mapping the next - mapping for the sustainable development agenda

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Dr. Mark Iliffe @markiliffe Geospatial Lead, N-LAB MAPPING THE NEXT: MAPPING FOR THE SUSTAINABLE DEVELOPMENT AGENDA

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Page 1: Mapping the Next - Mapping for the Sustainable Development Agenda

Dr. Mark Iliffe@markiliffe

Geospatial Lead, N-LAB

MAPPING THE NEXT:MAPPING FOR THE SUSTAINABLE DEVELOPMENT AGENDA

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1990 2000 2010 2020 2030 2040 -

200

400

600

800

1,000

1,200

African population growth

Urban RuralPo

pula

tion

(mill

ions

)

Rapid Urbanization and Unplanned Growth Brings ChallengesDar es Salaam Context

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Rapid Urbanization and Unplanned Growth Brings ChallengesDar es Salaam Context

Traffic Congestion

Solid Waste & Waste Water management

Safe Drinking water

Youth employment

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5.5 Million

People

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To end poverty, protect the planet, and ensure prosperity for allSustainable Development Goals

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“We also call for a data revolution for sustainable development, with a new international initiative to improve the quality of statistics and information available to citizens. We should actively take advantage of new technology, crowd sourcing, and improved connectivity to empower people with information on the progress towards the targets. “

The Report of the High-Level Panel of Eminent Persons on the Post-2015 Development Agenda, United Nations

Development Agenda 2015 - 2030

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“embrace open data and standards, innovative and creative approaches and platforms that are fit-for-purpose to collect and collate, share and distribute geospatial information”

“ ”

2016 UNGGIM Addis Ababa Declaration

Future Policy FrameworksData Requirements

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SDG Goal 11: Make cities inclusive, safe, resilient and sustainableDar es Salaam: Rapid and Unplanned Growth

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Hazard, Exposure, Vulnerability and RiskTypical Data Requirements

Hazard Analysis:• Elevation Model

• Land Use/ Land Cover

• Drainage network

• Rainfall Intensity Duration frequency

Exposure mapping:• Buildings, Roads

• Critical facilities

• Population distribution day/night

Vulnerability Assessment• Disabled

• Livelihoods

• Shelter access

• Early Warning

Hazards

Exposure

Vulnerability

Risk

+

+

+

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ChallengesData Requirements

Insufficient Data• Elevation Model 5% areas LIDAR 30cm

• Lack of Met data

• Rapid Hydrodynamic changes

Informal Data• 80% Unplanned Growth

• Inconsistent census and admin boundary data

Socio-Cultural Factors• Informal economy / livelihoods

• Rentals

Local Capacity• Data Management

• Data Analysis

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Research

Directions and Opportunities Geospatial Research

CROWDSOURCINGREMOTE SENSINGPOLICYDATA-DRIVEN DEVELOPMENT

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Crowdsourcing in Dar es Salaam: Ramani HuriaCase Study

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2011 Pilot in Tandale showed that Student and Citizen can be a source of Useful DataHow we Started

Collect very Local Data – eg. drain type, business types, etc

Fast changing features – eg. rubbish sites, flooding areas

Citizen can voice Issues on the map – eg. children play areas

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Citizen Data in Dar es Salaam: Ramani HuriaRamani Huria

In September 2011 25 Town Planning Students worked with 25 community members to map Tandale Ward in 3 weeks

August 2011 September 2011

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Mapping Campaigns in Dar es SalaamRamani Huria

Started March 2015: 165 Students, 100+ Community Members, 100 Red Cross Volunteers

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Citizen Data in Dar es Salaam: Ramani HuriaRamani Huria

Goal: 1 million residents in flood prone vulnerable communities / Currently:• Target Areas: 2012 Population: 1,127,729• Target Areas: 2015 Population est: 1,296,888 (~15% Growth)

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Mapping Outputs in Dar es SalaamRamani Huria

160,000 Building Footprints, 500km+ of waterways, rivers and drainage, 1000s of toilets, water points

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Target Areas: 2012 Population: 1,127,729 | Target Areas: 2015 Population est: 1,296,888 (15% growth)

Mapping Outputs in Dar es SalaamRamani Huria

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Tandale and Ndugumbi Wards, Kinondoni MunicipalityRamani Huria

Before

(August 2015)

After

(October 2015)

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Using Participatory Mapping with Students, Citizens and Ward OfficesKey Advantages

Affordable Data Collection for local level – approx. $10,000 per ward

Hyper-local details – trees, businesses, water points, facilities, drains

Community Context – digitizing critical features for citizens

Culture of participating in mapping strengthens relationship of officials with community

