한국농공학회논문집 (Journal of The Korean Society of Agricultural Engineers)

  • 제59권6호
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  • Pages.29-37
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  • 2017
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  • 1738-3692(pISSN)
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  • 2093-7709(eISSN)
한국농공학회 (The Korean Society of Agricultural Engineers)
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MODIS 이미지를 이용한 지표특성에 따른 토양수분의 시·공간적 분포 특성

Characteristics of Soil Moisture Distributions at the Spatio-Temporal Scales Based on the Land Surface Features Using MODIS Images

  • Kim, Sangwoo (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Shin, Yongchul (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Lee, Taehwa (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Lee, Sang-Ho (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Choi, Kyung-Sook (Department of Agricultural Civil Engineering, Kyungpook National University) ;
  • Park, Younshik (Department of Rural Construction Engineering, Kongju National University) ;
  • Lim, Kyoungjae (Department of Regional Infrastructure Engineering, Kangwon National University) ;
  • Kim, Jonggun (Institute of Agriculture and Life Science, Kangwon National University)
  • 투고 : 2017.08.22
  • 심사 : 2017.09.20
  • 발행 : 2017.11.30
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초록

In this study, we analyzed the impacts of land surface characteristics on spatially and temporally distributed soil moisture values at the Yongdam and Soyang-river dam watersheds in 2014 and 2015. The soil moisture, NDVI (Normalized Difference Vegetation Index) and temperature values at the spatio-temporal scales were estimated using satellite-based MODIS (MODerate Resolution Imaging Spectroradiometer) products. Then the Pearson correlations between soil moisture and land surface characteristics (NDVI, temperature and DEM-digital elevation model) were estimated and analyzed, respectively. Overall, the monthly soil moisture values at the time step were highly influenced by the precipitation amounts. Also, the results showed that the soil moisture has the strong correlation with DEM while the temperature was inversely correlated with the soil moisture. However the monthly correlations between NDVI and soil moisture were highly varied along the time step. These findings indicated that water loss near the land surface are highly occurred by soil and plant activities as evapotranspiration and infiltration during the no/less precipitation period. But the high precipitation amounts reduce the impacts of land surface characteristics because of saturated condition of land surface. Thus these results demonstrated that soil moisture values are highly correlated with land surface characteristics. Our findings can be useful for water resources/environmental management, agricultural drought, etc.

