Sources of Geographic InformationDigital ImagesSatellite Imagery - Sensing EMRSatellite Imagery - 4 ResolutionsSpatial ResolutionTemporal ResolutionElectromagnetic SpectrumSpectral ResolutionMultispectral Remote SensingRadiometric ResolutionImage Display - Single BandImage Display - Single BandImage Display - Single BandImage Display - Multi-BandImage Display - Multi-BandImage Display - StretchingImage Display - StretchingImage Display - StretchingImage Pre-ProcessingGeometric CorrectionGeometric CorrectionImage EnhancementsSpatial EnhancementsSpectral EnhancementsGenerating TVDI ValuesClassificationClassificationMODIS LULC In Climate DivisionsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005•Data properties: Spatial data, i.e. data that are associated with geographic locations•Data format: digital (analog data for traditional paper maps)•Data Inputs:•sampled from the real world•digitizing from paper maps•produced by government agencies, e.g. census bureau, USGS, USFS, state government, etc.•space or airborne remote sensing(NASA, NOAA, commercial, etc.)Approximately 80% of the duration of many large scale GIS projects is concerned with data input and managementSources of Geographic InformationDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005101030255301030301. The area is covered with a grid of cells2. Each cell has a digital numberindicating the amount of energy received from the cell (in a certain wavelength range)3. The cell is called a pixel (a picture element)4. The size of the pixel is the spatial resolution sensorDigital ImagesDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Satellite Imagery - Sensing EMR• Digital data obtained by sensors on satellite platformsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Satellite Imagery - 4 Resolutions• Satellite imagery can be described by four resolutions:– Spatial resolution: area on ground represented by each pixel, e.g.• Landsat Thematic Mapper - 30m• Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolutions Imaging Spectrometer (MODIS) - 1km• SPOT - 10m panchromatic /20m multispectral• IKONOS - 1m panchromatic /4m multispectral– Temporal resolution: how often a satellite obtains imagery of a particular area– Spectral resolution: specific wavelength intervals in the electromagnetic spectrum captured by each sensor (bands)– Radiometric Resolution: number of possible data values reportable by each sensor (how many bits)David Tenenbaum – GEOG 070 – UNC-CH Spring 2005AVHRR Image of the central and SE USA - 1 km pixelsSpatial ResolutionDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Landsat Image (543) of Greenville, NC - 30m pixelsSpatial ResolutionDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Spatial ResolutionSPOT Multispectral Image of Palm Springs, CA - 20m pixelsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005IKONOS panchromatic image of Sydney Olympic Park - 1mSpatial ResolutionDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Temporal Resolution• Number of days between overhead passes - satellite orbit– Landsat - 16 days– AVHRR & MODIS - daily– IKONOS - 1 to 3 daysDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Electromagnetic Spectrum•EMR at a wide range of wavelengths• Range typically from 10-12m to 103m• In remote sensing, we mainly focus on visible, infrared and microwave wavelengthsDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Spectral Resolution• Number, spacing and width of sampled wavelength bands (Landsat: 7 bands, AVIRIS: 224 bands!)• Multispectral vs. Panchromatic• Higher resolution results in more precision in the representation of spectral signaturesDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Spectral Bands of Landsat Thematic Mapper Sensorshttp://www.satelliteimpressions.com/landsat.html Multispectral Remote SensingDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Radiometric Resolution• Number of possible data values reported by the sensor, which determines how many levels of brightness it can distinguish• Range is expressed as 2npower– 8-bit radiometric resolution has 28values, or 256 values - range is 0-255 (e.g. Landsat TM data)– 16-bit resolution has 216 values, or 65,536 values- range is 0-65535 (e.g. MODIS data)• The value in each pixel is called the– Digital Number (DN)– Brightness Value (BV)David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Image Display - Single Band• Assume that the In and Out brightness values are equal• For a single band, the resultant color will be grayscale• All three colors display the same value, so the colors are shades of grayBVinBVoutBVinBVoutBVinBVoutBand 1 Band 1 Band 1David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Band 1 - BlueBand 3 - RedBand 2 - GreenBand 4 - NIRImage Display - Single BandDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Band 5 - IRBand 7 - FIRBand 6 - TIRImage Display - Single BandDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Image Display - Multi-Band• For a multi-band image, the resultant color will depend on which bands are assigned to which color gunsBVinBVoutBVinBVoutBVinBVoutRed (3) Green (2) Blue (1)BVinBVoutBVinBVoutBVinBVoutNear Infrared (4) Red (3) Green (2)True Color Composite(321)False Color Composite(432)David Tenenbaum – GEOG 070 – UNC-CH Spring 2005321 432543Image Display - Multi-BandDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005Image Display - Stretching• Contrast Enhancement - “stretching” all or part of the input BVs from the image data to the full 0-255 screen output range for better visual performance (i.e. we maximize the contrast so we can see the differences better)David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Image Display - Stretching•A linear stretch is one of the most common types of contrast enhancement• The minimum BV is remapped to 0• The maximum BV is remapped to 255• E.g. given a certain band histogram:0 2551270 25560 108 158David Tenenbaum – GEOG 070 – UNC-CH Spring 2005Image Display - Stretching• Two types of linear stretches:– The basic linear contrast stretch–A piecewise linear stretchBVinBVoutOutput2552550InputBVinBVoutStretched OutputEmphasizes middle “piece” of input range2552550InputLinear Contrast StretchPiecewise Linear StretchDavid Tenenbaum – GEOG 070 – UNC-CH Spring 2005David Tenenbaum – GEOG 070 – UNC-CH Spring 2005True-Color 321 ImageNo stretch appliedTrue-Color 321