Irrigated grassland monitoring using a time series of TerraSAR-X and COSMO-SkyMed X-Band SAR data

Remote Sensing

Volumn 6, Issue 10, 2014, Pages 10002-10032

  El Hajj, Mohammad ^a   Baghdadi, Nicolas ^a   Belaud, Gilles ^b   Zribi, Mehrez ^c   Cheviron, Bruno ^b   Courault, Dominique ^d   Hagolle, Olivier ^c   Charron, François ^b  

^a UMR TETIS   (France)

^b UMR G EAU   (France)

^c UNIVERSITÉ DE TOULOUSE   (France)

^d UAPV   (France)

Author keywords

COSMO SkyMed; Grassland; Irrigation; LANDSAT; Soil moisture; SPOT 4; TerraSAR X; Vegetation parameters

Indexed keywords

ECOLOGY; GEOMETRICAL OPTICS; IMAGE ACQUISITION; IRRIGATION; MOISTURE; POLARIZATION; RADAR; REGRESSION ANALYSIS; SATELLITES; SENSITIVITY ANALYSIS; SOIL MOISTURE; SOIL SURVEYS; SOILS; SPACE-BASED RADAR; SYNTHETIC APERTURE RADAR; TIME SERIES;

COSMO SKYMED; GRASSLAND; LANDSAT; SPOT-4; TERRASAR-X; VEGETATION PARAMETERS;

VEGETATION;

EID: 84923578196     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs61010002     Document Type: Article

References (94)

