Bibliografia

2 downloads 0 Views 113KB Size Report
over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms. In EGU Gene- ral Assembly Conference Abstracts, tom 18 serii ...
Bibliografia Adams, J. R., McNairn, H., Berg, A. A., i Champagne, C. (2015). Evaluation of near-surface soil moisture data from an AAFC monitoring network in Manitoba, Canada: Implications for L-band satellite validation. Journal of Hydrology, 521:582–592. Al-Yaari, A., Wigneron, J.-P., Ducharne, A., Kerr, Y., de Rosnay, P., de Jeu, R., Govind, A., Bitar, A. A., Albergel, C., Muñoz-Sabater, J., Richaume, P., i Mialon, A. (2014a). Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates. Remote Sensing of Environment, 149:181 – 195. Al-Yaari, A., Wigneron, J.-P., Ducharne, A., Kerr, Y., Wagner, W., Lannoy, G. D., Reichle, R., Bitar, A. A., Dorigo, W., Richaume, P., i Mialon, A. (2014b). Global-scale comparison of passive (SMOS) and active (ASCAT) satellite based microwave soil moisture retrievals with soil moisture simulations (MERRA-Land). Remote Sensing of Environment, 152:614–626. Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., i Martin, E. (2008). From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations. Hydrology and Earth System Sciences, 12(6):1323–1337. Alexander, L. V., Zhang, X., Peterson, T. C., Caesar, J., Gleason, B., Klein Tank, A. M. G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., Tagipour, A., Rupa Kumar, K., Revadekar, J., Griffiths, G., Vincent, L., Stephenson, D. B., Burn, J., Aguilar, E., Brunet, M., Taylor, M., New, M., Zhai, P., Rusticucci, M., i Vazquez-Aguirre, J. L. (2006). Global observed changes in daily climate extremes of temperature and precipitation. Journal of Geophysical Research: Atmospheres, 111(D5). D05109. Alexandridis, T. K., Cherif, I., Bilas, G., Almeida, W. G., Hartanto, I. M., van Andel, S. J., i Araujo, A. (2016). Spatial and temporal distribution of soil moisture at the catchment scale using remotely-sensed energy fluxes. Water, 8(1):32. Alvarez-Garreton, C., Ryu, D., Western, A. W., Su, C.-H., Crow, W. T., Robertson, D. E., i Leahy, C. (2015). Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes. Hydrology and Earth System Sciences, 19(4):1659–1676. Andrzejkiewicz, W. (2012). Ocena wpływu interferencji elektromagnetycznej na terenie Polski na obserwacje zdalne wilgotno´sci gleby wykonywane przy pomocy sondy satelitarnej MIRAS w ramach programu SMOS. Praca magisterska, Politechnika Warszawska. Arnell, N. W. (1999). Climate change and global water resources. Global Environmental Change, 9, Supplement 1:S31 – S49. Attema, E. P. W. i Ulaby, F. T. (1978). Vegetation modeled as a water cloud. Radio Science, 13(2):357–364.

Bibliografia Baghdadi, N., Chaaya, J. A., i Zribi, M. (2011). Semiempirical calibration of the integral equation model for SAR data in C-Band and cross polarization using radar images and field measurements. IEEE Geoscience and Remote Sensing Letters, 8(1):14–18. Balling, J., Søbjoerg, S., Kristensen, S., i Skou, N. (2010). RFI and SMOS: Preparatory campaigns and first observations from space. In Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 2010 11th Specialist Meeting on, strony 282–287. Bamler, R. i Eineder, M. (1996). Scansar processing using standard high precision sar algorithms. IEEE Transactions on Geoscience and Remote Sensing, 34(1):212–218. Beguería Santiago, Vicente-Serrano Sergio M., i Angulo-Martínez Marta (2010). A Multiscalar Global Drought Dataset: The SPEIbase: A New Gridded Product for the Analysis of Drought Variability and Impacts. Bulletin of the American Meteorological Society, 91(10):1351–1356. doi: 10.1175/2010BAMS2988.1. Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., i Harding, R. J. (2011). The joint uk land environment simulator (jules), model description part 1: Energy and water fluxes. Geoscientific Model Development, 4(3):677–699. Bindlish, R. i Barros, A. P. (2000). Multifrequency soil moisture inversion from SAR measurements with the use of IEM. Remote Sensing of Environment, 71(1):67 – 88. Bindlish, R. i Jackson, T. (2015). Aquarius L3 Gridded 1-Degree Daily Soil Moisture Data, Version 4. http:// nsidc.org/data/docs/daac/aquarius/aq3-sm/. Boulder, Colorado USA: NASA National Snow and Ice Data Center Distributed Active Archive Center, Dost˛ep: 2016-01-30. Bindlish, R., Jackson, T., Cosh, M., Zhao, T., i O’Neill, P. (2015). Global soil moisture from the aquarius/sac-d satellite: Description and initial assessment. Geoscience and Remote Sensing Letters, IEEE, 12(5):923–927. Boivin, P. (2011). Shrinkage and Swelling Phenomena in Soils, strony 733–735. Springer Netherlands, Dordrecht. Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., i Levizzani, V. (2014). Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research: Atmospheres, 119(9):5128–5141. 2014JD021489. Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., i Hahn, S. (2012). Assimilation of surface- and root-zone ascat soil moisture products into rainfall – runoff modeling. Geoscience and Remote Sensing, IEEE Transactions on, 50(7):2542–2555. Brown, M. E. i Escobar, V. M. (2014). Assessment of soil moisture data requirements by the potential smap data user community: Review of smap mission user community. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(1):277–283. Buis, A. (2015). SMAP Team Investigating Radar Instrument Anomaly. https://smap.jpl.nasa.gov/news/1244/ smap-team-investigating-radar-instrument-anomaly. Dost˛ep: 2017-02-04. Burgers, G., Leeuwen, P. J. V., i Evensen, G. (1998). On the analysis scheme in the ensemble kalman filter. Monthly Weather Review, 126:1719–1724. Carrão, H., Russo, S., Sepulcre-Canto, G., i Barbosa, P. (2015). An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data. International Journal of Applied Earth Observation and Geoinformation. Castro, R., Gutierrez, A., i Barbosa, J. (2012). A first set of techniques to detect radio frequency interferences and mitigate their impact on smos data. Geoscience and Remote Sensing, IEEE Transactions on, 50(5):1440–1447.

