Journal of Environmental Science International (한국환경과학회지)

The Korean Environmental Sciences Society (한국환경과학회)
권호 표지
DOI QR코드

DOI QR Code

Influence of Scaling in Drone-based Remotely Sensed Information on Actual Evapotranspiration Estimation

드론 원격정보 격자크기가 실제증발산량 산정에 미치는 영향

  • Lee, Khil-Ha (Department of Civil Engineering, Daegu University)
  • 이길하 (대구대학교 건설시스템공학과)
  • Received : 2017.12.13
  • Accepted : 2018.01.08
  • Published : 2018.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

The specification of surface vegetation is essential for simulating actual evapotranspiration of water resources. The availability of land cover maps based on remotely collected data makes the specification of surface vegetation easier. The spatial resolution of hydrologic models rarely matches the spatial scales of the vegetation data needed, and remotely collected vegetation data often are upscaled up to conform to the hydrologic model scale. In this study, the effects of the grid scale of of surface vegetation on the results of actual evapotranspiration were examined. The results show that the coarser resolution causes larger error in relative terms and that a more realistic description of area-averaged vegetation nature and characteristics needs to be considered when calculating actual evapotranspiration.

Keywords

References

  1. 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
  2. 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
  3. 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
  4. Lee, G., Kim, S., Hamm, S., Lee, K., 2016, Computation of actual evapotranspiration using drone-based remotely sensed information: preliminary test for a drought index, Journal of Environ. Sci. Int., 25, 1653-1660. https://doi.org/10.5322/JESI.2016.25.12.1653
  5. McNaughton, K. G., 1993, Effective stomatal and boundary layer resistances of heterogeneous surfaces, Plant Cell Environ., 17, 1061-1068.
  6. Monteith, J. L., 1965, Evaporation and environment, Symp. Soc. for Exp. Bio., 19, 205-224.
  7. 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, 81-92.
  8. Raupach, M. R., 1995, Vegetation-atmosphere interaction and surface conductance at leaf, canopy, and regional scales, Agri. Forest Meteorol., 73, 151-179. https://doi.org/10.1016/0168-1923(94)05071-D
  9. 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.
  10. Shuttleworth, W. J., 1998, Combining remotely sensed data using aggregation algorithms, Hydrology Earth Syst. Sci., 2, 149-158. https://doi.org/10.5194/hess-2-149-1998
  11. 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.