review for introduction to remote sensing: science concepts and technology
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Review for Introduction to Remote Sensing: Science Concepts and Technology. Ann Johnson Associate Director [email protected]. “Empowering Colleges: Expanding the Geospatial Workforce”. - PowerPoint PPT PresentationTRANSCRIPT
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Review for Introduction to Remote Sensing:
Science Concepts and Technology
Ann JohnsonAssociate [email protected]
Funded by National Science Foundation Advanced Technological Education program [DUE #1304591. Author’s opinions are not necessarily shared by NSF
“Empowering Colleges: Expanding the Geospatial Workforce”
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What is Remote Sensing and how is it used? Passive and Active Remote Sensing Electromagnetic Spectrum and sensor wavelength and their “band numbers” Resolutions – Temporal, Spatial, Spectral and Radiometric Composite images: Pixels, Brightness and Digital Numbers Pixels and its Remote Sensing Signature graphic
Finding and using data – Landsat focused
Lidar – what is it and how can it be used Resources to learn more
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USGS DefinitionAcquiring information about a natural
feature or phenomenon, such as the Earth’s surface, without actually being in contact with it.
Sensor can be ground based, aerial or satellite.
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Not just a pretty picture! How it can be used!
• Land Use Change• Climate• Disasters
▫ Floods, fires, volcanoes, earthquakes• Forestry• Agriculture• Many more!
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Factors to consider when you use remote sensing data to understand or solve a geospatial problem• Scale – or Resolution
▫ Where is the study location?▫ How large is the study are?▫ What is the “size” of features under study?▫ Is this a one time event or over multiple times
over days, months or years?• Access to needed resources:
▫ Data and its cost?▫ Hardware and software and skills to use them
• Why is study important? Important for “real-world use by industry or government - ROI
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•Use “sensors” to detect and acquire the “information” about features
The human eye as a sensor and brain
as processor!
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Two Types of Remote Sensing Sensors•Active – Energy source is “provided”
▫Lidar – Light Detection and Ranging using pulsed laser beam from one wavelength)
▫SAR – Synthetic Aperture Radar – pulses of radio wavelengths
•Passive – Sun as the “energy source”▫Landsat▫MODIS▫Aster
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Two Types of Remote Sensing Sensors•Active – Energy source is “provided”
▫Lidar – Light Detection and Ranging using pulsed laser beam (of varying wavelengths)
▫SAR – Synthetic Aperture Radar – pulses of radio wavelengths
•Passive – Sun as the “energy source”▫Landsat▫MODIS▫Aster
What about our eyes – Active or Passive?
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Graphic From: Natural Resources Canada Fundamentals of Remote Sensing Tutorial
Need:• energy source,• sensor(s),• target, • collection method, • processing method and • a distribution method
http://www.nrcan.gc.ca/earth-sciences/geomatics/satellite-imagery-air-photos/satellite-imagery-products/educational-resources/9309
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Electromagnetic Spectrum
•NASA Movie http://missionscience.nasa.gov/ems/index.html
•Can download a NASA book on the Tour of the Electromagnetic Spectrum
http://missionscience.nasa.gov/ems/TourOfEMS_Booklet_Web.pdf
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crestcrestOne Wavelength
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“Resolution”•Spectral –wavelengths of spectrum collected by sensors•Spatial – size of area on the ground
covered by one pixel (grid size) which can affect size of image footprint
•Temporal – how often data (image) isacquired for a location
•Radiometric – the sensitivity of sensor to collect very slight differences in emitted or reflected energy
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Landsat SensorsCollect data inspecific Wavelengthsor “Bands”of ElectromagneticSpectrum
• Band 1: 0.45 - 0.52 m (Blue)• Band 2: 0.52 - 0.60 m (Green)• Band 3: 0.63 - 0.69 m (Red)• Band 4: 0.76 - 0.90 m (Near infrared)• Band 5: 1.55 - 1.75 m (Mid-Infrared)• Band 6: 10.4 - 12.5 m (Thermal infrared)• Band 7: 2.08 - 2.35 m (Mid-infrared)
123
6 7 5 4
Our Eyes
Landsat 7
Spectral Resolutions
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Spectral Resolutions• SAR; radar• Lidar; 600-1000 nm (some visible and some
infrared)• Multispectral: 450-2300 nm (some visible and
some infrared) LidarMultispectral
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Spatial Resolution Comparison – Scale
• High spatial resolution:▫ Meter to sub meter pixels▫ Small objects can be identified▫ Small area for each image footprint
• Moderate spatial resolution▫ Generally 30 meter pixels (Landsat)▫ Object identification generally greater than 30
meters▫ Moderate area image footprint
• Low spatial resolution▫ 1 KM or larger pixels (MODIS)▫ Objects smaller than 1 KM not observable▫ Very large footprint
http://biodiversityinformatics.amnh.org/tool.php?content_id=144
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Look at Examples of Different types of Imagery and compare their “footprints” – logon to link below:
http://biodiversityinformatics.amnh.org/tool.php?content_id=144
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Temporal Resolution•How often data is collected of the
same location▫Only once▫Daily – or multiple times a day▫“Frequently” – every so many days
•Landsat missions▫Once every 16 days – but . . . .
