1. AGENDA ITEM 5.2:
COST EFFECTIVE TOOLS FOR DATA
COLLECTION
Valerie Bizier, Capacity Development Coordinator, FAO
Lars Gunnar Markland, Forestry Officer, FAO
Cristina Ribeiro, Consultant, FAO
Michael Rahija, Statistician, FAO
African Commission on Agriculture Statistics / Commission africaine des statistiques agricoles
Entebbe, Uganda, 13 - 17 Nov 2017
2. TABLE OF CONTENTS
• Rationale
• Cost effective tools for data collection
• Adoption of an integrated approach for data
collection
• Computer Assisted Personal Interviewing
Tools
• Geospatial Tools
• Other innovative technologies for fisheries
statistics
3. RATIONALE
• 232 SDG indicators
• Sustainable Development Solutions Network
(SDSN) estimates the cost at 1 billion USD for
monitoring only a subset of core indicators in 77
LIC countries
• As of 2015, the gap between donor and national
contributions was between 100 and 200 millio.
• FAO is the custodial agency for 21 SDG indicators,
and bares a responsibility to strengthen national
capacity
4. INTEGRATED APPROACH FOR DATA COLLECTION
• Making adequate use of resources through SPARS
and NSDS design and implementation
• Integrating data sources from surveys,
administrative registers and geospatial tools
• Adopting Integrated Survey Programs such as AGRIS
• Piggy-backing on existing surveys (HBS, LSMS, LFS,
DHS, MICS,...) rather than starting new survey
operations, in particular for FAO specific modules
on:
o Food Insecurity Experience Scale (SDG 2.2.1)
o Gender and Land Tenure (SDG 5.a.1)
5. INTEGRATED APPROACH FOR DATA COLLECTION
SDG 2.1.2
Prevalence of
moderate or severe
food insecurity in
the population,
based on the Food
Insecurity
Experience Scale
(FIES)
http://www.fao.org/in-action/voices-of-the-hungry/fies/en/
6. INTEGRATED APPROACH FOR DATA COLLECTION
SDG 5.a.1
(a) Proportion of total
agricultural population
with ownership or secure
rights over agricultural
land, by sex;
(b) share of women
among owners or rights-
bearers of agricultural
land, by type of tenure
More info available at: availablhttp://www.fao.org/sustainable-
development-goals/
7. COMPUTER ASSISTED PERSONAL INTERVIEWING
Barriers to adoption
1) the initial investment related to the acquisition of the
necessary equipment and technology
2) the extent of capacity-building required to assist
statistical agencies to adapt to this technology
9. COMPUTER ASSISTED PERSONAL INTERVIEWING
General CAPI Tools
• Global Strategy supported
Survey Solutions
• Addresses shortcomings of
other software suites
• Less training, more features,
and continuous
improvements
• Used in more than 100
countries for around 500
surveys
10. COMPUTER ASSISTED PERSONAL INTERVIEWING
Capacity Development Efforts
• Global Strategy to Improve Agricultural and Rural
Statistics
• Regional workshops in Asia and Africa during 2016-2017
• Country level assistance on specific surveys and training in
Asia and Africa.
• 10 Module E-learning course and training material for in-
classroom training available at www.gsars.org.
• Network of trainers and technical assistance providers
• World Bank Surveys and Methods Team
• Various workshops throughout the world on household
surveys.