252

Bibliografia CESBIO (2017). Lokalizacja i wielko´sc´ zanieczyszczenia RFI - dane przechowywane na serwerze CESBIO, dost˛ep marzec 2017. http://www.cesbio.ups-tlse.fr. Dost˛ep: 2016-05-06. Champagne, C., Rowlandson, T., Berg, A., Burns, T., L’Heureux, J., Tetlock, E., Adams, J. R., McNairn, H., Toth, B., i Itenfisu, D. (2015). Satellite surface soil moisture from {SMOS} and aquarius: Assessment for applications in agricultural landscapes. International Journal of Applied Earth Observation and Geoinformation. Champagne Catherine, Davidson Andrew, Cherneski Patrick, L’Heureux Jessika, i Hadwen Trevor (2014). Monitoring Agricultural Risk in Canada Using L-Band Passive Microwave Soil Moisture from SMOS. Journal of Hydrometeorology, 16(1):5–18. doi: 10.1175/JHM-D-14-0039.1. Corbella, I., Torres, F., Camps, A., Duffo, N., i Vall-llossera, M. (2009). Brightness-temperature retrieval methods in synthetic aperture radiometers. IEEE Transactions on Geoscience and Remote Sensing, 47(1):285–294. Cosh, M. H., Jackson, T. J., Starks, P., i Heathman, G. (2006). Temporal stability of surface soil moisture in the little washita river watershed and its applications in satellite soil moisture product validation. Journal of Hydrology, 323(1–4):168 – 177. Crow, W. T., Berg, A. A., Cosh, M. H., Loew, A., Mohanty, B. P., Panciera, R., de Rosnay, P., Ryu, D., i Walker, J. P. (2012). Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Reviews of Geophysics, 50(2). RG2002. Crow, W. T., Ryu, D., i Famiglietti, J. S. (2005). Upscaling of field-scale soil moisture measurements using distributed land surface modeling. Advances in Water Resources, 28(1):1 – 14. CSA (2015). Radarsat-2, opis misji. http://www.asc-csa.gc.ca/eng/satellites/radarsat2/. Dost˛ep: 2015-03-25. Daganzo-Eusebio, E., Oliva, R., Kerr, Y., Nieto, S., Richaume, P., i Mecklenburg, S. (2013). Smos radiometer in the 1400 - 1427-mhz passive band: Impact of the rfi environment and approach to its mitigation and cancellation. Geoscience and Remote Sensing, IEEE Transactions on, 51(10):4999–5007. Das, N. N., Entekhabi, D., i Njoku, E. G. (2011). An algorithm for merging SMAP radiometer and radar data for high-resolution soil-moisture retrieval.

IEEE Transactions on Geoscience and Remote Sensing,

49(5):1504–1512. Das, N. N., Entekhabi, D., Njoku, E. G., Shi, J. J. C., Johnson, J. T., i Colliander, A. (2014). Tests of the SMAP combined radar and radiometer algorithm using airborne field campaign observations and simulated data. IEEE Transactions on Geoscience and Remote Sensing, 52(4):2018–2028. Davidson, M. W. J., Mattia, F., Satalino, G., Verhoest, N. E. C., Toan, T. L., Borgeaud, M., Louis, J. M. B., i Attema, E. (2003). Joint statistical properties of RMS height and correlation length derived from multisite 1-m roughness measurements. IEEE Transactions on Geoscience and Remote Sensing, 41(7):1651–1658. de Griend, A. A. V. i Wigneron, J. P. (2004). The b-factor as a function of frequency and canopy type at H-polarization. IEEE Transactions on Geoscience and Remote Sensing, 42(4):786–794. de Jeu, R. i Dorigo, W. (2015). On the importance of satellite observed soil moisture. International Journal of Applied Earth Observation and Geoinformation. Decker, M., Brunke, M. A., Wang, Z., Sakaguchi, K., Zeng, X., i Bosilovich, M. G. (2012). Evaluation of the reanalysis products from gsfc, ncep, and ecmwf using flux tower observations. Journal of Climate, 25(6):1916–1944. Dente, L., Vekerdy, Z., Wen, J., i Su, Z. (2012). Maqu network for validation of satellite-derived soil moisture products. International Journal of Applied Earth Observation and Geoinformation, 17:55 – 65. Retrieval of Key Eco-hydrological Parameters for Cold and Arid Regions.

253

Bibliografia Djamai, N., Magagi, R., Goita, K., Merlin, O., Kerr, Y., i Walker, A. (2015). Disaggregation of SMOS soil moisture over the Canadian Prairies. Remote Sensing of Environment, 170:255–268. Dobson, M. C., Ulaby, F. T., Hallikainen, M. T., i El-rayes, M. A. (1985). Microwave dielectric behavior of wet soil-part ii: Dielectric mixing models. IEEE Transactions on Geoscience and Remote Sensing, GE-23(1):35–46. Dorigo, W., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiová, A., Sanchis-Dufau, A., Zamojski, D., Cordes, C., Wagner, W., i Drusch, M. (2013). Global automated quality control of in situ soil moisture data from the international soil moisture network. Vadose Zone Journal, 12(3). Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., i Jackson, T. (2011). The international soil moisture network: a data hosting facility for global in situ soil moisture measurements. Hydrology and Earth System Sciences, 15(5):1675–1698. Doroszewski, A., Jadczyszyn, J., Kozyra, J., Pudełko, R., Stuczy´nski, T., Mizak, K., Łopatka, A., Koza, P., Gór´ ski, T., i Wróblewska, E. (2012). Podstawy systemu monitoringu suszy rolniczej. Woda-Srodowisko-Obszary Wiejskie, T. 12, z. 2:77–91. Drusch, M., Wood, E. F., i Gao, H. (2005). Observation operators for the direct assimilation of trmm microwave imager retrieved soil moisture. Geophysical Research Letters, 32(15). L15403. Dubois, P. C., van Zyl, J., i Engman, T. (1995a). Measuring soil moisture with imaging radars. IEEE Transactions on Geoscience and Remote Sensing, 33(4):915–926. Dubois, P. C., vanZyl, J., i Engman, T. (1995b). Corrections to "measuring soil moisture with imaging radars". IEEE Transactions on Geoscience and Remote Sensing, 33(6):1340–. Dumedah, G. i Coulibaly, P. (2013). Evaluating forecasting performance for data assimilation methods: The ensemble Kalman filter, the particle filter, and the evolutionary-based assimilation. Advances in Water Resources, 60:47–63. Dumedah, G., Walker, J. P., i Merlin, O. (2015). Root-zone soil moisture estimation from assimilation of downscaled soil moisture and ocean salinity data. Advances in Water Resources, 84:14 – 22. Dabrowska-Zieli´ ˛ nska, K. (2017). Okre´slanie wilgotno´sci gleb z danych RADARSAT. http://www.igik.edu.pl/pl/ teledetekcja-okreslanie-wilgotnosci-gleb. Dost˛ep: 2017-04-13. Entekhabi, D., Das, N., Njoku, E., Yueh, S., Johnson, J., i Shi, J. (2014). Soil Moisture Active Passive (SMAP) L2 & L 3 Radar/Radiometer Soil Moisture . Technical report, Jet Propulsion Laboratory. Entekhabi, D., Das, N., Njoku, E. G., Johnson, J. T., i Shi, J. (2016). SMAP L3 Radar/Radiometer Global Daily 9 km EASE-Grid Soil Moisture, Version 3. http://nsidc.org/data/SPL3SMAP. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center, Dost˛ep: 2016-05-30. ESA (2017a).

