Satellite Imagery Characteristics, Uses and Delivery to GIS Systems. Wayne Middleton April 2014
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1 Satellite Imagery Characteristics, Uses and Delivery to GIS Systems Wayne Middleton April 2014
2 About Geoimage Founded in Brisbane 1988 Leading Independent company Specialists in satellite imagery and geospatial solutions
3 Geoimage Imagery Partners Providing access to the largest range of satellite imagery in Australia 19 satellite/satellite systems
4 Geoimage Partners Image Processing Software Specialty Imagery Products Spatial Data Management
5 Outline Review of optical and radar satellite imagery, their characteristics and derived products Application examples and delivery into GIS software
6 Electromagnetic spectrum Gamma Ray to Radio Waves
7 JAXA/METI DigitalGlobe Geoimage Pan-sharpening
8 Optical Satellite Imagery Passive sensor - senses reflected light from ground surfaces using the sun as illumination source Categorized by spatial resolution: Medium (5 to 30 metres) High (>1 to 5 metres) Very high (Sub-metre to 1m)
9 Optical Satellite Imagery Worldwide coverage at some scale Imagery of inaccessible areas Repeat coverage Large historical archive
10 Map-up of sub-metre pan-sharpened multispectral data assessed as <10% cloud cover and acquired in 2012 and to May 2013 All VHR vendors to that date shown Pleiades 1A and 1B on top
11 Optical Satellite Imagery Programmable Monoscopic or stereo capture (for DEM generation) Spectral analysis Cloud affected Best resolution is 0.5 metres
12 Optical Satellite Imagery Medium resolution (5m to 30m): Landsat 1 to 5 (decommissioned), Landsat 7 (faulty) Landsat 8 ASTER (SWIR decommissioned) SPOT 1 to 4 (decommissioned) SPOT 5 Multispectral ALOS AVNIR-2 (decommissioned) SPOT 6 Multispectral SPOT 7 Multispectral (to be launched in 2014)
13 ClearView TM PNG
14 Optical Satellite Imagery High resolution (>1m to 5m): SPOT 5 and 6 Panchromatic and pan-sharpened multispectral SPOT 7 Panchromatic and pan-sharpened multispectral (to be launched in 2014) ALOS PRISM (panchromatic) and pan-sharpened AVNIR-2 (multispectral) (decommissioned) VHR Multispectral (e.g. GE-1 2m BGRN multispectral) RapidEye
15 Manilla International Airport SPOT 6 PS-imagery Airbus D&S
16 Manilla International Airport SPOT 6 PS-imagery Airbus D&S
17 Optical Satellite Imagery Very high resolution (Sub-metre to 1m): IKONOS the oldest (1999) QuickBird WorldView-1, -2 and -3 (to be launched in 2014) GeoEye-1 Pleiades Kompsat-1, -2 and -3 (limited Australian archive) SkySat-1 and -2 (to be launched in 2014) include highdefinition video
18 WorldView-2 PS-imagery DigitalGlobe
19 WorldView-2 PS-imagery DigitalGlobe
20 WorldView-2 PS-imagery DigitalGlobe
21 DigitalGlobe 2014 WorldView-2 Brisbane (50cm)
22 Derived Products
23 Iran Pleiades imagery and DEM Airbus D&S
24 Iran Pleiades imagery and DEM Airbus D&S
25 Iran Pleiades imagery and DEM Airbus D&S
26 Iran Pleiades imagery and DEM Airbus D&S
27 Radar Satellite Imagery Active sensor - provides own energy to detect features on the ground, can penetrate cloud & be acquired at night Categorized by wavelength: L-Band (15cm to 30cm) C-Band (3.75cm to 7.5cm) X-Band (2.4cm to 3.75cm)
28 Radar Satellite Imagery Worldwide coverage at some wavelength Imagery of inaccessible areas and/or areas affected by constant cloud cover Repeat coverage Programmable or in archive Large historical archive
29 PALSAR imagery JAXA/METI versus Landsat imagery over PNG
30 PALSAR imagery JAXA/METI versus Landsat imagery over PNG
31 PALSAR imagery JAXA/METI versus Landsat imagery over PNG
32 PALSAR imagery JAXA/METI versus Landsat imagery over PNG
33 PALSAR imagery JAXA/METI versus Landsat imagery over PNG
34 Radar Satellite Imagery L-Band (15cm to 30cm): JERS (decommissioned) ALOS PALSAR (decommissioned)
