1. Theory of remote sensing and spectrum
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1 1. Theory of remote sensing and spectrum 7 August 2014 ONUMA Takumi
2 Outline of Presentation Electromagnetic wave and wavelength Sensor type Spectrum Spatial resolution Spectral resolution Mineral mapping theory
3 Related Web sites (1/2) Remote sensing : NASA tutorials Spectral International Inc. Canada Centre for Remote Sensing Natural Resources Canada
4 Related Web sites (2/2) Research remote sensing data and download data * Free download of Landsat data and ASTER G-DEM Landsat 8 : USGS website QGIS (Quantum GIS) website * Free Open Source GIS software
5 Electromagnetic wave Wavelength, Sensor type, Spectrum
6 Remote sensing Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object. Remote sensing is the technology to observe the Earth typically from satellite or aircraft and to detect and classify objects on the Earth. The sensors mounted on satellite or aircraft collect data of electromagnetic waves.
7 Electromagnetic waves When we listen to the radio, watch TV, or make a call, we are using electromagnetic waves. They differ from each other in wavelength. Wavelength is the distance between one wave crest to the next. wavelength amplitude crest (ridge) Light is also electromagnetic wave trough
8 Violet Blue Green Yellow Orange Red Wavelength VIS: VISible NIR: Near InfraRed SWIR: Short Wave InfraRed
9 Remote sensors There are two main sensors; passive and active. Passive sensors detect natural radiation that is emitted or reflected from Earth s surface, usually from the sun. Because of this, passive sensors can only be used to collect data during daytime. In contrast, active sensors emit energy in order to scan objects and areas. The sensors detect and measure the radiation that is reflected or backscattered from the target.
10 Two main sensors in remote sensing 1. Synthetic Aperture Radar (SAR) Active sensor Transmit microwaves and receive the backscatter of objects ex. PALSAR, ENVISAT ASER, RADARSAT 2. Optical sensor Passive sensor Obtain the reflection of objects from sun ex. Landsat, ASTER, SPOT, IKONOS Radar is used at airport, optical sensor is like digital camera.
11 Wavelength of optical and radar sensors cm X C S L P band Radar sensor Optical sensor
12 Synthetic Aperture Radar (SAR) Sensor 10km PALSAR data: spatial resolution 15m
13 2D / sectional SAR system Side looking scan area swath 3D
14 Backscatter of SAR smooth to rough surface amount of vegetation Side looking Transmission SAR image Reflection / Backscatter SAR image Reception SAR image
15 Backscatter of SAR Mountain Shadow (no data) SAR image SAR image Building Transmission Reflection Reception SAR image
16 Optical Sensor 10km Landsat 7 ETM+ data: spatial resolution 30m
17 System and theory of Optical Sensor Sunlight Optical Sensor Measuring Reflected spectrum Radiation Reflection Spectral absorption
18 Reflectance (%) Spectral pattern Generalized reflectance spectra of some earth surface materials Visible NIR SWIR Soil Altered rocks characteristic of a mineralized zone 10 0 Clear water Water with phytoplankton Healthy vegetation Wavelength in micrometers Clear water Water with phytoplankton Healthy vegetation Soil Altered rocks characteristic of a mineralized zone
19 Ground Reflectance (offset for clarity) Ground Emissivity (offset for clarity) Spectral patterns and bands location of several sensors ARGUS Hymap Aster Landsat TM hyperspectral multi band 90 dry vegetation 90 dry vegetation sandstone 64.5 sandstone 64.5 limestone green vegetation 39 limestone 39 dark soil dark soil green vegetation water TIR Thermal Infrared Electro-Magnetic Spectrum - Wavelength in Micrometer
20 Wavelength of satellite bands Visible-ray Infrared-ray wavelength short wave - infra red thermal infra red panchromatic
21 Band location of ASTER and LANDSAT Window of atmosphere Multiband sensor
22 Location of ASTER bands and mineral absorption ASTER band number and location
23 Spatial Resolution and Spectral Resolution
24 Spatial Resolution High spatial resolution : m» QuickBird» IKONOS/GeoEye» ALOS» SPOT-5» HyMap / 3-5m Medium spatial resolution : 5-30 m Actual size on the ground per pixel» ASTER / 15m (Band1-3), 30m (Band 4-9)» Landsat 7&8 / 30m (Band1-7), 15m (Band8)» Hyperion / 30m» AVIRIS / 20m HyMap and AVIRIS are hyperspectral airborne sensor