Envisat - environmental satellite.

https://earth.esa.int/web/guest/missions/esa-operational-eo-

missions/envisat. Dost˛ep: 2017-04-13. ESA (2017b). SMOS Data Products. dost˛ep: 2017-02-01. Escorihuela, M., Chanzy, A., Wigneron, J., i Kerr, Y. (2010). Effective soil moisture sampling depth of l-band radiometry: A case study. Remote Sensing of Environment, 114(5):995 – 1001. EUMETSAT (2012a). Product User Manual (PUM) for product H08 – SM-OBS-2. EUMETSAT (2012b). Product User Manual (PUM) for product H14 – SM-DAS-2. EUMETSAT (2014). Product User Manual (PUM) for product H25 – SM-OBS-4. Famiglietti, J. S., Cazenave, A., Eicker, A., Reager, J. T., Rodell, M., i Velicogna, I. (2015). Satellites provide the big picture. Science, 349(6249):684–685.

254

Bibliografia Fang, B. i Lakshmi, V. (2014). Soil moisture at watershed scale: Remote sensing techniques. Journal of Hydrology, 516:258–272. Determination of soil moisture: Measurements and theoretical approaches. Fascetti, F., Pierdicca, N., Pulvirenti, L., Crapolicchio, R., i Muñoz-Sabater, J. (2015). A comparison of ASCAT and SMOS soil moisture retrievals over europe and northern africa from 2010 to 2013. International Journal of Applied Earth Observation and Geoinformation. Fekete, B. M., Robarts, R. D., Kumagai, M., Nachtnebel, H.-P., Odada, E., i Zhulidov, A. V. (2015). Time for in situ renaissance. Science, 349(6249):685–686. Flerchinger, G. N. i Saxton, K. E. (1989). Simultaneous Heat and Water Model of a Freezing Snow-Residue-Soil System II. Field Verification. Ford, T. W., Harris, E., i Quiring, S. M. (2014). Estimating root zone soil moisture using near-surface observations from SMOS. Hydrology and Earth System Sciences, 18(1):139–154. Fung, A. K., Li, Z., i Chen, K. S. (1992). Backscattering from a randomly rough dielectric surface. IEEE Transactions on Geoscience and Remote Sensing, 30(2):356–369. Gaiser, P. W., Twarog, E. M., Li, L., Germain, K. M. S., Poe, G. A., Purdy, W., Jelenak, Z., Chang, P. S., i Connor, L. (2004). The windsat space borne polarimetric microwave radiometer: sensor description and mission overview. In IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium, tom 1, strona 374. Gerten, D., Heinke, J., Hoff, H., Biemans, H., Fader, M., i Waha, K. (2011). Global water availability and requirements for future food production. Journal of Hydrometeorology, 12(5):885–899. Gherboudj, I., Magagi, R., Berg, A. A., i Toth, B. (2011). Soil moisture retrieval over agricultural fields from multi-polarized and multi-angular RADARSAT-2 SAR data. Remote Sensing of Environment, 115(1):33 – 43. Gilewski, P. G. (2015). Wykorzystanie narz˛edzi Open Source w celu analizy radiometrycznych danych satelitarnych w badaniach wilgotno´sci gleby w skali regionalnej. Praca magisterska, Politechnika Warszawska. Gleick, P. (1993). World fresh water resources, chapter 2. Oxford University Press. Gonzalez-Gambau, V., Turiel, A., Martinez, J., Olmedo, E., i Corbella, I. (2014). A novel reconstruction algorithm for the improvement of SMOS brightness temperatures. In Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 2014 13th Specialist Meeting on, strony 124–127. González-Gambau, V., Olmedo, E., Turiel, A., Martínez, J., Ballabrera-Poy, J., Portabella, M., i Piles, M. (2016). Enhancing SMOS brightness temperatures over the ocean using the nodal sampling image reconstruction technique. Remote Sensing of Environment. González-Zamora, A., Sánchez, N., Martínez-Fernández, J., Ángela Gumuzzio, Piles, M., i Olmedo, E. (2015). Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the duero basin (spain). Physics and Chemistry of the Earth, Parts A/B/C, 83–84:123 – 136. Emerging science and applications with microwave remote sensing data. Gruszczy´nska, M. (1998). Zastosowanie zdj˛ec´ mikrofalowych z satelitów ERS-1 i ERS-2 do okre´slania wilgotno´sci gleb pod zboz˙ ami. Prace Instytutu Geodezji i Kartografii, T. 45, z. 97:117–135. Gumuzzio, A., Brocca, L., Sánchez, N., González-Zamora, A., i Martínez-Fernández, J. (2016). Comparison of SMOS, modelled and in situ long-term soil moisture series in the northwest of Spain. Hydrological Sciences Journal, 61(14):1–16. Hallikainen, M. T., Ulaby, F. T., Dobson, M. C., El-rayes, M. A., i k. Wu, L. (1985). Microwave dielectric behavior of wet soil-part 1: Empirical models and experimental observations. IEEE Transactions on Geoscience and Remote Sensing, GE-23(1):25–34.

