15 / Nov / 2017 Training Module A2 Session 3

TrainerKhaled Mashfiq

Searching, Exploring and Gathering Geospatial Data

In partnership with Introduction to the Use of Geospatial Information Technology for Drought Risk Management

Phnom Penh, Cambodia14-17 November, 2017

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Outline

Data Characteristics

Data Sources

Purpose of Geodata

Data Download

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Data Characteristics

Satellite Imagery

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The most common characterization of satellite imagery results from:

• Diverse acquisition date/time

• Sensor type

• Scene size

• Resolutions

• Data format

Data Characteristics

The spatial resolution specifies the pixel size of satellite images covering the earth surface

Very High/ High spatial resolution: 0.25 - 4 m

Medium spatial resolution: 4 - 30 m

Low spatial resolution: 30 - > 1000 m

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No. Sensor Name Sensor Type

Resolution(m)

PAN MS

1 GEO EYE-1 Optical 0.41 1.7

2 WORLDVIEW-1 Optical 0.45 -

3 WORLDVIEW-2 Optical 0.46 1.8/2.4

4 WORLDVIEW-3 Optical 0.31 1.24

5 IKONOS-2 Optical 1 4.0

6 CARTOSAT-2A Optical 1 -

7 SPOT 6&7 Optical - 1.5

8 CARTOSAT-1 Optical 2.5 -

9 FORMOSAT-2 Optical 2 8.0

10 Quickbird-2 Optical 0.6 2.4

11 SPOT-5 Optical 2.5 5/10/20m

12 TopSat Optical 2.9 5.7

13 SPOT 1 to 3 Optical 10 20/10m

14 SPOT-4 Optical 10 20/10m

15 Terra- ASTER Optical - 15/30/90

16 DEIMOS/UK-DMC2 Optical - 22.0

17 Landsat-7 ETM+ Optical 15 30.0

18 Landsat-5 TM Optical - 30.0

19 Terra/Aqua- MODIS Optical 250 – 10000.5m 5m 25m 50m

What is Spatial Resolution?

Swath Width 6

No. Sensor Name Sensor Type

Resolution(m) Swath Width (km)PAN MS

1 GEO EYE-1 Optical 0.41 1.7 15

2 WORLDVIEW-1 Optical 0.45 - 16

3 WORLDVIEW-2 Optical 0.46 1.8/2.4 16.4

4 WORLDVIEW-3 Optical 0.31 1.24 13.1

5 IKONOS-2 Optical 1 4.0 11

6 CARTOSAT-2A Optical 1 - 10

7 SPOT 6&7 Optical - 1.5 60

8 CARTOSAT-1 Optical 2.5 - 30

9 FORMOSAT-2 Optical 2 8.0 24

10 Quickbird-2 Optical 0.6 2.4 16.5

11 SPOT-5 Optical 2.5 5/10/20m 60

12 TopSat Optical 2.9 5.7 17/12.0

13 SPOT 1 to 3 Optical 10 20/10m 60

14 SPOT-4 Optical 10 20/10m 60

15 Terra- ASTER Optical - 15/30/90 60

16 DEIMOS/UK-DMC2 Optical - 22.0 Up to 600

17 Landsat-7 ETM+ Optical 15 30.0 185

18 Landsat-5 TM Optical - 30.0 185

19 Terra/Aqua- MODIS Optical 250 – 1000 2330

Swath width refers to the strip of the Earth’s surface from which data are collected by a satellite

