IAOS-OECD 2018 conference, 19-21 September 2018, Paris. More information at: http://www.oecd.org/iaos2018/

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Remote Sensing Data for
Better Statistics
Natalie Rosenski
Session 3 A: New technologies for compiling statistics
16th Conference of IAOS
OECD Headquarters, Paris, France, 19-21 September 2018
© Federal StatisticalOffice of Germany (Destatis)

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Remote Sensing I
2© Federal StatisticalOffice of Germany (Destatis)
0.1 m 1 m
30 m 300 m
Source: BKG,
Dr. Michael Hovenbitzer

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Remote Sensing II
3© Federal StatisticalOffice of Germany (Destatis)
Source: Nasa Earth observation, https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MODAL2_M_CLD_FR&date=2015-04-01,
accessed 31/08/2018

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Projects of Destatis with Remote Sensing Data
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 MAKSWELL - MAKing Sustainable development and WELL-being frameworks
work for policy analysis
 Deep Solaris - Merging statistics and geospatial information in EU Member
States
 Smart Statistics
 COP4STAT_2015plus – Copernicus for Statistics
 EmpQuaGa – Empirical district analysis for potential studies regarding building
automation
© Federal StatisticalOffice of Germany (Destatis)

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MAKSWELL
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 MAKing Sustainable development and WELL-being frameworks work for policy analysis
 Duration: November 2017 – May 2020
 Partner: ISTAT (leader), CBS, HCSO and the Universities of Trier, Pisa, Southampton
 Goals:
» Analysis of remote sensing data regarding its use for the development of well-
being and sustainability indicators
» Development of a methodology for measuring poverty and inequality at regional
level by using small-area-estimation
© Federal StatisticalOffice of Germany (Destatis)

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Possible analysis of urban poverty in Europe
6© Federal StatisticalOffice of Germany (Destatis)
© M. Wurm & H. Taubenböck,2017:
Detecting social groups from space – Assessment
of remote sensing-based mapped morphological
slums using income data.

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Deep Solaris
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 (Semi-)Automated analysis of satellite and aerial images for energytransition and
sustainability indicators
 Duration: January 2018 – January 2020
 Partner: CBS (leader), Statbel, IT.NRW, BISS
 Goals:
» Development of a machine learning algorithm in order to detect objects
» Counting of solar panels on the basis of remote sensing data
» Mapping of detected solar panels
© Federal StatisticalOffice of Germany (Destatis)

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Aerial pictures
8© Federal StatisticalOffice of Germany (Destatis)
© GeobasisNRW20 cm 10 cm

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Smart Statistics
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 Proof of Concepts regarding the ‘Internet of Things’ for the production of smart statistics in policy
areas of the European Commission
 Duration: February 2018 – March 2019
 Partner: SOGETI Luxemburg, Jožef Stefan InstituteSlovenia
 Goals:
» Identification of economic activities, which can be observed and quantified through
remote sensing data
» Production of real-time economic indicators
© Federal StatisticalOffice of Germany (Destatis)

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Economic indicators
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 Number of ships and containers at harbours
 Number of ships on rivers and canals
 Number of planes at airports
 Number of parked cars in front of supermarkets
 Length of traffic jams during rush hours
 Filling level of oil tanks
 Construction sites
© Federal StatisticalOffice of Germany (Destatis)

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Number of ships and containers at harbours
11© Federal StatisticalOffice of Germany (Destatis)
Source: BKG, Dr. Gopika Suresh
© Copernicus
2,5 m 10 m

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Containers at the port of Hamburg
12© Federal StatisticalOffice of Germany (Destatis)
© SpaceKnow
https://www.spaceknow.com/

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Filling level of oil tanks
13© Federal StatisticalOffice of Germany (Destatis)
Source: https://medium.com/from-the-macroscope/bringing-transparency-to-oil-supply-in-closed-economies-9bec49e8da2b,
accessed 05/09/2018

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© Federal StatisticalOffice of Germany (Destatis)
Thank you for your attention!
Any questions?
Institute for Research and Development in
Federal Statistics
Natalie Rosenski
+49 (0) 611 / 75 4284
natalie.rosenski@destatis.de