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NTIS 바로가기Journal of Korea Water Resources Association = 한국수자원학회논문집, v.49 no.3, 2016년, pp.263 - 273
이재현 (홍익대학교 토목공학과) , 최민하 (성균관대학교 수자원대학원 수자원학과) , 김동균 (홍익대학교 토목공학과)
This study applied conditional merging (CM) spatial interpolation technique to obtain the satellite and in-situ composite soil moisture data. For the analysis, 24 gages of hourly in-situ data sets from the Rural Development Administration (RDA) of Korea and the satellite soil moisture data retrieved...
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핵심어 | 질문 | 논문에서 추출한 답변 |
---|---|---|
토양수분은 어느 분야에서 사용되고 있는가? | 토양수분은 2010년 세계기상기구(World Meteorological Organization)에 의해 필수기후변수(Essential climate variable)로 지정될 만큼 기후변화에 있어 중요한 요소이고(WMO, 2010), 수문 모델, 농업시스템, 가뭄 분석 등 다양한 분야에서 사용되고 있다(Choi and Jacobs, 2008; Bindlish et al., 2009; Dorigo et al. | |
원격탐사기술에 사용되는 센서는 어떻게 구분되는가? | 원격탐사기술은 플랫폼(항공기, 위성)에 탑재된 센서를 이용하여 공간적인 스케일의 토양수분 관측을 가능하게 한다. 원격탐사기술에 사용되는 센서는 능동형 센서(Active sensor)와 수동형 센서(Passive sensor)로 구분된다. 수동형 센서는 태양에서 방출되어 관찰하고자 하는 대상에 반사된 전자기파를 측정하는 원리이고, 능동형 센서는 센서 자체에서 전자기 방사선을 방출해서 반사되는 전자기파를 측정하는 원리이다. | |
지상관측 토양수분 자료를 충분히 획득하는데 어려움이 있는 문제를 해결하는 방법은 무엇인가? | 최근 원격탐사 기술의 발전은 이러한 문제 해결의 가능성을 열어주었다. 원격탐사기술은 플랫폼(항공기, 위성)에 탑재된 센서를 이용하여 공간적인 스케일의 토양수분 관측을 가능하게 한다. 원격탐사기술에 사용되는 센서는 능동형 센서(Active sensor)와 수동형 센서(Passive sensor)로 구분된다. |
Albergel, C., de Rosnay, P., Gruhier, C., Munoz-Sabater, J., Hasenauer, S., Isaksen, L., Wagner, W. et al (2012). "Evaluation of remotely sensed and modelled soil moisture products using global ground-based in situ observations." Remote Sensing of Environment, Vol. 118, pp. 215-226.
Baik, J., Park, J., Ryu, D., and Choi, M. (2016). "Geospatial blending to improve spatial mapping of precipitation with high spatial resolution by merging satellite- and ground based data.", Hydrological Processes, DOI: 10.1002/hyp.10786.
Bardossy, A., and Lehmann, W. (1998). "Spatial Distribution of Soil Moisture in a Small Catchment. Part 1: Geostatistical Analysis." Journal of Hydrology, Vol. 206, No. 1, pp. 1-15.
Berndt, C., Rabiei, E., and Haberlandt, U. (2014). "Geostatistical merging of rain gauge and radar data for high temporal resolutions and various station density scenarios." Journal of Hydrology, Vol. 508, pp. 88-101.
Bindlish, R., Crow, W.T., and Jackson, T.J. (2009). "Role of passive microwave remote sensing in improving flood forecasts." Geoscience and Remote Sensing Letters, IEEE, Vol. 6, No. 1, pp. 112-116.
Bolten, J. D., Crow, W. T., Zhan, X., Jackson, T. J., and Reynolds, C. A. (2010). "Evaluating the utility of remotely sensed soil moisture retrievals for operational agricultural drought monitoring." Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, Vol. 3, No. 1, pp. 57-66.
Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., and Bittelli, M. (2011). "Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe." Remote Sensing of Environment, Vol. 115, No. 12, pp. 3390-3408.
Cho, E., and Choi, M. (2014). "Regional scale spatio-temporal variability of soil moisture and its relationship with meteorological factors over the Korean peninsula." Journal of Hydrology, Vol. 516, pp. 317-329.
Cho, E., Choi, M., and Wagner, W. (2015). "An assessment of remotely sensed surface and root zone soil moisture through active and passive sensors in northeast Asia." Remote Sensing of Environment, Vol. 160, No. 166-179.
Choi, J.G. (2007). Geostatistics. Sigmapress.
Choi, M., and Hur, Y. (2012). "A microwave-optical/infrared disaggregation for improving spatial representation of soil moisture using AMSR-E and MODIS products." Remote Sensing of Environment, Vol. 124, pp. 259-269.
Choi, M., and Jacobs, J.M. (2007). Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints. Advances in Water Resources, Vol. 30, No. 4, pp. 883-896.
Choi, M., and Jacobs, J.M. (2008). "Temporal variability corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) surface soil moisture: case study in Little River region, Georgia, US." Sensors, Vol. 8, No. 4, pp. 2617-2627.
