Ge111A Remote Sensing and GIS Imagery (optical and radar) Topography. Geographical Information...

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Transcript of Ge111A Remote Sensing and GIS Imagery (optical and radar) Topography. Geographical Information...

  • Ge111A Remote Sensing and GIS Lecture

    Remote Sensing - many different geophysical data sets. We concentrate on the following:

    Imagery (optical and radar) Topography

    Geographical Information Systems (GIS) – a way to organize the imagery as well as point, line, and shapefile data; useful for cataloguing and searching regional data bases

    Note: •Positions and ΔPositions (GPS @ end of quarter) •For more info on RS, there is a class:

    Introduction to the Physics of Remote Sensing (EE/Ge 157 abc)

  • Why use GIS in a field geophysics class?

    Understand what is in the field as best you can before you go there: • Terrain & topography • Geology • Roads • Access • Geomorphic features (faults, mountain ranges, etc)

    Add your own data and locations to the map (locations of survey points and/or lines)

    Easily produce base maps showing locations of our surveys

  • Equations relating wavelength, frequency, and speed:

    λ=c/f f=c/λ

    If the wave travels at the speed of light, c

    c=0.3 m/ns = 3x108 m/s.

    A wave with a frequency of 1015 Hz has a wavelength, λ, of 3 x 10-7 m, which is 300 nm or 0.3 μm – in the ultraviolet part of the spectrum.

    Thought questions:

    1) What happens to the wave if it travels in a medium with speed less than the speed of light?

    2) Can you find the mistake in the graph on this page?

  • Measurements conducted from: •Satellites •Aircraft •Handheld sensors

    Character of imagery is based on the reflectance and backscatter characteristics of the surface, f(λ)

    Different materials have different spectral behavior (rocks of different kinds, water, vegetation…)

    Both material type + physical state of material (grain size, weathering) are important

  • Ways you could correct for atmospheric absorption

    •Make atmospheric observations simultaneous with the remote sensing (hard to get usually) • Use an atmospheric model of absorption based on other dates or locations •Make surface spectrometer measurements for calibration, during the survey or during similar season and time as original survey •Don’t use bands in the spectral area of max. absorption

  • Spectra of common rocks/minerals

    Atmospheric absorption

    Spectra of common vegetation +

  • From Hunt (1977) spectral locations of absorption signals for different minerals and rocks

    Sensitive to: energy states of electrons in outer shells of transition metals (visible wavelengths)

    Twisting, rotation, vibrations of bonds in compounds (3-14 micron region)

  • Critical questions to ask when using imagery

    1. Spatial resolution (pixel size) 2. Image extent (General rule: target is always on the boundary) 3. Wavelengths 4. $$$$ 5. Date & Time of image acquisition

    Common systems

    Platform Pixel (m) Extent (km) Cost ($) Aster 15/30 60 Free (to some) or $80/scene Landsat 4,5,7 15/30 180 $400+* SPOT** 5/10 60 O(1000) Ikonos*** 1/4 10 O(1000) Planes/Helicopter O(10cm) 10**** ----

    + Quickbird…

    * A variety of cheaper combos exist ** French *** Military **** Camera + height above ground

  • Landsat: Only 7 spectral bands, not very useful for discerning material types

    But because of large image spatial extent and reasonable resolution, good for overview

  • Instrument VNIR SWIR TIR Bands 1-3 4-9 10-14 Spatial resolution 15m 30m 90m Swath width 60km 60km 60km Cross track pointing ±318km(±

    24°) ±116km(±

    8.6°) ±116km(±

    8.6°)) Quantization (bits) 8 8 12

    Note: Band 3 has nadir and backward telescopes for stereo pairs from a single orbit.

    ASTER (14 bands)

  • Example: Aster band combination

    Saline Valley

    Assign different λ bands or combination of bands to RGB to form color image

    Thermal infrared bands 13, 12 and 10 as RGB

    Variations in:

    quartz content appear as more or less red;

    carbonate rocks are green

    mafic volcanic rocks are purple

  • Hyperspectral Imagery

    Multiple bands (images) each at different wavelengths

    e.g. AVIRIS - 224 bands

    Large data volumes!

  • What is the advantage of hyperspectral images?

    Much narrower wavelength bands – easier to see smaller features in the absorption spectrum.