255

Bibliografia Hisdal, H., Stahl, K., Tallaksen, L. M., i Demuth, S. (2001). Have streamflow droughts in europe become more severe or frequent? International Journal of Climatology, 21(3):317–333. Hogg, E., Barr, A., i Black, T. (2013). A simple soil moisture index for representing multi-year drought impacts on aspen productivity in the western canadian interior. Agricultural and Forest Meteorology, 178–179:173 – 182. Special Issue:Drought Inner Asia. Hornbuckle, B. K., England, A. W., Anderson, M. C., i Viner, B. J. (2006). The effect of free water in a maize canopy on microwave emission at 1.4 GHz. Agricultural and Forest Meteorology, 138(1–4):180 – 191. Hornbuckle, B. K. i Rowlandson, T. L. (2008). Evaluating the first-order tau-omega model of terrestrial microwave emission. In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, tom 1, strony I–193–I–196. Houser, P., De Lannoy, G., i Walker, J. P. (2012). Hydrologic Data Assimilation. Approaches to Managing Disaster - Assessing Hazards, Emergencies and Disaster Impacts. Huang, S., Tsang, L., Njoku, E. G., i Chan, K. S. (2010). Backscattering coefficients, coherent reflectivities, and emissivities of randomly rough soil surfaces at l-band for smap applications based on numerical solutions of maxwell equations in three-dimensional simulations. IEEE Transactions on Geoscience and Remote Sensing, 48(6):2557–2568. Hunt, E. D., Hubbard, K. G., Wilhite, D. A., Arkebauer, T. J., i Dutcher, A. L. (2009). The development and evaluation of a soil moisture index. International Journal of Climatology, 29(5):747–759. Jackson, T., Cosh, M., Bindlish, R., Starks, P., Bosch, D., Seyfried, M., Goodrich, D., Moran, M., i Du, J. (2010). Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products. Geoscience and Remote Sensing, IEEE Transactions on, 48(12):4256–4272. Jackson, T. i Schmugge, T. (1991). Vegetation effects on the microwave emission of soils. Remote Sensing of Environment, 36(3):203 – 212. Jackson, T. J., Bindlish, R., Cosh, M. H., Zhao, T., Starks, P. J., Bosch, D. D., Seyfried, M., Moran, M. S., Goodrich, D. C., Kerr, Y. H., i Leroux, D. (2012). Validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture over watershed networks in the u.s. IEEE Transactions on Geoscience and Remote Sensing, 50(5):1530–1543. Kankaku, Y., Suzuki, S., i Shimada, M. (2015). ALOS-2 first year operation result. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), strony 4121–4124. Kasprzak, M. i Traczyk, A. (2010). Geomorfometria granitowej cz˛es´ci Karkonoszy. Landform Analysis, 13:33–46. Kerr, Y., Reul, N., Martín-Neira, M., Drusch, M., Alvera-Azcarate, A., Wigneron, J.-P., i Mecklenburg, S. (2016). ESA’s Soil Moisture and Ocean Salinity Mission – Achievements and applications after more than 6 years in orbit. Remote Sensing of Environment, 180:1 – 2. Special Issue: ESA’s Soil Moisture and Ocean Salinity Mission - Achievements and Applications. Kerr, Y., Waldteufel, P., Wigneron, J.-P., Delwart, S., Cabot, F., Boutin, J., Escorihuela, M.-J., Font, J., Reul, N., Gruhier, C., Juglea, S., Drinkwater, M., Hahne, A., Martin-Neira, M., i Mecklenburg, S. (2010). The SMOS Mission: New Tool for monitoring key elements ofthe global water cycle. Proceedings of the IEEE, 98(5):666–687. Kieffer, D. (2009). TDR 300 Soil Moisture Meter. Spectrum Technologies, 3600 Thayer Ct., Aurora IL 60504, 1 edition. Kim, S., Moghaddam, M., Tsang, L., Burgin, M., Xu, X., i Njoku, E. (2014). Models of L-Band radar backscattering coefficients over global terrain for soil moisture retrieval. Geoscience and Remote Sensing, IEEE Transactions on, 52(2):1381–1396.

256

Bibliografia Kim, Y. i van Zyl, J. J. (2009). A time-series approach to estimate soil moisture using polarimetric radar data. IEEE Transactions on Geoscience and Remote Sensing, 47(8):2519–2527. Kojima Yuki, Oki Kazuo, Noborio Kosuke, i Mizoguchi Masaru (2016). Estimating Soil Moisture Distributions across Small Farm Fields with ALOS/PALSAR. International Scholarly Research Notices, 2016:4203783. K˛edzior, M. A., Prze´zdziecki, K., i Zawadzki, J. (2012). Wykorzystanie bazy danych GLDAS i narz˛edzi Open Source w badaniach wilgotno´sci gleby. Roczniki Geomatyki, T. 10, z. 3:67–76. K˛edzior, M. A. i Zawadzki, J. (2016). Comparative study of soil moisture estimations from SMOS satellite mission, GLDAS database, and cosmic-ray neutrons measurements at COSMOS station in Eastern Poland. Geoderma, 283:21 – 31. K˛edzior, M. A. i Zawadzki, J. (2017). SMOS data as a source of the agricultural drought information for the Vistula catchment. Geoderma, wysłane do redakcji, numer: GEODER 2017 223. wysłane do redakcji. Łab˛edzki, L., Bak, ˛ B., Kanecka-Geszke, E., Smarzy´nska, K., i Bolewski, T. (2013). System monitorowania i prognozowania warunków wilgotno´sciowych ekosystemów rolniczych. Wiadomo´sci Melioracyjne i Łakarskie, ˛ 56(4). Rekord w opracowaniu. Laiolo, P., Gabellani, S., Campo, L., Silvestro, F., Delogu, F., Rudari, R., Pulvirenti, L., Boni, G., Fascetti, F., Pierdicca, N., Crapolicchio, R., Hasenauer, S., i Puca, S. (2015). Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model. International Journal of Applied Earth Observation and Geoinformation. Laur1, H., Bally, P., Meadows, P., Sanchez, J., Schaettler, B., Lopinto, E., i Esteban, D. (2004). ERS SAR Calibration. Derivation of the Backscattering coefficient in ESA ERS PRI Products. https://earth.esa.int/pub/ ESA_DOC/ers_sar_calibration_issue2_5f.pdf. Dost˛ep: 2016-12-27. Lee, J. H. i Im, J. (2015). A novel bias correction method for soil moisture and ocean salinity (SMOS) soil moisture: Retrieval ensembles. Remote Sensing, 7(12):15824. Lee, J. H., Pellarin, T., i Kerr, Y. (2015). EnOI optimization for SMOS soil moisture over west africa. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 8(4):1821–1829. Lehner, B., Döll, P., Alcamo, J., Henrichs, T., i Kaspar, F. (2006). Estimating the impact of global change on flood and drought risks in europe: A continental, integrated analysis. Climatic Change, 75(3):273–299. Lei, F., Crow, W. T., Shen, H., Parinussa, R. M., i Holmes, T. R. H. (2015). The impact of local acquisition time on the accuracy of microwave surface soil moisture retrievals over the contiguous united states. Remote Sensing, 7(10):13448. Łukowski, M. i Usowicz, B. (2014). Surface soil moisture. Satellite and ground-based measurements. Acta Agrophysica Monographiae, 1:1–107. ISSN 2084-3429, ISBN 978-83-89969-24-8. Mahmoodi, A., Buchan, I., i inni (2011). Algorithm Theoretical Basis Document (ATBD) for the SMOS Level 2 Soil Moisture Processor. Technical Report 3.5, Expert Support Laboratories, CBSA, UoR, TV and INRA. Manabe, S. (1969). Climate and the ocean circulation. Monthly Weather Review, 97(11):739–774. Marco, T. (2010). Contribution to the Improvement of the Soil Moisture and Ocean Salinity (SMOS) Mission Sea Surface Salinity Retrieval Algorithm. rozprawa doktorska, Universidad Politécnica de Cataluña. Marczewski, W., Slominski, J., Slominska, E., Usowicz, B., Usowicz, J., Romanov, S., Maryskevych, O., Nastula, J., i Zawadzki, J. (2010). Strategies for validating and directions for employing SMOS data, in the Cal-Val project SWEX (3275) for wetlands. Hydrology and Earth System Sciences Discussions, 7:7007–7057.

