Effect of Land Cover Heterogeneity on Soil Moisture Retrieval Using Active Microwave Remote Sensing Data
Abstract
:1. Introduction
2. Methodology
2.1. Study Area and Data Acquisition
2.2. Neural network application
3. Results and Discussion
3.1. Sub-pixel variability of NDVI
3.2. Backscatter and Vegetation Variability
Date / Site | Central Facility | Little Washita |
---|---|---|
July 2nd 1997 data | 0.515 | 0.376 |
July 12th 1997 data | 0.427 | 0.466 |
3.3. Land-cover Heterogeneity Impact on Soil Moisture Retrieval
4. Conclusions
Acknowledgements
References and Notes
- Engman, E.T.; Chauhan, N. Status of microwave soil moisture measurements with remote sensing. Remote Sens. Environ. 1995, 51, 189–198. [Google Scholar] [CrossRef]
- Santanello, J.J.A.; Peters-Lidard, C.D.; Garcia, M.E.; Mocko, D.M.; Tischler, M.A.; Moran, S.M.; Thoma, D.P. Using remotely-sensed estimates of soil moisture to infer soil texture and hydraulic properties across a semi-arid watershed. Remote Sens. Environ. 2007, 110, 79–97. [Google Scholar] [CrossRef]
- Ulaby, F.T.; Moore, R.; Fung, A. Microwave Remote Sensing Active and Passive From Theory to Applications; Artech House Norwood: MA, USA, 1986. [Google Scholar]
- Famiglietti, J.S.; Ryu, D.; Berg, A.A.; Rodell, M.; Jackson, T.J. Field observations of soil moisture variability across scales. Water Resour. Res. 2008, 44, W01423. [Google Scholar] [CrossRef]
- Crow, W.T.; Drusch, M.; Wood, E.F. An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrievals. IEEE Trans. Geosci. Remote Sens. 2001, 39, 1622–1632. [Google Scholar] [CrossRef]
- Bindlish, R.; Barros, A.P. Sub-pixel variability of remotely sensed soil moisture: an inter-comparison study of SAR and ESTAR. Remote Sens. Environ. 2002, 40, 326–337. [Google Scholar] [CrossRef]
- Loew, A. Impact of surface heterogeneity on surface soil moisture retrievals from passive microwave data at the regional scale: The Upper Danube case. Remote Sens. Environ. 2008, 112, 231–248. [Google Scholar] [CrossRef]
- Kasischke, E.; Smith, K.; Bourgeau-Chavez, L.; Romanowicz, E.; Brunzell, S.; Richardson, C. Effects of seasonal hydrologic patterns in south Florida wetlands on radar backscatter measured from ERS-2 SAR imagery. Remote Sens. Environ. 2003, 88, 423–441. [Google Scholar] [CrossRef]
- Brakke, T.W.; Kanemasu, E.T.; Steiner, J.L. Microwave radar response to canopy moisture, leaf-area index, and dry weight of wheat, corn and sorghum. Remote Sens. Environ. 1981, 11, 207–220. [Google Scholar] [CrossRef]
- Benediktsson, J.; Swain, P.; Ersoy, O.K. Neural network approaches versus statistical methods in classification of multi-source remote sensing data. IEEE Trans. Geosci. Remote Sens. 1990, 28, 540–552. [Google Scholar] [CrossRef]
- Jackson, T.J.; Vine, D.L.; Hsu, A.Y.; Oldak, A.; Starks, P.; Swift, C.; Isham, J.; Haken, M. Soil moisture mapping at regional scales using microwave radiometry: the Southern Great Plains Hydrology Experiment. IEEE Trans. Geosci. Remote Sens. 1999, 37, 2136–2151. [Google Scholar] [CrossRef]
- Paola, J.; Schowengerdt, R.A. A review and analysis of back-propagation neural networks for classification of remotely-sensed multi-spectral imagery. Int. J. Remote Sens. 1995, 16, 3033–3058. [Google Scholar] [CrossRef]
- Low, H.K.; Chuah, H.T.; Ewe, H.T. A neural network land use classifier for SAR images using textural and fractal information. Geocarto Int. 1999, 14, 66–73. [Google Scholar] [CrossRef]
- Carpenter, G.A.; Gopal, S.; Macomber, S.; Martens, S.; Woodcock, C.E.; Franklin, J. A neural network method for efficient vegetation mapping. Remote Sens. Environ. 1999, 70, 326–338. [Google Scholar] [CrossRef]
- Lakhankar, T. Estimation of soil moisture using active microwave remote sensing data. Ph.D Thesis, City University of New York, New York, NY, USA, 2006. [Google Scholar]
- Lakhankar, T.; Ghedira, H.; Temimi, M.; Sengupta, M.; Khanbilvardi, R.; Blake, R. Non-parametric Methods for Soil Moisture Retrieval from Satellite Remote Sensing Data. Remote Sens. 2009, 1, 3–21. [Google Scholar] [CrossRef] [Green Version]
© 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Share and Cite
Lakhankar, T.; Ghedira, H.; Temimi, M.; Azar, A.E.; Khanbilvardi, R. Effect of Land Cover Heterogeneity on Soil Moisture Retrieval Using Active Microwave Remote Sensing Data. Remote Sens. 2009, 1, 80-91. https://doi.org/10.3390/rs1020080
Lakhankar T, Ghedira H, Temimi M, Azar AE, Khanbilvardi R. Effect of Land Cover Heterogeneity on Soil Moisture Retrieval Using Active Microwave Remote Sensing Data. Remote Sensing. 2009; 1(2):80-91. https://doi.org/10.3390/rs1020080
Chicago/Turabian StyleLakhankar, Tarendra, Hosni Ghedira, Marouane Temimi, Amir E. Azar, and Reza Khanbilvardi. 2009. "Effect of Land Cover Heterogeneity on Soil Moisture Retrieval Using Active Microwave Remote Sensing Data" Remote Sensing 1, no. 2: 80-91. https://doi.org/10.3390/rs1020080