Rapid Assessment of Crop Status: An Application of MODIS and SAR Data to Rice Areas in Leyte, Philippines Affected by Typhoon Haiyan

نویسندگان

  • Mirco Boschetti
  • Andrew Nelson
  • Francesco Nutini
  • Giacinto Manfron
  • Lorenzo Busetto
  • Massimo Barbieri
  • Alice G. Laborte
  • Jeny V. Raviz
  • Francesco Holecz
  • Mary Rose O. Mabalay
  • Alfie P. Bacong
  • Eduardo Jimmy P. Quilang
چکیده

Asian countries strongly depend on rice production for food security. The major rice-growing season (June to October) is highly exposed to the risk of tropical storm related damage. Unbiased and transparent approaches to assess the risk of rice crop damage are essential to support mitigation and disaster response strategies in the region. This study describes and demonstrates a method for rapid, pre-event crop status assessment. The ex-post test case is Typhoon Haiyan and its impact on the rice crop in Leyte Province in the Philippines. A synthetic aperture radar (SAR) derived rice area map was used to delineate the area at risk while crop status at the moment of typhoon landfall was estimated from specific time series analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) data. A spatially explicit indicator of risk of standing crop loss was calculated as the time OPEN ACCESS Remote Sens. 2015, 7 6536 between estimated heading date and typhoon occurrence. Results of the analysis of preand post-event SAR images showed that 6500 ha were flooded in northeastern Leyte. This area was also the region most at risk to storm related crop damage due to late establishment of rice. Estimates highlight that about 700 ha of rice (71% of which was in northeastern Leyte) had not reached maturity at the time of the typhoon event and a further 8400 ha (84% of which was in northeastern Leyte) were likely to be not yet harvested. We demonstrated that the proposed approach can provide pre-event, in-season information on the status of rice and other field crops and the risk of damage posed by tropical storms.

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عنوان ژورنال:
  • Remote Sensing

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2015