All Issue

2019 Vol.61, Issue 5 Preview Page
Estimation of High-Resolution Soil Moisture based on Sentinel-1A/B SAR Sensors

Sentinel-1A/B SAR 센서 기반 고해상도 토양수분 산정

Sangwoo Kima
,
Taehwa Leeb
,
Yongchul Shinc†
김 상우a
,
이 태화b
,
신 용철c†
aMS Student, Department of Agricultural Civil Engineering, Kyoungpook National University
bPhD Student, Department of Agricultural Civil Engineering, Kyoungpook National University
cProfessor, Department of Agricultural Civil Engineering, Kyoungpook National University
a경북 대학교 농업 토목 공학과
b경북 대학교 농업 토목 공학과 학사
c경북 대학교 농업 토목 공학과 교수
† Corresponding author Tel.: +82-53-950-5734 Fax: +82-53-950-6752 E-mail: ycshin@knu.ac.kr
2019. pp. 89-99
PDF XML Citation
Abstract

In this study, we estimated the spatially-distributed soil moisture at the high resolution (10 m×10 m) using the satellite-based Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images. The Sentinel-1A/B raw data were pre-processed using the SNAP (Sentinel Application Platform) tool provided from ESA (European Space Agency), and then the pre-processed data were converted to the backscatter coefficients. The regression equations were derived based on the relationships between the TDR (Time Domain Reflectometry)-based soil moisture measurements and the converted backscatter coefficients. The TDR measurements from the 51 RDA (Rural Development Administration) monitoring sites were used to derive the regression equations. Then, the soil moisture values were estimated using the derived regression equations with the input data of Sentinel-1A/B based backscatter coefficients. Overall, the soil moisture estimates showed the linear trends compared to the TDR measurements with the high Pearson’s correlations (more than 0.7). The Sentinel-1A/B based soil moisture values matched well with the TDR measurements with various land surface conditions (bare soil, crop, forest, and urban), especially for bare soil (R: 0.885~0.910 and RMSE: 3.162~4.609). However, the Mandae-ri (forest) and Taean-eup (urban) sites showed the negative correlations with the TDR measurements. These uncertainties might be due to limitations of soil surface penetration depths of SAR sensors and complicated land surface conditions (artificial constructions near the TDR site) at urban regions. These results may infer that qualities of Sentinel-1A/B based soil moisture products are dependent on land surface conditions. Although uncertainties exist, the Sentinel-1A/B based high-resolution soil moisture products could be useful in various areas (hydrology, agriculture, drought, flood, wild fire, etc.).

Keywords
Satellite
sentinel-1A/B
soil moisture
SAR
TDR
References

REFERENCES

1
D. Entekhabi, 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, Proceedings of the IEEE, The soil moisture active passive (SMAP) mission., 98(5); 704-716 (2010)27295638
2
Q. Gao, M. Zribi, M. J. Escorihuela and N. Baghdadi, Sensors, Synergetic use of Sentinel-1 and Sentinel-2 data for soil moisture mapping at 100 m resolution., 17(9); 1966 (2017)10.3390/s1709196628846601PMC5621168
3
M. Hornacek, W. Wagner, D. Sabel, H. L. Truong, P. Snoeij, T. Hahmann, E. Diedrich and M. Doubková, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Potential for high resolution systematic global surface soil moisture retrieval via change detection using Sentinel-1., 5(4); 1303-1311 (2012)10.1109/jstars.2012.219013627295638
4
A. Y. Hou, R. K. Kakar, S. Neeck, A. A. Azarbarzin, C. D. Kummerow, M. Kojima, R. Oki, K. Nakamura and T. Iguchi, Bulletin of the American Meteorological Society, The Global Precipitation Measurement(GPM) mission., 95(5); 701-722 (2014)10.1175/bams-d-13-00164.1
5
K. Imaoka, M. Kachi, H. Fujii, H. Murakami, M. Hori, A. Ono, T. Igarashi, K. Nakagawa, T. Oki, Y. Honda and H. Shimoda, Proceedings of the IEEE, Global Change Observation Mission (GCOM) for monitoring carbon, water cycles, and climate change., 98(5); 717-734 (2010)10.1109/jproc.2009.203686927295638
6
J. C. Jang, Retrieval of sea surface wind from Sentinel-1A/B SAR data in the seas around Korea, doctoral dissertation., (in Korean)., Seoul National University. (2018)
7
Y. H. Kerr, P. Waldteufel, J. P. Wigneron, J. A. M. J. Martinuzzi, J. Font and M. Berger, IEEE Transactions on Geoscience and Remote Sensing, Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission., 39(8); 1729-1735 (2001)10.1109/36.94255127295638
8
V. Lakshmi, ISRN Soil Science.Remote Sensing of Soil Moisture. (2013)
9
A. Le Morvan, M. Zribi, N. Baghdadi and A. Chanzy, Sensors, Soil moisture profile effect on radar signal measurement., 8(1); 256-270 (2008)10.3390/s801025627879707PMC3681152
10
S. J. Lee, S. W. Hong, J. Cho and Y. W. Lee, Korean Journal of Remote Sensing, Experimental retrieval of soil moisture for cropland in South Korea using Sentinel-1 SAR Data., 33(6); 947-960, (in Korean).10.7780/ kjrs.2017.33.6.1.4
11
S. Paloscia, S. Pettinato, E. Santi, C. Notarnicola, L. Pasolli and A. Reppucci, Remote Sensing of Environment, Soil moisture mapping using Sentinel-1 images: Algorithm and preliminary validation., 134; 234-248 (2013)
12
F. F. Sabins, Remote sensing: Principles and applications., Waveland Press.. (2007)
13
W. Wagner, D. Sabel, M. Doubkova, A. Bartsch and C. Pathe, In Symposium of Earth Observation and Water Cycle Science.The potential of Sentinel-1 for monitoring soil moisture with a high spatial resolution at global scale. (2009)
14
W. Wagner, G. Lemoine and H. Rott, Remote Sensing of environment, A method for estimating soil moisture from ERS scatterometer and soil data., 70(2); 191-207 (1999)10.1016/S0034-4257(99)00036-X
Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 61
  • No :5
  • Pages :89-99
  • Received Date : 2019-05-21
  • Revised Date : 2019-08-30
  • Accepted Date : 2019-09-02
  • DOI :https://doi.org/10.5389/KSAE.2019.61.5.089
Journal Informaiton Journal of Korean Society of Agricultural Engineers Journal of Korean Society of Agricultural Engineers
  • NRF
  • KOFST
  • crossref crossmark
  • crossref cited-by
  • crossref funder-registry
  • crosscheck
  • orcid
  • open access
Journal Informaiton Journal Informaiton - close