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Mapping rice in Africa and assessing the potential for development
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Transcript of Mapping rice in Africa and assessing the potential for development
Mapping rice in Africa and assessing the potential for
development
Sander ZwartResearcher Remote Sensing & GIS
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Short CV – Sander Zwart
Born in 1976 in the Netherlands
Wageningen:• 1994-2000 MSc Irrigation and Water Engineering• 2000-2002 MSc Geoinformation Science• 2002-2010 WaterWatch company (water resources /
remote sensing, ET mapping)
(Delft:)• 2003-2010 PhD Mapping and modelling of water
productivity
Cotonou:• 2010-present Africa Rice Center
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Africa Rice Center - Introduction
• Started as 40 years ago as the West-African Rice Development Association (WARDA/ADRAO)
• Pan-African organization with member states• Goals: reduce poverty and reduce imports
through increasing rice production in Africa• Member of the CGIAR group of international
agricultural research organizations
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
West Africa Rice Development Association
(WARDA)
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Africa Rice Center(AfricaRice)
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Future
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Africa Rice Center - Introduction
4 pillars:• Genetic Diversity and Improvement (rice
breeding)• Sustainable Productivity Enhancement
(rice agronomy) • Policy, Innovation Systems and Impact
Assessment (economy, sociology & impact)• RiceTIME: Training, Information Management
and Extension linkages (extension)
– major achievement: NERICA
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Africa Rice Center – Modus Operandi
1. Projects are always in collaboration with National Agricultural Research Systems (NARS) + capacity building
2. Taskforces (Gender, Rice Breeding, Policy, Agronomy)
3. Rice Sector Development Hubs
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Africa Rice Center – Introduction
Rice Sector Development Hubs:• Regions where research and development are
concentrated along the entire rice value chain• Participatory on-farm / real-life research• Hubs are operated by NARS; locations are
appointed by NARS• Efficient impact pathway: research answers to
demands and is tested in real conditions, adopted by development sector for scaling out
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Africa Rice Center – Spatial analysis activities
Unit is operational again since 4 years• Researcher• Postdoctoral Fellow• Three research assistant• Two PhD students
Strong collaboration between IRRI and AfricaRice through CRP GRiSP – exchange of data and development of approaches
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Africa Rice Center – Spatial analysis activities
1. Mapping rice and rice ecologies (upland/lowland/mangrove/deep water)
2. Mapping the potential for rice development
3. Mapping biotic and abiotic stresses in rice production systems
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping rice
Justification
Rice statistics are very unreliable in Africa
Rice is spatially highly dynamic compared to Asia
Rice is booming in Africa
Impact assessment AfricaRice
Figure
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping rice
AfricaRice and IRRI co-organized an expert meeting in Cotonou (June 2012)
Goal: discuss the options for mapping rice using remote sensing (optical/radar) and develop a strategy for operational monitoring
Question: what methodologies exist and can they they be applied for African rice environments?
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping rice
Differences between Asian and African rice environemnts
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Asia AfricaIrrigated rice (80%) upland rainfed
lowland rainfedlowland irrigated (~10%)
Stable area Dynamic & expanding
30% of arable land 4% of arable land
Contiguous rice areas Fragmented
Paddy land preparation Dry land preparation
High fertilizer inputs Low fertilizer inputs
Spatial analysis – Mapping rice
Recommendations/findings:- Radar remote sensing is best bet- Alternative method needs to be adopted- Sentinel program will likely provide high spatial
and temporal resolution imagery- Focus on monitoring rice area in Rice Sector
Development Hubs- Mapping of inland valleys and lowland to
distinguish upland from lowland
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping rice
Pilot testing of radar remote sensing in two hubs:
Cosmo-SkyMed imagery is acquired every 16 days during rice season
Spatial resolution of 3m
Senegal: irrigated rice conditions (July-December)
Benin: upland and lowland rice (June-december)
Goals: mapping rice and assessing crop phenology dates (SoS and harvest)
Field validation collected (500 points)
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping rice
Preliminary results December 2013
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping inland valleys
Inland valley
Areas suitable for rice production due to favorable hydrological conditions
Important for current and future rice production
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping inland valleys
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping inland valleys
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping inland valleys
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
stream
20 20 212123 23
2425m25
24 altitude (m)
Selected inland valley bottom
30m
Digital Elevation Model(2-dimensional)
Spatial analysis – Mapping inland valleys
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping inland valleys
Benin: IMPETUS project (Germany): +/- 100 digitized inland valleys from Benin (accomplished)
Togo: SMART-IV project: student collecting field data with GPS, 50 in Benin and 50 in Togo
Burkina Faso: existing data set from Min of Agriculture
Mali: RAP-IV project, 40 inland valleys
Sierra Leone & Liberia: RAP-IV project (planned)
GOAL: entire West-Africa mapped and validated
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping inland valleys
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping inland valleys
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping potential
Question what is the potential for development?
Currently only 10% cultivated
Goal: provide maps that indicate the potential for development of rice-based systems in an IV.
Users: NGO’s, government bodies (inland valley development cell, national IV development projects, etc.)
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping potential
Suitability mapping is usually done with a selection of indicators that are given a value of importance based on expert knowledge
Disadvantage: not objective, biased
Random Forest is a statistical analysis tool that allows explaining the presence or non-presence without prior knowledge.
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping potential
Methodology has been applied to map the potential for irrigated rice development in Laos (IRRI / Laborte et al., 2012)
Use of data sets on roads, travel distance, villages, markets, population density, soil suitability, water availability, rainfall, precipitation, etc., etc.
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Spatial analysis – Mapping potential
• On-going activity in two pilot sites in Benin.• Collection of data on inland valleys and
presence or non-presence of rice or agriculture• Building a spatial data base containing roads,
markets, travel distance, population density, villages, inland valleys, soil types, water availability, rainfall (remote sensing), etc.
Outlook: application at national level for west-African states. Implementation and validation with national partners and users.
Remote Sensing – Beyond Images14-15 December 2013, Mexico City
Thank you! Merci!
Center of Excellence for Rice Research