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Targeting Surra Interventions In Mindanao Using Remote Sensing, Geographic Information System And Global Positioning System
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Targeting Surra Interventions In Mindanao Using Remote Sensing, Geographic Information System And Global Positioning System

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GIS project presented during Remote Sensing Workshop at University of the Philippines-Los Baños, Laguna

GIS project presented during Remote Sensing Workshop at University of the Philippines-Los Baños, Laguna

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  • 1. Targeting Surra interventions in Mindanao using Remote Sensing, Geographic Information System and Global Positioning System Jennifer A. Alforque Agriculturist II Department of Agriculture Regional Field Unit No. XI Davao City
  • 2.
    • Surra is a vector-borne disease (vector is a blood-sucking fly “tabanus) of livestock and is a major animal health problem in Mindanao.This disease causes low productivity, abortion, infertility and ultimately, death in livestock animals that are affected by it.
    • Currently, MUSCA has established that it is prevalent in many parts of Mindanao based on the large amount that has been collected through surveys and active surveillance.The data on the disease distribution is still inadequate because it lacks information on the status of risk based on the environmental and climatic factors associated with the disease.
    • The use of remotely sensed data, Geographic Information System and Global Positioning System can help improve the quality of information provided to the decision makers particularly in the prioritization of areas for monitoring and control of Surra.
    •  
    Rationale
  • 3. MUSCA POST RADDL - RFU XIII P 39,600 RADDL - RFU X P 40,800 RADDL – ARMM P 33,000 RADDL - RFU IX P 40,800 Mindanao RADDL – RFU XII P 33,000 RADDL-RFU XI P 43,200 Allocation for drugs and supplies per region: (2006) Total: P230,400
  • 4.
    • General
        • To improve the existing decision support system on planning Surra control by producing Mindanao Surra risk maps
      • Specific
        • Identify locations of Surra high and low risk areas using Digital Elevation Model
        • Correlate climatic and environmental factors to Surra incidence and outbreaks
    Objectives
  • 5.
    • Digital Elevation Model
    • Rainfall distribution
    • Animal Population density
    • Municipal boundaries
    Required Datasets Minimum Themes
    • Elevation
    • Rainfall patterns
    • Population Density
  • 6. Criteria for analysis
    • The stronger rainfall and the lower elevation, the higher the risk.
    • The breeding potential and survival of vectors that facilitates the transmission of Surra increases during the wet season and settles in the lowland areas.
  • 7. Flowchart of GIS analysis and modeling for identifying potential high and low Surra risk areas ADMINISTRATIVE BOUNDARIES CLIMATE DEMOGRAPHY TOPOGRAPHY RAINFALL POPULATION DENSITY DEM MUNICIPAL BOUNDARIES reclass interpolate RAINFALL PATTERNS ELEVATION intersect POTENTIAL SURRA HIGH-RISK AREAS IDENTIFIED Decision-makers
  • 8. Rainfall Patterns 1 = low rainfall distribution [low risk] 10 = high rainfall distribution [high risk)
  • 9. Rainfall patterns
  • 10. Elevation 1 = high elevation (low risk) = not suitable for flies 10 = low elevation (high risk) = suitable for flies
  • 11. Potential Surra Risk Areas in Caraga Region
    • High Risk Areas identified:
    • Surigao Del Sur
    • - Tagbina (25)
    • Hinatuan (24)
    • Agusan Del Sur
    • San Francisco (27)
    • Rosario (11)
    • Bunawan (10)
    • Trento (16)
    • Veruela (20)
    • Loreto (17)
    • La Paz (15)
    • Talacogon (16)
    • High Risk Areas identified:
    • Surigao Del Norte
    • Surigao City (50)
    • San Francisco (11)
    • Sison (12)
    • Taganaan (14)
    • Mainit (21)
    • Malimono (14)
    • Tubod (9)
    • Bacuag (9)
    • Alegria (12)
    • Monica (11)
    • Burgos (6)
    • San Benito (6)
    • San Isidro (12)
    • Pilar (15)
    • Dapa (29)
    • General Luna (19)
    • Del Carmen (20)
    Analysis: the stronger rainfall distribution with the lower elevation area, the risk is high
  • 12. High Risk Population Total Positive Cases
  • 13. Results and Discussions
    • Based on the rainfall and elevation model, Surra high and low risk areas are identified.
    • Decision makers can properly allocate the resources for surveillance and monitoring activities
    • The efficacy of prevention efforts can be enhanced because of efficient targeting of high-risk areas.
    • Movement of animals from identified high risk areas should be minimized.
    • More effective and directed information dissemination on Surra high risk areas.
  • 14. Conclusions and Recommendations
    • Satellite images of MODIS - Land Surface Temperature (LST), Elevation, Enhanced Vegetation Index, Land Cover to monitor the environmental and climatic conditions that will be suitable for Surra occurrence.
    • Refinement of model by integrating the vector distribution model.
  • 15. Acknowledgements Dr. David Bourn Dr. Jose Molina Dr. Neil Bantayan Prof. Jun Tiburan Co-participants Resource persons
  • 16. Daghang salamat sa pagpaminaw! [Thank you for listening!]

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