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위성기반의 식생지수를 활용한 농업적 가뭄감시

Agricultural drought monitoring using the satellite-based vegetation index

  • 백슬기 (중부대학교 대학원 토목공학과) ;
  • 장호원 (중부대학교 대학원 토목공학과) ;
  • 김종석 (서울시립대학교 도시홍수연구소) ;
  • 이주헌 (중부대학교 공과대학 토목공학과)
  • 투고 : 2015.12.14
  • 심사 : 2016.02.22
  • 발행 : 2016.04.30

초록

본 연구에서는 농업적 가뭄을 시, 공간적으로 파악하기 위하여 Terra의 MODIS 원격탐사 자료를 활용하여 가뭄의 정량적 평가를 실시하였다. 여러 가지 위성영상 중에서 식생 상태의 변화가 관찰되는 MOD13A3 영상을 통하여 NDVI (Normalized Difference Vegetation Index)와 EVI (Enhanced Vegetation Index)를 선정하였으며, 토지정보를 효율적으로 수집할 수 있는 MCD12Q1 영상의 Type1을 통하여 물, 도심지역 등을 제외한 식생부분만을 나타낼 수 있도록 토지피복분류를 하였다. 토지피복분류된 자료를 이용하여 NDVI와 EVI를 중권역별로 산정하여 나타낸 결과 계절적인 성향이 강하게 나타나 이를 보완하고자 EVI의 표준화 지수인 VSIA (Vegetation Stress Index Anomaly)를 우리나라의 극심한 가뭄해인 2001년에 대하여 중권역별로 산정하였다. 또한, 과거 우리나라의 농업가뭄 피해를 조사하였으며, 지상강우관측소의 자료를 통하여 SPI (Standardized Precipitation Index)를 중권역별로 산정하였다. SPI와 위성영상의 표준화 지수인 VSIA를 우리나라의 농업적 가뭄피해 연도와 비교하였으며, VISA의 시공간적 분석을 통해 한반도의 농업적 가뭄을 평가할 수 있는 활용성 및 적용 가능성을 검토하였다.

In this study, a quantitative assessment was carried out in order to identify the agricultural drought in time and space using the Terra MODIS remote sensing data for the agricultural drought. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were selected by MOD13A3 image which shows the changes in vegetation conditions. The land cover classification was made to show only vegetation excluding water and urbanized areas in order to collect the land information efficiently by Type1 of MCD12Q1 images. NDVI and EVI index calculated using land cover classification indicates the strong seasonal tendency. Therefore, standardized Vegetation Stress Index Anomaly (VSIA) of EVI were used to estimated the medium-scale regions in Korea during the extreme drought year 2001. In addition, the agricultural drought damages were investigated in the country's past, and it was calculated based on the Standardized Precipitation Index (SPI) using the data of the ground stations. The VSIA were compared with SPI based on historical drought in Korea and application for drought assessment was made by temporal and spatial correlation analysis to diagnose the properties of agricultural droughts in Korea.

