• Two cameras are onboard SPOT
• one has a 20m x 20m ground resolution cell size
  and records data in 3 spectral bands while
• the other has one panchromatic band with a ground
  cell size of 10m x 10m.
• The SPOT scenes acquired for this project were
  taken on March 2, 1993 for both the 3-band color
  and the 1-band panchromatic.
• The average water level at the USGS gauging
  station located in Lake Kissimmee was 50.74 AMSL
  on this date.
• The cost of an uncertified 60 km x 60 km SPOT
  scene was 1,500.00 per Level 1A processing.
  Therefore imagery cost for this project is
  2.40/km2

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SPOT Image
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SPOT Image
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IKONOS

•  The IKONOS, which was launched in the year 2000,
  is one of the latest commercial earth-looking
  remote sensing satellites. IKONOS has two
  cameras one has a 3-band, four meter ground cell
  size while the other has one-band, one-meter
  ground cell size resolution.
•  The price of uncertified IKONOS imagery taken
  over the United States is 18.00/km2 for
  onemeter resolution panchromatic and 20/km2 for
  four meter, 3 band color imagery.

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IKONOS Image
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QuickBird


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Quickbird Image
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Great Pyramid of Giza Quickbird Image
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Is it a Aerial photograph?
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Hyperspectral Scanners Compact Airborne
Spectrographic Imager (CASI)  

• The hyperspectral instrument used in this study
  was taken by the Compact Airborne Spectrographic
  Imager (CASI) which is a charge couple device
  push-broom imaging spectrograph intended for the
  acquisition of visible and near infrared
  hyperspectral imagery.
• The CASI combines some of the better features of
  aerial photography and satellite imagery with the
  analytical potential of a spectrometer.
• The CASI sensor detects an array of narrow
  spectral bands in the visible and infrared
  wavelengths, using along-track scanning.
• The spectral range covered by the 288 channels
  is between 0.4 and 0.9 µm. Each band covers a
  wavelength range of 0.018 µm.
• Spatial resolution depends on the altitude of the
  aircraft, the spectral bands measured and the
  bandwidths used are all programmable.

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CASI Image
WHITE TARGETS USED TO AID GROUND DATA COLLECTION
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Radar

• The microwave atmospheric window is nearly 100
  clear
• Much longer wavelengths cm to m scale
• Primarily an active form of remote sensing
• Energy return is dominated by surface roughness
  and measured as a function of the travel time of
  the radar pulse
• Difference between Radar and other remote sensing
  are pulse generator, duplexer and antenna
  ,duplexer controls timing of pulse release and
  reception

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Advantages

• All time / all weather capability
• Information on surface roughness at the human
  scale
• Centimeters rather than microns
• Penetration of soil function of the dielectric
  constant
• Rule of thumb is that for dry soils, penetration
  depth (cm) 10
• For hyper-arid environments, radar can penetrate
  3-5 meters

Disadvantages

• Very costly
•   Imagery is complex and typically hard to
  interpret
•   Little to no information on composition of the
  surface materials

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RADAR Image
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Radar Bands

• Radar pulses are sent and received in discrete
  wavelength regions (designated with letters)
• Controlled by the federal government so as not to
  interfere with commercial broadcasting and
  emergency frequencies
• Most commonly used
• Ka-band 0.8 1.1 cm (1.0 cm)
• C-band 3.8 - 7.5 cm (5.3 cm) L-band 15.0 -
  30.0 cm (23.5 cm)
• X-band 2.4 3.8 cm (3.0 cm)
• S-band 12 cm
• P-band 30.0 - 100.0 cm (68 cm)

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Two Radar Modes

• 1. Passive same principles as emitted energy in
  the Thermal IR however, energy is a function of
  the surface dielectric constant as well as the
  temperature the dielectric constant is greater
  for metals and soils with higher moisture content
   
• 2. Active most common form of radar remote
  sensing. 90 of all data collected
• known as SLAR (side-looking airborne radar) SLAR
  can be either real aperture radar (RAR) or
  synthetic aperture radar (SAR). Active remote
  sensing controls the source as well as the data
  collection
• Energy is transmitted and received by an antenna
  looking off at an angle to
• the surface typically mounted to the side of a
  planes fuselage for airborne systems
• Side-looking geometry affects how the signal
  interacts with the surface
• also causes unique geometric distortions that
  must be corrected
• Nadir-viewing radar systems are known as radar
  altimeters used for mapping topography

