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Venue: Shed 6, 4 Queens WharfTe Aro, Wellington
BRINGING DATA TO LIFE: APPLYINGGEOAI AND GEOBI IN LOCAL GOVERNMENT
O R B I C A . W O R L D
FROM NEW ZEALAND TO EUROPEINTRO TO ORBICA
Our purpose is simple.
“To enhance a billion
lives through the power
of geography.”
CONSTANTLY THINKING OUTSIDE THE QUADRILATERALMEET THE ORBICANS
KURT JANSSENCEO & Founder
NEAL JOHNSTONLocation Data Specialist
ANTONIN CAENGeospatial Architect
FAISAL ABBASGeospatial Craftsman
LOUISA TAYLORCommercial Manager
SANTOSH SESHADRIGeospatial Innovator
BRIDGET EDWARDSChief Financial Officer
SUVARNA DUDAMIT Specialist
WILL JONESLocation Data Specialist
SAGAR SONIData Scientist (AI)
ROB PARSONSGeospatialist
VANESSA O’BRIENCommunications Manager
PETER ROSEDirector (Europe)
BANIKA SIROHIFull-stack Developer
SUNNY SUNGeospatial Developer
LAURA WINDERSPA/team support
RIMU BODDYFull-stack Developer
PHIL CLUNIES-ROSSFreshwater Scientist
JUSTIN FAILService Delivery Manager
SAKINAH ABDULFull-stack Developer
SAM DAVIDSONJunior data scientist
KURT JOYRemote Sensing Specialist
ARTHUR MCGREGORFull-stack Developer
BRONWYN ASHBYEmployee Experience Manager
EXTRACTING VALUE FROM DATADATA DATAEVERYWHERE
• We’re getting better at collecting data• But less than 0.5% of data is analysed or has
intelligence extracted from it
EXTRACTING VALUE FROM DATADATA VISUALISATION
EXTRACTING VALUE FROM DATADATA VISUALISATION
• Empower you to tell the story of your data so that end users can understand it and make informed decisions
• Engage with your community• Visually communicate multi-level data in an
interactive, easy-to-understand way
We’ve found that smart, interactive data visualisations…
AT THE INTERSECTION OF MAPS, BI AND STORY-TELLINGGEOBI
WHAT IS GeoBI?
CASE STUDY https://rates.ecan.govt.nz/
OBJECTIVE: To enable ECan to visually tell the story about the portfolios and projects its rates’ collection funds.
Environment Canterbury rates’ tool
CASE STUDY https://rates.boprc.govt.nz/ratescalculator/
OBJECTIVE: To enable BOPRC to visually tell the story of the portfolios that rates fund, to enable rate payers to visualise their personal rates break-down and to get feedback on proposed spend.
Bay of Plenty Regional Council rates’ calculator
CASE STUDY https://geo.orbica.world/YourRates/
OBJECTIVE: To enable WDC to visually tell the story of the portfolios that rates fund, and to enable rate payers to visualise their personal rates break-down.
Waimakariri District Council “Your Rates”
https://ptadvocacy.casey.vic.gov.au/TRANSPORT GeoBI
OBJECTIVE: To deliver insight into the inequality of public transport across Melbourne’s South East
City of Casey: Public transport accessibility
OUTCOMES
➢ Customer experience➢ Engagement➢ Transparency➢ Understanding ➢ Relevance
WHAT GEOBI ACHIEVES
FEATURE EXTRACTIONGeoAI
WHAT IS GeoAI?
EARTH OBSERVATIONGeoAI
THE EARTH OBSERVATION AGE IS HERE, AND IT’S CHANGING THE WAY WE LIVE
BIG DATAGeoAI
Earth observation data – BIG data - is increasing exponentially… and fast
REAL INFORMATION, REAL TIMEGeoAI
TRANSFORMING DATA INTO INSIGHT, IN NEAR REAL TIME, CREATES VALUE
Construction progressreporting
Environmental change
Disaster management
Urban development
Market identification
FEATURE EXTRACTIONHOW BIG IS THE DATA?
CANTERBURY
FEATURE EXTRACTIONAUTOMATED METHODOLOGY
ORBICA’S SOLUTION: AUTOMATION
AI AND FEATURE EXTRACTIONDEEP LEARNING
A programme that can sense, reason, act and adapt
Algorithms whose performance improve as they are exposed to more data over time
Subset of machine learning in which multi-layered neural networks learn from vast amounts of data
TRANSFORM LOCATION DATA INTO SOLUTIONSRESULTS – Water Extraction
➢ RGB (3 band ONLY)
➢ 12,000 by 8,000 pixels.
➢ 96 million individual
pixels per image
➢ 30cm ground resolution
➢ Raw results displayed.
No clean-up or Passover
filters or geoprocessing
operations have been
applied.
TRANSFORM LOCATION DATA INTO SOLUTIONSRESULTS – Building Extraction
➢ RGB (3 band ONLY)
➢ 4,800 by 3,200 pixels
➢ 15 million individual
pixels per image
➢ 7.5cm ground resolution
➢ Raw results displayed.
No clean-up or Passover
filters or geoprocessing
operations have been
applied.
AI AND FEATURE EXTRACTIONHOW IT WORKS
GeoAI in action
VECTOR BASED AI
Feature Engineering
• Area
• Perimeter
• Elevation (min,max,diff)
• Area to length Ratio
• No of Nodes
• Avg of polygon width
GIS Data
and
Imagery
Deep Neural Networks (AI)
TRANSFORM LOCATION DATA INTO SOLUTIONSWHAT ORBICA DOES
Training Accuracy
(LINZ)
99.00 %
(67742 / 68423)
Testing Accuracy
(Canterbury Maps)
95.82
(5896 / 6153)
CANALs vs. RIVERS
TRAINING DATA & BIAS
When is a lake a
pond and vice
versa?
FROM DRONE IMAGES TO 3D MODELSBUILD PROGRESS
BUILD
MEASURE
LEARN
FROM DRONE IMAGES TO 3D MODELSACTUAL PROGRESS
FROM DRONE IMAGES TO 3D MODELSACTUAL PROGRESS
FROM DRONE IMAGES TO 3D MODELSACTUAL PROGRESS
https://demos.orbica.world/ECAN/GrassSwipe/GeoAI AND REMOTE SENSING
OBJECTIVE: To obtain accurate estimates of ground cover percentages for living vegetation, dead vegetation and bare ground (rock and soil) in historical high-county imagery.
High-Country ground cover classification
https://demos.orbica.world/ECAN/GrassSwipe/GeoAI AND REMOTE SENSING
https://demos.orbica.world/LandMonitor/GeoAI AND REMOTE SENSING
OBJECTIVE: A web platform for observing land use change utilising Sentinel 2 satellite imagery
OrbEx
GeoAI AND REMOTE SENSING
OBJECTIVE: To define the extent of the Himalayan Tahr through probability modelling using geographic information systems, remote sensing and machine learning.
Tahr project
GeoAI
Absence Points
Presence Points
GDAL
Training Data
Machine Learning(Classify/Predict)
Python Scikit-LearnSaga GIS
Topography
Ecosystem Climate
Spectral
Model Output
Multiple Linear Regression
Logistic Regression
Random Forest
Future Observations
Geographically Weighted Regression
GDALCovariates
GeoAI
• Logistic Regression • Multiple Regression
ASK US YOUR QUESTIONSTHE FUTURE
A FUTURE OF EXPERIENCE, INNOVATION AND CREATIVITY
Let the magic begin…
KURT JANSSENCEO & Founder
kurt@orbica.world
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