Leaf area index estimation using vegetation indices derived from airborne hyperspectral images in winter wheat

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 7, Issue 8, 2014, Pages 3586-3594

  Xie, Qiaoyun ^a   Huang, Wenjiang ^a   Liang, Dong ^b   Chen, Pengfei ^a   Wu, Chaoyang ^a   Yang, Guijun ^c   Zhang, Jingcheng ^c   Huang, Linsheng ^b   Zhang, Dongyan ^b  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b ANHUI UNIVERSITY   (China)

^c BEIJING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

Author keywords

Hyperspectral remote sensing; leaf area index (LAI); vegetation index (VI); winter wheat

Indexed keywords

CROPS; CULTIVATION; MEAN SQUARE ERROR; REMOTE SENSING; SPECTROSCOPY;

DETERMINATION COEFFICIENTS; HYPERSPECTRAL REMOTE SENSING; LEAF AREA INDEX; NORMALIZED DIFFERENCE VEGETATION INDEX; PUSH BROOM HYPERSPECTRAL IMAGER; REMOTE SENSING TECHNOLOGY; VEGETATION INDEX; WINTER WHEAT;

VEGETATION;

AIRBORNE SENSING; ENVIRONMENTAL CONDITIONS; ERROR ANALYSIS; ESTIMATION METHOD; LEAF AREA INDEX; NDVI; SPECTRAL ANALYSIS; SPECTRAL REFLECTANCE; VEGETATION INDEX; WHEAT; WINTER;

TRITICUM AESTIVUM;

EID: 85027925382     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2014.2342291     Document Type: Article

References (25)

1. J. Monteith and M. Unsworth, Principles of Environmental Physics: Plants, Animals, and the Atmosphere. New York, NY, USA: Academic, 2013.
2. Y. Dong, Analyzing Special Scale Problems of Crop Growth Parameters for Growth Monitoring With Multi-Scale Remote Sensing Data. Hangzhou, China: School Res. Environ., Zhejiang Univ., 2013.
3. Y. Knyazikhin et al., "Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data," J. Geophys. Res.: Atmos. (1984-2012), vol. 103, no. D24, pp. 32257-32275, 1998.
4. C. Bacour, F. Baret, and D. Beal, "Neural network estimation of LAI, fAPAR, fCover and LAI, from top of canopy MERIS reflectance data: Principles and validation," Remote Sens. Environ., vol. 105, no. 4, pp. 313-325, 2006.
5. F. Baret et al., "LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm," Remote Sens. Environ., vol. 110, no. 3, pp. 275-286, 2007.
6. F. Canisius, R. Fernandes, and J. Chen, "Comparison and evaluation of medium resolution imaging spectrometer leaf area index products across a range of land use," Remote Sens. Environ., vol. 114, no. 5, pp. 950-960, 2010.
7. R. Fernandes et al., "Landsat-5 TM and Landsat-7 ETM+ based accuracy assessment of leaf area index products for Canada derived from SPOT-4 VEGETATION data," Can. J. Remote Sens., vol. 29, no. 2, pp. 241-258, 2003.
8. R. Pu and P. Gong, "Wavelet transform applied to EO-1 hyperspectral data for forest LAI and crown closure mapping," Remote Sens. Environ., vol. 91, no. 2, pp. 212-224, 2004.
9. J. Liu, E. Pattey, and J. Guillaume, "Assessment of vegetation indices for regional crop green LAI estimation from Landsat images over multiple growing seasons," Remote Sens. Environ., vol. 123, pp. 347-358, 2012.
10. P. Gong et al., "Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 6, pp. 1355-1362, Jun. 2003.
11. E. Boegh et al., "Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture," Remote Sens. Environ., vol. 81, no. 2, pp. 179-193, 2002.
12. N. H. Broge and J. V. Mortensen, "Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data," Remote Sens. Environ., vol. 81, no. 1, pp. 45-57, 2002.
13. R. Colombo et al., "Retrieval of leaf area index in different vegetation types using high resolution satellite data," Remote Sens. Environ., vol. 86, no. 1, pp. 120-131, 2003.
14. P. Curran, "Estimating green LAI [leaf area index] from multispectral aerial photography," Photogramm. Eng. Remote Sens., vol. 49, no. 12, pp. 1709-1720, 1983.
15. A. Viña et al., "Comparison of different vegetation indices for the remote assessment of green leaf area index of crops," Remote Sens. Environ., vol. 115, no. 12, pp. 3468-3478, 2011.
16. D. Haboudane et al., "Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture," Remote Sens. Environ., vol. 90, no. 3, pp. 337-352, 2004.
17. J. Rouse, Jr., et al., "Monitoring vegetation systems in the great plains with ERTS," NASA Spec. Publ., vol. 351, pp. 309, 1974.
18. R. Darvishzadeh et al., "Mapping grassland leaf area index with airborne hyperspectral imagery: A comparison study of statistical approaches and inversion of radiative transfer models," ISPRS J. Photogramm. Remote Sens., vol. 66, no. 6, pp. 894-906, 2011.
19. J. Qi et al., "A modified soil adjusted vegetation index," Remote Sens. Environ., vol. 48, no. 2, pp. 119-126, 1994.
20. K. Huber et al., "Leaf area index determination of wheat indicating heterogeneous soil conditions," vol. 6359, pp. 63590M-63590M-9, 2006.
21. W. Huang et al., "Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging," Precis. Agric., vol. 8, no. 4-5, pp. 187-197, 2007.
22. S. Abraham and M. J. E. Golay, "Smoothing and differentiation of data by simplified least squares procedures," Anal. Chem., vol. 36, no. 8, pp. 1627-1639, 1964.
23. N. H. Broge and E. Leblanc, "Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density," Remote Sens. Environ., vol. 76, no. 2, pp. 156-172, 2001.
24. C. Wu et al., "Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements," Can. J. Remote Sens., vol. 36, no. 4, pp. 301-312, 2010.
25. R. Pu et al., "Extraction of red edge optical parameters from Hyperion data for estimation of forest leaf area index," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 4, pp. 916-921, Apr. 2003.