What is Spectral Resolution? 7

No. Sensor NameResolution(m) Bands

PAN MS PAN MS

1 GEO EYE-1 0.41 1.7 1 -

2 WORLDVIEW-1 0.45 - 1 -

3 WORLDVIEW-2 0.46 1.8/2.4 1 8 (R,G,B,NIR,RE,Y,NIR2)

4 WORLDVIEW-3 0.31 1.24 1

8 (Coastal, R,G,B,NIR,RE,Y,NIR2), 8 SWIR bands, 12 CAVIS

Bands

5 IKONOS-2 1 4.0 1 MS (RGB-NIR)

6 CARTOSAT-2A 1 - 1 -

7 SPOT 6&7 - 1.5 1 4(R,G,B,NIR)

8 CARTOSAT-1 2.5 - 1 -

9 FORMOSAT-2 2 8.0 - 4(RGB-NIR)

10 Quickbird-2 0.6 2.4 1 MS (RGB-NIR)

11 SPOT-5 2.5 5/10/20 1 3(R,G,NIR)

12 TopSat 2.9 5.7 1 3(R,G,B)

13 SPOT 1 to 3 10 20/10 1 3(R,G,NIR)

14 SPOT-4 10 20/10 1 3(R,G,NIR)

15 Terra- ASTER - 15/30/90 - 6(VNIR,G,R,NIR,SWIR,TIR)

16 DEIMOS/UK-DMC2 - 22.0 - 3(R,G,NIR)

17 Landsat-7 ETM+ 15 30.0 1 7(RGB-NIR-MIR-TH)

18 Landsat-5 TM - 30.0 - 5 (RGB-NIR-MIR-TH)

19 Terra/Aqua- MODIS 250 – 1000 - 36

The wavelength width of the different frequencies recorded by the satellite sensors

Frequency Acronym wave length range

Region Sub Region From To

Ultraviolet UV ~0.01μm ~0.40μm

Visible VIS ~0.40μm ~0.75μm

Infrared Near Infrared NIR ~0.75μm ~1.3μm

Short Wave Infrared SWIR ~1.3μm ~3μm

Mid Wave Infrared MWIR ~3.0μm ~6.0μm

Thermal TIR ~6.0μm ~15.0μm

Far Infrared FIR ~15.0μm ~0.1cm

What is Temporal Resolution? 8

No. Sensor Name Revisit Time

1 GEO EYE-1 2 – 8

2 WORLDVIEW-1 2 – 6

3 WORLDVIEW-2 1 – 3

4 WORLDVIEW-3 1

5 IKONOS-2 2 – 5

6 CARTOSAT-2A 5

7 SPOT 6&7 1

8 CARTOSAT-1 5

9 FORMOSAT-2 1

10 Quickbird-2 2 – 6

11 SPOT-5 2 – 3

12 TopSat 2-2.5

13 SPOT 1 to 3 -

14 SPOT-4 2 – 3

15 Terra- ASTER 4 – 16

16 DEIMOS/UK-DMC2 2 – 3

17 Landsat-7 ETM+ 16

18 Landsat-5 TM 16

19 Terra/Aqua- MODIS 1

The shortest revisit time elapsed between observations of the same

point on earth by a satellite

What is Radiometric Resolution?9

No. Sensor Name Bit size

1 GEO EYE-1 (11 bits) reassigned to 16 or 8

2 WORLDVIEW-1 (11 bits) reassigned to 16 or 8

3 WORLDVIEW-2 (11 bits) reassigned to 16 or 8

4 WORLDVIEW-3 (11 bits pan and 14 bits SWIR)

5 IKONOS-2 (11 bits) reassigned to 16 or 8

6 CARTOSAT-2A (10 bits) reassigned to 16 or 8

7 SPOT 6&7 (12 bits) reassigned to 16 or 8

8 CARTOSAT-1 (10 bits) reassigned to 16 or 8

9 FORMOSAT-2 (8 bits) delivered as 8 bits

10 Quickbird-2 (11 bits) reassigned to 16 or 8

11 SPOT-5 (10 bits) reassigned to 16 or 8

12 TopSat (11 bits) reassigned to 16 or 8

13 SPOT 1 to 3 (11 bits) reassigned to 16 or 8

14 SPOT-4 (11 bits) reassigned to 16 or 8

15 Terra- ASTER For 15/30m - 8bits, 90m - 16 bits

16 DEIMOS/UK-DMC2 (10 bits) reassigned to 8

17 Landsat-7 ETM+ (11 bits) reassigned to 16 or 8

18 Landsat-5 TM (11 bits) reassigned to 16 or 8

19 Terra/Aqua- MODIS (12 bits) reassigned to 16 or 8

Number of digital levels used to express the data collected by the sensor

http://pages.csam.montclair.edu/~chopping/rs/CCRS/chapter2/chapter2_5_e.html

Off-Nadir Angle 10

No. Sensor Name Off Nadir Angle1 GEO EYE-1 +/- 36 max.2 WORLDVIEW-1 +/- 37 max.3 WORLDVIEW-2 +/- 32 max.4 WORLDVIEW-3 +/- 30 max.