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Terminology

•  
• 1. Ground range distance away from the nadir
  point (perpendicular to the flight direction)
• 2. Slant range distance along the beam path
• 3. Azimuth distance along the flight direction
• 4. Look angle angle from the vertical to the
  beam
• 5. Depression angle complement to the look angle
  
• 6. Swath width illuminated surface on the
  ground
• 7. Pulse duration time of the pulse

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Radar in Operation

• Beam pulse transmitted to surface illuminates a
  narrow strip of land
• Returned energy (backscatter) is received by the
  antenna and the timing logged
• Energy only returned if the surface is rough
  compared to the wavelength
• Corner reflector is an object on the surface
  with a certain geometry with respect to the
  incident energy whereby all the energy is
  returned to the antenna
• Near-range is received first (shorter travel
  time) then the far-range  
• All backscatter within any given zone of the
  swath width perpendicular to the azimuth
  direction is received at the same time. there is
  no way to resolve features within this strip
  (azimuth resolution)

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Radar Resolution

• The ability of the radar return to distinguish
  between two objects in the range direction only
  can happen if the received pulse from the object
  closest to the antenna ends before the returned
  pulse of the far-range object begins can be
  defined in terms of the pulse duration and the
  ground range distance
• Shorter pulse duration and smaller depression
  angles result in better range resolution  
• Common pulse duration 0.05 - 0.3 µseconds,
• Small depression angles produce large radar
  shadows
• Short pulse durations result in less return and
  more noise

R ct/2 cos 0  Where C speed of light T
pulse duration 0depression angle  
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Azimuth Resolution

• Distance parallel to the azimuth (flight)
  direction
• Azimuth resolution equals the swath width
• Best resolution achieved with commercial systems
  15-60m

Ra GR B Where GR ground range B antenna
beamwidth
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Synthetic Aperture Radar (SAR)

• way around the RAR limitation by using the
  motion of the plane (artificially enlarge the
  antenna length)
• Uses the principle of Doppler shift to track the
  motion of objects in the azimuth direction
  through successive pulses
• Objects in the near range are observed for
  shorter times than those in the far-range
• Synthesized beam is much narrower than the
  original swath width azimuth resolution can be
  decreased to 5-20m

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Radar Polarization

• SLAR systems can commonly transmit and receive in
  different polarization planes (horizontal and
  vertical)
• results in image designations such as
• C-band horizontal send, vertical receive
• P-band horizontal send, horizontal receive
• Interaction with surface features can depolarize
  the beam
• The physical process of depolarization is not
  always well understood
• Horizontal send and receive is the strongest
  most objects on the surface have a vertical
  orientation therefore they scatter back most of
  the energy
• Depending on the surface properties of the
  surface under study, vertical send/receive may
  be important

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Light Detection And Ranging (LiDAR)

• Light Detection And Ranging uses the same
  principle as RADAR. The LiDAR instrument
  transmits light out to a target. The transmitted
  light interacts with and is changed by the
  target. Some of this light is reflected scattered
  back to the instrument where it is analyzed. The
  change in the properties of the light enables
  some property of the target to be determined. The
  time for the light to travel out to the target
  and back to the LiDAR is used to determine the
  range to the target.

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LiDAR Cntd.

• There are three basic generic types of LiDAR
• Range finders - helps to measure the distance
  from the lidar instrument to a solid or hard
  target.
• Differential Absorption LiDAR - used to measure
  chemical concentrations (such as ozone, water
  vapor, pollutants) in the atmosphere. A DIAL
  lidar uses two different laser wavelengths which
  are selected so that one of the wavelengths is
  absorbed by the molecule of interest whilst the
  other wavelength is not. The difference in
  intensity of the two return signals can be used
  to deduce the concentration of the molecule being
  investigated.
• Doppler LiDAR - Doppler lidar is used to measure
  the velocity of a target. When the light
  transmitted from the lidar hits a target moving
  towards or away from the lidar, the wavelength of
  the light reflected/scattered off the target will
  be changed slightly. This is known as a Doppler
  shift - hence Doppler LiDAR.

