Charles Situma (charles.situma@yahoo.com) Vincent Mate Imala (vineima@yahoo.com) Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
DEPARTMENT OF RESOURCE SURVEYS & REMOTE SENSING (DRSRS) Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Institutional and Human Capacity Professional/T Established in 1976 28% echnical Staff 72% In 1984 upgraded to a full- Administratio n/Support fledged Department (DRSRS) Staff 102 staff Survey aircraft Satellite Antenna Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Fleet of Aircraft DRSRS acquired a new survey aircraft • Cessna with modern intercom • Aircraft arrived on 16-7-2011 Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco 4
RC 30 Survey Camera • Black and white film • Colour film Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
DRSRS STRUCTURE Director Deputy Director Assistant Director Administration Technical Services Ground Aerial Remote Data Supply Library Accounts Air Surveys Sensing Surveys Management Chain Services Others Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
DEPARTMENT OF RESOURCE SURVEYS AND REMOTE SENSING (DRSRS) VISION MANDATE DRSRS strives to be a national centre of DRSRS is mandated to capture, excellence in geo-information services store, update, analyze and on earth-based natural resources for disseminate geo-spatial data and sustainable development information on earth-based natural resources/environment to enhance spatial planning and decision making for sustainable development MISSION “To generate, provide and Data collected and generated form the basis for research, promote geo-information development of management on earth-based resources plans and formulation of land in support of planning, use policies management and decision-making for Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco sustainable development”.
DRSRS Methods of Data Acquisition Multi-Stage Sampling Concept OUTPUTS Maps Stage 1: Remote Sensing Statistic Satellite Imagery - Land cover Approach Models Orbiting Space Satellite (3,000 - 35,000 Report km) Advantages: - Cheap, faster, synoptic, Scale covers wide area and easily Stage 2: Aerial Surveys comparable High Level Photography: Land cover / use Low-High Flight Aircraft Aerial Photography (100-3,000m ) Animal Census (100-200m) Costs Implication: Dependent on size of area, sampling resolution and efforts Wildlife Livestock Scale Stage 3: Ground Surveys/Measurement Attribute identification, scale GIS Servers accuracy and socio-economic surveys Conventional Cost Implication: Often expensive and time Scientific Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco consuming Methods
Overview of Crop Monitoring in Kenya Started in 1984 following prolonged drought episode The impact was Famine and hunger affected 60% of the population Over 17% of livestock were decimated The cost incurred affected normal Government development plan Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Impacts of Drought Example: Year 2000 Drought Devastation The government declared the episode a national disaster WFP incurred US$ 102 million on food relief in 2000 -2001 Example: Year 2008/9 Drought Devastation Government spent in excess of US $. 169 million on relief food to combat the drought emergency Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
STRATEGY • Launched a crop monitoring programme using remote sensing techniques • The Department of Resource Surveys and Remote Sensing (DRSRS) was tasked to undertake this exercise • DRSRS mandated to provide statistical estimates on area and yield under crop Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Overview of Crop Forecast in Kenya Maize and wheat are the main staple food in Kenya accounting for over 80 percent of total cereals used at a household level Rice is the third most consumed cereal Each year the Food Steering Committee (FSC) of the Office of State, Special Programmes require information on Area, Yield and Production of these cereals Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Overview of Major Food Crops in Kenya Cereals: Maize, Wheat, Rice, Sorghum, Millet Root Irish Pototoes, Sweet Pototoes, Tubers: Cassava, etc Pulses Beans, peas, etc Nuts Ground nuts, Cashew Nuts, etc Livestock Milk, Meat, etc Products Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
60’s -70s Spatial 70’s – 80’s Population Distribution N 80’s - 90’s 90’s – 2000’s Legend Population density/Sq.Km Low : <50 Moderate: 51 - 100 High: 101 - 500 Very high: >501 0 300 600 Kilometers Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Population growth and Shrinking land base of Kenya Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Changes in population demography (1948-2009) 45 3,50 40 3,40 35 3,30 Population (Millions) 30 3,20 Growth rate (%) 25 3,10 20 3,00 15 2,90 10 2,80 5 2,70 0 2,60 1948 1962 1969 1979 1989 1999 2009 Years Total Annual Intercensal growth rate (%) Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Kenya’s projected rural and urban population, 1950 -2050 Population as of 2010 By 2030, it is projected that 33 per cent of Kenyans will live in urban areas Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Users of maize and wheat crop data Crop Satellite NDVI Crop Crop Aerial Area Images Yield Prod Photos Min of Agriculture Min of State -FSC Universities/Research Bureau of Statistics FEWSNET RCMRD NGOs Private Firms Individuals Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
METHODS • Crop area stratification • Estimation of area crop using vertical aerial photography • Determination of crop yield per hectare • Computation of crop production • Computation of consumption Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Agriculture expansion between 1990’s and 2000’s • Population of Kenya in 2009 census = 38,610,097 people • 20 % of Kenya support crop cultivation significant to the economy • Kenya requires approx 31 - 34 million bags of maize and 9 -11 million bags of wheat annually • Balance in food deficit met by substantial quantities of rice, potatoes and pulses produced locally and also from imports Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Satellite Data for Determination of Crop Strata • 16 Landsat satellite scenes cover agricultural area of 33 scenes • Cost: free for Landsat • Cost: Aster = US D 1,520 • Economical • Poor accuracy Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Satellite Data for Determination of Crop Strata Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
METHODS: ESTIMATION AREA Aircraft: • High winged twin or single engine (P68 or Cessna ) • Flying height of 488 m (1600 ft) Camera: • A 35 mm camera, 20 mm wide-angle lens GPS: Set to UTM WGS 84 datum or Geographic Photographs: • Vertical • Scale is approx. fixed at 1:22,000 • Area on ground 46 ha Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Sample Dot-Grid for Vertical Photograph Photograph taken 5Km 2.5Km Photos covering entire crop stratum are: 10,000 Area under crop: 14,500 Sq Km Cost: US D 72,375 Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco Cost per photo: USD 7.8
Photo Interpretation: Dot-Grid technique N # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # 100 0 100 200 Meters # 100 Dot grid Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Photo Interpretation: 100 Dot-Grid Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Photo Interpretation: 150 Dot-Grid Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Photo Interpretation: 200 Dot-Grid Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Accuracy levels in Photo Interpretation 100 90 80 70 60 Accuracy (%) 50 40 30 20 10 0 0 50 100 150 200 250 No. of dots used Source: Sinange, 1996 Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
Area of Crop S.F = Oρ/η Where: S.F = Sampling Fraction of the strata Oρ = Total No. of sample (points) photos observed with crop η = Total No. of Points (photos) taken in district strata n Hence: A = S.F ΣC (1/ Oρ *100) i Where: A = Area of survey stratum (ha) S.F = Sampling Fraction of the strata Oρ = Total No. of sample photos observed with crop n = n th photo in the strata i = i th photo in the strata Workshop on Crop Yield Forecast: 12-14/10/2011: INRA, Rabat, Morocco
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