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Welc lcome Conversations with Academia Big Data for Big Challenges: The Swiss Data Cube for Environmental Monitoring 1. Understand how Earth Observations (EO) acquired by satellites can be used for environmental monitoring Session 2.


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Welc lcome

Conversations with Academia Big Data for Big Challenges: The Swiss Data Cube for Environmental Monitoring

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Session Objectives

  • 1. Understand how Earth Observations (EO)

acquired by satellites can be used for environmental monitoring

  • 2. Explore the potential and challenges of EO

data to drive progress against key national and international development agendas like the Sustainable Development Goals

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Speakers

  • Dr. Gregory Giuliani

Senior Lecturer, University of Geneva, Head of the Digital Earth Unit, GRID-Geneva

  • Professor Pascal Peduzzi

Director, GRID-Geneva

  • Dr. Claudia Röösli

Senior Lecturer, University of Zurich, Group Leader, Remote Sensing Laboratories

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Big Data for Big Challenges:

The Swiss Data Cube for Environmental Monitoring

  • Dr. Gregory Giuliani, Dr. Claudia Röösli, Prof. Pascal Peduzzi
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The key to sustainable development…

…is achieving a balance between the exploitation of natural resources for socio- economic development, and conserving ecosystem services that are critical to everyone’ s wellbeing and livelihoods.

Natural Capital Socio-Economic needs

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The Challenge: Evidence-based policy-making

Knowledge: inform us about the limits of the planet Action: Societies decide how to use resources of our planet

Decisions Understanding Knowledge Information Data

Meaning Value

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To better understand these changes… Our plant is under continuous

  • bservation

from satellites

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Copernicus – Europe’s Eye on Earth Largest EO data provider in the World: 250TB/day data Archive: 250PB of data stored, daily growth rate: 220TB

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Sentinel-2: 22’000 images to cover the Earth Every 5 days! > 1’600’000 images per year!

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https://apps.sentinel-hub.com/eo-browser/

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Spatial Resolution = Pixel Size

Freely available Commercial satellites

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Not just photos…

‘p ’

Courtesy of Geoscience Australia

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VIS NIR SWIR 1 SWIR 2 TIR

VIS Visible Light RGB NIR Near Infra-Red (IR) SWIR Shortwave IR TIR Thermal IR

13 bands 11 bands 8 bands 14 bands 36 bands

Spectral Resolution

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Page 16 (See also Cicalaet al., 2018)

  • Vesuv ITA
  • Sentinel-2
  • 12-July-2017
  • Red, green, blue

Spectral Resolution

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Page 17

  • Vesuv ITA
  • Sentinel-2
  • 12-July-2017
  • SWIR2, SWIR1, NIR

(See also Cicalaet al., 2018)

Spectral Resolution

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Temporal Resolution → a game changer

Landsat 8 Landsat 8 + Sentinel-2A&B

Li & Roy (2017)

Images per year

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Sentinel-2: 22’000 images to cover the Earth Every 5 days! > 1’600’000 images per year!

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How to transform this large amount

  • f data in useful

information and support evidence- based decisions?

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Everything is in place… Why doesn’t the world use satellite data?

  • It requires scientific knowledge to understand what data is needed… optical (which

resolution?), radar (which type?)

  • It is hard to access or download
  • It is hard to prepare… atmospheric correction, grid formats, pixel alignment, speckle

filtering

  • It requires capacity building and training

A New Solution… DATA CUBES

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Sampling a Data Cube

Adapted from CEOS

Longitude Latitude Time A single time slice, similar to a standard “scene” can be used to assess a single point in time Pixels in the Data Cube are processed, aligned, and compressed and ready for data analysis

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Sampling a Data Cube

Longitude Latitude Time Several time slices can be combined into one to form a “Mosaic”. This is

  • ften used to

reduce clouds or create seasonal or annual images. Typical Mosaics ... Most/Least Recent Pixel, Mean/Median, Geomedian, Min/Max NDVI

Adapted from CEOS

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Sampling a Data Cube

Longitude Latitude Time Examples of Time Series analyses include: Land Change (PyCCD), Water Change (WOFS), Parameter variation along a transect (Hovmoller plot) Time Series analyses consider the variation of data

  • ver time to assess change

Adapted from CEOS

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  • Governments

have national and international reporting commitments and obligations as well as national environmental programs.

  • They

all need information that is synoptic, consistent, spatially explicit, sufficiently detailed to capture anthropogenic impacts, and national in scope.

  • EO Data Cube can provide the long baseline required

to determine trends, define present, and inform

  • future. This can fit these interests to inform programs

and communities.

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Session X: Session Title Slide 28

36 years

FROM 1984 to 2020

10-30-90m

PIXEL RESOLUTION

7 sensors

LANDSAT 5/7/8; SENTINEL-1/2 A-B

> 450 million

PIXELS

> 1000 billion

OBSERVATIONS

~ 12500 images

INGESTED

~5 TB

ANALYSIS READY DATA

~10 millions CHF

COST OF DATA WITHOUT OPEN DATA ACCESS POLICY

SWISS DATA CUBE in Numbers

A unique Analysis Ready Data Archive

Updated every week!