1. Eineder, M.; Fritz, T.; Mittermayer, J.; Roth, A.; Boerner, E.; Breit, H. TerraSAR-X Ground Segment, Basic Product Specification Document; DTIC Document; Cluster Applied Remote Sensing: Munich, Germany, 2008.
2. Schwerdt, M.; Bräutigam, B.; Bachmann, M.; Döring, B. TerraSAR-X calibration results. In Proceedings of the 2008 7th European Conference on Synthetic Aperture Radar (EUSAR), Friedrichshafen, Germany, 2-5 June 2008; pp. 1-4.
3. Agenzia Spaziale Italiana. COSMO-SkyMed System Description&User Guide; Agenzia Spaziale Italiana: Roma, Italy, 2007. Available online: http://www.cosmo-skymed.it/docs/ASI-CSM-ENGRS-093-A-CSKSysDescriptionAndUserGuide.pdf (accessed on 15 October 2014).
4. Iorio, M.; Mecozzi, R.; Torre, A. Cosmo SkyMed: Antenna elevation pattern data evaluation. Ital. J. Remote Sens. 2010, 42, 69-77.
5. Asrar, G.; Fuchs, M.; Kanemasu, E.T.; Hatfield, J.L. Estimating absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat. Agron. J. 1984, 76, 300-306.
6. Baret, F.; Guyot, G. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environ. 1991, 35, 161-173.
7. Baret, F.; Hagolle, O.; Geiger, B.; Bicheron, P.; Miras, B.; Huc, M.; Berthelot, B.; Niño, F.; Weiss, M.; Samain, O. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm. Remote Sens. Environ. 2007, 110, 275-286.
8. Carlson, T.N.; Ripley, D.A. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens. Environ. 1997, 62, 241-252.
9. Duchemin, B.; Hadria, R.; Erraki, S.; Boulet, G.; Maisongrande, P.; Chehbouni, A.; Escadafal, R.; Ezzahar, J.; Hoedjes, J.C.B.; Kharrou, M.H. Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices. Agric. Water Manag. 2006, 79, 1-27.
10. Weiss, M.; Baret, F. Evaluation of canopy biophysical variable retrieval performances from the accumulation of large swath satellite data. Remote Sens. Environ. 1999, 70, 293-306.
11. Weiss, M.; Baret, F.; Smith, G.J.; Jonckheere, I.; Coppin, P. Review of methods for in situ leaf area index (LAI) determination: Part II. Estimation of LAI, errors and sampling. Agric. For. Meteorol. 2004, 121, 37-53.
12. Baret, F.; Guerif, M. Remote detection and quantification of plant stress: Opportunities remote sensing observations. Comp. Biochem. Physiol. Mol. Integr. Physiol. 2006, 143, S148-S148.
13. Bsaibes, A.; Courault, D.; Baret, F.; Weiss, M.; Olioso, A.; Jacob, F.; Hagolle, O.; Marloie, O.; Bertrand, N.; Desfond, V. Albedo and LAI estimates from FORMOSAT-2 data for crop monitoring. Remote Sens. Environ. 2009, 113, 716-729.
14. Courault, D.; Bsaibes, A.; Kpemlie, E.; Hadria, R.; Hagolle, O.; Marloie, O.; Hanocq, J.-F.; Olioso, A.; Bertrand, N.; Desfonds, V. Assessing the potentialities of FORMOSAT-2 data for water and crop monitoring at small regional scale in South-Eastern France. Sensors 2008, 8, 3460-3481.
15. Courault, D.; Hadria, R.; Ruget, F.; Olioso, A.; Duchemin, B.; Hagolle, O.; Dedieu, G. Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region. Hydrol. Earth Syst. Sci. Discuss. 2010, 7, 1731-1744.
16. Edirisinghe, A.; Hill, M.J.; Donald, G.E.; Hyder, M. Quantitative mapping of pasture biomass using satellite imagery. Int. J. Remote Sens. 2011, 32, 2699-2724.
17. Ferreira, L.G.; Fernandez, L.E.; Sano, E.E.; Field, C.; Sousa, S.B.; Arantes, A.E.; Araújo, F.M. Biophysical properties of cultivated pastures in the Brazilian savanna biome: An analysis in the spatial-temporal domains based on ground and satellite data. Remote Sens. 2013, 5, 307-326.
18. Schino, G.; Borfecchia, F.; de Cecco, L.; Dibari, C.; Iannetta, M.; Martini, S.; Pedrotti, F. Satellite estimate of grass biomass in a mountainous range in central Italy. Agrofor. Syst. 2003, 59, 157-162.
19. Todd, S.W.; Hoffer, R.M.; Milchunas, D.G. Biomass estimation on grazed and ungrazed rangelands using spectral indices. Int. J. Remote Sens. 1998, 19, 427-438.
