GEOBIA Evolving Beyond Segmentationgeobia2014.web.auth.gr/geobia14/sites/default/files/... ·...
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GEOBIA –Evolving Beyond Segmentation
GEOBIA –Evolving Beyond Segmentation
GEOBIA 2014, Thessaloniki, GreeceKeynote Presentation – May 24, 2014
Geoffrey J. Hay (PhD)B. Hemachandran, M. Rahman, B. Karim, I. Couloigner, R. Kamberov
Foothills Facility for Remote Sensing and GIScience
Department of Geography, University of Calgary, Alberta, Canada, Email: [email protected]
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© 2014 G.J.Hay
Briefly describe GEOBIA evolution through changes to its definition.
Provide a new evolved definition of GEOBIA Provide 2 challenges to the GEOBIA Community Describe an award winning GEOBIA GeoWeb project Briefly describe 4 NEW GEOBIA technologies based on existing GIS Vector Objects
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Outline
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© 2014 G.J.Hay
How long have you been ‘involved’ in GEOBIA research?
20+ yrs? 10+ yrs? 5+ yrs? 3+ yrs? 1+ yrs?
We are a young discipline
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What is GEOBIA to You?
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© 2014 G.J.Hay 4
Brief Evolution of GEOBIA Definitions
GEOBIA
Barrysworld.biz
OBIA?
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OBIA 2006
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© 2014 G.J.Hay
Wikipedia “OBIA”: An obia (also spelt obeah)
is a monster in West African Folklore
What is OBIA?
Google “OBIA”: Offshore Biologically
Important Area Ontario Brain Injury
Association Oregon Building Industry
Association
Source: http://www.cinemastrikesback.com/news/daily/king-kong-1000-4.jpg
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© 2014 G.J.Hay
Lacking a formal definition – we made one up…
“…OBIA is a sub‐discipline of GIScience devoted topartitioning remote sensing (RS) imagery into meaningfulimage‐objects, and assessing their characteristics throughspatial, spectral and temporal scale. At its most fundamentallevel, OBIA requires image segmentation, attribution,classification and the ability to query and link individualobjects (a.k.a. segments) in space and time…”
Hay and Castilla (OBIA, 2006)
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OBIA Definition #1
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© 2014 G.J.Hay
GEO‐OBIA Tenets Earth centric: its data sources originate from
the surface of this planet Multi‐source capable: its methods provide
for the integration of many different digital data types/sources
Geo‐object‐based: geo‐object segmentationis a pre‐requisite
Multi‐scale: a scene is composed of image‐objects of different size, shape and spatial arrangement
Contextual: it has the ability or integrate‘surrounding’ information and attributes.
Adaptive: it allows for the inclusion of human semantics and hierarchical networks to generate new Geographic Information
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© 2014 G.J.Hay
“…GEOBIA is a sub‐discipline of GIScience devoted devoted todeveloping automated methods to partition remote sensingimagery into meaningful image‐objects, and assessing theircharacteristics through spatial, spectral and temporal scales,so as to generate new geographic information in GIS‐ready
format…”
Geographic Object‐Based Image Analysis (GEOBIA): A new name for a new discipline (Hay and Castilla, 2008)
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GEOBIA Definition #2
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GEOBIA 2008
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© 2014 G.J.Hay
Innovation+ transdisciplinary,
new product/solution markets
Identification+ automated object detection
+ feature extraction
Integration+ web-shared semantic models,
Geo-database architectures, bridging of RS+GIS
Interpretation+ expert rules, + semantic networks + model building
Images + multiscale, multisource
Intelligence Acquisition+ geo-content in context
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© 2014 G.J.Hay
“…GEOBIA is a sub‐discipline of GIScience devoted devoted todeveloping automated methods to partition remote sensingimagery into meaningful image‐objects, and assessing theircharacteristics through spatial, spectral and temporal scales.Its primary objective is the generation of geographicinformation (in GIS‐ready format) from which new geo‐intelligence can be obtained. Here, geo‐intelligence isdefined as geospatial content in context… ”
Forward ‐ 2010 PE&RS GEOBIA Special Issue, Hay and Blaschke (2010)
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GEOBIA Definition #3
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© 2014 G.J.Hay 13
GEOBIA 2010
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© 2014 G.J.Hay
Evolving Community Needs
Processing/Methods: BIG (LOTs of) Data Capable H‐Resolution Capable Easily implemented Automated Repeatable, Transferable,
Shared Software‐as‐a‐service…
Results: Diverse Geo‐Information
Products Validated (Error Analysis) Meaningful for Multiple
Users Web Accessible (VGI
inputs) Machine Usable – OGC
Standards
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GEOBIA 2012
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© 2014 G.J.Hay
Is GEOBIA a sub‐discipline of Geoinformatics or GIScience?