  • At radar wavelengths, the atmosphere is transparent

    Frequencies and Wavelength of the IEEE Radar Band designation

    Band Frequency (GHz) Wavelength (cm) L 1-2 30-15 S 2-4 15-7.5 C 4-8 7.5-3.75 X 8-12 3.75-2.50 Ku 12-18 2.5-1.67 K 18-27 1.67-1.11 Ka 27-40 1.11-0.075

  • SAR/InSAR Platforms

    Both from: JPLFrom: H. Zebker

    Satellites: Repeat pass Fly over once, repeat days-years later •Images •Measures deformation and topography

    Space shuttle: Shuttle Radar Topography Mission (SRTM)

    Aircraft: Shown here: AIRSAR Measures topography, ocean currents

  • Radar is active imaging

    Natural image coordinates are in units of time: along track & line-of-sight (LOS) range

    foreshortening

    layover

    shadows

    Imaging radar is side looking (why?)

    Achieve resolution by clever combination of consecutive radar images: Synthetic Aperture Radar (SAR)

  • Methods

    •Land surveys (now GPS or total station) •Radar altimeter •Air or space borne laser - point or swath mapping altimeter •Stereo imagery (air photos, also now satellite) •Radar interferometry a.k.a. InSAR (plane, shuttle, satellite) •Optical interferometry a.k.a. LIDAR

    Practical availability

    •U.S.: 10-30 m/px (USGS, SRTM) on the net 0.5-15 m (Airborne InSAR, optical, laser swath) - e.g., TOPSAR

    •Foreign: 90 m/px (SRTM 60S-60N), 30-60 m/px by begging (classified) 900 m/px open access

    •Make your own (InSAR, optical) 10-20 m/px

    Topography (DEM, DTM, DTED, topo, height,…)

  • ALOS satellite (Japan) image of changes in land height due to July 2007 Niigata-Ken Chuetsu offshore earthquake

    L band radar (PALSAR) can see through vegetation

    Other sensors: PRISM, AVNIR- 2

  • Practical Concerns with Imagery and DEMs 1. Continuity of adjacent images 2. Reference mapping information

    • Origin • Georeferencing – how many tie points are needed? • Datum (WGS84, NAD27, NAD83) • Projections…

    UTM - eastings and northings (m) Geographic - longitude and latitude (deg)

    3. File format • # px in x and y coordinates • How to store multiple bands (BIL, BIP) • Precision (bytes/band/pixel) - always in binary

    4. Software (raster + vector) • ESRI - ArcGIS • ERDAS - Imagine • Matlab/IDL (ENVI software) • GIS permits easy use of data bases and geographical logic

    5. Imaging combinations • Shaded relief (intensity) + color (something else) • Use Google Earth for simple tasks

  • The next few images are from Jane Dmochowski’s PhD thesis (Caltech Seismo Lab, 2005)

    Isla San Luis is an active volcanic island in the Gulf of California (Mexico)

    The imagery is Modis-Aster Simulator (MASTER) airborne data, with about a 4 m pixel size. It was collected with a very low- flying small airplane.

    The MASTER sensor has 50 spectral bands from visible to thermal infrared (TIR).

  • LIDAR images of San Andreas fault – from P4 project (high resolution topography) – can see through the trees

    LIDAR – “light detection and ranging” works at optical frequencies

  • Cajon Pass I-15 Fault Crossing

  • Another example of LIDAR data for topography along the San Andreas fault

  • Current or recently acquired LIDAR projects in or near California

    See www.geongrid.org for the complete list of available data sets: •Northern California faults •Southern California Faults (just started data acquisition on March 31, 2008 so not available to us yet) •Mt Ranier •Eastern California Shear Zone (Mojave Desert) •P4 (Southern San Andreas Fault) •Northern San Andreas Fault

    http://www.geongrid.org/

  • Ge111a GIS project

    • Topographic map (USGS) • SPOT image • ASTER bands 1-3 • Landsat-Thematic Mapper bands 1-3 • 2 DEMs made from different data sets • Geographic features (roads, drainages) • Partial coverage geological map

  • Homework – due Thurs April 24th, 2008

    1. Construct a basemap(s) of the greater Queen Valley region. Annotate your map with any geologically interesting features (faults, major alluvial fans, place names etc.) and include scale bars and geographic reference (ticks or something) as well as legends for any colors or symbols that you use.

    Print out your map to turn in, but save the file so you can use it later on in the class. Remember, you are going to need a base map for your Ge111B final report, so the more you do on this now, the less you will have to do later on!

    2. Make a perspective image of the Coyote Springs fault using Google Earth or similar product (based on aerial photographs and an unknown DEM). Turn this in with your HW.

    3. Write a paragraph comparing the strengths and weaknesses of the different data types you have available in the GIS project (DEM, shaded relie