Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
권호 표지
DOI QR코드

DOI QR Code

Spatio-Temporal Resolution Analysis based on Landsat/AMSR2 Soil Moisture

Landsat/AMSR2 기반 토양수분의 시공간적 해상도 분석

  • Lee, Taehwa (Department of Agricultural Civil Engineering, Kyoungpook National University) ;
  • Kim, Sangwoo (Department of Agricultural Civil Engineering, Kyoungpook National University) ;
  • Shin, Yongchul (Department of Agricultural Civil Engineering, Kyoungpook National University)
  • Received : 2019.10.30
  • Accepted : 2019.11.28
  • Published : 2020.01.31
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study is to determine the spatial and temporal resolutions that can represent land surface characteristics comprised of various land use using Landsat/AMSR2-based soil moisture data. We estimated the Landsat (30 m×30 m)-based soil moisture values using the soil moisture regression model. Then, the Landsat (30 m×30 m)-based soil moisture (reference values) were resampled to the relatively coarse resolutions from 1 km to 4 km, respectively. Comparing the reference values to the resampled soil moisture values, we confirmed that uncertainties were increased with the spatial resolutions of 2 km~4 km indicating that the spatial resolution of 1 km×1 km is required to represent the complicated land surface. Also, the AMSR2 soil moisture values have less uncertainties compared to SMAP data with the temporal resolution of 1~2 days. Thus, our findings can be useful for various areas such as agriculture, hydrology, forest, etc.

Keywords

References

  1. Entekhabi, D., E. G. Njoku, P. E. O'Neill, K. H. Kellogg, W. T. Crow, W. N. Edelstein, J. K. Entin, S. D. Goodman, T. J. Jackson, J. Johnson, J. Kimball, J. R. Piepmeier, R. D. Koster, N. Martin, K. C. McDonald, M. Moghaddam, S. Moran, R. Reichle, J. C. Shi, M. W. Spencer, S. W. Thurman, L. Tsang, and J. Van Zyl, 2010. The soil moisture active passive (SMAP) mission. Proceedings of the IEEE 98(5): 704-716. doi:10.1109/JPROC.2010.2043918.
  2. Imaoka, K., M. Kachi, H. Fujii, H. Murakami, M. Hori, A. Ono, T. Igarashi, K. Nakagawa, T. Oki, Y. Honda, and H. Shimoda, 2010. Global change observation mission (GCOM) for monitoring carbon, water cycles, and climate change. Proceedings of the IEEE 98(5): 717-734. doi:10.1109/JPROC.2009.2036869.
  3. Kerr, Y. H., P. Waldteufel, J. Wigneron, J. Martinuzzi, J. Font, and M. Berger, 2001. Soil moisture retrieval from space: The soil moisture and ocean salinity (SMOS) mission. IEEE Transactions on Geoscience and Remote Sensing 39(8): 1729-1735. doi:10.1109/36.942551.
  4. Kim, S., Y. Shin, T. H. Lee, S. H. Lee, K. S. Choi, Y. S. Park, K. J. Yim, and J. Kim, 2017. Characteristics of soil moisture distributions at the spatio-temporal scales based on the land surface features using MODIS images. Journal of The Korean Society of Agricultural Engineers 59(6): 29. doi:10.5389/KSAE.2017.59.6.029.
  5. Njoku, E. G., T. L. Jackson, V. Lakshmi, T. Chan, and S. V. Nghiem, 2003. Soil moisture retrieval from AMSR-E. IEEE Transactions on Geoscience and Remote Sensing 41: 215-229. doi:10.1109/TGRS.2002.808243.
  6. Scott, C. A., W. G. M. Bastiaanssen, and M. D. Ahmad, 2003. Mapping root zone soil moisture using remotely sensed optical imagery. Journal of Irrigation and Drainage Engineering 129(5): 362-335. doi:10.1061/(ASCE)0733-9437(2003)129:5(326).
  7. Shin, Y., K. S. Choi, Y. Jung, J. E. Yang, and K. J. Lim, 2016a. Soil moisture estimation and drought assessment at the spatiotemporal scales using remotely sensed data: (I) Soil moisture. Journal of Korean Society on Water Environment 32(1): 60-69. doi:10.15681/KSWE.2016.32.1.60.
  8. Shin, Y., K. S. Choi, Y. Jung, J. E. Yang, and K. J. Lim, 2016b. Soil moisture estimation and drought assessment at the spatiotemporal scales using remotely sensed data: (II) Drought. Journal of Korean Society on Water Environment 32(1): 70-79. doi:10.15681/KSWE.2016.32.1.70.
  9. Shin, Y., T. Lee, S. Kim, H. W. Lee, K. S. Choi, J. Kim, and K. Lee, 2017. Development of agricultural drought assessment approach using SMAP soil moisture footprints. Journal of The Korean Society of Agricultural Engineers 59(1): 57-70. doi:10.5389/KSAE.2017.59.1.057.