Must be clear (or have a percent cloud coverage)
Must be “important” (U.S. and outside U.S.)
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Landsat Image – Orbits (Path and Rows)
View Orbits video
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Why focus on Landsat Data?
•Cost •Access•Archive •Tools and other
resources
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Atmosphere “blocks” some wavelengths: sensors collect wavelength data in specific regions (bands or channels) of the spectrum
Lidar
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Gray shading: Wavelength Regions with good transmission
Lidar
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What Does “data” look like? Landsat 7 Spectral Bands and “gray scale” values of each band data set
Landsat 7 - Band data comes in as rasters with grayscale values 0 to 255Landsat 8 – more than 4,000 scaled to 55,000 gray values
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Radiometric Resolution Ability of a Sensor to
discriminate very small differences in reflected or emitted energy
Pixel Brightness – White to Black in shades of Gray for one band
Digital Number: the numeric values of its Brightness
Landsat 5 and 7 are 8 bit for 256 gray levels (0 to 255)
Landsat 8 is 12 Bit for 4,096 gray levels (scaled to 55,000)
A B
C
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Creating Visualizations: CompositesBrightness values (DN) from three Bands are combined and colored on a computer monitor by designating which of the 3 bands will be coded as Red, Blue or Green
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Landsat 7Natural or True ColorBands 3, 2, 1
False ColorBand 5, 4, 3
Pseudo Color Bands 7, 5, 3
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Selecting three different bands as Red, Green or Blue creates different images of the same location
Note: Band numbers for Landsat 5 and 7 are different than for Landsat 8
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Resource for Viewing Natural and False Color Composites on USGS Website•http://landsat.usgs.gov/
LDCM_Image_Examples.php
•Go to this site and use the swipe to see the difference using different bands for images from four regions of the U.S.
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Change Matters Website•See
http://www.esri.com/software/landsat-imagery/viewer
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Identifying and Classifying Features •Visual investigate using composites•Using “band algebra” with data from
bands ▫Normalized Difference Vegetation Index
(NDVI) uses Near Infra Red and Red bands
•Classification using spectral data from multiple bands for one pixel creating a “spectral signature”
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Spectral Signatures From Different Surfaces in an Image
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NDVI Leaf
NDVI –Image Analysis and “Greeness” Using NIR and Red Bands
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Land Cover Change – and “Greeness” - NDVI
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Classification Using Software
•Unsupervised Classification▫User tells Software how many “classes” to
group the image data into and software “gathers like values” into “classes” with similar spectral values
▫User then labels the classes into land use types and may combine classes
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Unsupervised Classification
Natural Color Composite of San Fernando Valley, CA
Data clustered by software and colored to match Land Use types (i.e. blue = water, green = vegetation, etc.)
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•Supervised Classification
▫User identifies pixels that are different types of feature (soil, urban, vegetation, etc) and creates a file with spectral information that can be used by software.
▫Software uses spectral value file of the different features and classifies pixels based on the specified land cover types.
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So many satellites! Resources:•Satellite Viewer•http://science.nasa.gov/iSat/?
group=visual&satellite=14484
•EarthNow! Landsat Image Viewer▫Real time view as data is collected
showing current path of satellite▫http://earthnow.usgs.gov/
earthnow_app.html?sessionId=fdbe7bc05944802eda2c68d1e603ed8462919
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Finding Data:https://lpdaac.usgs.gov/data_access
https://lpdaac.usgs.gov/data_access/glovishttp://earthexplorer.usgs.gov/ http://glovis.usgs.gov/
Go to GloVIS and Try Path 41 and Row 36
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Lidar – Active Remote Sensing NOAA Lidar Tutorial: http://www.csc.noaa.gov/digitalcoast/_/pdf/lidar101.pdf
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Thank You!Much of the material for this Presentation was
developed by iGETT-Remote Sensing grant from the National Science Foundation (DUE 1205069)
More Exercises:iGETT.delmar.edu
Concept Modules on YouTube Channel atiGETT Remote Sensing Education
Ann [email protected]@kctcs.edu