This presentation was given at FOSS4G NA 2019 by Ross Bernet and Jacob Bouffard from Azavea.

1. How FOSS4G can Support the Sustainable
Development Goals (SDGs)
Ross Bernet
Project Manager
@rosszb
FOSS4G-NA | April 16, 2019 | @azavea
Jacob Bouffard
Software Engineer

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Advance the state of the art in geospatial
technology and apply it for civic, social
and environmental impact.
Our Mission

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This That

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SDGs
● Goals
● Targets
● Indicators

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SDGs + FOSS4G

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SDGs + FOSS4G

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SDGs
15.1.1 Forest area as a
proportion of total land area

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SDGs
14.5.1 Coverage of protected
areas in relation to
marine areas

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SDGs
11.7.1 Average share of the
built-up area of cities that
is open space for public use for
all, by sex, age and
persons with disabilities

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SDGs
9.1.1 Proportion of the rural
population who live
within 2 km of an all-season
road

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SDG - Goal
● Goal 9: Industry, Innovation, and Infrastructure

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SDG - Goal
● Goal 9: Build resilient infrastructure, promote
inclusive and sustainable industrialization and
foster innovation

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SDG - Target
● 9.1 Develop quality, reliable, sustainable and resilient
infrastructure, including regional and trans-border
infrastructure, to support economic development and
human well-being, with a focus on affordable and equitable
access for all

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SDG - Indicator
● 9.1.1 Proportion of the rural population who live within 2
km of an all-season road

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How are the SDGs
being monitored now?

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How are the SDGs
being monitored now?
● Tier system
● Tier 1
● Clear, established
methodology
● Data is regularly produced
for 50% of countries
● Tier 2
● Clear methodology
● Data are not regularly
collected by countries
● Tier 3
● Methodology is not
established

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How are the SDGs
being monitored now?
● Tier system
● Custodian Agencies

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How are the SDGs
being monitored now?
● Tier system
● Custodian Agencies
● National Statistic
Offices

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UN Global Platform
Powered by Raster Foundry
Geospatial data hub for UN
statistics offices, managed by
the UK Office of National
Statistics

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Raster Foundry
Discover, combine and analyze
earth imagery data
Use public datasets or upload
aerial, drone or commercial
imagery
Create and run analysis
pipelines like NDVI

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SDG 9.1.1
● Roads
● Population
● Rural Boundary
Proportion of the rural population who
live within 2 km of an all-season road

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SDG 9.1.1
● OpenStreetMap
● NASA GPWv4
● GRUMP

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Opportunities
● Global benchmark
● Increase participation
● Transparency

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Challenges
● Definitions
● Data quality
● Methodology

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Calculating the SDG for
South America

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Questions We Asked Ourselves

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Questions We Asked Ourselves
● How do you read and format OSM data?

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Questions We Asked Ourselves
● How do you read and format OSM data?
● How do you calculate the SDG?

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Questions We Asked Ourselves
● How do you read and format OSM data?
● How do you calculate the SDG?
● What format should the saved data be in?

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Questions We Asked Ourselves
● How do you read and format OSM data?
● How do you calculate the SDG?
● What format should the saved data be in?
● How can we do all of the above at scale?

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Reading in OSM Data

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Apache Spark
● Distributed Framework
● API around working
with distributed
datasets
● RDDs and DataFrames

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VectorPipe
A Vector Processing Library

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VectorPipe
● A Scala library for processing OSM data

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VectorPipe
● A Scala library for processing OSM data
● Uses Spark, GeoTrellis, and Geomesa

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GeoTrellis
A Scala GeoSpatial Library

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GeoTrellis
● Distributed GeoSpatial
Processing Using Spark
● Mostly supports Raster data
● Wraps JTS for Vector
support
● Supports VectorTile reading
and creation

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VectorPipe
● A Scala library for processing OSM data
● Uses Spark, GeoTrellis, and Geomesa
● OSM Data => Spark DataFrame

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VectorPipe
● A Scala library for processing OSM data
● Uses Spark, GeoTrellis, and Geomesa
● OSM Data => Spark DataFrame
● JTS Geometries => VectorTiles

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VectorTiles
● Standardized data format
for displaying Vector data
● Allows for quick and
responsive maps
● Can be stylized

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We can calculate SDG entirely from
open data and software.

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The Workflow

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Reading in OSM Data

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Reading in Population
Data
● Data was already ingested
● Saved to S3
● Will be masked by
geometries to determine
population count

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Formatting and Filtering OSM Data

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Removing Invalid
Geometries
Invalid
Valid

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Splitting Geometries
by Country
Brazilian
Road
Uruguayan
Road

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Buffering Geometries
(X, Y)
Original
Geometry
Find Central
Point
Reproject to
UTM
Buffer by 2
km

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Calculating the SDG
Values

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Clipping Geometries

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Clipping Geometries
(0, 0)
(0, 1)
(0, 2)
(0, 3)
(1, 0)
(1, 1)
(1, 2)
(1, 3)
(2, 0)
(2, 1)
(2, 2)
(2, 3)
(3, 0)
(3, 1)
(3, 2)
(3, 3)
(4, 0)
(4, 1)
(4, 2)
(4, 3)

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Clipping Geometries
(2, 1)
(2, 2) (3, 2)

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Clipping Geometries

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Saving Our Results

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Saving the DataFrame
● The processed DataFrame will
be saved as an orc to S3
● Provides an efficient way to
aggregate data
● Can query data for later use

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Saving as VectorTiles

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Filtering Geometries By
Zoom Level
● Aggregate roadType by zoom
level
● Higher zoom levels contain
more detail
● Required for improved
performance
Zoom
Level

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Filtering Geometries By Zoom Level

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And Now to Show Off the
VectorTiles

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Link to demo

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Whats next?

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Open questions
- Is global, public data good enough to
measure SDGs?
- What role do private companies have in
SDG monitoring?
- http://sdgfunders.org/sdgs/

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How might you be able to get involved?
- Your work may already align with SDGs
- Contribute to OSM
- Read up on SDGs - do you know of
open datasets that can be helpful?

70. Thank you!

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74. Thank you!