Quanti-litative Revolution in GIS
Pre-NextLab
Licence in Maths, ULg
Licence in Computer Sciences, ULg
Geospatial specialization, ULg
Many years in GIS (Ionic Software and its mutations)
Always in data management and semantic
New technologies enthusiast
NextLab age
Project in GIS for the SPW
Project in IoT for Virdata
Wrote a book about Play! 2
Open data evangelist (OKFN, ...), Big Data speaker
Distributed Computing + Distributed Machine Learning expert
Wajug co-founder | Devoxx4Kids organizer
And the list goes on... and on...
@Noootsab
@NextLab_be
Qualitative GIS
Coined in 1963
Raster
vulgus: Big Fat MultiBand Images
- SPOT (see later)
- IKONOS (greek: image)
- LANDSAT
- ALOS
- QuickBird: resolution 64cm → 2m44cm
Vector
vulgus... nah, vector
- Feature extraction
- Landmeters (rare)
- Field surveying
- ~GPS (GNS)
hence, Producers were...
Govs!
thus, Users were
Govs!
Oh yeah, researchers as well... huh!? wait!
Okay, very feeeew privates
in consequence, Analyses were
- Performed by experimented folks...
- ... or nerds
finally, Tools were...
You don't even know them!
ESRI, Oracle Spatial,
OGC, RedSpider (yeah), ...
Qualitative GIS
"Started" around 2000
Actually, not really before 2010
GIS Revolution
Induce theories from data
The river has flooded on 3km
The river will flood if it rains more than...
New producers
Google, 4², OSM, GPS
old: Mappy, Michelin, ...
New Users
Devs, Lambda
Billioooooons
Analyses
Routing, Accurate GWR¹, ...
Disaster prediction, flood prevention, crash probability, ...
¹Geospatial Weight Regression
Tools?
User friendly and/or Open Source
OSM
GeoServer
Google Maps
OpenLayers
Quantilitative GIS
Coined by @Noootsab^^
WTF?!
Questions
Data
Hypotheses
Rasters today (f.i. Spot7)
- Red Green Blue + Near Infra Red Bands
- One shot: 60x60km (3.600 sq km)
- Takes 3.600.000 sq km of geodata per DAY
- Resolution 2 satellites at 1.5m and 2 others at 50cm
- Revolution: 110 minutes
- 26 days to complete the geoid (all pieces of crap covered)
- 1 single f*****g file for a 60x60km tile is worth up to
12Gb
Vector (mostly position)
- Twitter, Facebook, ...
- Foursquare, Instagram
- Waze
- Google (in its whole)
- Connected Devices
everywhere and everytime
Presidente
Model-Driven
Deductive
Top-Down
Quantitative
Lagged Time
Commandante
Data-Driven
Inductive
Bottom-Up
Qualitative
Real Time
GIS Putsch
Marcelino
Data Lake
Machine Learning
Variety
Value
Velocity
VOLUME? It was there for ages!
Who, What, How
You thought I was joking, huh!
Socrata
Evan Chan using Spark
- Customers have streaming point data (many millions of rows)
- PostGIS: point-in-polygon and other does not scale
Soluce:
- Partitioning point data in Cassandra (tiling, Z-curve)
- Partitions into Spark for quick analysis
- Adding spatial indexes to Spark for speeding up
Azavea
Rob Emanuele on Geotrellis
- Run distributed model on 200 TB of climate data against daily temperature and precipitation data out to 2009
- Create suitability maps over high-res raster layers spanning the entire continental US for Urban Forestry Modeling.
Soluce:
- GeoTrellis is providing Spark with geospatial capabilities.
- Ingest, mosaic and pyramid raster data into Accumulo or HDFS for fast (sub-500ms) tile fetching
Snips
Rand Hindi in his Labs
- Tranquilien: Predicting seating availability in public transport
- RiskContext: Determining the risk of bicycle and car accident from context
Soluce:
- Using blazing fast technologies that can scale linearly (Akka, Scala)
- Thanks to the bottom up reactivity of the architecture, the clusters keeps crunching data in a resilient manner
Done!
Thx & cu on Twitter
@noootsab
@NextLab_be
Quantilitative Revolution in GIS
By andy petrella
Quantilitative Revolution in GIS
Talk to be given in the context of SpaceTech event organized byt the Café Numérique Liège the 8th of October 2014. Ref. http://www.cafenumerique.org/liege/event/space-tech/
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