• https://support.mysurvey.solutions
12. GEOSPATIAL TOOLS
Global Positioning
Systems
• time-saving and
more objective
area measurement
method compared
to the rope and
compass method
Source: LSMS Handbook on Land Area
Measurement. World Bank. 2016
14. GEOSPATIAL TOOLS
Remote Sensing
• Land cover mapping and
monitoring
• Designing Sampling
Frames (Area Frame) and
Improving Sampling
efficiency
• Classification and mapping
• Estimation and Forecasting
www.gsars.org
15. GEOSPATIAL TOOLS
FAO New tools for data collection and reporting
• SEPAL
• Open Foris Toolbox and Collect Earth
16. AFCAS25, Entebbe, Uganda 13-17 Nov 2017
www.fao.org/forestry
SEPAL
System for Earth Observation Data Access, Processing and Analysis for
Land Monitoring
Objectives
Improve data access and delivery of (pre)processed satellite data and
forest information products to enable developing countries to build the
autonomous capacity to monitor their forest-related REDD+ activities
GEOSPATIAL TOOLS - SEPAL
17. What is SEPAL?
• SEPAL is an open source cloud-based platform for land
monitoring
• Easy query, access and processing of satellite data
• Expandable with user scripts
• A ‘barrier buster’: Analysis Ready Data, Supercomputing
power, Maintenance and Dependencies
GEOSPATIAL TOOLS - SEPAL
18. What can be done with SEPAL?
• Create composites / mosaics of Landsat and Sentinel
• Process RADAR data
• Classification and change detection
• Image segmentation
• Time-series analysis
• Sample-based area estimation
• Compliant with GFOI Methods and Guidance
GEOSPATIAL TOOLS - SEPAL
19. How can SEPAL assist in monitoring the SDGs?
• Can be used by countries to obtain better data for
15.1.1 and 15.2.1
• Can be used for any other indicators that use satellite
imagery, as it includes much more image processing
capabilities than Collect Earth which is a visual
interpretation tool
GEOSPATIAL TOOLS - SEPAL
23. How can Collect Earth assist in monitoring the SDGs?
• Can be used to calculate indicator 15.4.1 and some
sub-indicators of 2.4.1
• Can be used for any other indicators that can be
derived from visual interpretation of high resolution
satellite imagery
GEOSPATIAL TOOLS – COLLECT EARTH
26. Collect Earth
an open tool for augmented visual interpretation
Spatial dimension
Temporal dimension
Combining Very High spatial and temporal resolution data
GEOSPATIAL TOOLS – COLLECT EARTH
27. OTHER INNOVATIVE TOOLS FOR FISHERY STATISTICS
IT partnerships for innovative technologies
Catch statistics with
• Higher species breakdown
• Known geographic distribution
• Consistent time series
Stock assessment and SDG reporting
• Training more accessible and efficient
• Data services for monitoring of stock status
Objectives
Effort statistics
• More available with geographic breakdown
• For better estimation of CPUEs
Fishery statistics
• Integrated and harmonized
• Ease of reporting
SDG 14.4.1 – Capacity Development/Technical Assistance
28. OTHER INNOVATIVE TOOLS FOR FISHERY STATISTICS
IT partnerships for innovative technologies
Catch statistics with
• Higher species breakdown
• Known geographic distribution
• Consistent time series
Stock assessment and SDG reporting
• Training more accessible and efficient
• Data services for monitoring of stock status
Objectives
Effort statistics
• More available with geographic breakdown
• For better estimation of CPUEs
Fishery statistics
• Integrated and harmonized
• Ease of reporting
SDG 14.4.1 – Capacity Development/Technical Assistance
FAO Mobile for data collection (SmartForms)
29. OTHER INNOVATIVE TOOLS FOR FISHERY STATISTICS
IT partnerships for innovative technologies
Catch statistics with
• Higher species breakdown
• Known geographic distribution
• Consistent time series
Stock assessment and SDG reporting
• Training more accessible and efficient
• Data services for monitoring of stock status
Objectives
Effort statistics
• More available with geographic breakdown
• For better estimation of Catch per Unit Effort
Fishery statistics
• Integrated and harmonized
• Ease of reporting
SDG 14.4.1 – Capacity Development/Technical Assistance
FAO - Google Earth Engine
FI - Global Fishing Watch
30. OTHER INNOVATIVE TOOLS FOR FISHERY STATISTICS
IT partnerships for innovative technologies
Catch statistics with
• Higher species breakdown
• Known geographic distribution
• Consistent time series
Stock assessment and SDG reporting
• Training more accessible and efficient
• Data services for monitoring of stock status
Objectives
Effort statistics
• More available with geographic breakdown
• For better estimation of CPUEs
Fishery statistics
• Integrated and harmonized
• Ease of reporting
SDG 14.4.1 – Capacity Development/Technical Assistance
FAO software Fmk for country use
iMarine data infrastructure (EU-H2020)
Integrated national information systems
Data sharing in repositories
Data harmonization
Data aggregation
31. OTHER INNOVATIVE TOOLS FOR FISHERY STATISTICS
IT partnerships for innovative technologies
Catch statistics with
• Higher species breakdown
• Known geographic distribution
• Consistent time series
Stock assessment and SDG reporting
• Training more accessible and efficient
• Data services for monitoring of stock status
Objectives
Effort statistics
• More available with geographic breakdown
• For better estimation of CPUEs
Fishery statistics
• Integrated and harmonized
• Ease of reporting
SDG 14.4.1 – Capacity Development/Technical Assistance
iMarine data infrastructure (EU-H2020)
VRE
32. SDG 14.4.1 – Capacity Development/Technical Assistance
IT partnerships for innovative technologies
On-line Stock Monitoring Tools for Limited Data
FAO GUI is currently being developed to host online interactive
assessment methods to estimate stock status; methods include:
- CMSY (estimating the maximum sustainable yield for a
marine species in a certain area)
- ELEFAN (estimating growth and mortality parameters)
- Mean length mortality estimator and Yield per recruit
modelling.