20. Payero, J.O.; Neale, C.M.U.; Wright, J.L. Comparison of eleven vegetation indices for estimating plant height of alfalfa and grass. Appl. Eng. Agric. 2004, 20, 385-393.
21. Chen, D.; Huang, J.; Jackson, T.J. Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near-and short-wave infrared bands. Remote Sens. Environ. 2005, 98, 225-236.
22. Jackson, T.J.; Chen, D.; Cosh, M.; Li, F.; Anderson, M.; Walthall, C.; Doriaswamy, P.; Hunt, E. Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sens. Environ. 2004, 92, 475-482.
23. Serrano, L.; Ustin, S.L.; Roberts, D.A.; Gamon, J.A.; Penuelas, J. Deriving water content of chaparral vegetation from AVIRIS data. Remote Sens. Environ. 2000, 74, 570-581.
24. Gu, Y.; Brown, J.F.; Verdin, J.P.; Wardlow, B. A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States. Geophys. Res. Lett. 2007, 34, doi:10.1029/2006GL029127.
25. Gao, B.-C. NDWI-A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens. Environ. 1996, 58, 257-266.
26. Anderson, M.C.; Neale, C.M.U.; Li, F.; Norman, J.M.; Kustas, W.P.; Jayanthi, H.; Chavez, J. Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery. Remote Sens. Environ. 2004, 92, 447-464.
27. Aubert, M.; Baghdadi, N.; Zribi, M.; Douaoui, A.; Loumagne, C.; Baup, F.; El Hajj, M.; Garrigues, S. Analysis of TerraSAR-X data sensitivity to bare soil moisture, roughness, composition and soil crust. Remote Sens. Environ. 2011, 115, 1801-1810.
28. Baghdadi, N.; Gaultier, S.; King, C. Retrieving surface roughness and soil moisture from SAR data using neural networks. In Retrieval of Bio-and Geo-Physical Parameters from SAR Data for Land Applications; ESTEC Publishing Division: Sheffield, UK, 2002; Volume 475, pp. 315-319.
29. Baghdadi, N.; Cresson, R.; El Hajj, M.; Ludwig, R.; la Jeunesse, I. Estimation of soil parameters over bare agriculture areas from C-band polarimetric SAR data using neural networks. Hydrol. Earth Syst. Sci. 2012, 16, 1607-1621.
30. Srivastava, H.S.; Patel, P.; Sharma, Y.; Navalgund, R.R. Large-area soil moisture estimation using multi-incidence-angle RADARSAT-1 SAR data. IEEE Trans. Geosci. Remote Sens. 2009, 47, 2528-2535.
31. Zribi, M.; Saux-Picart, S.; André, C.; Descroix, L.; Ottle, C.; Kallel, A. Soil moisture mapping based on ASAR/ENVISAT radar data over a Sahelian region. Int. J. Remote Sens. 2007, 28, 3547-3565.
32. Zribi, M.; Baghdadi, N.; Holah, N.; Fafin, O. New methodology for soil surface moisture estimation and its application to ENVISAT-ASAR multi-incidence data inversion. Remote Sens. Environ. 2005, 96, 485-496.
33. Zribi, M.; Dechambre, M. A new empirical model to retrieve soil moisture and roughness from C-band radar data. Remote Sens. Environ. 2003, 84, 42-52.
34. Inoue, Y.; Kurosu, T.; Maeno, H.; Uratsuka, S.; Kozu, T.; Dabrowska-Zielinska, K.; Qi, J. Seasonlong daily measurements of multifrequency (Ka, Ku, X, C, and L) and full-polarization backscatter signatures over paddy rice field and their relationship with biological variables. Remote Sens. Environ. 2002, 81, 194-204.
35. Ferrazzoli, P.; Paloscia, S.; Pampaloni, P.; Schiavon, G.; Sigismondi, S.; Solimini, D. The potential of multifrequency polarimetric SAR in assessing agricultural and arboreous biomass. IEEE Trans. Geosci. Remote Sens. 1997, 35, 5-17.
36. Kim, S.; Kim, B.; Kong, Y.; Kim, Y.-S. Radar backscattering measurements of rice crop using X-band scatterometer. IEEE Trans. Geosci. Remote Sens. 2000, 38, 1467-1471.
37. Wigneron, J.-P.; Ferrazzoli, P.; Olioso, A.; Bertuzzi, P.; Chanzy, A. A simple approach to monitor crop biomass from C-band radar data. Remote Sens. Environ. 1999, 69, 179-188.
38. Wigneron, J.-P.; Fouilhoux, M.; Prévot, L.; Chanzy, A.; Olioso, A.; Baghdadi, N.; King, C. Monitoring sunflower crop development from C-band radar observations. Agron.-Sci. Prod. Veg. Environ. 2002, 22, 587-596.
