Quantitative retrieval of soil moisture content in the upper reaches of the Minjiang river

• Autorzy: Bing X. , Wu-nian Y. , Xiao-ai D. , Yu-lan W. , Xin Y.
• Języki publikacji: EN

Abstrakty

EN

This paper analyzes the correlation between soil moisture data and different spectral data transformation, and it reveals that the correlation coefficient of soil moisture is highest near 584 nm, 711 nm, 1,055 nm, 1,420 nm, 1,635 nm, 2,176 nm, and 2,257 nm. The highest correlation coefficient can be up to 0.83206. Multiple regression analysis can be done to understand the correlation between the two, find out the reflectance values at the above fixed spectrum through a bilinear correlation, and quantitatively invert soil moisture in the study area, shedding new light on soil moisture in this large area.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2018
• Tom: 27
• Numer: 5
• Opis fizyczny: p.1959-1964,fig.,ref.

Twórcy

autor

Bing X.

• Key Laboratory of Geoscience Spatial Information Technology of Land and Resources, Chengdu University of Technology, Chengdu, China

autor

Wu-nian Y.

• Key Laboratory of Geoscience Spatial Information Technology of Land and Resources, Chengdu University of Technology, Chengdu, China

autor

Xiao-ai D.

• Key Laboratory of Geoscience Spatial Information Technology of Land and Resources, Chengdu University of Technology, Chengdu, China

autor

Yu-lan W.

• Key Laboratory of Geoscience Spatial Information Technology of Land and Resources, Chengdu University of Technology, Chengdu, China

autor

Xin Y.

• Key Laboratory of Geoscience Spatial Information Technology of Land and Resources, Chengdu University of Technology, Chengdu, China

Bibliografia

• 1. CHAMPAGNE C., MCNAIRN H., BERG A.A. Monitoring agricultural soil moisture extremes in Canada using passive microwave remote sensing. Remote Sensing of Environment, 115, 2434, 2011.
• 2. DANIEL A.S., JOHN A.G. Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: a comparison of indices based on liquid water and chlorophyll absorption features. Remote Sensing of Environment, 84, 526, 2003.
• 3. JEU R.A.M., WAGNER W., HOLMES T.R.H., DOLMAN A.J., van de GIESEN N.C., FRIESEN J. Global soil moisture patterns observed by space borne microwave radiometers and scatterometers. Surveys in Geophysics, 29, 399, 2008.
• 4. FLORES A.N., IVANOV V.Y., ENTEKHABI D., BRAS R.L. Impact of hillslope-scale organization of topography, soil moisture, soil temperature, and vegetation on modeling surface microwave radiation emission. IEEE Transactions on Geoscience & Remote Sensing, 47, 2557, 2009.
• 5. GARY C.H., PATRICK J.S., LAJPAT R.A., THOMAS J.J. Assimilation of surface soil moisture to estimate profile soil water content. Journal of Hydrology, 279, 1, 2003.
• 6. JACKSON T.J. Measuring surface soil moisture using passive microwave remote sensing. Hydrological Processes, 7, 139, 1993.
• 7. KOSTOV K.G., JACKSON T.J. Estimating profile soil moisture from surface layer measurements: A review. Proc. SPIE, 1941, 125, 1993.
• 8. BéHAEGEL M., SAILHAC P., MARQUIS G. On the use of surface and ground temperature data to recover soil water content information. Journal of Applied Geophysics, 62, 234, 2007.
• 9. MERLIN O., AL B.A., WALKER J.P. An improved algorithm for disaggregating microwave-derived soil moisture based on red, nearinfrared and thermal-infrared data. Remote Sensing of Environment, 114, 2305, 2010.
• 10. PAN M., Sahoo A.K., Wood E.F. Improving soil moisture retrievals from a physically based radiative transfer model. Remote Sensing of Environment, 140, 130, 2014.
• 11. TEMIMI M., LECONTE R., CHAOUCH N., SUKUMAL P., KHANBIVARDI R., BRISSETTE F. A combination of remote sensing data and topographic attributes for the spatial and temporal monitoring of soil wetness. Journal of Hydrology, 388, 28, 2010.
• 12. PARINUSSA R.M., HOLMES T.R.H., de JEU R.A.M. Soil moisture retrievals from the WindSat spaceborne polarimetric microwave radiometer. IEEE Transactions on Geoscience and Remote Sensing, 50, 2683, 2012.
• 13. SUNGWOOK H., INCHUL S. A physically-based inversion algorithm for retrieving soil moisture in passive microwave remote sensing. Journal of Hydrology 405, 24, 2011.
• 14. ROTH K., SCHULIN R., FLUEHLER H., ATTINGER W. Calibration of TDR for water content measurement using a composite dielectric approach. Water Resources Research, 26, 2267, 1990.
• 15. RAHIMZADEH-BAJGIRAN P., BERG A.A., CHAMPAGNE C. Estimation of soil moisture using optical/thermal infrared remote sensing in the Canadian Prairies. ISPRS Journal of Photogrammetry and Remote Sensing, 83, 94, 2013.
• 16. QU W., BOGENA H.R., HUISMAN J.A., VEREECKEN H. Calibration of a novel low-cost soil water content sensor based on a ring oscillator. Vadose Zone J. 12, 1, 2013.
• 17. RAHIMZADEH-BAJGIRAN P., OMASA K., SHIMIZU Y. Comparative evaluation of the Vegetation Dryness Index (VDI), the Temperature Vegetation Dryness Index (TVDI) and the improved TVDI (iTVDI) for water stress detection in semi-arid regions of Iran. ISPRS Journal of Photogrammetry and Remote Sensing, 68, 1, 2012.
• 18. ROSENBAUM U., BOGENA H.R., HERBST M., HUISMAN J.A., PETERSON T.J., WEUTHEN A., WESTERN A.W. VEREECKEN H. Seasonal and event dynamics of spatial soil moisture patterns at the small catchment scale. Water Resources Research, 48, 3472, 2012.
• 19. RüDIGER C., WALKER J.P., KERR Y., KIM E.J., HACKER J., GURNEY R., BARRETT D, MARSHALL J. Toward Vicarious Calibration of Microwave Remote-Sensing Satellites in Arid Environments. IEEE Transactions on Geoscience and Remote Sensing, 52, 1749, 2014.
• 20. SCHWALM C.R., EK A.R. A process-based model of forest ecosystems driven by meteorology. Ecological Modelling, 179, 317, 2004.
• 21. HASAN S., MONTZKA C., RüDIGER C., ALI M., BOGENA H.R., VEREECKEN H. Soil moisture retrieval from airborne L-band passive microwave using high resolution multispectral data. ISPRS Journal of Photogrammetry and Remote Sensing, 91, 59, 2014.
• 22. WAN Z., WANG P., LI X. Land Surface Temperature and Normalized Difference Vegetation Index Products for Monitoring Drought in the Southern Great Plains. International Journal of Remote Sensing, 25, 61, 2005.
• 23. JU W.M., GAO P., WANG J. Combining an ecological model with remote sensing and GIS techniques tomonitor soil water content of croplands with a monsoon climate. Agricultural Water Management, 97, 1221, 2010.

Identyfikatory

DOI

10.15244/pjoes/78676