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http://dx.doi.org/10.5322/JESI.2016.25.12.1653

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

Lee, Geun-Sang (Cadasree & Civil Engineering, Vision College of Jeonju)
Kim, Sung-Wook (Geo-information Institute, GI Co. Ltd.)
Hamm, Se-Yeong (Department of Geological Science, Pusan National University)
Lee, Khil-Ha (Department of Civil Engineering, Daegu University)
Publication Information
Journal of Environmental Science International / v.25, no.12, 2016 , pp. 1653-1660 More about this Journal
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
Actual evapotranspiration; Drone; Drought index; Natural disaster; PT-JPL;
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  • Reference
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.   DOI
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.   DOI
4 Huete, A. R., 1988, A Soil-adjusted vegetation index (SAVI), Remote Sens. Environ., 25, 295-309.   DOI
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.   DOI
7 Lee, K., 2016, Korea has no water scarcity!, Water Res., 43(3), 579-582.   DOI
8 Maidment, D. R., 1993, Handbook of hydrology, McGraw-Hill, New York.
9 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.   DOI
10 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.   DOI
11 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.
12 Savenije, H. H. G., 2000, Water scarcity indicators; The deception of the numbers, Phys. Chem. Earth, Ser. B, 25(3), 199-204.   DOI
13 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.
14 Monteith, J. L., 1965, Evaporation and environment, Symp. Soc. for Exp. Bio., 19, 205-224.