39. Gao, S.; Niu, Z.; Huang, N.; Hou, X. Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2. Int. J. Appl. Earth Obs. Geoinf. 2013, 24, 1-8.
40. Aubert, M.; Baghdadi, N.N.; Zribi, M.; Ose, K.; El Hajj, M.; Vaudour, E.; Gonzalez-Sosa, E. Toward an operational bare soil moisture mapping using TerraSAR-X data acquired over agricultural areas. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2013, 6, 900-916.
41. Baghdadi, N.; Saba, E.; Aubert, M.; Zribi, M.; Baup, F. Evaluation of radar backscattering models IEM, Oh, and Dubois for SAR data in X-band over bare soils. IEEE Geosci. Remote Sens. Lett. 2011, 8, 1160-1164.
42. Baghdadi, N.; Cresson, R.; Pottier, E.; Aubert, M.; Zribi, M.; Jacome, A.; Benabdallah, S. A potential use for the C-band polarimetric SAR parameters to characterize the soil surface over bare agriculture fields. IEEE Trans. Geosci. Remote Sens. 2012, 50, 3844-3858.
43. Baghdadi, N.; Aubert, M.; Zribi, M. Use of TerraSAR-X data to retrieve soil moisture over bare soil agricultural fields. IEEE Geosci. Remote Sens. Lett. 2012, 9, 512-516.
44. Hegarat-Mascle, L.; Zribi, M.; Alem, F.; Weisse, A.; Loumagne, C. Soil moisture estimation from ERS/SAR data: Toward an operational methodology. IEEE Trans. Geosci. Remote Sens. 2002, 40, 2647-2658.
45. Srivastava, H.S.; Patel, P.; Manchanda, M.L.; Adiga, S. Use of multiincidence angle RADARSAT-1 SAR data to incorporate the effect of surface roughness in soil moisture estimation. IEEE Trans. Geosci. Remote Sens. 2003, 41, 1638-1640.
46. Zribi, M.; André, C.; Decharme, B. A method for soil moisture estimation in Western Africa based on the ERS scatterometer. IEEE Trans. Geosci. Remote Sens. 2008, 46, 438-448.
47. Singh, D. A simplistic incidence angle approach to retrieve the soil moisture and surface roughness at X-band. IEEE Trans. Geosci. Remote Sens. 2005, 43, 2606-2611.
48. Anguela, T.P.; Zribi, M.; Baghdadi, N.; Loumagne, C. Analysis of local variation of soil surface parameters with TerraSAR-X radar data over bare agricultural fields. IEEE Trans. Geosci. Remote Sens. 2010, 48, 874-881.
49. Shi, J.; Wang, J.; Hsu, A.Y.; O'Neill, P.E.; Engman, E.T. Estimation of bare surface soil moisture and surface roughness parameter using L-band SAR image data. IEEE Trans. Geosci. Remote Sens. 1997, 35, 1254-1266.
50. Ponnurangam, G.G.; Rao, Y.S. Soil moisture mapping using ALOS PALSAR and ENVISAT ASAR data over India. In Proceedings of the 2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar (APSAR 2011), Seoul, South Korea, 26-30 September 2011; pp. 1-4.
51. Sonobe, R.; Tani, H.; Wang, X.; Fukuda, M. Estimation of soil moisture for bare soil fields using ALOS/PALSAR HH polarization data. Agric. Inf. Res. 2008, 17, 171-177.
52. Baghdadi, N.; Holah, N.; Zribi, M. Soil moisture estimation using multi-incidence and multi- polarization ASAR data. Int. J. Remote Sens. 2006, 27, 1907-1920.
53. Baghdadi, N.; Cerdan, O.; Zribi, M.; Auzet, V.; Darboux, F.; El Hajj, M.; Kheir, R.B. Operational performance of current synthetic aperture radar sensors in mapping soil surface characteristics in agricultural environments: Application to hydrological and erosion modelling. Hydrol. Process. 2008, 22, 9-20.
54. Quesney, A.; le Hégarat-Mascle, S.; Taconet, O.; Vidal-Madjar, D.; Wigneron, J.P.; Loumagne, C.; Normand, M. Estimation of watershed soil moisture index from ERS/SAR data. Remote Sens. Environ. 2000, 72, 290-303.
55. Attema, E.P.W.; Ulaby, F.T. Vegetation modeled as a water cloud. Radio Sci. 1978, 13, 357-364.
56. Paris, J.F. The effect of leaf size on the microwave backscattering by corn. Remote Sens. Environ. 1986, 19, 81-95.
57. Ulaby, F.T.; Sarabandi, K.; McDonald, K.; Whitt, M.; Dobson, M.C. Michigan microwave canopy scattering model. Int. J. Remote Sens. 1990, 11, 1223-1253.
