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Institute for Environmental Analytics: How Data Drives Environmental Decisions

Institute for Environmental Analytics: How Data Drives Environmental Decisions

This presentation is by Jon Blower, CTO at the Institute for Environmental Analytics. It supported his talk at Swirrl's 2016 data conference 'Data-Driven Decisions'.

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May 26, 2016
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  1. DELIVERING VALUE FROM BIG DATA 1 DELIVERING VALUE FROM BIG

    DATA WHAT COULD ENVIRONMENTAL DATA DO FOR YOU? Jon Blower CTO Institute for Environmental Analytics
  2. DELIVERING VALUE FROM BIG DATA WHAT IS THE INSTITUTE FOR

    ENVIRONMENTAL ANALYTICS? •  Established mid-2015 with c.£6m start-up funding from HEFCE •  Aim to be a leading worldwide centre of excellence for big data analytics focussed on environmental challenges. •  Expert team with knowledge of data science, algorithm development, software engineering and data visualisation. •  Growing partnership with diverse expertise (science, technology, remote sensing, supercomputing, ...) •  Focus on development of pre-commercial big data technology applications with industry and public sector •  Helping users to make decisions using environmental data •  We work with all kinds of environmental data, not just satellite data
  3. DELIVERING VALUE FROM BIG DATA Application Identify Merge Analyse Display

    Earth Observation Social Media Open Data Telecoms Internet of Things 4
  4. Benefits of Earth Observation Wide area observation capability Uniform -

    same sensor used at many different places in the world Rapid measurement – sensors can be targeted by operators at any point on earth, including remote and inhospitable areas. Continuity - single sensors or series of sensors providing long time series of data Many sources are Open Data
  5. ESA UNCLASSIFIED - For Official Use Sentinel-2 – mapping urban/rural

    land use S2-A launched 23 June 2015, •  13 Bands (VIR, NIR, SWIR, red edge), •  290km swath, •  10-20-60m resolution, •  10d revisit. Image of Pavia acquired on 27 June 2015 at 10:25 UTC, Credit: Copernicus data (2015) / ESA 11
  6. 12 Situational Awareness using thermal imaging •  High resolution infrared

    monitoring of thermal anomalies. •  Refrigerated and Air- con buildings are illustrated as dark. •  Warmed up cars show a clear white colour- indicating their high relative heat Hot Cold
  7. Ground   mo)on  from   L’Aquila   earthquake,   Italy,

     2009     ENVISAT  SAR   (few  cm   wavelength)  
  8. ESA UNCLASSIFIED - For Official Use EO to determine water

    stress Source: ESA / ITC / TU Wien / VU Amsterdam / DWD / KNMI / Planetary Visions 15
  9. DMR-CMS-SUPSC03-PRE-11-E © DEIMOS Space S.R.L. Precision agriculture - KORE 17

    Augmenting a precision agriculture service using Satellite and UAV Earth Observation imagery to provide cost effective crop management advice
  10. DELIVERING VALUE FROM BIG DATA SUSTAINABLE TUNA FISHING (“FREE SCHOOL

    FISHING”) •  EO data •  Chlorophyll •  Sea Surface Temperature •  Turbidity •  RSR •  Supplemented by: •  Wind Speed •  Ocean Current •  Daily (or as close as possible) for 2015, Maldives EEZ, As high spatial resolution as possible. •  Ecosystem model uses above data to predict fish abundance
  11. DataSpring: A different approach to data access www.esspartnership.org www.thedataspring.org In

    addition to ‘traditional’ service delivery, we’re working across government to develop DataSpring, a one-stop shop web service providing direct access to authoritative cross-government environmental and EO data for developers and innovators based on consistent and open data standards. Reducing barriers to innovation, stimulating growth and supporting decision making Our data will be easy to find; easy to understand; easy to use, share and integrate
  12. DELIVERING VALUE FROM BIG DATA BIG DATA DIVERSE DATA DYNAMIC

    DATA COMPLEX DATA NUANCED DATA IMPERFECT DATA
  13. ESA UNCLASSIFIED - For Official Use From Big Data …

    to insight Credit: www.mashable.com | Sven Sachsalber 25
  14. THE JASMIN DATA CLOUD •  Data-processing facility for environmental data

    •  In-place access to Sentinel and other environmental data
  15. “The  uniqueness  of  SHEM  is  that  it  gives  us  highly

     accurate  es9mates  of  what  a  stream   gauge  would  normally  be  sending  out  in  place  of  a  failed  gauge  when  a  flood  is  taking  place.”                  Tim  PeDy,  PhD  candidate,  University  of  Alaska,  Fairbanks   Streamflow  hydrology  es)mate  using  machine  learning  (SHEM)  project  is  a  Cortana   Intelligence  Suite  experiment  that  creates  a  predic)ve  model  that  can  act  as  a  proxy  for     streamflow  data  when  a  stream  gauge  fails.  
  16. DELIVERING VALUE FROM BIG DATA SUMMARY •  Many useful satellite

    datasets are now Open Data •  Can still be hard to access, understand and use •  Good example of a silo! •  But many possible applications for public and private sectors •  Need to turn data into services •  A lot of supporting capability is needed •  Other (contextual) data sources •  Expert knowledge •  IT infrastructure/expertise •  We want to make all of this simpler for the end user! •  What are your challenges? How could we help? •  Could we think of a feasibility study or demonstrator?
  17. DELIVERING VALUE FROM BIG DATA The Institute for Environmental Analytics

    is a unique flagship centre, formed in January 2015 with £5.6m from the HEFCE Catalyst Fund and coordinated by the University of Reading. [email protected] @Jon_Blower