25
26 Landsat 7 RGB=B4,B3,B2 30m ASTER RGB=B3,B2,B1 15m HyMap RGB=B25,B16,B9 3.3m Vegetation is shown in red color.
27 HyMap(3.3m) Google Earth (1m?)
28 Spectral Resolution
29 Spectral resolution High spectral resolution: <= 230 bands» AVIRIS» HyMap Hyperspectral sensor» Hyperion Medium spectral resolution: 5-15 bands» ASTER / 14 bands» Landsat 8 / 11 bands Low spectral resolution: <= 4 bands» QuickBird» IKONOS/GeoEye» ALOS» SPOT-5 HyMap and AVIRIS are hyperspectral airborne sensor
30 HyMap airborne hyperspectral data
31 Comparison of spectral patterns Spectrometer AVIRIS HyMap ASTER Landsat 7& Wavelength (micrometer) => Wavelength (micrometer)
32 High spatial resolution is effective for geological identification. High spectral resolution is effective for mineralogical identification. High resolution brings high accuracy. It is necessary to select the kind of data according to the objectives and the cost.
33 Comparison of typical data Name Band # Pixel size (m) Data cost Airborne AVIRIS Free (restricted) Spaceborne HyMap V. High Hyperion Moderate ASTER 14 15/30/90 Low Landsat /30 Free SPOT /10/20 High IKONOS 4 0.5/1 High QuickBird 4 0.6/2.5 High
34 Optical sensor data with relation between spatial and spectral resolution High spatial data Low spatial data High spectral data HyMap AVIRIS Hyperion HISUI (plan) ASTER Landsat 7&8 Low spectral data SPOT-5 IKONOS QuickBird Landsat 3 HyMap and AVIRIS are hyperspectral airborne sensor
35 Problems 1. Higher resolution needs more data volume. 2. High resolution sensor has difficulties in mechanism. Spaceborne data has more noise than airborne data. Hyperspectral sensor uses many sensors. Generally, high spatial resolution spaceborne sensors have 4 to 5 bands and hyperspectral sensors have narrow swath.
36 Coverage area of one scene : LANDSAT / ASTER / HyMap spaceborne airborne Landsat : 185km x 185km ASTER : 60km x 60km Path of satellite HyMap : 1.7km x 70km (depending on the altitude) IKONOS/Geoeye 10-15km swath
37 Mineral mapping theory
38 Hyperspectral images provide distinctive spectral shapes that allow identification of mineral types, clay soil types, plant species, plant health within species types, and hot and cold spring microorganisms. These spectra are from Mammoth Mountain Long Valley hyperspectral imagery but are representative of most areas. Hyperspectral sensor has 120 to 250 bands.
39 Ground Reflectance (offset for clarity) Ground Emissivity (offset for clarity) Spectral-Mineral Wavelength Regions iron oxides REEs vegetation OH-bearing hydroxyls (kaolinite, chlorite, mica, amphibole) sulphates carbonates ARGUS Hymap VNIR SWIR Aster Landsat TM TIR Non-OH-bearing silicates (quartz, feldspars, pyroxene, garnet) sulphates carbonates 90 dry vegetation 90 dry vegetation sandstone 64.5 sandstone 64.5 limestone green vegetation 39 limestone 39 dark soil 13.5 dark soil green vegetation Electro-Magnetic Spectrum - Wavelength in Micrometer
40 Spectral patterns of alteration minerals Absorption bands of ASTER B5 B6,B5 B6,B8 B8 ASTER bands (B1 to B9)
41 Mineral Mapping Theory Diagnostic absorption features of hydroxyl mineral groups in the SWIR * Al(OH) : nm Topaz, Pyrophyllite, Kaolinite, Montmorillonite, Muscovite, Illite * Mg(OH) : nm Chlorite, Talc, Epidote, Amphibole, Antigorite, Biotite, Phlogopite * Fe(OH) : nm Jarosite, Nontronite, Saponite, Hectorite * Si(OH): 2240 nm (broad) Opaline silica
42 ASTER data analysis to detect minerals Alunite : B4/B5, B6/B5 Pyrophyllite : B4/B5 Kaolinite : B4/B6, B4/B5 Sericite : B4/B6, B4/B8 Montmorillonite : B4/B6 Chlorite : B4/B8, B3/B4 Epidote : B4/B8, B6/B7 Calcite : B4/B8 Acidic alteration Phyllic alteration Propyritic alteration
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