Remote sensing uses sensors on satellites and aircraft to observe and analyze areas from a distance without direct contact. The document discusses the history of remote sensing from early color photography to modern high-resolution satellites. It also describes applications like mapping and monitoring land use and permafrost. Finally, it provides a tutorial on deriving vegetation indices from Sentinel-2 satellite data using free and open-source software.

1. Satellite eyes observe our world:
An intro to remote sensing
Christian Kuntzsch @DeEgge
Andreas Fricke @incentivious
Harald Schernthanner @hatschito

2. • What is remote sensing ? History and future ?
• Applications, e.g. mapping permafrost
• Tutorial: How to derive a vegetation index from
Sentinel-2 data ?

3. Remote Sensing
"Remote Sensing is the science and art of obtaining
information about an object, area, or phenomenon
through the analysis of data acquired by a device
that is not in contact with the object, area, or
phenomenon under investigation.“
Lillesand, T., Kiefer, R. W., & Chipman, J. (2014). Remote sensing and
image interpretation. John Wiley & Sons.

4. History of remote sensing
1914 WWI
1860 Boston
1854 Nadar 1860 Boston

5. History of remote sensing
1940´s
Colored photography
1942 - Kodak patents
first false color I.R.
sensitive film
CIR (coloured inrared)

6. Discovering historical imagery in google earth
Kreuzberg, 12/1943

7. History of remote sensing
Kreuzberg 03/2015

8. Milestone in remote sensing
- 1940 Color infrared CIR
- 1972: Launch of ERTS-1 = Landat 1. Satellite copy of CIR
sensor
- 80m pixel resolution
- 1986: Launch of SPOT-1
- 1999: Landsat 7 ETM
- 2000: Shuttle SRTM Mission
- 2001: Digitalglobe Quickbird
- 61 cm pixel resolution
- 2005: Google Inc. releases
Keyhole, http://earth.google.com
- 2007:- 2014: WorldView 3: Eight band multispectral: 0,31
cm geometric resolution, SWIR: 3,7
- 2015: Launch of Sentinel-2
- 2016 Nano satellites
- permanently available HD video from space:

9. Future ?
Nano - Satellites Unmanned aerial vehicles, UAV

10. How many satellites are in space?

11. 2,271 satellites:
Stuff in Space ?

12. Where are the satellites?
Real time satellite tracking

13. Applications ?
- Primary data source for mapping
- Land use/cover classification
- Land change
- Environmental analysis
- Geography / Geology / Hydrology /
Forestry
- …..
Aral lake shrinking timelapse, classical example

14. ANDREAS PERMAFROST

15. Where to get data from ?
• Commercial data providers: Price: around 20 US$ / sq. km with
minimum order of 24 sq. km = Berlin scene ca. 18 000€
• https://browse.digitalglobe.com/
• http://eyefind.rapideye.com/
• Free data sources:
• 15 free data sources: http://gisgeography.com/free-satellite-imagery-data-
list/
• USGS Earth Explorer: http://earthexplorer.usgs.gov/
• Sentinels scientific data hub: https://scihub.copernicus.eu/
• How to search Sentinel data: http://www.digital-
geography.com/downloading-sentinel-satellite-
imagery/#.VtVRDpPhBsM

16. Where to get data from ?
• Data search and preprocessing can be very time consuming!
• Knowledge about the data is necessary:
• Sentinel-2 processing levels

17. Sentinel-2a
• 6 satellite missions by ESA
• Satellite eyes see more!
• Sentinel-2A: 13 bands / 10
days revisit time

18. Data & preprocessing
• Downloaded scene covering Berlin: 8GB of data
• Acquisition data: 24.12.2015
• Subset and export as geotiff was done in the Sentinel
toolbox: http://step.esa.int/main/toolboxes/snap/
• Open source, but unstable and memory consuming,
but getting better from version to version…
• Dataformat only can be handled by SNAP

19. Entire scene in false colors:
200 km east-west
320 km north - south
Berlin

20. Video tutorials by Luca
Congedo, developer of the
semiautomatic classification
plugin
https://www.youtube.com/user/f
romgistors
Commercial image processing software
Open source image processing software
Monteverdi 3.0

21. NDVI of Berlin
• NDVI = Normalized differenced vegetation index
• Index of photosynthetic activity of plants
• Active vegetation absorbes light in red part of the EMS
(electromagnetic spectrum) and reflects in the NIR part
IMPORTANT INFORMATION
VISUALLY AWFUL

22. Loading raster data in QGIS
GeoTIFF
Open
raster
icon

24. False color in QGIS

26. NDVI in QGIS
NDVI = (NIR-Red)/(NIR+Red)

27. Raster calculator QGIS
Raster substraction in QGIS

28. Raster calculator in QGIS

29. NDVI formula in QGIS Raster calculator
Band 1: red, Band 2: green, band 3: blue, band 4: near infrared
Expression: float(image@4 - image@1) /(image@4 + image@1)
float: conversion from integer to floating point
@1…4 : band number

30. NDVI result

31. NDVI classes
NDVI
Barren rock, sand, snow -1 <0,1
Sparse vegetation >0,1 - 0,5
Dense vegetation >0,5 - 1
Ranges from -1 to 1: USGS classification
http://phenology.cr.usgs.gov/ndvi_foundation.php

32. Classify NDVI result
Right click on data layer -> properties -> style

33. Classified NDVI

34. Want to learn more ?
• NASA remote sensing tutorial:
http://earthobservatory.nasa.gov/Features/Remote
Sensing/
• Great tutorials and youtube channel by Luca
Congedo:
https://www.youtube.com/user/fromgistors
• http://fromgistors.blogspot.com/search/label/Tutor
ial?max-results=5

35. Questions ?
Thank you for your attention!