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Drought Hazard Assessment using MODIS-based Evaporative Stress Index (ESI) and ROC Analysis

MODIS 위성영상 기반 ESI와 ROC 분석을 이용한 가뭄위험평가

  • Yoon, Dong-Hyun (Department of Bioresources and Rural Systems Engineering, Hankyong National University) ;
  • Nam, Won-Ho (School of Social Safety and Systems Engineering, Institute of Agricultural Environmental Science, National Agricultural Water Research Center, Hankyong National University) ;
  • Lee, Hee-Jin (Department of Bioresources and Rural Systems Engineering, Hankyong National University) ;
  • Hong, Eun-Mi (School of Natural Resources and Environmental Science, Kangwon National University) ;
  • Kim, Taegon (Department of Bioproducts and Biosystems Engineering, University of Minnesota)
  • Received : 2020.03.27
  • Accepted : 2020.05.14
  • Published : 2020.05.31

Abstract

Drought events are not clear when those start and end compared with other natural disasters. Because drought events have different timing and severity of damage depending on the region, various studies are being conducted using satellite images to identify regional drought occurrence differences. In this study, we investigated the applicability of drought assessment using the Evaporative Stress Index (ESI) based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. The ESI is an indicator of agricultural drought that describes anomalies in actual and reference evapotranspiration (ET) ratios that are retrieved using remotely sensed inputs of Land Surface Temperature (LST) and Leaf Area Index (LAI). However, these approaches have a limited spatial resolution when mapping detailed vegetation stress caused by drought, and drought hazard in the actual crop cultivation areas due to the small crop cultivation in South Korea. For these reasons, the development of a drought index that provides detailed higher resolution ESI, a 500 m resolution image is essential to improve the country's drought monitoring capabilities. The newly calculated ESI was verified through the existing 5 km resolution ESI and historical records for drought impacts. This study evaluates the performance of the recently developed 500 m resolution ESI for severe and extreme drought events that occurred in South Korea in 2001, 2009, 2014, and 2017. As a result, the two ES Is showed high correlation and tendency using Receiver Operating Characteristics (ROC) analysis. In addition, it will provide the necessary information on the spatial resolution to evaluate regional drought hazard assessment and and the small-scale cultivation area across South Korea.