5 IKONOS-2 +/- 36 max.

6 CARTOSAT-2A +/- 45 max.

7 SPOT 6&7 +/- 45 max.

8 CARTOSAT-1 +/- 45 max.

9 FORMOSAT-2 +/- 45 max.

10 Quickbird-2 +/- 37 max.

11 SPOT-5 +/- 31 max.

12 Top Sat +/- 45 max.

13 SPOT 1 to 3 +/- 31 max.

14 SPOT-4

15 Terra- ASTER

16 DEIMOS/UK-DMC2 +/- 12 max.

17 Landsat-7 ETM+

18 Landsat-5 TM

19 Terra/Aqua- MODIS

The angle that the satellite lens looks at the earth from

At-nadir : point the satellite is looking directly down at the ground

Off-nadir : how far the angle of the lens is tilted

http://marswiki.jrc.ec.europa.eu/wikicap/index.php/VHR_spaceborne_sensors,_suitable_for_LPIS_creation_and_update

San Francisco, 45 deg. off-nadir - an extreme example

Archived vs and Tasked Imagery 11

Archive imagery is from a library of data that has been collected and stored from

the launch date of the satelliteTasked imagery are new

acquisition planned for the future

Can weather or clouds affect the imagery? 12

Clouds affect optical imageries but radar imagery can capture through clouds

Check for the percentage of clouds in the scene through online catalogue before ordering the imagery

18/04/2011- TerraSAR -X30/04/2011- World view 01

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Geodata

Formats

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Data Format : Vector and Raster Data

Dhaka

Khulna

Rajshahi

Chittagong

Comilla

Vector Data

- Shapefile (.shp)

Raster Data

- TIFF

- JPEG

- HDF

- netCDF

Data Formats: Raster 15

No. Sensor Name Data Format1 GEO EYE-1 Geo TIFF, NITF-2.0/2.1

2 WORLDVIEW-1 Geo TIFF, NITF-2.0/2.1

3 WORLDVIEW-2 Geo TIFF, NITF-2.0/2.1

3 WORLDVIEW-3 Geo TIFF, NITF-2.0/2.1

4 IKONOS-2 Geo TIFF, NITF-2.0/2.1

5 CARTOSAT-2A LGSOWG, Geo TIFF, Fast Format

6 SPOT 6&7 DIMAP, Geo TIFF

7 CARTOSAT-1 LGSOWG, Geo TIFF, Fast Format

8 FORMOSAT-2 DIMAP, Geo TIFF

9 Quickbird-2 Geo TIFF, NITF-2.0/2.1

10 SPOT-5 DIMAP, Geo TIFF

11 TopSat JPEG, TIFF, GeoTIFF

12 SPOT 1 to 3 DIMAP, Geo TIFF

13 SPOT-4 DIMAP, Geo TIFF

14 Terra- ASTER HDF, Geo TIFF

15 DEIMOS/UK-DMC2 DIMAP, Geo TIFF

16 Landsat-7 ETM+ Fast Format, HDF,

17 Landsat-5 TM Fast Format, HDF

18 Terra/Aqua- MODIS HDF, GeoTIFF

Few of the commonly available formats:

• Geo Tagged Image File Format- Geo TIFF

• Joint Photographic Experts Group -JPEG2000

• Band Interleaved by Line- BIL

• Band Sequential – BSQ

• Hierarchical Data Format - HDF

• National Imagery Transmission Format – NITF

• Digital Image Map Format- DIMAP

• Multi resolution seamless image database –MrSID

• Landsat Ground Station Operators Working Group - LGSOWG

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Data Sources

Where can we get data from?