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Raw LiDAR data
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LiDAR data on the Digital Surface Model
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After filtering out the non-ground points
LiDAR data of the bare earth is very useful for
generating contours and also useful to generate
the Orthophoto, which is one among the data
sources for GIS.
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LiDAR data
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Raw LiDAR data and Processed data
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Remote Sensing Applications

• Satellites Humans third-eye in the space.
• Applications
• Forest management
• Landuse management
• Mapping
• Agriculture
• Geology
• Coastal Management
• Etc.

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Remote Sensing Applications Cntd.

• Forest management
• To estimate the deforestation
• To identify the diseased forest area
• Biomass estimation
• Land Use Land Cover Change detection
• Landuse change
• Urban Expansion
• After disaster Assessment
• Agriculture
• Vegetation mapping
• Vegetation monitoring
• Yield estimation

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Remote Sensing Applications Cntd.

• Geology
• Mineral exploration and Structural Mapping
• Sedimentation mapping and monitoring
• Lithological mapping
• Mapping
• Topological mapping
• DEMs
• Thematic Mapping
• Coastal Management
• Oil spill detection
• Ocean management
• Fish and ocean-life assessment
• Etc.
• Glacier-melt assessment
• Flood damage assessment

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Potential for Remote Sensing to Locate the
Ordinary High Water Line A Case Study of Lakes
Kissimmee and Hatchineha
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Ordinary High Water Line What is it?

• A boundary line
• A point to which the water normally rises during
  the high water season
• It excludes floods and freshets
• It is an ambulatory line that shifts in response
  to long term gradual, natural changes in water
  levels or the shoreline

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Why use remote sensing to locate the OHWL?

• Efficiency
• It has been suggested that it works
• Theoretically, if it works, there would be only
  one variable, vegetation

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Reasons remote sensing may work to locate the
OHWL

• Davis (1973) found a relationship between the
  OHWL, and the location of upland and wetland
  vegetation
• Under normal hydrologic conditions, distinct
  vegetation shifts are expected on shorelines
• Remote sensors primarily detect vegetation on the
  ground
• Davis, J.H., Jr. 1973. Establishment of Mean
  High Water Lines in Florida Lakes. Publication
  No. 24. Florida Water Resources Research Center.
  Research Project Technical Completion Report.
  ORR Project Number A-015-FLA.

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Reasons remote sensing may work to locate the
OHWL (contd.)

• Remote sensing technology provides researchers
  with the ability to determine land use/land cover
  types on a broad scale
• The USGS Gap Analysis Project found Landsat
  images sufficient for mapping vegetation and
  habitat
• Landscape ecologists use satellite imagery to
  characterize vegetation, species distributions,
  and communities

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Study Hypotheses

• Vegetation can be used as an indicator of the
  OWHL
• Landsat, SPOT, IRS, and IKONOS will not be
  effective for locating the OHWL
• CASI will be useful for locating the OHWL

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Study Area
 
Figure 1-1. Study Area.
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Methods

• Obtain satellite images from Landsat, IRS, SPOT
  and IKONOS when water known to be at OHWL
• Obtain CASI airborne hyperspectral images
• Landsat image was geometrically rectified and the
  SPOT image was rectified to it
• IRS, IKONOS and CASI came pre-processed
  radiometrically and geometrically
• An unsupervised classification was performed

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Methods (contd.)

• Ground truth surveys were conducted by land use
  type that included
• Taking GPS point at the OHWL
• Collecting and recording vegetation 50m below the
  OHWL and up to 50m above the OHWL
• Vegetation information was charted and visual
  interpretation of the images was conducted
• Descriptive statistics were used to establish the
  accuracy of vegetation as an indicator of OHWL

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Figure 3-5 Idealized vegetation transect chart
and terminology used in vegetation analysis. In
this figure, Species 2 has a landward edge value
of 1 and a waterward edge value of 4. These
values indicate that on the landward side of
OHWL, Species 2 had a minimum distance of 1m from
OHWL, and on the waterward side, Species 2 had a
minimum distance of 4m from OHWL.
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A Usability Index was developed Usability Index
(Frequence of Occurrence)/ (Minimum Avg.
Distance)100 Range of possible values is from
0.1 to 1000. Higher values equate to better
indicators of the OHWL.
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Results

• Open water could be detected in all the images
• Water could not be identified in areas with dense
  emergent vegetation
• All images had observable changes in pixel
  classes, but no discernable change in class
  corresponded to the OHWL for Landsat, IRS or SPOT
  images.