References

  1. Allen, R. G., L. S. Pereira, D. Raes, and M. Smith, 1998. Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations, Rome.
  2. Anderson, M. C., J. M. Norman, G. R. Diak, W. P. Kustas, and J. R. Mecikalski, 1997. A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sensing of Environment 60(2): 195-216. doi:10.1016/S0034-4257(96)00215-5. https://doi.org/10.1016/S0034-4257(96)00215-5
  3. Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas, 2007. A climatological study of evapotranspiration and moisture stress across the continental U.S. based on thermal remote sensing: I. model formulation. Journal of Geophysical Research 112: D10117. doi:10.1029/2006JD007506.
  4. Anderson, M. C., C. Hain, J. Otkin, X. Zhan, K. Mo, M. Svoboda, B. Wardlow, and A. Pimstein, 2013. An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with U.S. drought monitor classifications. Journal of Hydrometeorology 14: 1035-1056. doi:10.1175/JHM-D-12-0140.1. https://doi.org/10.1175/JHM-D-12-0140.1
  5. Anderson, M. C., C. A. Zolin, C. R. Hain, K. Semmens, M. T. Yilmaz, and F. Gao, 2015. Comparison of satellitederived LAI and precipitation anomalies over Brazil with a thermal infrared-based evaporative stress index for 2003-2013. Journal of Hydrology 526: 287-302. doi:10.1016/j.jhydrol.2015.01.005. https://doi.org/10.1016/j.jhydrol.2015.01.005
  6. Anderson, M. C., C. A. Zolin, P. C. Sentelhas, C. R. Hain, K. Semmens, M. T. Yilmaz, F. Gao, J. A. Otkin, and R. Terault, 2016. The evaporative stress index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts. Remote Sensing of Environment 174: 82-99. doi:10.1016/j.rse.2015.11.034. https://doi.org/10.1016/j.rse.2015.11.034
  7. Bae, D. H., K. H. Son, and H. A. Kim, 2013. Derivation & evaluation of drought threshold level considering hydro-meteorological data on South Korea. Journal of Korea Water Resources Association 46(3): 287-299 (in Korean). doi:10.3741/JKWRA.2013.46.3.287. https://doi.org/10.3741/JKWRA.2013.46.3.287
  8. Jeong, M. S., J. S. Kim, H. W. Jang, and J. H. Lee, 2016. ROC evaluation for MLP ANN drought forecasting model. Journal of Korea Water Resources Association 49(10): 877-885 (in Korean). doi:10.3741/JKWRA.2016.49.10.877.
  9. Jeoung, J., D. Kim, and M. Choi, 2017. A study on the utilization of geostationary ocean color imager on communication, ocean and meteorological satellite for drought monitoring. Journal of the Korean Society of Hazard Mitigation 17(3): 69-77 (in Korean). doi:10.9798/KOSHAM.2017.17.3.69. https://doi.org/10.9798/KOSHAM.2017.17.3.69
  10. Kim, G. S., and H. G. Park, 2010. Estimation of drought index using CART algorithm and satellite data. Journal of the Korean Association of Geographic Information Studies 13(1): 128-141 (in Korean).
  11. Kim, G. S., and J. W. Lee, 2011. Evaluation of drought indices using the drought records. Journal of Korean Water Resources Association 44(8): 639-652 (in Korean). doi:10.3741/JKWRA.2011.44.8.639. https://doi.org/10.3741/JKWRA.2011.44.8.639
  12. Kim, J. S., S. J. Lee, Y. S. Oh, G. J. Cho, B. S. Sim, M. S. Kim, S. P. Moon, and C. H. Kim, 2016. Development of ESS control algorithm for smoothing the output of renewable energy using pearson's correlation coefficient. Journal of the Korean Institute of Illuminating and Electrical Installation Engineer 30(9): 33-39 (in Korean). doi:10.5207/JIEIE.2016.30.9.033.
  13. Lee, H. J., W. H. Nam, D. H. Yoon, E. M. Hong, D. E. Kim, M. D. Svoboda, T. Tadesse, B. D. Wardlow, 2019. Satellite-based Evaporative Stress Index (ESI) as an Indicator of Agricultural Drought in North Korea. Journal of the Korean Society of Agriculture Engineers 61(3): 1-14 (in Korean). doi:10.5389/KSAE.2019.61.3.001
  14. Lee, J. H., S. M. Jeong, S. J. Kim, and M. H. Lee, 2006. Development of drought monitoring system: I. applicability of drought indices for quantitative drought monitoring. Journal of Korea Water Resources Association 39(9): 787-800 (in Korean). https://doi.org/10.3741/JKWRA.2006.39.9.787
  15. Monteith, J. L., 1965. Evaporation and environment. Symposium of the Society of Experimental Biology 19: 205-224.
  16. Mun, Y. S., W. H. Nam, M. G. Jeon, T. Kim, E. M. Hong, M. J. Hayes, and T. Tadesse, 2019. Application of meteorological drought index using Climate Hazards Group InfraRed Precipitation wigh Station (CHIRPS) based on global satellite-assisted precipitation products in Korea. Journal of the Korean Society of Agriculture Engineers 61(2): 1-11 (in Korean). doi:10.5389/KSAE.2019.61.2.001.
