DOI QR코드

DOI QR Code

Computation of Actual Evapotranspiration using Drone-based Remotely Sensed Information: Preliminary Test for a Drought Index

드론 원격정보를 활용한 실제증발산량의 산정: 가뭄지수를 위한 사전테스트

  • 이근상 (전주비전대학교 지적토목학과) ;
  • 김성욱 (지아이 지반정보연구소) ;
  • 함세영 (부산대학교 지질환경과학과) ;
  • 이길하 (대구대학교 건설시스템공학과)
  • Received : 2016.08.17
  • Accepted : 2016.10.31
  • Published : 2016.12.31

Abstract

Drought is a reoccurring worldwide natural hazard that affects not only food production but also economics, health, and infrastructure. Drought monitoring is usually performed with precipitation-based indices without consideration of the actual state and amount of the land surface properties. A drought index based on the actual evapotranspiration can overcome these shortcomings. The severity of a drought can be quantified by making a spatial map. The procedure for estimating actual evapotranspiration is costly and complicated, and requires land surface information. The possibility of utilizing drone-driven remotely sensed data for actual evapotranspiration estimation was analyzed in this study. A drone collected data was used to calculate the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI). The spatial resolution was 10 m with a grid of $404{\times}395$. The collected data were applied and parameterized to an actual evapotranspiration estimation. The result shows that drone-based data is useful for estimating actual evapotranspiration and the corresponding drought indices.

Keywords

References

  1. Brustaert, W., 1991, Evaporation into the atmosphere, theory, history and application, Kluwer, Dordrecht, The Netherlands.
  2. Falkenmark, M., Rockstrom, J., 2006, The new blue and green water paradigm: Breaking new ground for water resources planning and management, J. Wat. Res. Planning Manag. - ASCE, 132(3), 129-132. https://doi.org/10.1061/(ASCE)0733-9496(2006)132:3(129)
  3. Fisher, J., Tu, K., Baldocchi, D., 2008, Global estimates of the land atmosphere water flux based on monthly AVHRR and ISLSCPII data, validated at 16 FLUXNET sites, Remote Sens. Environ., 112, 901-919. https://doi.org/10.1016/j.rse.2007.06.025
  4. Huete, A. R., 1988, A Soil-adjusted vegetation index (SAVI), Remote Sens. Environ., 25, 295-309. https://doi.org/10.1016/0034-4257(88)90106-X
  5. IPCC (interpanel of climate change), 2007, Climate change 2007: The physical science basis, Cambridge University Press, Cambridge, UK and NY, USA.
  6. June, T., Evans, J. R., Farquhar, G. D., 2004, A Simple new equation for the reversible temperature dependence of photosynthetic electron transport: A Study on soybean leaf, Func. Plan. Biol., 31, 275-283. https://doi.org/10.1071/FP03250
  7. Lee, K., 2016, Korea has no water scarcity!, Water Res., 43(3), 579-582. https://doi.org/10.1134/S0097807816030088
  8. Maidment, D. R., 1993, Handbook of hydrology, McGraw-Hill, New York.
  9. Monteith, J. L., 1965, Evaporation and environment, Symp. Soc. for Exp. Bio., 19, 205-224.
  10. Narasimhan, B., Srinivasan, R., 2005, Development and evaluation of soil moisture deficit index (SMDI) and evapotranspiration deficit index (ETDI) for agricultural drought monitoring, Agri. and For. Met., 133(1-4), 69-88. https://doi.org/10.1016/j.agrformet.2005.07.012
  11. Priestley, C. H. B., Taylor, R. J., 1972, On the assessment of surface heat flux and evaporation using large-scale parameters, Mon. Weather Rev., 100(2), 81-92. https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2
  12. Rouse, J. W., Haas, R. H., Scheel, J. A., Deering, D. W., 1974, Monitoring vegetation systems in the great plains with ERTS, Proceedings, 3rd Earth Resource Technology Satellite (ERTS) Symposium, 1, 48-62.
  13. Savenije, H. H. G., 2000, Water scarcity indicators; The deception of the numbers, Phys. Chem. Earth, Ser. B, 25(3), 199-204. https://doi.org/10.1016/S1464-1909(00)00004-6
  14. Xiao, X., Hollinger, D., Aber, J. D., Goltz, M., Davidson, E., Zhang, Q., 2003, Satellite-based modeling of gross primary production in an evergreen needle leaf forest, Remote Sens. of Environ., 89, 519-534.

Cited by

  1. Influence of Scaling in Drone-based Remotely Sensed Information on Actual Evapotranspiration Estimation vol.27, pp.2, 2018, https://doi.org/10.5322/JESI.2018.27.2.135