257

Bibliografia Martínez-Fernández, J., González-Zamora, A., Sánchez, N., i Gumuzzio, A. (2015). A soil water based index as a suitable agricultural drought indicator. Journal of Hydrology, 522:265 – 273. Massari, C., Brocca, L., Pellarin, T., Kerr, Y., Crow, W., Cascon, C., i Ciabatta, L. (2016). Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms. In EGU General Assembly Conference Abstracts, tom 18 serii EGU General Assembly Conference Abstracts, strona 6373. Masson, V., Champeaux, J.-L., Chauvin, F., Meriguet, C., i Lacaze, R. (2003). A global database of land surface parameters at 1-km resolution in meteorological and climate models. Journal of Climate, 16(9):1261–1282. McKnight, J. Y. (2015). Linking soil moisture and carbon-cycle processes in two understudied terrestrial ecosystems: Ecuadorian páramo grasslands and cons tructed agricultural wetlands. rozprawa doktorska, Uniwersytet w Tennessee. Meisl, P., Thompson, A., i Luscombe, A. (2017). Radarsat-2 Mission: Overview And Development Status. http: //a-a-r-s.org/aars/proceeding/ACRS2000/Papers/MSP00-2.htm. Dost˛ep: 2017-02-04. Merlin, O., Escorihuela, M. J., Mayoral, M. A., Hagolle, O., Bitar, A. A., i Kerr, Y. (2013). Self-calibrated evaporation-based disaggregation of SMOS soil moisture: An evaluation study at 3 km and 100 m resolution in catalunya, spain. Remote Sensing of Environment, 130:25 – 38. Merlin, O., Walker, J. P., Chehbouni, A., i Kerr, Y. (2008). Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency. Remote Sensing of Environment, 112(10):3935 – 3946. Miler, A. T. (2013). Kompleksowa metodyka oceny stosunków wodnych w lasach. Wyd. Uniwersytetu Przyrodniczego w Poznaniu. Monografia. Mironov, V. L., Kosolapova, L. G., i Fomin, S. V. (2009). Physically and mineralogically based spectroscopic dielectric model for moist soils. IEEE Transactions on Geoscience and Remote Sensing, 47(7):2059–2070. Mishra, A. K. i Singh, V. P. (2010). A review of drought concepts. Journal of Hydrology, 391(1–2):202 – 216. Mishra, A. K. i Singh, V. P. (2011). Drought modeling – a review. Journal of Hydrology, 403(1–2):157 – 175. Molero, B., Merlin, O., Malbéteau, Y., Bitar, A. A., Cabot, F., Stefan, V., Kerr, Y., Bacon, S., Cosh, M., Bindlish, R., i Jackson, T. (2016). SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results. Remote Sensing of Environment, 180:361 – 376. Special Issue: ESA’s Soil Moisture and Ocean Salinity Mission - Achievements and Applications. Montzka, C., Bogena, H. R., Zreda, M., Monerris, A., Morrison, R., Muddu, S., i Vereecken, H. (2017). Validation of spaceborne and modelled surface soil moisture products with cosmic-ray neutron probes. Remote Sensing, 9(2). Montzka, C., Moradkhani, H., Weihermüller, L., Franssen, H.-J. H., Canty, M., i Vereecken, H. (2011). Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter. Journal of Hydrology, 399(3–4):410 – 421. Moore, R. J. (2007). The PDM rainfall-runoff model. Hydrology and Earth System Sciences, 11(1):483–499. Moran, M., Clarke, T., Inoue, Y., i Vidal, A. (1994). Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index. Remote Sensing of Environment, 49(3):246 – 263. Moran, M. S., Peters-Lidard, C. D., Watts, J. M., i McElroy, S. (2004). Estimating soil moisture at the watershed scale with satellite-based radar and land surface models. Canadian Journal of Remote Sensing, 30(5):805–826.