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Figure 4-2 Classified Landsat image of Lake
Kissimmee and corresponding Transect 9.
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Figure 4-5 Classified SPOT image of Lake
Hatchineha and corresponding Transect 31.
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Results (contd.)

• The IKONOS image corresponding to Lake Kissimmee
  Transect 7 appeared to show a correlation between
  change in pixel class designation and the OHWL.
  Maximum accuracy of this edge is 4m.
• CASI images showed the best potential for
  locating the OHWL.

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Figure 4-9 Classified IKONOS image of Lake
Kissimmee and corresponding Transect 7.
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Figure 4-14 Classified CASI image of a portion
of Lake Kissimmee and corresponding Transect 9.
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Figure 4-11 Histogram of FACU, FAC, FACW or OBL
species classified in each CASI hyperspectral
class. The variation within each class
illustrates the inability of the imagery to
discriminate wetland designations within this
littoral zone.
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Results (contd.)

• Vegetation data for combined lakes finds that
  within the top 25 of the total species
  identified, only 2 species occur in both the most
  frequently occurring list and the list of species
  found closest to the OHWL (Cyperus lecontei and
  Sesbania herbacea)
• The highest usability index for combined lakes
  was 58.82

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Discussion/Conclusions

• Case law requires that the best methods
  available be used to locate the OHWL
• Landsat, IRS and SPOT were constrained in their
  usefulness due to a number of factors including
  their relatively low spatial resolution,
  therefore, none can be counted as the best
  method available for locating the OHWL
• IKONOS only indicated a high correlation between
  the OHWL and vegetation in 1 of 17 transects,
  therefore, it cannot be relied upon to locate the
  OHWL

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Discussion/Conclusions (contd.)

• CASI has potential
• Floridas flat topography and low bank lakes make
  it difficult to find evidence of the OHWL both on
  the ground and with remote sensing technology
• The fact that no good vegetation indicators of
  the OHWL may be the result of an extended drought
  and/or a consequence of the channelization of the
  Kissimmee River

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Figure 4-15 Transect 33, note watermarks on
cypress trees.
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Problems with this study

• There was insufficient CASI coverage
• Use of a quadrat vegetation collection method
  would have provided more information and may have
  allowed further investigation into different
  classification schemes

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Change DetectionObjectives

• Identifying the Fire affected region in the study
  area using Expert Image Classifier
• Calculating the area lost to fire in each
  classes.

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Study Area

• Our study area falls within Alachua county.It is
  located 15 miles NE of Gainesville.
• The area coverage is
• Long 82 18 21.5W
• Lat 29 42 11.3 N
• And
• Long 82 08 54.2W
• Lat 29 49 58.4 N

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Before Fire
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After Fire
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Study Area (Before Fire)
Urban area -no interest region
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Study Area(After Fire)
Urban areas
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Fire Affected Region and Classification
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Area Lost in Each Forest Type
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Area Lost in Each Forest Type

• Type Area lost(Ha)
• 8 yrs 1218.33
• 4-8 yrs 133.56
• 0-3 yrs 47.7
• Wetland forest 473.49
• Total area lost 1873.08

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Natural Resource Information SystemCase Study

• GAP project is a good example of a Remote Sensing
  GIS application
• What is Gap?
• Gap Analysis is a means for assessing to what
  extent native animal and plant species are being
  protected.
• Every state in the US is doing a GAP Analysis

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Raster data used in the Florida GAP project

• Landsat TM
• Aerial Digital Camera

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Analog Videography
South Florida Flight lines
Advantage Inexpensive Disadvantage Poor
resolution and image quality
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Birds
118
Brazilian Pepper vs Citrus
119
Example Imagery
120
Example Imagery Schinus
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Ground Truth
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Haze Reduction
125
FLUCCS classification code
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Classified Landsat Image
127
Land Cover Classification
128
Mammalian species Richness
129
Reptile and Amphibian Species Richness
130
Suitable Habitat for Hooded Warbler
131
FL Wildlife Habitat Models
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GAP Applications

• Business and non-governmental organization
• County and city planning
• State uses
• Federal agency applications