  17. Nam, W. H., T. Tadesse, B. D. Wardlow, M. W. Jang, and S. Y. Hong, 2015. Satellite-based hybrid drought assessment using vegetation drought response index in South Korea (VegDRI-SKorea). Journal of the Korean Society of Agricultural Engineers 57(4): 1-9 (in Korean). doi:10.5389/KSAE.2015.57.4.001.
  18. Nam, W. H., T. Tadesse, B. D. Wardlow, M. J. Hayes, M. D. Svoboda, E. M. Hong, Y. A. Pachepsky, and M. W. Jang, 2018. Developing the vegetation drought response index for South Korea (VegDRI-SKorea) to assess the vegetation condition during drought events. International Journal of Remote Sensing 39(5): 1548-1574 (in Korean). doi:10.1080/01431161.2017.1407047. https://doi.org/10.1080/01431161.2017.1407047
  19. Norman, J. M., W. P. Kustas, and K. S. Humes, 1995. Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agricultural and Forest Meteorology 77(3-4): 263-292. doi:10.1016/0168-1923(95)02265-Y. https://doi.org/10.1016/0168-1923(95)02265-Y
  20. Otkin, J. A., M. C. Anderson, C. Hain, and M. Svoboda, 2014. Examining the relationship between drought development and rapid changes in the Evaporative Stress Index. Journal of Hydrometeorology 15: 938-956. doi:10.1175/JHM-D-13-0110.1. https://doi.org/10.1175/JHM-D-13-0110.1
  21. Otkin, J. A., M. Svoboda, E. D. Hunt, T. W. Ford, M. C. Anderson, C. Hain, and J. B. Basara, 2018. Flash droughts: A review and assessment of the challenges imposed by rapid-onset droughts in the United States. Bulletin of the American Meteorological Society 99(5): 911-919. doi:10.1175/BAMS-D-17-0149.1. https://doi.org/10.1175/BAMS-D-17-0149.1
  22. Park, J. S., and K. T. Kim, 2009. Evaluation of MODIS NDVI for drought monitoring: Focused on comparison of drought index. The Journal of GIS of Korea 17(1): 117-129 (in Korean).
  23. Running, S. W., Q. Mu, M. Zhao, and A. Moreno, 2019. User's guide MODIS global terrestrial evapotranspiration (ET) product (MOD16A2/A3 and year-end gap-filled MOD16A2GF/A3GF) NASA earth observing system MODIS land algorithm (For collection 6). NASA: Washington, DC, USA.
  24. Schober, P., C. Boer, and L. A. Schwarte, 2018. Correlation coefficients: Appropriate use and interpretation. Anesthesia & Analgesia 126(5): 1763-1768. doi:10.1213/ANE.0000000000002864. https://doi.org/10.1213/ANE.0000000000002864
  25. So, J. M., K. H. Sohn, and D. H. Bae, 2014. Estimation and assessment of bivariate joint drought index based on copula functions. Journal of Korea Water Resources Association 47(2): 171-182 (in Korean). doi:10.3741/JKWRA.2014.47.2.171. https://doi.org/10.3741/JKWRA.2014.47.2.171
  26. Sur, C. Y., K. J. Kim, W. J. Choi, J. H. Shim, and M. H. Choi, 2014. Drought assessments using satellite-based drought index in Korea; Southern region case in 2013. Journal of the Korean Society of Hazard Mitigation 14(3): 127-131 (in Korean). doi:10.9798/KOSHAM.2014.14.3.127.
  27. Svoboda, M., D. Lecomte, M. Hayes, R. Heim, K. Gleason, J. Angel, B. Rippey, R. Tinker, M. Palecki, D. Stooksbury, D. Miskus, and S. Stephens, 2002. The drought monitor. Bulletin of the American Meteorological Society 83: 1181-1190. doi:10.1175/1520-0477-83.8.1181. https://doi.org/10.1175/1520-0477-83.8.1181
  28. Tadesse, T., J. F. Brown, and M. J. Hayes, 2005. A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains. ISPRS Journal of Photogrammetry & Remote Sensing 59(4): 244-253. doi:10.1016/j.isprsjprs.2005.02.003. https://doi.org/10.1016/j.isprsjprs.2005.02.003
  29. Wilhite, D. A., M. J. Hayes, C. Knutson, and K. H. Smith, 2000. Planning for drought: Moving from crisis to risk management. Journal of the American Water Resources Association 36(4): 697-710. https://doi.org/10.1111/j.1752-1688.2000.tb04299.x
  30. Yoo, J. Y., H. Song, T. W. Kim, and J. H. Ahn, 2013. Evaluation of short-term drought using daily standardized precipitation index and ROC analysis. Journal of the Korean Society of Civil Engineers 33(5): 1851-1860 (in Korean). doi:10.12652/Ksce.2013.33.5.1851. https://doi.org/10.12652/Ksce.2013.33.5.1851
  31. Yoon, D. H., W. H. Nam, H. J. Lee, E. M. Hong, T. G. Kim, D. E. Kim, A. K. Shin, and M. D. Svoboda, 2018. Application of evaporative stress index (ESI) for satellite-based agricultural drought monitoring in South Korea. Journal of the Korean Society of Agricultural Engineers 60(6): 121-131 (in Korean). doi:10.5389/KSAE.2018.60.6.121.
  32. Yoon, D. H., W. H. Nam, H. J. Lee, E. M. Hong, F. Song, B. D. Wardlow, T. Tadesse, M. D. Svoboda, M. J. Hayes, and D. E. Kim, 2020. Agricultural drought assessment in East Asia using satellite-based indices. Remote Sensing 12(3): 1-16. doi:10.3390/rs12030444.
  33. Zhang, L., and T. Zhou, 2015. Drought over East Asia: A review. Journal of Climate 28: 3375-3399. doi:10.1175/JCLI-D-14-00259.1. https://doi.org/10.1175/JCLI-D-14-00259.1