Crow, W.T., Miralles, D.G., and Cosh, M.H. (2010). "A quasi-global evaluation system for satellite-based surface soil moisture retrievals." Geoscience and Remote Sensing, IEEE Transactions on, Vol. 48, No. 6, pp. 2516-2527.
Dorigo, W.A., Scipal, K., Parinussa, R.M., Liu, Y.Y., Wagner, W., De Jeu, R.A.M., and Naeimi, V. (2010). "Error characterisation of global active and passive microwave soil moisture datasets." Hydrology and Earth System Sciences, Vol. 14, No. 12, pp. 2605-2616.
Draper, C. S., Walker, J. P., Steinle, P. J., de Jeu, R. A., and Holmes, T. R. (2009). "An evaluation of AMSR-E derived soil moisture over Australia." Remote Sensing of Environment, Vo. 113, No. 4, pp. 703-710.
Ehret U. (2002). Rainfall and flood nowcasting in small catchments using weather radar. PhD Thesis, University of Stuttgart.
Goudenhoofdt, E., and Delobbe, L. (2009). "Evaluation of radargauge merging methods for quantitative precipitation estimates." Hydrology and Earth System Sciences, Vol. 13, No. 2, pp. 195-203.
Jackson, T.J., Cosh, M.H., Bindlish, R., Starks, P.J., Bosch, D.D., Seyfried, M., and Du, J. et al. (2010). "Validation of advanced microwave scanning radiometer soil moisture products." Geoscience and Remote Sensing, IEEE Transactions on, Vol. 48, No. 12, pp. 4256-4272.
Kim, B. J., Kripalani, R. H., Oh, J. H., and Moon, S. E. (2002). "Summer monsoon rainfall patterns over South Korea and associated circulation features." Theoretical and applied climatology, Vol. 72, No. 1-2, pp. 65-74.
Kim, H., Seonwoo, W., Kim, S., and Choi, M. (2016). Construction and estimation of soil moisture site with FDR and COSMIC-ray (SM-FC) sensors for calibration/validation of satellite-based and COSMIC-ray soil moisture products in Sungkyunkwan university, South Korea, Korea Water Resources Association. (in Press)
Kim, S., Liu, Y.Y., Johnson, F.M., Parinussa, R.M., and Sharma, A. (2015). "A global comparison of alternate AMSR2 soil moisture products: Why do they differ?" Remote Sensing of Environment, Vol. 161, pp. 43-62.
Koike, T., Nakamura, Y., Kaihotsu, I., Davva, G., Matsuura, N., Tamagawa, K., et al. (2004). "Development of an advanced microwave scanning radiometer (AMSR-E) algorithm for soil moisture and vegetation water content." Annual Journal of Hydraulic Engineering, JSCE, Vol. 48, No. 2, pp. 6.
Loew, A., Holmes, T., and de Jeu, R. (2009). "The European heat wave 2003: Early indicators from multisensoral microwave remote sensing?" Journal of Geophysical Research: Atmospheres (1984-2012), Vol. 114, No. D5.
Miralles, D.G., Crow, W.T., and Cosh, M.H. (2010). "Estimating spatial sampling errors in coarse-scale soil moisture estimates derived from point-scale observations." Journal of Hydrometeorology, Vol. 11, No. 6, pp. 1423-1429.
Njoku, E., Jackson, T., Lakshmi, V., Chan, T., and Nghiem, S.V. (2003), "Soil moisture retrieval from AMSR-E", IEEE Trans. Geosci. Remote Sens., Vol. 41, pp. 215-229.
Owe, M., De Jeu, R. A.M., and Holmes, T.R.H. (2008). "Multisensor historical climatology of satellite derived global land surface moisture." Journal of Geophysical Research, Vol. 113(F1 F01002).
Paloscia, S., Macelloni, G., and Santi, E. (2006). "Soil moisture estimates from AMSR-E brightness temperatures by using a dual-frequency algorithm." Geoscience and Remote Sensing, IEEE Transactions on, 44(11), 3135-3144.
Pandey, V., and Pandey, P.K. (2010). "Spatial and temporal variability of soil moisture." International Journal of Geosciences, Vol. 1, No. 2, pp. 87.
Pegram, G.G.S. (2002). Spatial interpolation and mapping of rainfall: 3. Optimal integration of rain gauge, radar & satellitederived data in the production of daily rainfall maps. Progress report to the Water Research Commission.
Rudiger, C., Calvet, J.C., Gruhier, C., Holmes, T.R., De Jeu, R. A., and Wagner, W. (2009). "An intercomparison of ERS-Scat and AMSR-E soil moisture observations with model simulations over France." Journal of Hydrometeorology, Vol. 10, No. 2, pp. 431-447.
Sinclair, S., and Pegram, G. (2005). "Combining radar and rain gauge rainfall estimates using conditional merging." Atmospheric Science Letters, Vol. 6, No. 1, pp. 19-22.
WMO (2010). Implementation plan for the global observing system for climate in support of the UNFCCC (2010 update). World Meteorological Organization. GCOS-138.
Zhang, A., and Jia, G. (2013). "Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data." Remote Sensing of Environment, Vol. 134, pp. 12-23.
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