258

Bibliografia Narayan, U., Lakshmi, V., i Njoku, E. G. (2004). A simple algorithm for spatial disaggregation of radiometer derived soil moisture using higher resolution radar observations. In Geoscience and Remote Sensing Symposium, 2004. IGARSS ’04. Proceedings. 2004 IEEE International, tom 3, strony 1877–1879. Narvekar, P., Entekhabi, D., bum Kim, S., i Njoku, E. (2015). Soil moisture retrieval using l-band radar observations. Geoscience and Remote Sensing, IEEE Transactions on, 53(6):3492–3506. Niemeyer, S. (2008). New drought indices. Options Méditerranéenne, 80:267–274. 1. International Conference Drought Management: Scientific and Technological Innovations, 2008/06/12-14, Zaragoza (Spain). Njoku, E. G., Jackson, T. J., Lakshmi, V., Chan, T. K., i Nghiem, S. V. (2003). Soil moisture retrieval from amsr-e. IEEE Transactions on Geoscience and Remote Sensing, 41(2):215–229. Ochsner, T. E., Cosh, M. H., Cuenca, R. H., Dorigo, W. A., Draper, C. S., Hagimoto, Y., Kerr, Y. H., Njoku, E. G., Small, E. E., i Zreda, M. (2013). State of the art in large-scale soil moisture monitoring. Soil Science Society of America Journal, 77. 6. Oh, Y. (2004). Quantitative retrieval of soil moisture content and surface roughness from multipolarized radar observations of bare soil surfaces. IEEE Transactions on Geoscience and Remote Sensing, 42(3):596–601. Orth, R., Koster, R. D., i Seneviratne, S. I. (2013). Inferring soil moisture memory from streamflow observations using a simple water balance model. Journal of Hydrometeorology, 14(6):1773–1790. Orth, R., Zscheischler, J., i Seneviratne, S. I. (2016). Record dry summer in 2015 challenges precipitation projections in Central Europe. Scientific Reports, 6:28334 EP –. Article. Pan, M., Fisher, C. K., Chaney, N. W., Zhan, W., Crow, W. T., Aires, F., Entekhabi, D., i Wood, E. F. (2015). Triple collocation: Beyond three estimates and separation of structural/non-structural errors. Remote Sensing of Environment, 171:299 – 310. Panciera, R., Walker, J. P., Kalma, J. D., Kim, E. J., Saleh, K., i Wigneron, J.-P. (2009). Evaluation of the SMOS L-MEB passive microwave soil moisture retrieval algorithm. Remote Sensing of Environment, 113(2):435–444. Parinussa, R. M., Holmes, T. R. H., i de Jeu, R. A. M. (2012). Soil moisture retrievals from the WindSat spaceborne polarimetric microwave radiometer. IEEE Transactions on Geoscience and Remote Sensing, 50(7):2683–2694. Parkinson, C. L. (2003). Aqua: an earth-observing satellite mission to examine water and other climate variables. IEEE Transactions on Geoscience and Remote Sensing, 41(2):173–183. Parrens, M., Zakharova, E., Lafont, S., Calvet, J.-C., Kerr, Y., Wagner, W., i Wigneron, J.-P. (2012). Comparing soil moisture retrievals from SMOS and ASCAT over france. Hydrology and Earth System Sciences, 16(2):423–440. Pathe, C., Wagner, W., Sabel, D., Doubkova, M., i Basara, J. B. (2009). Using ENVISAT ASAR global mode data for surface soil moisture retrieval over Oklahoma, USA. IEEE Transactions on Geoscience and Remote Sensing, 47(2):468–480. Patil, B. N., Zope, P. H., i Patil, K. S. (2015). Development of Low Cost TDR System for Soil Moisture Measurement. International Journal of Advanced Research in Education Technology, 2(3). Pellarin, T., Wigneron, J. P., Calvet, J. C., Berger, M., Douville, H., Ferrazzoli, P., Kerr, Y. H., Lopez-Baeza, E., Pulliainen, J., Simmonds, L. P., i Waldteufel, P. (2003). Two-year global simulation of L-band brightness temperatures over land. IEEE Transactions on Geoscience and Remote Sensing, 41(9):2135–2139. Pierdicca, N., Pulvirenti, L., Fascetti, F., Crapolicchio, R., i Talone, M. (2013). Analysis of two years of ASCATand SMOS-derived soil moisture estimates over Europe and North Africa. European Journal of Remote Sensing, 46:759–773.

259

Bibliografia Piles, M., Camps, A., Vall-llossera, M., Corbella, I., Panciera, R., Rudiger, C., Kerr, Y. H., i Walker, J. (2011). Downscaling SMOS-derived soil moisture using MODIS visible/infrared data. IEEE Transactions on Geoscience and Remote Sensing, 49(9):3156–3166. Piles, M., Entekhabi, D., i Camps, A. (2009). A change detection algorithm for retrieving high-resolution soil moisture from smap radar and radiometer observations. IEEE Transactions on Geoscience and Remote Sensing, 47(12):4125–4131. Piles, M., Petropoulos, G. P., Sánchez, N., González-Zamora, A., i Ireland, G. (2016).

Towards improved

spatio-temporal resolution soil moisture retrievals from the synergy of SMOS and MSG SEVIRI spaceborne observations. Remote Sensing of Environment, 180:403–417. Special Issue: ESA’s Soil Moisture and Ocean Salinity Mission - Achievements and Applications. Potop, V., Možný, M., i Soukup, J. (2012). Drought evolution at various time scales in the lowland regions and their impact on vegetable crops in the Czech Republic. Agricultural and Forest Meteorology, 156:121 – 133. Qin, J., Yang, K., Lu, N., Chen, Y., Zhao, L., i Han, M. (2013). Spatial upscaling of in-situ soil moisture measurements based on modis-derived apparent thermal inertia. Remote Sensing of Environment, 138:1 – 9. Qin, J., Zhao, L., Chen, Y., Yang, K., Yang, Y., Chen, Z., i Lu, H. (2015). Inter-comparison of spatial upscaling methods for evaluation of satellite-based soil moisture. Journal of Hydrology, 523:170 – 178. Quinn, P., Beven, K., Chevallier, P., i Planchon, O. (1991). The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models. Hydrological Processes, 5(1):59–79. Reichle, R. H., De Lannoy, G. J. M., Forman, B. A., Draper, C. S., i Liu, Q. (2013). Connecting satellite observations with water cycle variables through land data assimilation: Examples using the NASA GEOS-5 LDAS. Surveys in Geophysics, 35(3):577–606. Reichle, R. H., Koster, R. D., Lannoy, G. J. M. D., Forman, B. A., Liu, Q., Mahanama, S. P. P., i Touré, A. (2011). Assessment and enhancement of MERRA land surface hydrology estimates. Journal of Climate, 24(24):6322–6338. Robock, A., Vinnikov, K. Y., Srinivasan, G., Entin, J. K., Hollinger, S. E., Speranskaya, N. A., Liu, S., i Namkhai, A. (2000). The global soil moisture data bank. Bulletin of the American Meteorological Society, 81(6):1281–1299. Rodell M., Houser P. R., Jambor U., Gottschalck J., Mitchell K., Meng C-J., Arsenault K., Cosgrove B., Radakovich J., Bosilovich M., Entin* J. K., Walker J. P., Lohmann D., i Toll D. (2004). The Global Land Data Assimilation System. Bulletin of the American Meteorological Society, 85(3):381–394. doi: 10.1175/BAMS-85-3-381. Romano, N. (2014). Soil moisture at local scale: Measurements and simulations. Journal of Hydrology, 516:6 – 20. Determination of soil moisture: Measurements and theoretical approaches. Rosolem, R., Shuttleworth, W. J., Zreda, M., Franz, T. E., Zeng, X., i Kurc, S. A. (2013). The effect of atmospheric water vapor on neutron count in the cosmic-ray soil moisture observing system. Journal of Hydrometeorology, 14(5):1659–1671. Roy, S. K., Rowlandson, T. L., Berg, A. A., Champagne, C., i Adams, J. R. (2015). Impact of sub-pixel heterogeneity on modelled brightness temperature for an agricultural region. International Journal of Applied Earth Observation and Geoinformation. Saleh, K., Wigneron, J.-P., de Rosnay, P., Calvet, J.-C., Escorihuela, M. J., Kerr, Y., i Waldteufel, P. (2006). Impact of rain interception by vegetation and mulch on the L-band emission of natural grass. Remote Sensing of Environment, 101(1):127–139.