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참고문헌

  1. Bastiaanssen, W. G. M., 2000. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey, Journal of hydrology 229(1): 87-100. https://doi.org/10.1016/S0022-1694(99)00202-4
  2. Crow, W. T. E. F. Wood, and R. Dubayah, 2000. Potential for downscaling soil moisture maps derived from space borne imaging radar data, Journal of Geophysical Research 105: 2203-2212. https://doi.org/10.1029/1999JD901010
  3. Donlon, C., 2008. Sentinel-3 OLCI and SLSTR, In Medspiration/ GlobColour symposium, 20th November.
  4. Engman, T., 1991. Application of microwave remote sensing of soil moisture for water resources and agriculture, Remote Sensing Environment 35: 213-226. https://doi.org/10.1016/0034-4257(91)90013-V
  5. Gwak, Y. S., S. H. Kim, S. W. Jung, Y. G. Lee, J. H. Lee, and S. J. Kim, 2015. Spatial and Seasonal Variability of Soil Moisture Properties along Transect Line on a Forest Hillslope in the Cheong-Mi Catchment, Korean Journal of Agricultural and Forest Meteorology 17(1): 45-57. https://doi.org/10.5532/KJAFM.2015.17.1.45
  6. HA, R., H. J. Shin, M. S. Lee, and S. J. Kim, 2010. Estimation of Spatial Evapotranspiration Using satellite images and SEBAL Model, Journal of Korean Society of civil Engineers, B 30(3B): 233-242.
  7. HUR, Y. M., M. H. Choi, H. W. Kim, S. D. Kim, and J. H. Ahn, 2011. Analysis of soil moisture response due to co-hydrological change, Journal of Korean Wetlands Society 13(2): 171-179.
  8. IPCC, 2014: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp.
  9. Jeong, J., 2016. Estimation of Soil Erosion Using National Land Cover Map and USLE, Journal of Korean Society of Environmental Impact Assessment 25(6): 525-531. https://doi.org/10.14249/eia.2016.25.6.525
  10. Kerr, Y. H., P. Waldteufel, J. P. Wigneron, J. M. Martnuzzi, J. Fondt, and M. Berger, 2001. Soil moisture retrieval from space: The soil moisture and ocean salinity (SMOS) mission, IEEE Transaction of Geoscience remote sensing 39(8): 1729-1735. https://doi.org/10.1109/36.942551
  11. Kim, J. H., K. T. Kim, and H. J. Lee, 2009. Analysis of Korea Soil erosion yields and Soil loss hazard zone, The journal of geographic information system association of Korea 17(3): 261-268.
  12. Kim, N. S., H. C. Lee, and J. Y. Cha, 2013. A Study on Changes of Phenology and Characteristics of Spatial Distribution Using MODIS Images, Journal of the Korea Society of Environmental Restoration Tecnology 16(5): 59-69. https://doi.org/10.13087/kosert.2013.16.5.059
  13. Lee, J. H., S. K. Kang, K. C. Jang, J. H. Ko, and S. Y. Hong, 2011. The evaluation of meteorological inputs retrieved from MODIS for estimation of gross primary productivity in the US corn belt region, Korean Journal of Remote Sensing 27(4): 481-494. https://doi.org/10.7780/kjrs.2011.27.4.481
  14. Lee, J. H., 2011. The Study about Reasonableness Assessment of Soil Erosion Load Computed using USLE Model. Master's Thesis, Seoul, Hanyang University.
  15. Merlin, O., G. Chehbouni, Y. Kerr, E. G. Njoku, and D. Entekhabi, 2005. A combined modeling and multi-spectral/multi-resolution remote sensing approach for disaggregation of surface soil moisture:Application to SMOS configuration, IEEE Transaction of Geoscience Remote Sensing 43(9): 2036-2050. https://doi.org/10.1109/TGRS.2005.853192
  16. Merlin, O., C. Rudiger, A. Al Bitar, J. P. Walker, and Y. H. Kerr, 2012. Disaggregation of SMOS soil moisture in sourheastern Australia, IEEE Transaction of Geoscience Remote Sensing 50(5): 1556-1571. https://doi.org/10.1109/TGRS.2011.2175000
  17. Njoku, E., 2008. AMSR-E/Aqua dail L3 surface soil moisture, interpretive parameter & QC EASE-Grids V002, National Snow and Ice Data Center, Boulder, CO.
  18. Park, C. W., Y. K. Sonn, Y. S. Zhang, S. Hong, B. K. Hyun, K. C. Song, and Y. H. Moon, 2010. Soil erosion risk assessment in the upper Han River basis using spatial soil erosion map, Korean Journal of Soil Science and Fertilizer 43(6): 828-836.
  19. Park, C. W., Y. K. Sonn, B. K. Hyun, K. C. Song, H. C. Chun, H. J. Cho, ... and S. G. Yun, 2012. Soil erosion risk assessment by soil characteristics and landuse in the upper Nakdong River basin, Korean Journal of Soil Science and Fertilizer 45(6): 890-896. https://doi.org/10.7745/KJSSF.2012.45.6.890
  20. Park, J. Y., H. Jung, C. H. Jang, and S. J. Kim, 2014. Assessing climate change impact on hydrological components of Yongdam dam watershed using RCP emission scenarios and SWAT model, Journal of the Korean Society of Agricultural Engineers 56(3): 19-29. https://doi.org/10.5389/KSAE.2014.56.3.019
  21. Shin, Y., B. P. Mohanty, and A. V. M. Ines, 2012. Soil hydraulic properties in one-dimensional layered soil profile using layerspecific soil moisture assimilation scheme, Water Resources Research 48: 1-15. https://doi.org/10.1016/j.advwatres.2012.07.002
  22. Sunwoo, W., D. Kim, S. Hwang, and M. Choi, 2014. Analysis of Regional Antecedent Wetness Conditions Using Remotely Sensed Soil Moisture and Point Scale Rainfall Data, Korean Journal of Remote Sensing 30(5): 587-596. https://doi.org/10.7780/kjrs.2014.30.5.4
  23. Shin, H. J., M. J. Park, E. H. Hwang, H. S. Chae, and S. J. Park, 2015. A Study of Spring Drought Using Terra MODIS Satellite Image-For the Soyanggang Dam Watershed, Journal of the Korean Association of Geographic Information Studies 18(4): 145-157. https://doi.org/10.11108/kagis.2015.18.4.145
  24. Shin, Y., K. S. Choi, Y. Jung, J. E. Yang, and K. J. Lim, 2016. Soil Moisture Estimation and Drought Assessment at the Spatio-Temporal Scales using Remotely Sensed Data : (I) Soil Moisture, Journal of Korean Society on Water Environment 32(1): 60-69. https://doi.org/10.15681/KSWE.2016.32.1.60
  25. Van der Werf, H. M. and J. Petit, 2002. Evaluation of the environmental impact of agriculture at the farm level: a comparison and analysis of 12 indicator-based methods, Agriculture, Ecosystems & Environment 93(1): 131-145. https://doi.org/10.1016/S0167-8809(01)00354-1
  26. Wischmeier, W. H. and D. D. Smith, 1978. Predicting rainfall erosion losses, A Guide to Conservation Planning, The USDA Agricultural Handbook No.537.
  27. Y. G. Lee, S. H. Kim, S. R. Ahn, M. H. Choi, K. S. Lim, and S. J. Kim, 2015. Estimation of Spatial Evapotranspiration Using Terra MODIS Satellite Image and SEBAL Model - A Case of Yongdam Dam Watershed -, Journal of the Korean Association of Geographic Information Studies 18(1): 90-104. https://doi.org/10.11108/kagis.2015.18.1.090