Geoinformatics has been described as "the science and technology dealing with the structure and character of spatial information, its capture, its classification and qualification, its storage, processing, portrayal and dissemination, including the infrastructure necessary to secure optimal use of this information”(http://en.wikipedia.org/wiki/Geoinformatics)
GIScience is “the science behind the systems,” it’s concerned with a set of fundamental questions raised by GIS and allied technologies (Goodchild, 1992).
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Round‐Table:GeoInformatics vs. GIScience
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Branches of Geoinformatics
Cartography
Source: http://en.wikipedia.org/wiki/Geoinformatics
Geodesy GIS
GNSS Photogrammetry Remote Sensing
Spatial Analysis
Web Mapping
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“… GEOBIA is a sub‐discipline of GeoInformatics focused on(i) developing automated methods to extract meaningfulimage‐object attributes from remote sensing imagery, (ii)assessing their multi‐scale characteristics through time andspace, (iii) and generating new geo‐intelligence (i.e.,geospatial content ‘in context’) from related multi‐sourcedatasets….”
Hay, (GEOBIA, 2014)
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GEOBIA Definition #4
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© 2014 G.J.Hay
Extract vs. Segment”… extract meaningful image‐object attributes from remote sensing imagery…”
Segmentation is an ill‐posed problem, in the sense it has no unique solution, e.g.,
Even human photo‐interpreters will not delineate exactly the same things…
Why segment if image‐objects are well represented by existing GIS vectors?
Dubé. P and G.J.Hay, 1998
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Geoffrey M. Smith and R. Daniel Morton, 2010. Real World Objects in GEOBIA through the Exploitation of Existing Digital Cartography and Image Segmentation, PE&RS Vol. 76, No. 2, Feb, pp. 163–171
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Use Existing GIS Vector Image‐Objects
Cadastral vectors overlaid 1.0 m ortho-air photography
Cadastral vectors overlaid 25 m TM imagery
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© 2014 G.J.Hay
Evolving Community NeedsInput: Earth‐Centric Multisource Capable Geo‐object‐based Multi‐scale Contextual Adaptive
Processing/Methods: BIG (LOTs of) Data Capable H‐Resolution Capable Easily implemented
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Automated Repeatable, Transferable, Shared Software‐as‐a‐service…
Results: Diverse Geo‐Information Products Validated (Error Analysis) Meaningful for Multiple Users Web Accessible (VGI inputs) Machine Usable – OGC Standards
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© 2014 G.J.Hay
Based on increasingly sophisticated user needs, and the fact that segmentation has no unique solution, we advocate …that GEOBIA segmentation technology (though not perfect) has sufficiently evolved, and challenge the GEOBIA community to:
1. Rediscover the wealth of existing high quality GIS vector data, and where appropriate use these as segmented image‐objects;
2. Redirect research towards generating geo‐web accessible ‘geo‐intelligence’.
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GEOBIA Community Challenge
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© 2014 G.J.Hay
HEAT (Heat Energy Assessment Technologies) is a Free GeoWeb service,designed to help residents (i) improve their Home Energy Efficiency,(ii) save their money, and (iii) reduce their green-house-gas (GHG)emissions by discovering their HEAT Score and visualizing the amountand location of waste heat leaving their homes and communities, as easilyas clicking on their house in Google Maps.