260

Bibliografia Sanchez, N., Martinez-Fernandez, J., Scaini, A., i Perez-Gutierrez, C. (2012). Validation of the SMOS L2 soil moisture data in the remedhus network (Spain). IEEE Transactions on Geoscience and Remote Sensing, 50(5):1602–1611. Scaini, A., Sánchez, N., Vicente-Serrano, S. M., i Martínez-Fernández, J. (2015). SMOS-derived soil moisture anomalies and drought indices: a comparative analysis using in situ measurements. Hydrological Processes, 29(3):373–383. Scipal, K., Dorigo, W., i deJeu, R. (2010). Triple Collocation - a new tool to determine the error structure of global soil moisture products. Geoscience and Remote Sensing Symposium (IGARSS), strony 4426–4429. Scipal, K., Drusch, M., i Wagner, W. (2008). Assimilation of a ERS scatterometer derived soil moisture index in the ECMWF numerical weather prediction system. Advances in Water Resources, 31(8):1101 – 1112. Sepulcre-Canto, G., Horion, S., Singleton, A., Carrao, H., i Vogt, J. (2012). Development of a combined drought indicator to detect agricultural drought in europe. Natural Hazards and Earth System Sciences, 12(11):3519–3531. Shi, J., Li, S., Zuo, Q., i Ben-Gal, A. (2015). An index for plant water deficit based on root-weighted soil water content. Journal of Hydrology, 522:285 – 294. Shi, J., Wang, J., Hsu, A. Y., O’Neill, P. E., i Engman, E. T. (1997). Estimation of bare surface soil moisture and surface roughness parameter using l-band sar image data. IEEE Transactions on Geoscience and Remote Sensing, 35(5):1254–1266. Shimada, M., Isoguchi, O., Tadono, T., i Isono, K. (2009). PALSAR Radiometric and Geometric Calibration. IEEE Transactions on Geoscience and Remote Sensing, 47(12):3915–3932. Soldo, Y., Cabot, F., Khazaal, A., Miernecki, M., Słomi´nska, E., Fieuzal, R., i Kerr, Y. (2015). Localization of RFI sources for the SMOS mission: A means for assessing SMOS pointing performances. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 8(2):617–627. Sorensen, R., Zinko, U., i Seibert, J. (2006). On the calculation of the topographic wetness index: evaluation of different methods based on field observations. Hydrology and Earth System Sciences, 10:101–112. Soulis, K. X. i Valiantzas, J. D. (2012). Scs-cn parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-cn system approach. Hydrology and Earth System Sciences, 16(3):1001–1015. Stoffelen, A. (1998). Toward the true near-surface wind speed: Error modeling and calibration using triple collocation. Journal of Geophysical Research: Oceans, 103(C4):7755–7766. Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research: Atmospheres, 106(D7):7183–7192. Temimi, M., Leconte, R., Brisette, F., i Toussaint, T. (2003). A dynamic estimate of a soil wetness index for the mackenzie river basin from ssm/i measurements. Geoscience and Remote Sensing Symposium, 2003. IGARSS ’03. Proceedings. 2003 IEEE International, 2:920–922. Thornthwaite, C. W. (1948). An approach toward a rational classification of climate. Geographical Review, 38(1):55–94. Todisco, F., Brocca, L., Termite, L. F., i Wagner, W. (2015). Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale. Hydrology and Earth System Sciences, 19(9):3845–3856. Trnka, M., Brázdil, R., Balek, J., Semerádová, D., Hlavinka, P., Možný, M., Štˇepánek, P., Dobrovolný, P., Zahradníˇcek, P., Dubrovský, M., Eitzinger, J., Fuchs, B., Svoboda, M., Hayes, M., i Žalud, Z. (2015). Drivers of soil drying in the Czech Republic between 1961 and 2012. International Journal of Climatology, 35(9):2664–2675.