Estimating the Reference Points to support Monitoring
SDG 14.6.1
OTHER INNOVATIVE TOOLS FOR FISHERY STATISTICS
33. PANEL QUESTIONS
• What emerging tools to reduce the cost of data
collection has your country implemented or is
thinking of implementing?
• What are the main challenges in implementing
these tools and how FAO can help countries to
adopt them?
34. FOR MORE INFORMATION, PLEASE CONTACT:
MICHAELAUSTIN.RAHIJA@FAO.ORG (CAPI)
VALERIE.BIZIER@FAO.ORG (RS HANDBOOK, CAPACITY DEVELOPMENT)
LARSGUNNAR.MARKLUND@FAO.ORG (OPENFORIS, SEPAL)
CRISTINA.RIBEIRO@FAO.ORG (TOOLS FOR FISHERY STATISTICS)
36
Editor's Notes
In this context, FAO has developed its own products and incorporated the latest cost-effective technologies into its recommendations and practices. In recent years, particular advancements have been in the areas of computer assisted personal interviewing (CAPI), geospatial technologies, and developing modules for specific SDG monitoring. This ppt will highlight specific tools recommended by FAO to lower cost, and empower countries to high quality SDG data.
Provides standard module also for individual level rather than plot level.
This is in contrast to the paper and pen interviewing (PAPI) in which the enumerator records responses on paper which then must be manually entered into a software prior to analysis. This small discrepancy in method has a major impact on the overall cost of survey implementation.
The use of CAPI implies a large change of the survey/census operation processes
All validation and monitoring processes have to be in place and tested before going to the field
Validation processes are different to those using PAPI
Data processing is done at the same time as the field work
Supervision structures are different
The central question regarding the cost effectiveness of using CAPI is whether or not the cost of purchasing equipment (i.e. tablets, batteries, etc.) is offset by the elimination or reduction in printing, storage, and data entry costs.
Results show that electronic equipment costs more than offset the costs of data entry, and paper questionnaire costs (Rahija 2016). This is consistent with other studies showing that reduction or elimination of costs such as double-data entry, paper storage, and printing makes CAPI a cost effective alternative to PAPI (Zhang, et al 2012; King, et. al 2013, Leisher 2014).
Due to the availability of low cost tablet and GPS devices, using geo-referencing in large scale farm surveys is now realistic. In addition to advanced geo-spatial analysis of agricultural variables, geo-referencing provides opportunities to improve field logistics and sampling frames. In Survey Solutions CAPI software, geo-references can be taken by the tablet marking the exact location of the farm, parcel, etc. In Figure 2 below, there is simulated data which shows geo-referenced holding integrated with the boundaries of an enumeration area (EA).
It can be seen from Figure 2 that some holding listed in EA 003B are outside the EA boundary. These should be removed prior to sampling. Furthermore, the georeferenced sampled holdings can be loaded into the enumerator’s GPS devices to help reduce travel time, and ensure that the correct holding is enumerated.
According to World Bank research, Rope and Compass took on average 4 times longer than GPS.
