ASSESSING THE IMPACT OF NATIONAL FOOD SECURITY POLICIES ON IRRIGATED RICE
CULTIVATION IN SENEGAL USING ADVANCED REMOTE SENSING AND MODELLING TECHNOLOGIES
Sander Zwart Lorenzo Busetto Mirco Boschetti Mandiaye Diagne
Performed under a CRADA between Consiglio Nazionale delle Ricerche-Istituto per il Rilevamento Elettromagnetico dell’Ambiente (UOS Milano), International Rice Research Institute, Faculty ITC of the University of Twente and sarmap SA
OUTLINE
Setting the scene: Senegal and Food Security Policies supporting food security
Monitoring rice cultivation and farmer activities PhenoRice and time series analysis
Detected policy-induced changes Key messages
SENEGAL AND FOOD SECURITY
Population of 15 million: 61% < 25 years old
Median age: 18.1 years Growth rate 2.39%
SENEGAL AND FOOD SECURITY
Nutrition: rice, millet, maize, sorghum, vegetables and fish
National dish: Tchep Djen (broken rice with fried fish and vegetables)
Demand is outpacing the production due high
SENEGAL AND FOOD SECURITY
Senegal is a net food importer High dependency on international market 2008 Food crisis: price of rice increased by 300% in just 3 monthsPOLICIES SUPPORTING FOOD
SECURITY
2 major policies were developed and implemented: Great Offensive for Food and Abundance
Grand offensive pour la nourriture et l’abondance (GOANA)
Rice Sector Development Strategy (RSDS)
Ambitious goal to become self-sufficient for the
major staple crops
Major efforts on rice as major loss of foreign
POLICIES SUPPORTING FOOD
SECURITY
Become self-sufficient for rice by 2018
Focus on irrigated rice production systems Investing in the rice value chain
(input supply, mechanization, marketing, etc.) Area expansion [AREA] – public and private
investments
Intensification [PRODUCTIVITY, CROPPING INTENSITY]
POLICIES SUPPORTING FOOD
SECURITY
Low average annual rainfall in north (<300mm) – Sahel arid zone
Rains from August to November Rainfed agriculture in the central and southern parts
Irrigated agriculture (rice,
vegetables) in the floodplains and
delta of the Senegal River
MONITORING RICE CULTIVATION AND FARMER ACTIVITIES
General goal: to support monitoring the impact of rice
development policies using remote sensing technologies Case study in Senegal:
Potential to support monitoring and evaluation of rice policies
Dynamic rice growing environment
Long-term data availability for validation / comparison
MONITORING RICE CULTIVATION AND FARMER ACTIVITIES
Specific goals:
Validate PhenoRice algorithm for detecting trends in area and rice phenology (2003 – 2016)
Detecting policy induced changes in farmer practices [RICE CULTIVATED AREA]
[CROPPING INTENSITY] [CROP ESTABLISHMENT]
[CROP HARVEST]
[CROPPING SEASONS]
Setting the scene: Senegal and Food Security Policies supporting food security
Monitoring rice cultivation and farmer activities
PhenoRice and time series analysis
Detected policy-induced changes Key messages
PHENORICE AND TIME SERIES
ANALYSIS
PhenoRice algorithm
Rule-based approach to detect to
1) Detect rice pixels
2) Estimate phenological metrics
- Start of Season (SoS) – sowing or transplanting date of rice - End of Season (EoS) – harvesting date
- Length of Season (LoS) – EoS minus SoS in #days Time series analysis of spectral indices derived from combined MODIS Aqua and Terra data
PHENORICE AND TIME SERIES
ANALYSIS
1. MOD13Q1 / MYD13Q1 16-day products
Create smooth EVI profiles
Derive Normalised Difference Flooding Index
Busetto et al. 2016. MODIStsp: An R package for automatic preprocessing of MODIS Land Products time series
2. Detect rice pixels
Rule-based decision to detect rapid vegetation development after flooding for land preparation
PHENORICE AND TIME SERIES
ANALYSIS
3. Detect # of seasons (1 to 3) and assess SoS and EoS dates for each season
Rule-based, threshold values
Boschetti et al. 2017. PhenoRice: A method for automatic extraction of spatio-temporal information on rice crops using satellite data time series. Rem. Sens. Environ. 194, 347-365.
PHENORICE AND TIME SERIES
ANALYSIS
Validation / comparison data sets
[RICE AREA] official statistics provided by government (1960 – 2017) [RICE ESTABLISHMENT] [RICE HARVEST]
Farmer reported dates (n=100, 2 different zones) (2002 – 2010)
DETECTED POLICY-INDUCED CHANGES
DETECTED POLICY-INDUCED CHANGES
DETECTED POLICY-INDUCED CHANGES
[RICE CULTIVATED AREA] – VALIDATION
OFFICIAL STATISTICS THIS STUDY
DETECTED POLICY-INDUCED CHANGES
DETECTED POLICY-INDUCED CHANGES
DETECTED POLICY-INDUCED CHANGES
DETECTED POLICY-INDUCED CHANGES
DETECTED POLICY-INDUCED CHANGES
[CROPPING SEASONS]
DETECTED POLICY-INDUCED CHANGES
DETECTED POLICY-INDUCED CHANGES
[VARIETIES]
Adoption of medium-length varieties in the wet season
Explanation: short period between harvest of dry season and land preparation of wet season (labour & equipment shortage)
KEY MESSAGES
Detecting rice area:
Not all rice pixels, but we detect trends
Assessing growing seasons:
Yes! #seasons, length, start, harvest, cropping intensity
Assessing varieties:
Not individual varieties, but shifts from medium to short-duration
Policy impacts in Senegal:
Strong increase in rice area since 2008 Shift from wet to dry season
