1 / 21

Remote Sensing and Internet Data Sources

Remote Sensing and Internet Data Sources. Unit 3: Module 12, Lecture 1 – Satellites and Aerial Photography. Sources of spatial and environmental data. Remotely sensed data (raster data) Airphoto Satellite Digital data repositories - (Module 14) On-line Electronic media

virgil
Download Presentation

Remote Sensing and Internet Data Sources

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Remote Sensing and Internet Data Sources Unit 3: Module 12, Lecture 1 – Satellites and Aerial Photography

  2. Sources of spatial and environmental data • Remotely sensed data (raster data) • Airphoto • Satellite • Digital data repositories - (Module 14) • On-line • Electronic media • GPS data (point data) - (Module 16) • Input of hard-copy data – (Module 16) • Digitizing (vector data) • Scanning (raster data)

  3. Sources of data: remote imagery • Satellite imagery • Digital imagery • Numerous satellites with different levels of resolution • SeaWIFS • SPOT • LANDSAT • AVHRR • MODIS MODIS image of Hurricane Isobel off US East Coast, September 17, 2003

  4. SeaWIFS image of California FiresOct 26, 2003 SeaWIFS • 1 km res • Daily • NASA

  5. QuickBird image of Grand Prix Fire, CAOctober 27, 2003 60 cm resolution natural color image

  6. QuickBird image of Grand Prix Fire, CAOctober 27, 2003 – detail view

  7. GOES Weather Satellite • Geostationary orbit 36,000 km above earth • East and West satellites provide complete coverage • High frequency (up to 15 min intervals) • Visible • Infrared • Water vapor

  8. Resolution in Satellite imagery • Satellite sensors vary in the different types of resolution • Spatial resolution = pixel size • Spectral resolution = # of bands, band width • Radiometric resolution = data intensity in band • Temporal resolution = frequency of sampling

  9. Pixel resolution • 1 km AVHRR classification of forest land • Relatively coarse • Broad picture of landscape • Regional assessment • 30 m LANDSAT classification of forest and land use • Much finer detail • Local assessment

  10. Spectral Resolution: Number of bands • “Bands” are regions of the electromagnetic spectrum sampled by the sensor • Visible light (RGB) • Near and far infrared • Other frequencies • More bands = more information to classify land features • Multispectral • Hyperspectral – very fine divisions of the spectrum

  11. Landsat Thematic Mapper bands

  12. Image classification • Remote sensing satellites and aircraft-borne sensors simply record information on spectral reflectance • The science of “Image Classification” makes these volumes of information useful • Goal – develop a relationship between the “spectral signature” and a classification of the landscape • Coarse: forest, ag, urban • Fine: aspen forest, corn, high-density residential

  13. Differences in “spectral signatures” are used to classify land features

  14. Common classified satellite images

  15. Sources of data: remote imagery Aerial photography and imagery • Film technology • Oblique • Vertical • Black and White • Color Infrared - common in agriculture and forestry applications • Usually interpreted as map polygons (vector format) B & W photo Photointerpreted Oblique photo Color IR

  16. Aerial photography and imagery Digital imagery Images from non-photographic sensors Usually classified by computer algorithms Multispectral or hyperspectral available Sources of data: remote imagery AISA hyperspectral sensor Hyperspectral crop circles courtesy CALMIT labs, NE

  17. Hyperspectral data • A large number of spectral bands (30-100s) • Capable of discriminating very fine differences in color (reflectance) • Used to map aquatic veg, Chlorophyll content, turbidity, many other attributes Hyperspectral image of Kingsbury Creek – image acquired by Nebraska Space Grant for WOW

  18. Common aerial photography: DOQs • USGS Digital Orthophoto Quad • Natl’ Aerial Photography Program (NAPP) • Cloud-free • 20000 ft altitude • B&W or CIR • Each photo 5.5 x 5.5 mi • Began in 1987 • 5-7 yr photography cycle • Big files! • Med resolution – 40 Mb • High res. – 117 Mb-1.3 Gb Color-infrared NAPP photo San Diego, CA

  19. Common aerial photography: FSA DOQs • Farm Services Administration (FSA) Color Orthophotos • 1 m resolution natural color imagery • Summer – leaf on • Available in quarter quads • Available as unclassified imagery, but very good resolution FSA photo – 1:7,000 scake Houston Co, MN

  20. Sources of data: scanned imagery • Scanning and rectification (raster data) • Hard copies of airphotos or other images can be scanned at high resolution (600-800 dpi) • These typically need to be georectified to use with other spatial layers (correct for camera lens abberations, plane tilt, etc) • Control points (known locations on ground) are used to georectify image • ImageWarp or other software used to “stretch” image to fit control points • Image can then be used as a backdrop for other spatial data layers, or for classification

  21. Summary • Classified data from satellites are useful for land use planning, but the efforts involved in classification mean these are updated relatively infrequently (years) • Real-time satellite data (AVHRR, SeaWIFS, GOES) are typically unclassified, but can be interpreted visually with relatively little effort • Aerial photographs provide high resolution coverage (meter to submeter), and many on-line sources of recent photography exist

More Related