58. Bindlish, R.; Barros, A.P. Parameterization of vegetation backscatter in radar-based, soil moisture estimation. Remote Sens. Environ. 2001, 76, 130-137.
59. Prevot, L.; Champion, I.; Guyot, G. Estimating surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer. Remote Sens. Environ. 1993, 46, 331-339.
60. De Roo, R.D.; Du, Y.; Ulaby, F.T.; Dobson, M.C. A semi-empirical backscattering model at L-band and C-band for a soybean canopy with soil moisture inversion. IEEE Trans. Geosci. Remote Sens. 2001, 39, 864-872.
61. Sikdar, M.; Cumming, I. A modified empirical model for soil moisture estimation in vegetated areas using SAR data. In Proceedings of the 2004 IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, USA, 20-24 September 2004; Volume 2, pp. 803-806.
62. Gherboudj, I.; Magagi, R.; Berg, A.A.; Toth, B. Soil moisture retrieval over agricultural fields from multi-polarized and multi-angular RADARSAT-2 SAR data. Remote Sens. Environ. 2011, 115, 33-43.
63. Wang, S.G.; Li, X.; Han, X.J.; Jin, R. Estimation of surface soil moisture and roughness from multiangular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER). Hydrol. Earth Syst. Sci. 2011, 15, 1415-1426.
64. Yu, F.; Zhao, Y. A new semi-empirical model for soil moisture content retrieval by ASAR and TM data in vegetation-covered areas. Sci. China Earth Sci. 2011, 54, 1955-1964.
65. Zribi, M.; Chahbi, A.; Shabou, M.; Lili-Chabaane, Z.; Duchemin, B.; Baghdadi, N.; Amri, R.; Chehbouni, A. Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation. Hydrol. Earth Syst. Sci. 2011, 15, 345-358.
66. Yang, G.; Shi, Y.; Zhao, C.; Wang, J. Estimation of soil moisture from multi-polarized SAR data over wheat coverage areas. In Proceedings of the 2012 First International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Shanghai, China, 2-4 August 2012; pp. 1-5.
67. Kweon, S.-K.; Hwang, J.-H.; Yisok, O. COSMO SkyMed AO projects-soil moisture detection for vegetation fields based on a modified water-cloud model using COSMO-SkyMed SAR data. In Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 22-27 July 2012; pp. 1204-1207.
68. Fieuzal, R.; Duchemin, B.; Jarlan, L.; Zribi, M.; Baup, F.; Merlin, O.; Hagolle, O.; Garatuza-Payan, J. Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops. Hydrol. Earth Syst. Sci. 2011, 15, 1117-1129.
69. Mérot, A. Analyse et modélisation du fonctionnement biophysique et décisionnel d'un système prairial irrigué-Application aux prairies plurispécifiques de Crau en vue de l'élaboration d'un Outil d'Aide à la Décision. Thèse de Doctorat, Ecole Nationale Superieure Agronomique de Montpellier-AGRO, Montpellier, France, 2007.
70. Merot, A.; Wery, J.; Isberie, C.; Charron, F. Response of a plurispecific permanent grassland to border irrigation regulated by tensiometers. Eur. J. Agron. 2008, 28, 8-18.
71. Bottraud, J.C.; Bornand, M.; Servat, E. Mesures de résistivité appliquées à la cartographie en pédologie. Sci. Sol. 1984, 4, 279-294.
72. Torre, A.; Calabrese, D.; Porfilio, M. COSMO-SkyMed: Image quality achievements. In Proceedings of the 2011 5th International Conference on Recent Advances in Space Technologies (RAST), Istanbul, Turkey, 9-11 June 2011; pp. 861-864.
73. Hagolle, O.; Dedieu, G.; Mougenot, B.; Debaecker, V.; Duchemin, B.; Meygret, A. Correction of aerosol effects on multi-temporal images acquired with constant viewing angles: Application to Formosat-2 images. Remote Sens. Environ. 2008, 112, 1689-1701.
74. Rahman, H.; Dedieu, G. SMAC: A simplified method for the atmospheric correction of satellite measurements in the solar spectrum. Int. J. Remote Sens. 1994, 15, 123-143.
75. Masek, J.G.; Vermote, E.F.; Saleous, N.; Wolfe, R.; Hall, F.G.; Huemmrich, F.; Gao, F.; Kutler, J.; Lim, T.K. LEDAPS Calibration, Reflectance, Atmospheric Correction Preprocessing Code, Version 2. Available online: http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1146 (accessed on 15 October 2014).