The FRA 2020 platform is the tool used directly for reporting on 15.1.1 and 15.2.1. The Collect Earth tool is being directly used for 15.4.2, but could potientially be used for any indicator that could be derived from visual interpretation of high resolution satellite imagery. The SEPAL tool can be used by countries to obtain better data for 15.1.1 and 15.2.1 as well as for any other indicators that use satellite imagery, as it includes much more image processing capabilities than Collect Earth which is a visual interpretation tool.
The SEPAL tool can be used by countries to obtain better data for 15.1.1 and 15.2.1 as well as for any other indicators that use satellite imagery, as it includes much more image processing capabilities than Collect Earth which is a visual interpretation tool.
Tool for visual interpretation of very high resolution satellite images available in Google Earth, Bing maps and other sources
Highly configurable sample based tool. Layout of sample plots over the landscape / country / globe. Configurable size and data entry cards
The Collect Earth tool is being directly used for 15.4.2, but could potientially be used for any indicator that could be derived from visual interpretation of high resolution satellite imagery.
FAO – Capacity Development/Technical Assistance
FAO corporate IT
Mobile for data collection (SmartForms)
Software framework for national integrated statistics and management information system
Google and Global Fishing Watch Partnership
estimation of fishing effort based on AIS data
EU/iMarine partnership
Cloud-based Regional database for collaborative data sharing
On-line interactive hands-on e-curriculum for stock assessment
Global record of Stocks and Fisheries: data services for publishing unique identifiers of stocks and fisheries
FAO – Capacity Development/Technical Assistance
FAO corporate IT
Mobile for data collection (SmartForms)
Software framework for national integrated statistics and management information system
Google and Global Fishing Watch Partnership
estimation of fishing effort based on AIS data
EU/iMarine partnership
Cloud-based Regional database for collaborative data sharing
On-line interactive hands-on e-curriculum for stock assessment
Global record of Stocks and Fisheries: data services for publishing unique identifiers of stocks and fisheries
FAO – Capacity Development/Technical Assistance
FAO corporate IT
Mobile for data collection (SmartForms)
Software framework for national integrated statistics and management information system
Google and Global Fishing Watch Partnership
estimation of fishing effort based on AIS data
EU/iMarine partnership
Cloud-based Regional database for collaborative data sharing
On-line interactive hands-on e-curriculum for stock assessment
Global record of Stocks and Fisheries: data services for publishing unique identifiers of stocks and fisheries
FAO – Capacity Development/Technical Assistance
FAO corporate IT
Mobile for data collection (SmartForms)
Software framework for national integrated statistics and management information system
Google and Global Fishing Watch Partnership
estimation of fishing effort based on AIS data
EU/iMarine partnership
Cloud-based Regional database for collaborative data sharing
On-line interactive hands-on e-curriculum for stock assessment
Global record of Stocks and Fisheries: data services for publishing unique identifiers of stocks and fisheries
FAO – Capacity Development/Technical Assistance
FAO corporate IT
Mobile for data collection (SmartForms)
Software framework for national integrated statistics and management information system
Google and Global Fishing Watch Partnership
estimation of fishing effort based on AIS data
EU/iMarine partnership
Cloud-based Regional database for collaborative data sharing
On-line interactive hands-on e-curriculum for stock assessment
Global record of Stocks and Fisheries: data services for publishing unique identifiers of stocks and fisheries
The model is perfect for scenarios where limited data on a species are available. The only input needed for the model is historical data on the catch of the species and a qualitative evaluation (low, medium or high) of its natural reproductive capacity and recovery (resilience and productivity, according to the biological jargon).'CMSY' will be used in coming years to establish the catch limits on fishery within the seas of northern Europe by contributing to the European economy.
Elefan by TropFishR: toolbox compiling single-species stock assessment methods specifically designed for data-limited fisheries analysis using length-frequency data. It includes methods for (i) estimating biological stock characteristics such as growth and mortality parameters, (ii) exploring technical aspects of the fisheries (e.g. exploitation rate and selectivity characteristics), (iii) assessing size and composition of a fish stock by means of virtual population analysis (VPA), and (iv) assessing stock status with yield prediction and production models..