Giuliani G., Chatenoux B., De Bono A., Rodila D., Richard J.-P., Allenbach K., Dao H., Peduzzi P. (2017) Building an Earth Observations Data Cube: lessons learned from the Swiss Data Cube (SDC) on generating Analysis Ready Data (ARD). Big Earth Data 1(1):1-18

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Bondo Landslide – 23 august 2017

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Earth Observations is useful for monitoring SDG’s

http://earthobservations.org/geo_sdgs.php

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Water detection – Drought impact (2018)

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Urbanization – Bulle 1985/2018

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Rhône glacier – 1985/2018/2020

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  • 6. August 2015

13 .September 2020

~410m

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ESA UNCLASSIFIED - For Official Use Gregory Giuliani | ESRIN | 12/09/2019 | Slide 32

SDG 15.3.1 Land Degradation…

… is undermining the well-being of 3.2 billion people (IPBES)

Collaboration: University of Geneva; GEO; ESA, CNR, JRC; UN Environment http://www.geoessential.eu Giuliani et al., submitted

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ESA UNCLASSIFIED - For Official Use Gregory Giuliani | ESRIN | 12/09/2019 | Slide 34

Aggregated indicators…

… are not enough for public policy!

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ESA UNCLASSIFIED - For Official Use Gregory Giuliani | ESRIN | 12/09/2019 | Slide 35

Disaggregation of indicators…

… to capture spatial (maps) and temporal dynamics (graphs)

How much? Where? When? Who?

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SDG15.3.1 – Results from Switzerland

Official value: 4.7% SDC value: 9.7% Official definition in Switzerland is based

  • nly on soil sealing and do not consider

land productivity! Do not comply with the official UN definition!

Giuliani G., Chatenoux B., Benvenuti A., Lacroix P., Santoro M., Mazzetti P., Monitoring Land Degradation at national level using satellite EO time-series data to support SDG15 – Exploring the potentiation

  • f

Data Cube, Big Earth Data, https://doi.org/10.1080/20964471.2020.1711633

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0.0002 (mol/m2)

  • Jan. 2020

Sentinel 5P - Air Pollution Monitoring (NO2)

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0.0002 (mol/m2)

  • Mar. 2020

Sentinel 5P - Air Pollution Monitoring (NO2)

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0.0002 (mol/m2)

  • Apr. 2020

Sentinel 5P - Air Pollution Monitoring (NO2)

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Drone orthomosaic: Hossein Torabzadeh

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Essential Biodiversity Variables (EBVs)

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PhenoSwiss – Joint UNIGE/UZH project

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PhenoSwiss – Joint UNIGE/UZH project

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The SDC supports the « Digital Switzerland » strategy

▪ Support innovation and growth in the digital economy ▪ Improve efficiency and effectiveness of government investments ▪ Improve management of natural resources ▪ Stimulate research ▪ Effective monitoring mechanism ▪ Generate information products ▪ Improve data access and use & enable new products/services that can transform everyday life

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Session X: Session Title Slide 49

  • Open

Data: Landsat 5,7, 8 ARD; Sentinel 1-2 ARD + All scientific/decision- ready products are freely,

  • penly

available & FAIR compliant

  • Open Notebooks: All algorithms are

documented and openly available

  • Open Access: All publications
  • Open Source: All applications
  • Open Educational Resources: Bringing

ODC into practice

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Com

  • mmon

n Sens nsing - https://www.com

  • mmon
  • nsensing.org.uk
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Di Digit ital l Earth Australia lia -

http://www ww.ga.gov.au/dea

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Digital Ear arth Af Africa a -

https ps:// //www.di digitaleartha hafrica.or

  • rg
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Open pen Data Cub ube e

https://www ww.opendatacube.org

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Session X: Session Title Slide 55

Aims at facilitating the generation and use of an ODC instance virtually anywhere in the World. Users are only required to specify:

  • an area of interest on a web-based mapping

application;

  • types of sensors between Landsat 5-7-8 and

Sentinel-2;

  • desired temporal frame;

Then automatically an empty ODC instance is instantiated and desired data are ingested.

Data Cube on Demand (DCoD)

Giuliani G., Chatenoux B., Piller T., Moser F., Lacroix P. (2020) Data Cube on Demand (DCoD): Generating Earth Observation Data Cube anywhere, International Journal of Applied Earth Observation and Geoinformation 87:102035 https://doi.org/10.1016/j.jag.2019.102035

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Generating a Data Cube anywhere in the World…

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World Environment Situation Room – https://wesr.unep.org

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EO Data Cubes have the potential… … to enhance scientific accountability and credibility

Without trust and shared knowledge:

  • Doing science can be difficult
  • Taking sound decisions can be

problematic

  • And envisioning a sustainable

development can be complicated

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Follow us

http://www.swissdatacube.ch

@SwissDataCube GRIDgva/SwissDataCube gregory.giuliani@unepgrid.ch

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gregory.giuliani@unige.ch gregory.giuliani@unepgrid.ch http://www.unige.ch/envirospace/people/giuliani/

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Tha hank you

  • u for
  • r joi
  • ining!

!

Conversations with Academia Big Data for Big Challenges: The Swiss Data Cube for Environmental Monitoring

To provide feedback, please scan this QR code: To share ideas, please email us at commons@un.org. Visit commons.ungeneva.org/eventsfor upcoming sessions events and connection details.

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