76. Ulaby, F.T.; Moore, R.K.; Fung, A.K. Volume scattering and emission theory. In Microwave Remote Sensing: Active and Passive, Vol. III, From Theory to Applications; Inc Dedham Mass: Dedham, MA, USA, 1986; pp. 1797-1848.
77. Lievens, H.; Vernieuwe, H.; Alvarez-Mozos, J.; de Baets, B.; Verhoest, N.E. Error in radar-derived soil moisture due to roughness parameterization: An analysis based on synthetical surface profiles. Sensors 2009, 9, 1067-1093.
78. Oh, Y.; Kay, Y.C. Condition for precise measurement of soil surface roughness. IEEE Trans. Geosci. Remote Sens. 1998, 36, 691-695.
79. Baghdadi, N.; Cresson, R.; Todoroff, P.; Moinet, S. Multitemporal observations of sugarcane by TerraSAR-X images. Sensors 2010, 10, 8899-8919.
80. Balenzano, A.; Mattia, F.; Satalino, G.; Davidson, M. Dense temporal series of C-and L-band SAR data for soil moisture retrieval over agricultural crops. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2011, 4, 439-450.
81. Brown, S.C.; Quegan, S.; Morrison, K.; Bennett, J.C.; Cookmartin, G. High-resolution measurements of scattering in wheat canopies-Implications for crop parameter retrieval. IEEE Trans. Geosci. Remote Sens. 2003, 41, 1602-1610.
82. Picard, G.; le Toan, T.; Mattia, F. Understanding C-band radar backscatter from wheat canopy using a multiple-scattering coherent model. IEEE Trans. Geosci. Remote Sens. 2003, 41, 1583-1591.
83. Baghdadi, N.; Bernier, M.; Gauthier, R.; Neeson, I. Evaluation of C-band SAR data for wetlands mapping. Int. J. Remote Sens. 2001, 22, 71-88.
84. Merot, A.; Bergez, J.E.; Wallach, D.; Duru, M. Adaptation of a functional model of grassland to simulate the behaviour of irrigated grasslands under a Mediterranean climate: The Crau case. Eur. J. Agron. 2008, 29, 163-174.
85. Ulaby, F.T.; Bush, T.F.; Batlivala, P.P. Radar response to vegetation II: 8-18 GHz band. IEEE Trans. Antennas Propag. 1975, 23, 608-618.
86. Mattia, F.; le Toan, T.; Picard, G.; Posa, F.I.; D'Alessio, A.; Notarnicola, C.; Gatti, A.M.; Rinaldi, M.; Satalino, G.; Pasquariello, G. Multitemporal C-band radar measurements on wheat fields. IEEE Trans. Geosci. Remote Sens. 2003, 41, 1551-1560.
87. Champion, I. Etude et mise au point de modèles Semi-empiriques représentant la réponse de couverts végétaux dans le domaine hyperfréquence. Complémentarité avec le domaine optique. Thèse de Doctorat, Université Paris VII, Paris, France, 1991.
88. Fieuzal, R.; Baup, F.; Marais-Sicre, C. Monitoring wheat and rapeseed by using synchronous optical and radar satellite data-From temporal signatures to crop parameters estimation. Adv. Remote Sens. 2013, 2, 162-180.
89. Lin, H.; Chen, J.; Pei, Z.; Zhang, S.; Hu, X. Monitoring sugarcane growth using ENVISAT ASAR data. IEEE Trans. Geosci. Remote Sens. 2009, 47, 2572-2580.
90. Liu, C.; Shang, J.; Vachon, P.W.; McNairn, H. Multiyear crop monitoring using polarimetric RADARSAT-2 data. IEEE Trans. Geosci. Remote Sens. 2013, 51, 2227-2240.
91. Macelloni, G.; Paloscia, S.; Pampaloni, P.; Marliani, F.; Gai, M. The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops. IEEE Trans. Geosci. Remote Sens. 2001, 39, 873-884.
92. Ulaby, F.T.; Allen, C.T.; Eger Iii, G.; Kanemasu, E. Relating the microwave backscattering coefficient to leaf area index. Remote Sens. Environ. 1984, 14, 113-133.
93. Fontanelli, G.; Paloscia, S.; Zribi, M.; Chahbi, A. Sensitivity analysis of X-band SAR to wheat and barley leaf area index in the Merguellil Basin. Remote Sens. Lett. 2013, 4, 1107-1116.
94. Cookmartin, G.; Saich, P.; Quegan, S.; Cordey, R.; Burgess-Allen, P.; Sowter, A. Modeling microwave interactions with crops and comparison with ERS-2 SAR observations. IEEE Trans. Geosci. Remote Sens. 2000, 38, 658-670.