Ge111A Remote Sensing and GIS Imagery (optical and radar) Topography. Geographical Information...
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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:
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.
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
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
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**** ----
* 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(±
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
Assign different λ bands or combination of bands to RGB to form color image
Thermal infrared bands 13, 12 and 10 as RGB
quartz content appear as more or less red;
carbonate rocks are green
mafic volcanic rocks are purple
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
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
Imaging radar is side looking (why?)
Achieve resolution by clever combination of consecutive radar images: Synthetic Aperture Radar (SAR)
•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
•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
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