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Data Sets Thermal Imagery:
– 44 Flight Lines (630 GB) TABI‐1800 (Thermal Airborne Broadband Imager)
– Swath width: 1800 pix, @50 cm
– Spectral region: 3.7‐4.8 µm– Thermal res’: 0.05 C– Ability to collect up to 175 km2
per hour at 1.0 m
City Data:– The City of Calgary GIS
building layers, RGB‐NIR ortho‐photography
– MLS: Roof materials
GEOBIA:– Roof Feature Detection
24(Figure) 15 cm TABI 1800 image showing community, houses, vehicles in driveway, roof structure and tree wind shadow (April, 2011).
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© 2014 G.J.Hay 25(Figure) 15 cm TABI 1800 image showing community, houses, vehicles in driveway, roof structure and tree wind shadow (April, 2011).
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© 2014 G.J.Hay
Waste HEAT Maps – Call to Action
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Community EngagementHome owners,
rentersConstruction Companies
Real‐Estate agents
Green Service Providers
Community and City SaveHEAT Competitions.
www.andrewhuffer.com.au
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© 2014 G.J.Hay
Choice of Green Energy Service Providers
Green EnergyWind, solar, geothermal
Energy Efficient Products windows, doors, roofing
HVAC Systems
Solarphotovoltaic, hot water
Carbon Offset Purchases
Green roofsGreen Construction18
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Near Future ‐MyHEAT City ProgramI. Scale‐up and apply in
cities with populations greater than one million inhabitants;
II. Implement over time to establish monitoring programs;
III. Initiate Save‐heat competitions between and within different communities and cities.
IV. Develop solutions for the industrial, commercial and municipal building sectors
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© 2014 G.J.Hay
Near Future ‐MyHEAT City ProgramI. Scale‐up and apply in
cities with populations greater than one million inhabitants;
II. Implement over time to establish monitoring programs;
III. Initiate Save‐heat competitions between and within different communities and cities.
IV. Develop solutions for the industrial, commercial and municipal building sectors
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© 2014 G.J.HayUrban Waste Heat Plumes, G. J. Hay Calgary Feb, 2011
We estimate Total Calgary Savings (Natural Gas) of $33,564,386 and a reduction of 198,216T of CO2e per/yr
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© 2014 G.J.Hay* Alex Steffen – SXSW Eco Conference Keynote (Oct 05, 2011)
“... The great killer app of energy use: … letting people know how they’re doing
relative to others…
Comparison will change behaviours very quickly, because nobody wants to
be the outlying energy hog...”*
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Our Mission is to show 'what urban energy efficiency looks like', 'where it is located', 'what it costs' and
'what to do about it'.
HEAT Mission
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We believe that if people could see the waste heat they generate and if they knew how much it cost (financially and to the environment), that they would want to take action.
We want to show them how.
HEAT Mission
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Won from over 400 contestants world‐wide;
25 Media Interviews: Provincial, National, International;
Over 10 days received 40,343 visits, 110,962 page‐views from 1017 cities in 97 countries in 38 different languages.
Interest from 6 core sectors: (i) Energy, (ii) Banks and Investment, (iii) Residential Construction, (iv) Real‐Estate, (v) Information Technology and (vi) Governments/Municipalities
MIT – Climate CoLab2013 Grand Prize Winner
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© 2014 G.J.Hay
HEAT Maps/Metrics ‐ 44 flight‐lines of H‐Res TABI 1800 airborne imagery (630GB at 50cm and 0.05 deg. C):
1. TURN ‐ Thermal Urban Road Normalization
2. RRN ‐ Relative Radiometric Normalization (RRN)
3. OBM ‐ Geo‐Object Based Mosaicing (OBM)
4. OBGC ‐ Geo‐Object‐Based Geometric Correction (OBGC)
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4 NEW GIS‐Based Geo‐Object Technologies
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Thermal Urban Road Normalization (TURN) ‐reduces the microclimatic variability within thermal flight‐lines based on temperatures extracted from (GIS buffered) road‐objects(and interpolated from 10, 20,50 100 m samples for 825sq km).