261

Bibliografia Trnka, M., Kyselý, J., Možný, M., i Dubrovský, M. (2009). Changes in central-european soil-moisture availability and circulation patterns in 1881–2005. International Journal of Climatology, 29(5):655–672. Ulaby, F., Moore, R., i Fung, A. (1986). Microwave remote sensing: active and passive. Volume III: from theory to applications. Artech House; Remote Sensing Series, 4. Urbaniak, M., Olejnik, J., Miler, A. T., Krysztofiak-Kaniewska, A., i Ziemblinska, K. (2014). Składowe bilansu wodnego w pionowym profilu dla sze´sc´ dziesi˛ecioletniego drzewostanu sosnowego w nadle´snictwie Tuczno. Infrastruktura i Ekologia Terenów Wiejskich, II(3/2014). Usowicz, B., Marczewski, W., Usowicz, J., Łukowski, M., i Lipiec, J. (2014). Comparison of surface soil moisture from SMOS satellite and ground measurements. International Agrophysics, 28:359–369. Van Loon, A. F. (2015). Hydrological drought explained. Wiley Interdisciplinary Reviews: Water, 2(4):359–392. Venkataramana, S., G., H. K., Jinsheng, Y., i D., H. E. (2008). Development of the Soil Moisture Index to Quantify Agricultural Drought and Its “User Friendliness” in Severity-Area-Duration Assessment. Journal of Hydrometeorology, 9(4):660–676. doi: 10.1175/2007JHM892.1. Vicente-Serrano, S. M., Beguería, S., i López-Moreno, J. I. (2010a). A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. Journal of Climate, 23(7):1696–1718. Vicente-Serrano, S. M., Beguería, S., López-Moreno, J. I., Angulo, M., i El Kenawy, A. (2010b). A new global 0.5 gridded dataset (1901–2006) of a multiscalar drought index: Comparison with current drought index datasets based on the palmer drought severity index. Journal of Hydrometeorology, 11(4):1033–1043. Vine, D. L., Lagerloef, G., Yueh, S., Pellerano, F., Dinnat, E., i Wentz, F. (2006). Aquarius mission technical overview. In 2006 IEEE International Symposium on Geoscience and Remote Sensing, strony 1678–1680. Wagner, W. (2012). Soil moisture measurements from space and application to operational hydrology. prezentacja przedstawiona w czasie Komisji Hydrologicznej Mi˛edzynarodowej Organizacji Meteorologicznej, która miała miejsce w dniach 6 - 14 listopada 2012 roku. Wagner, W., Hahn, S., Kidd, R., Melzer, T., Bartalis, Z., Hasenauer, S., Figa-Saldaña, J., de Rosnay, P., Jann, A., Schneider, S., Komma, J., Kubu, G., Brugger, K., Aubrecht, C., Züger, J., Gangkofner, U., Kienberger, S., Brocca, L., Wang, Y., Blöschl, G., Eitzinger, J., i Steinnocher, K. (2013). The ascat soil moisture product: A review of its specifications, validation results, and emerging applications. Meteorologische Zeitschrift, 22(1):5–33. Wagner, W., Lemoine, G., i Rott, H. (1999). A method for estimating soil moisture from ERS scatterometer and soil data. Remote Sensing of Environment, 70(2):191 – 207. Wagner, W., Naeimi, V., Scipal, K., Jeu, R., i Martinez-Fernandez, J. (2006). Soil moisture from operational meteorological satellites. Hydrogeology Journal, 15(1):121–131. Walker, J. P. i R., H. P. (2005). Hydrologic Data Assimilation. Advances in Water Science Methodologies. Wanders, N., Karssenberg, D., Bierkens, M., Parinussa, R., de Jeu, R., van Dam, J., i de Jong, S. (2012). Observation uncertainty of satellite soil moisture products determined with physically-based modeling. Remote Sensing of Environment, 127:341 – 356. Wang, J. i Choudhury, B. (1981). Remote sensing of soil moisture content, over bare field at 1.4 ghz frequency. Journal of Geophysical Research: Oceans, 86(C6):5277–5282. Wang, Q., van der Velde, R., Su, Z., i Wen, J. (2015). Aquarius L-band scatterometer and radiometer observations over a Tibetan Plateau site. International Journal of Applied Earth Observation and Geoinformation, 45:165–177.

262

Bibliografia Wibig, J. (2012). Warunki wilgotno´sciowe w Polsce w s´wietle wska´znika standaryzowanego klimatycznego bi´ lansu wodnego. Woda - Srodowisko - Obszary Wiejskie, 12(2[38]). Wigneron, J.-P., Calvet, J.-C., Pellarin, T., de Griend, A. V., Berger, M., i Ferrazzoli, P. (2003). Retrieving near-surface soil moisture from microwave radiometric observations: current status and future plans. Remote Sensing of Environment, 85(4):489–506. Wigneron, J.-P., Kerr, Y., Waldteufel, P., Saleh, K., Escorihuela, M.-J., Richaume, P., Ferrazzoli, P., de Rosnay, P., Gurney, R., Calvet, J.-C., Grant, J., Guglielmetti, M., Hornbuckle, B., Mätzler, C., Pellarin, T., i Schwank, M. (2007). L-band microwave emission of the biosphere (L-MEB) model: Description and calibration against experimental data sets over crop fields. Remote Sensing of Environment, 107(4):639 – 655. Wigneron, J. P., Parde, M., Waldteufel, P., Chanzy, A., Kerr, Y., Schmidl, S., i Skou, N. (2004). Characterizing the dependence of vegetation model parameters on crop structure, incidence angle, and polarization at L-band. IEEE Transactions on Geoscience and Remote Sensing, 42(2):416–425. Wu, L. i Zhang, J. (2015). The relationship between spring soil moisture and summer hot extremes over North China. Advances in Atmospheric Sciences, 32(12):1660–1668. Xu, X., Tolson, B. A., Li, J., Staebler, R. M., Seglenieks, F., Haghnegahdar, A., i Davison, B. (2015). Assimilation of SMOS soil moisture over the Great Lakes basin. Remote Sensing of Environment, 169:163–175. Yilmaz, M. T. i Crow, W. T. (2014). Evaluation of Assumptions in Soil Moisture Triple Collocation Analysis. American Meteorological Society, 15. Zahradníˇcek, P., Trnka, M., Brázdil, R., Možný, M., Štˇepánek, P., Hlavinka, P., Žalud, Z., Malý, A., Semerádová, ˇ D., Dobrovolný, P., Dubrovský, M., i Rezníˇ cková, L. (2015). The extreme drought episode of august 2011–may 2012 in the Czech Republic. International Journal of Climatology, 35(11):3335–3352. Zawadzki, J. i K˛edzior, M. A. (2014). Statistical analysis of soil moisture content changes in central europe using gldas database over three past decades. Central European Journal of Geosciences, 6(3):344–353. Zawadzki, J. i K˛edzior, M. A. (2015). Soil moisture variability over Odra watershed: Comparison between SMOS and GLDAS data. International Journal of Applied Earth Observation and Geoinformation. ´ Zreda, M., Nitychoruk, J., Chodyka, M., Swierczewska–Pietras, K., i Zbucki, Ł. (2015). Nowa metoda pomiaru wilgotno´sci gleby z wykorzystaniem neutronów kosmogenicznych. Przeglad ˛ Geologiczny, 63(4):239–246. Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., i Rosolem, R. (2012). COSMOS: the COsmic-ray Soil Moisture Observing System. Hydrology and Earth System Sciences, 16(11):4079–4099. Zribi, M., Pardé, M., Rosnay, P. D., Baup, F., Boulain, N., Descroix, L., Pellarin, T., Mougin, E., Ottlé, C., i Decharme, B. (2009). ERS scatterometer surface soil moisture analysis of two sites in the south and north of the Sahel region of West Africa. Journal of Hydrology, 375(1–2):253 – 261. Surface processes and water cycle in West Africa, studied from the AMMA-CATCH observing system.

263