Government Space Agencies

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• National Aeronautics and Space Administration | NASA

• Russian Federal Space Agency | FKA

• European Space Agency | ESA

• Centre national d'études spatiales | CNES

• Japan Aerospace Exploration Agency | JAXA

• German Aerospace Center | DLR

• Indian Space Research Organization | ISRO

• China National Space Administration | CNSA

• Canadian Space Agency | CSA

• And many more … … …

Source: NASA

Where can we get data from?

Private/Commercial Space Agencies

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• DigitalGlobe

• Worldview 1 and 2

• Quickbird

• Geoeye

• IKONOS

• OrbView-1

• GeoEye-1

• SPOT IMAGE

• DMC International Imaging Images Copyright © DigitalGlobe.

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Purpose of Geodata

How do I choose among the different options?

Purpose of Data 20

• All geospatial projects must have a goal/purpose

• Who is your end user ?

• What specific information you want to convey?

• What questions will you be answering?

• What do you want to display/highlight on your map?

• i.e. Hazard extent, population distribution in a city, location of schools, etc

Which data do I need for my project? 21

• What is the temporal resolution that I need?

• What is the level of details I want to achieve?

• Does the data already exist or should I collectthem ?

• Which format will I be able to process the data in?

• What is the level of processing required to turn my data into valuable information?

• What is the total cost of the image(s)? Do I have the funding availability?

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Data Download

Free Data Portals 23

Data is also available FREE of charge

• MODIS data products

• Copernicus Sentinels

• World Pop

• TRMM and GPM Rainfall Measurement

• Open Street Map

• LANDSAT and ASTER imagery can be obtained through USGS

• Digital Elevation Models (DEM) (SRTM/GDEM)

• OCHA datasets for humanitarian response

(COD/FOD)

Research about availability of free dataset before purchasing online

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How to review, assess and approach data

Data Assessment

Content: Information the data displays

Complexity: Level of detail provided in the data

Consistency: Check the data for accuracy through out the whole data set

Completeness: How much of the area does the data set cover. Are there any gaps in the information?

Vector: Check the 4 C’s

MODIS Rapid Response – Satellite Image25

https://earthdata.nasa.gov/earth-observation-data/near-real-time/rapid-response/modis-subsets

DEMO: USGS Earth Explorer

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http://earthexplorer.usgs.gov/

Copernicus : Sentinels

27https://scihub.copernicus.eu/

28DEMO: Digital Globe

https://browse.digitalglobe.com/

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DEMO: Precipitation Data

http://giovanni.gsfc.nasa.gov/giovanni/

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DEMO: Humanitarian Data Exchange

https://data.humdata.org/

ArcGIS Online – Vector , Raster, Data Service31

Can be accessed from ArcMap Add data menu

Openstreet Map – Vector Baseline

BBBike Extracts - OpenStreetMap

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http://extract.bbbike.org/ extract.bbike.org

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Gridded Population: WorldPop

http://www.worldpop.org.uk/data/get_data/

Rapid Response Products: UNOSAT

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http://www.unitar.org/unosat/

UNITARInternational Environment HouseChemin des Anémones 11-13,CH-1219 Châtelaine, Geneva - SwitzerlandT +41 22 917 8400F +41 22 917 8047www.unitar.org

United Nations Institute for Training and ResearchInstitut des Nations Unies pour la Formation et la RechercheInstituto de las Naciones Unidas para Formación Profesional e InvestigacionesУчебньıй и научно-исследовательский институтОрганизации Объединенньıх Нацийمعھد الأمم المتحدة للتدریب والبحث

This presentation should not be copied or disseminated in any manner without the express permission of UNOSAT.

In partnership with Introduction to the Use of Geospatial Information Technology for Drought Risk Management

Phnom Penh, Cambodia14-17 November, 2017