키워드

참고문헌

  1. Eidenshink, J.C. (1992). The 1990 Conterminous U.S. AVHRR Dataset, Photogrammetric Engineering & Remote Sensing, Vol. 58, No. 6, pp. 809-813.
  2. Eoh, M.S. (2001). Drought and measures 2001, Journal of Urban Hazard Mitigation, Korean Society of Hazard Mitigation, Vol. 1 , No. 2, pp. 4-8.
  3. IPCC (2007). Climate Change 2007: The physical science basis, Contribution of Working Group I to the Fourth Assessment, in S. Solomon, D. Qin, M. Mannigna, Z.Chen, M. Marquis, K.B. Averyt, M. Tignor, and H.L. Miller (Eds.), Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996.
  4. IPCC (2014). Climate change (2014): Impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press.
  5. Jhang, J.H., Jiang, L.G., Feng, Z.M., and Li, P. (2012). Etecting Effects of the Recent Drought on Vegetatin in Southwestern China J. Resour. Ecol. Vol. 3. No. 1. pp. 43-49. https://doi.org/10.5814/j.issn.1674-764x.2012.01.007
  6. Kim, G.S., and Park, H.G. (2010). Estimation of Drought Index Using CART Algorithm and Satellite Data, The Korean Association of Geographic Information Studies Vol. 13, No. 1, pp. 128-141.
  7. Kim, G.S., and Park, J.S. (2006). Correlation Analysis of Vegetation Index and Drought Index Korean Welands Society, Vol. 8, No. 1, pp. 49-58.
  8. Kim, B.S., and Lee, J.W. (2011). Evaluation of Drought Indices using the Drought Records, Journal of Korea Water Resources Association, Vol. 44, No. 8, pp. 639-652. https://doi.org/10.3741/JKWRA.2011.44.8.639
  9. Kim, B.S., Sung, J.H., Lee, B.H., and Kim, D.J. (2013). Evaluation on the impact of extreme droughts in South Korea using the SPEI and RCP8.5. Climate Change Scenario Journal of Kosham, Vol. 13, No. 2, pp. 97-109.
  10. Kogan, F.N. (1990). Remote Sensing of Drought, Proceedings of International Geoscience and Remote Sensing Symposium, pp. 591-594.
  11. Kogan, F.N. (1995). Application of Vegetation Index and Brightness Temperature for Drought Detection, Adv. in Space Res., Vol. 15, pp. 91-100.
  12. Kogan, F.N. (1997). Global drought watch from space, Bulletin of the American Meteological Society, Vol. 78, pp. 621-636. https://doi.org/10.1175/1520-0477(1997)078<0621:GDWFS>2.0.CO;2
  13. Kogan, F.N., Gitelson, A., Edige, Z., Spivak, I., and Lebed, L. (2003). AVHRR-Based Spectral Vegetation Index for Quantitative Assessment of Vegetation Sate and Productivity: Calibration and Validation, Photogram metric Engineering & Remote Sensing, Vol. 69, No. 8, pp. 899-906. https://doi.org/10.14358/PERS.69.8.899
  14. Korea Water Resources Corporation (2002). 2001 National Drought Investigation Report, pp. 57-95.
  15. Lee, J.H., Kim, J.S., Jang, H.W., and Lee, J.C. (2013). Drought Forecasting Using the Multi Layer Perceptron (MLP) Artificial Neural Network Model, Journal of Korea Water Resources Association, Vol. 46, No. 12, pp. 1249-1263. https://doi.org/10.3741/JKWRA.2013.46.12.1249
  16. Liu, H.Q., and Huete, A.R. (1995). A feedback based modification of the NDVI to minimize canopy background and atmospheric noise, IEEE Trans. Geosci. Remote Sensing 33, pp. 457-465. https://doi.org/10.1109/36.377946
  17. Ministry of Land, Infrastructure and Transport (MLIT) (2002). 2001 Drought Impact Investgation Report.
  18. Park, J.S., Kim, K.T., and Kim, J.H. (2005). Analysis of the Possibility for Practical Use of Vegetation Indices and Drought Indices for Drought Detection, Proceedings of the KSRS Conference, Korean Society of Remote Sensing, pp. 157-160.
  19. Rouse, J.W. (1974). "Monitoring vegetation Systems in the Great Plains with ERTS," Proceedings, Third Earth Resources Technology Satellite-1 Symposium, Greenbelt: NASA SP-351, 3010-317.
  20. Shin, S.H. (2005). Applicability Analysis of Drought Index using Multi-temporal NDVI, M.S. dissertation, Inha University, pp. 33-54.
  21. Son, K.H., Bae, D.H., and Cheong, H.S. (2015). Construction & Evaluation of GloSea5-Based Hydrological Drought Outlook System, Atmosphere Korean Meteorological Society, Vol. 25, No. 2, pp. 271-281.
  22. Wilhite, D.A. (2000). Drought as a natural hazard: concepts and definitions. In: Wilhite D.A. (ed) Drought: a global assessment, Routledge, pp. 3-18.

피인용 문헌

  1. Appraisal of drought characteristics of representative drought indices using meteorological variables 2017, https://doi.org/10.1007/s12205-017-1744-x
  2. Evaluation of multi-sensor satellite data for monitoring different drought impacts vol.32, pp.9, 2018, https://doi.org/10.1007/s00477-018-1537-x