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Case Study

Remote Sensing

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Low Cost Mapping DronesRemote Sensing

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Aerial Imagery, UAV Comparison

UAVs

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Using UAVs for Urban MappingKey Advantages

Simple & Affordable – approx. $1,000 for phantom, $25,000 for ebee – low running costs

High resolution – up to 3cm Basemap, 8cm Elevation model

Timeliness – can choose exact day of mapping to suit project needs for baseline

Cloud free – advantages over satellite and manned aircraft as drone fly under clouds

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Participatory Inundation Modelling: Mapping Risk Reduction PrioritiesCase Study

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Mapping Risk Reduction Priorities: Participatory Inundation ModellingMaps as a Platform

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Mapping Risk Reduction Priorities: Participatory Inundation ModellingMaps as a Platform

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Mapping Risk Reduction Priorities: Participatory Inundation ModellingMaps as a Platform

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Fusing Data StreamsRamani Huria

• 745,989 Building Footprints

• 88km of Imagery and Surface Models

• 2091km of Roads

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Low Cost Mapping DronesCitizen Data

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Fusing Hydrological Models with Participatory MappingMaps as a Platform

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Mapping Risk Reduction Priorities: Participatory Inundation ModellingMaps as a Platform

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Geospatial Policy DevelopmentPolicy and Process

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Assessing Public PolicyMaps as a Platform

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Assessing Public PolicyMaps as a Platform

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Zanzibar Mapping InitiativeBuilding a Geospatial Platform

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• Creating a map of Zanzibar Islands at very high resolution, released as open data

• Introduction of a cost effective technology for land monitoring

• Building different projects around the data (Conservation, Land tenure, Urban Planning, etc…)

• Local Capacity Building• Increasing the efficiency in data colection from

the Commission of Lands• Creating opportunities for new local businesses

to develop around the technology

Zanzibar Mapping InitiativeBuilding a Geospatial Platform

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• 9 drones are deployed in 3 different teams of local operators

• 2 power full computer for processing data at a high speed

• 3 field computers for flight planning and control• NAS for storing over 10TB of Data• 2’400sq/km to map• 239 zones unguja and 182 in Pemba• 3 teams of 4-5 composed of local surveyors with

support of students of State University of Zanzibar• Mission kick-off August 15th 2016 for 2 months

Equipment, Team and MissionBuilding a Geospatial Platform: Zanzibar Mapping Initiative

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ScopeBuilding a Geospatial Platform: Zanzibar Mapping Initiative

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• Each grid covers an area of 3km x 3 km (9km²). • In optimal conditions (no wind), one zone can be covered in 6 flights (at a GSD= 7

cm).• In order to facilitate data management, each grid has been assigned a unique Zone

ID.• There are currently 239 zones in Unguja and 182 Zones in Pemba. In the future, it will

be possible to add more zones. Important is to keep the Zone_ID as a unique identifier.

• This has been done in order to manage size of data per square and being able to work with it.

ScopeBuilding a Geospatial Platform: Zanzibar Mapping Initiative

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ZanzibarBuilding a Geospatial Platform

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Urban PlanningBuilding a Geospatial Platform

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3D ModelsBuilding a Geospatial Platform

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Building Volume CalculationBuilding a Geospatial Platform

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Land TenureBuilding a Geospatial Platform

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Towards Sustainable SkillsBuilding a Geospatial Platform

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ERS&ENV S1

• Before • AfterSupporting ResponseBukoba Earthquake

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ERS&ENV S1

Level of Change potential damage areas

0 very low

1 very high

Change detection analysis over BukobaBukoba Earthquake

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Working with a Global Mapping CommunityBukoba Earthquake

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Machine LearningBuilding a Geospatial Platform

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Discrepancy between distributions hypothesized to be due to large repairs on metal rooftops, which the algorithm detects as individual buildings.

Machine LearningBuilding a Geospatial Platform

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Participatory MappingKey Challenges

Coordination: Mix of Universities, COSTECH, City and Disaster Management Department UAV

Permits: require Ministry of Defense, Lands and Survey, Aviation Authority

Data Processing: flying is easy, processing takes trial and error for good outputs

Community Mapping: low cost but labour intensive – relies on steady supply of students

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Research as a PlatformTowards

In an analogue world, policy dictates delivery.In a digital world, delivery informs policy.“ ”

Mike Bracken

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An Agenda for Mapping the NextTowards

Policy and legislation for government use of citizen generated open data

Outreach to policy/decision makers on how ‘maps’ can provide efficiency

Optimize local and international communities with new forms data and methods

Mapping where there are no opportunities for maps – NeoDemographics

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Dr Mark Iliffe@markiliffe

THANK YOU