The first instance of discrete geo‐objects (roads) being used to create continuous surfaces.
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TURN
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Relative Radiometric Normalization (RNN) ‐(automatically) samplesimage‐object groups in the overlap between flight‐lines to create non‐linear models that mitigate the between flight‐line radiometric variability
So it appears that all flight‐lines were acquired at the same time
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RRN
Rahman & Hay, 2014. A comparison of four relative radiometric normalization(RRN) techniques for mosaicing H-res multi-temporal thermal infrared (TIR)flight-lines of a complex urban scene.” In Review, RSE-D-14-00440.
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OBM
House
House
House
House
House
House
Traditional Mosaic
OBM
Geo‐Object Based Mosaicing (OBM) – uses GIS roof polygons to automatically mosaic around 14,209 individual roofs, rather than arbitrarily bisecting them along mosaic join‐lines
Resulting in improvedthermal based maps and metrics, i.e., Hot‐spot detection
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Object‐Based Geometric Correction (OBGC) – Automatically and accurately ties different high‐resolution (i.e., 25cm – 1m) images of the same location – but acquired with different spatial, spectral and temporal resolutions ‐ to 330,000+ pre‐defined GIS house‐objects.
This effectively allows GIS polygons to automatically be used as masks to extract the image information beneath them
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(OBGC)
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(OBGC)
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Shifting 29,000+ polygons in one of 9 cardinal directions
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OBGCObject‐Based Geometric Correction
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Shifting 29,000+ polygons a distance of 1 – 4+ pixels
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OBGCObject‐Based Geometric Correction
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The needs of the GEOBIA community are evolving Our definitionmust also evolve to guide these changes Segmentation is problematic Propose 2 Challenges to the GEOBIA Community:
1. Rediscover the wealth of existing high quality GIS vector data, and where appropriate use these as segmented image‐objects;
2. Redirect research towards generating geo‐web accessible ‘geo‐intelligence’
The HEAT project is an award winning GEOBIA GeoWeb project that incorporates 4 NEW GEOBIA technologies based on existing GIS Vector Objects to generate new Geointelligence (geospatial content in context).
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Conclusion
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HEAT TEAM Members (Current): (PI) Geoffrey J. Hay (PhD,Geography, ISEEE Fellow) Bharani Hemachandran (MSc) Mustafiz Rahman (PhD Candidate, Geog) Bilal Karim (MSc Candidate, Geog) Rustam Kamberov (PhD Candidate, Geog) Isabelle Couloigner, (Research Associate, Fr.Ing, PhD) Wen Cao, (Research Associate, MSc ComSci) Tak S. Fung (PhD, Math ‐ Statistics) Joseph L. Arvai (PhD, ISEEE ‐ Decision Support) Tang Lee (PhD, EVDS ‐ Building Envelope/Efficiency) Joule Bergerson (PhD, ISEEE – Life Cycle Analysis/Modeling)
Acknowledgements
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© 2014 G.J.Hay
GEOBIA is much more than segmentation The needs of the GEOBIA community are evolving Our definitionmust also evolve to guide these changes Segmentation is problematic We Challenge the GEOBIA Community to
1. Rediscover the wealth of existing high quality GIS vector data, and where appropriate use these as segmented image‐objects;
2. Redirect research towards generating geo‐web accessible ‘geo‐intelligence’
The HEAT project is an award winning GEOBIA GeoWeb project that incorporates 4 NEW Geo‐Object Based technologies based on existing GIS Vector Objects
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Conclusion