35 PALSAR FBS outlines over Central Papua JAXA/METI
36 Composite PALSAR Fine Beam Mode over Central Papua JAXA/METI
37 Radar Satellite Imagery C-Band (3.75cm to 7.5cm): Radarsat-1 and -2 ERS-1 and -2 (decommissioned) Envisat (decommissioned) X-Band (2.4cm to 3.75cm): TerraSAR-X / TanDEM-X COSMO-SkyMed
38 Applications
39 Application Examples Medium Resolution Optical Satellite Imagery ASTER Bands in VNIR, SWIR and TIR useful for spectral mapping for mineral exploration Availability limited to pre May 2007
40 Application Examples Medium Resolution Optical Satellite Imagery Electromagnetic spectrum Visible to SWIR
41 ASTER Spectral Processing
42 ASTER Spectral Processing
43 ASTER Spectral Processing
44 ASTER Spectral Processing
45 ASTER Spectral Processing
46 ASTER Spectral Processing
47 ASTER Spectral Processing
48 ASTER Spectral Processing
49 Application Examples High Resolution Optical Satellite Imagery SPOTMaps existing 2.5m pansharpened natural colour mosaic Dates vary from 2009 to 2012 over Australia Low cloud, accurate (5m to 10m CE90), low-cost, background image Uses include vector extraction to cost effectively map or update roads, hydrology, other natural and man-made features
50 NSW SPOTMaps imagery Airbus D&S
51 NSW SPOTMaps imagery Airbus D&S
52 Application Examples Very High Resolution Optical Satellite Imagery GeoEye-1 0.5m stereo fresh capture DEM generation at 1m resolution 0.5m pan-sharpened background imagery DEM colour drape Terrain shaded relief showing discrete height classes
53 Chile GeoEye-1 PS RGB imagery DigitalGlobe 2013
54 Chile GeoEye-1 PS RGB imagery DigitalGlobe 2013
55 Chile GeoEye-1 PS RGB imagery DigitalGlobe 2013
56 Chile GeoEye-1 PS RGB imagery DigitalGlobe 2013
57 Chile GeoEye-1 PS RGB imagery draped over generated DEM DigitalGlobe 2013
58 Chile GeoEye-1 PS RGB imagery draped over generated DEM DigitalGlobe 2013
59 Chile GeoEye-1 PS RGB imagery draped over generated DEM DigitalGlobe 2013
60 Chile GeoEye-1 PS RGB imagery draped over generated DEM DigitalGlobe 2013
61 Chile GeoEye-1 PS RGB imagery draped over generated DEM DigitalGlobe 2013
62 Chile GeoEye-1 PS RGB imagery draped over generated DEM DigitalGlobe 2013
63 Chile GeoEye-1 PS RGB imagery draped over generated DEM DigitalGlobe 2013
64 Chile GeoEye-1 Terrain Shaded Relief DigitalGlobe 2013
65 Chile GeoEye-1 Terrain Shaded Relief DigitalGlobe 2013
66 Chile GeoEye-1 Terrain Shaded Relief DigitalGlobe 2013
67 Application Examples Radar Satellite Imagery Global Seeps Database ( Airbus D&S) of off-shore oil slicks Constructed by systematically screening the world s offshore basins using a wide range of archive and fresh capture radar satellite data including ERS-1 and -2, TerraSAR-X, Radarsat-1 and 2, JERS-1, Envisat and PALSAR and optical satellite data including Landsat and ASTER
68 Current Australian Coverage Airbus D&S
69 Application Examples Radar Satellite Imagery Radar is used in preference to optical because it can penetrate cloud, can be acquired at night and is well suited to discriminate oil on the sea surface
70 Application Examples Radar Satellite Imagery Archive currently includes over interpreted scenes Database is continually updated, over 3000 new scenes were added in 2013 Slicks are characterized and ranked as probable natural seepage or man-made pollution based on a 3-part methodology
71 Application Examples Radar Satellite Imagery GIS-ready deliverables Description and interpretation results of radar scenes Slick interpretation results Ship and oil rig/platform locations Thumbnail images of each slick Radar images Geodatabase relationships between raster and vector data ArcGIS toolbar
72 25m chip over oil slick feature (left), 100m full radar satellite scene (right) Airbus D&S
73 Seep Browser ArcGIS toolbar Airbus D&S
74 Thank you
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