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    <subfield code="a">Sinha, Shweta</subfield>
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    <subfield code="a">Agricultural risk management through crop insurance using geospatial technologies</subfield>
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    <subfield code="a">Pathum Thani, Thailand :</subfield>
    <subfield code="b">Asian Institute of Technology,</subfield>
    <subfield code="c">2017</subfield>
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    <subfield code="a">1 online resource (118 p.) :</subfield>
    <subfield code="b">ill. </subfield>
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    <subfield code="a">Dissertation ;</subfield>
    <subfield code="v">no. RS-17-01</subfield>
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    <subfield code="a">A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of PhilosophyinRemote Sensing &amp; Geographic Information Systems</subfield>
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    <subfield code="a">Crop  insurance  has  significant  potential  to  mitigate  risks  that  individuals  and  countries  are exposed  to  in  light  of  rising  disasters  in  Asia-Pacific  region. The  sector  is  a  growth  business areafor insurance and a much needed requirement for governments and individuals.To realize the  potential,  it  is  important  that  the  ecosystem  encouragesnew  types  of  insurance  productsthat  is  attractive  to  end  users  as  well  as  providers.Although  it  is difficultto  compare  the demand and  growth of crop insurance products in different countries, most of the developing countries are striving to adopt these products learningfrom the experiences of successful crop insurance  deployment.The  advancement  of  technology  has  provided  an  opportunity  forthe insurance  industry to  transitionfrom  traditional  crop  insurance  to  weather  based  crop insurance and/or satellite based crop insurance though there still existchallenges offeasibility, scalability and sustainability.While there is significant interest in crop insurance, basis risk remains a key challenge for the growth  of  weather  index  insurance  (WII)  products.  Correlations  between  criticalparameters andyield  hold  the  key  for  the  development  of  the  market. Analysis  performed  at  province, district and farm level in Thailand indicated additional factors other than rainfall contributing to  yield. DevelopingGeneralized  Monsoon  Index  (GMI)  maps  indicated2012  as  a  severe drought year.Field based discussion withrice experts and farmers confirmed use of irrigation and drought resistant rice varieties (RD6 and KDML-150). In absence of long term historical data, confirmation of correlations between weather parameters and yield solely is challenging. Using Generalized  Monsoon  Index(GMI)and Hybrid Satellite Agriculture  Drought  Indices(HySADI)can improve the agricultureinsurance methodsthat are solely  based on  rainfall.  It can also be used to validate appropriate areas to justify payouts in loss years and reduce basis risk for the crop insurance industry.The key contributions of the dissertation includes:1.Identifyingtheimplementationpractices  and  challenges  in  usingcrop  insurance  as  a  risk mitigation  tool with  detailed  analysis  oftworice  producing  developingeconomies:  India and Thailand.2.Itis the first comprehensive study on agriculture insurance inThailandas well asthe first attempt to  assess the  feasibility of  drought  indices  at  province,  district  and  farm  level  of Thailand.3.The   study   uses Multi-temporal   agro-meteorological   drought   index   like   Generalized Monsoon   Index  (GMI)  and  remote  sensing  based  drought  indices  like  Normalized Difference  Vegetation  Index  (NDVI),  Land  Surface  Temperature  (LST)  and  Temperature Vegetation  Index (TVX) to evaluate drought impact on rice  yield in Khon Kaen province of  Thailand  for  2011,  2012  and  2013.The existing  insurance  productsin  Thailandare based on rainfall only. iv4.Province level GMI maps indicated 2012 as a severe drought year. However, the first crop rice  yield  (1987-2014)  did  not  show  good  correlation  with  in-season  rainfall.  Analysis  at district  level  also  did  not  show  good  correlation  between  yield  and  GMI  for  2011,  2012 and 2013.5.Strong  positive  correlation  between NDVIsum and  LSTsumwith  R2 =  0.968  in  Khon  Kaen farm land was observed whichsuggests that water is not the only factor limiting vegetation growth  and  thus  considering  only  rainfall  as  a  proxy  for  yield  would  not  be  adequate indicator  for  the  level  of  drought  in  the  region.Area  specific  relationship  between  NDVI and LST would be useful for a better understanding of factors limiting vegetation growth. In  absence  of  long  term  historical  data,  confirmation  of  correlations  between  weather parameters  and  yield  solely  is  challenging. Interview  and  discussion  with  riceandinsurance experts and focused  group discussion (FGD) with farmers during the field visit indicated  that non-weather  parameters  such  as  irrigation  and  rice  varieties  play  an important role.A model taking into account quantitative indicators and qualitative factors can  be  deployed  to  significantly  improve  the  efficiency  of  crop  insurance  and  reduce  the basis risk.6.Developing seasonal GMI drought maps at province level would be useful in assessing and reducing  basisrisk.  GMI  can  also  be  used  to  develop  thresholds  that  would  consider  the amount of rainfall based on the growth stages of the crop.  7.GISmaps  generated  indicate  good  yield  for  districts  like  Nam  Phong  and  Mueang  Khon Kaen  despite  drought  conditions  usingGeneralized  Monsoon  Index  (GMI)  in  2012.Districts  found  to  have  irrigation  facilities, could  come  up  with  updated  threshold  water levels  to  be  eligible  for  weather  index  insurance  (WII)  schemes  based  on  further  study. Also,  drought  resistant  rice  varieties  and  its  impact  on  threshold  weather  level  for insurance  payments  would  be  useful  for  insurance  companies  to  reduce  adverse  selection and is an important area for further study.8.The  use  of  Generalized  Monsoon  Index  and  Satellite  based  indices  with  modifications  to take  into  account  non  weather  parameters  (e.g.  type  of  rice,  availability  of  irrigation)  can improve the weather insurance models that are solely based on rainfall. It can also be used to  validate  appropriate  areas  to  justify  payouts  in  loss  years  and reduce  basis  risk  for  the crop insurance industry and also enhance the efficiency of drought subsidy programs. 9.Discussion  with  farmers,  insurance  company  and  BAAC  in  Thailand  suggested  low awareness among farmers about the potential benefits of weather index insurance products. Relatively  low  compensation  is  also  an  obstacle.  Proper  marketing  and  awareness  raising campaigns should accompany any future introduction of index-based insurance.10.The  thorough  review  of  crop  insurancepractice,  policy  and  technology at  country  leveland drought  related data  analysis at province,  district  and farm  levelcarried  out  in  this study  wouldfacilitatedevelopment  of  index  that  would  assist  in  reducing  the  basis  risk. Possible solutions suggested would further improve the confidence of insurance providersand farmersin use of agro-meteorological data  for successful adoption of crop insurance.  vThe  output  of  this  research will  be very  valuablefor  insurance  sector,  government  and future researchers in reducing individual risks of farmers</subfield>
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