Satellite eyes observe our world:

An intro to remote sensing

Christian Kuntzsch @DeEgge

Andreas Fricke @incentivious

Harald Schernthanner @hatschito

• What is remote sensing ? History and future ?

• Applications, e.g. mapping permafrost

• Tutorial: How to derive a vegetation index from

Sentinel-2 data ?

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.

History of remote sensing

1914 WWI

1860 Boston

1854 Nadar 1860 Boston

History of remote sensing1940´s

Colored photography

1942 - Kodak patents

first false color I.R.

sensitive film

CIR (coloured inrared)

Discovering historical imagery in google earth

Kreuzberg, 12/1943

History of remote sensing

Kreuzberg 03/2015

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:

Future ?

Nano - Satellites Unmanned aerial vehicles, UAV

How many satellites are in space?

2,271 satellites:

Stuff in Space ?

Where are the satellites?

Real time satellite tracking

Applications ? - Primary data source for mapping

- Land use/cover classification

- Land change

- Environmental analysis

- Geography / Geology / Hydrology /

Forestry

- …..

Aral lake shrinking timelapse, classical example

ANDREAS PERMAFROST

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

Where to get data from ?

• Data search and preprocessing can be very time consuming!

• Knowledge about the data is necessary:

• Sentinel-2 processing levels

Sentinel-2a

• 6 satellite missions by ESA

• Satellite eyes see more!

• Sentinel-2A: 13 bands / 10

days revisit time

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

Entire scene in false colors:

200 km east-west

320 km north - south

Berlin

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

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

Loading raster data in QGIS

GeoTIFF

Open

raster

icon

False color in QGIS

NDVI in QGISNDVI = (NIR-Red)/(NIR+Red)

Raster calculator QGIS

Raster substraction in QGIS

Raster calculator in QGIS

NDVI formula in QGIS Raster calculatorBand 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

NDVI result

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

Classify NDVI resultRight click on data layer -> properties -> style

Classified NDVI

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

Questions ?

Thank you for your attention!