A comparative analysis of broadband and narrowband derived vegetation indices in predicting LAI and CCD of a cotton canopy

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 62, Issue 1, 2007, Pages 25-33

  Zhao, Dehua ^a   Huang, Liangmei ^a   Li, Jianlong ^a   Qi, Jiaguo ^b  

^a NANJING UNIVERSITY   (China)

^b MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

Bandwidth and wavelength selection; Broadband vegetation indices; Canopy chlorophyll density (CCD); Cotton; Hyperspectral remote sensing; Leaf area index (LAI); Narrowband VIs

Indexed keywords

BANDWIDTH; BIOPHYSICS; CHLOROPHYLL; CROPS; REMOTE SENSING;

CANOPY CHLOROPHYLL DENSITY (CCD); HYPERSPECTRAL REMOTE SENSING; LEAF AREA INDEX (LAI); NARROWBAND VEGETATION INDICES; WAVELENGTH SELECTION;

VEGETATION;

AGRONOMY; BROADBAND DATA; CANOPY; CHLOROPHYLL; COMPARATIVE STUDY; COTTON; LEAF AREA INDEX; NDVI; PREDICTION; REMOTE SENSING; VEGETATION INDEX;

COTTON; FOREST CANOPY; PLANTS; REMOTE SENSING;

GOSSYPIUM HIRSUTUM;

EID: 34247595039     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2007.01.003     Document Type: Article

References (34)

1. Aparicio N., Villegas D., Araus J.L., Casadesús J., and Royo C. Relationship between growth traits and spectral vegetation indices in durum wheat. Crop Science 42 5 (2002) 547-1555
2. Baret F., Guyot G., and Major D.J. TASVI: a vegetation index which minimizes soil brightness effects on LAI and APAR estimation. Proc. IGARSS' 89 and 12th Canadian Symposium on Remote Sensing, Vancouver, Canada, 10-14 July, 1989 (1989) 1355-1358
3. Blackburn G.A. Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leaves. International Journal of Remote Sensing 19 4 (1998) 657-675
4. Broge N.H., and Leblanc E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment 76 2 (2001) 156-172
5. Broge N.H., and Mortensen J.V. Deriving crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data. Remote Sensing of Environment 81 1 (2002) 45-57
6. Carlson T.N., and Ripley D.A. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment 62 3 (1997) 241-252
7. Casanova D., Epema G.F., and Goudriaan J. Monitoring rice reflectance at field level for estimating biomass and LAI. Field Crops Research 55 1-2 (1998) 83-92
8. Chang J.Y., Clay D.E., Dalsted K., Clay S., and O'Neill M. Corn yield prediction using multispectral and multidate reflectance. Agronomy Journal 95 6 (2003) 1447-1453
9. Danson F.M. Developments in the remote sensing of forest canopy structure. In: Danson F.M., and Plummer S.E. (Eds). Advances in Environmental Remote Sensing (1995), Wiley, Chichester, UK 53-69
10. Datt B. A new reflectance index for remote sensing of chlorophyll content in higher plants: tests using eucalyptus leaves. Journal of Plant Physiology 154 1 (1999) 30-36
11. Demetriades-Shah T.H., Steven M.D., and Clark J.A. High-resolution derivative spectral in remote sensing. Remote Sensing of Environment 33 1 (1990) 55-64
12. Dobermann A., and Ping J.L. Geostatistical integration of yield monitor data and remote sensing improves yield maps. Agronomy Journal 96 1 (2004) 285-297
13. Elvidge C., and Chen Z. Comparison of broadband and narrow-band red and near-infrared vegetation indices. Remote Sensing of Environment 54 1 (1995) 38-48
14. Hansen P.M., and Schjoerring J.K. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sensing of Environment 86 4 (2003) 542-553
15. Gitelson A.A., and Merzlyak M.N. Signature analysis of leaf reflectance spectra: algorithm development for remote sensing of chlorophyll. Journal of Plant Physiology 148 4 (1996) 494-500
16. Gitelson A.A., Kaufman Y.J., Stark R., and Rundquist D. Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment 80 1 (2002) 76-87
17. Goel P.K., Prasher S.O., Landry J.A., Patel R.M., Viau A.A., and Miller J.R. Estimation of crop biophysical parameters through airborne and field hyperspectral remote sensing. Transactions of the ASAE 46 4 (2003) 1235-1246
18. Jago R.A., Cutler M.E.J., and Curran P.J. Estimating canopy chlorophyll concentration from field and airborne spectra. Remote Sensing of Environment 68 3 (1999) 217-224
19. Kumar L., Schmidt K.S., Dury S., and Skidmore A.K. Imaging spectrometry and vegetation science. In: Van der Meer F., and De Jong S.M. (Eds). Imaging Spectrometry (2001), Kluwer Academic Publishers, Dordrecht, the Netherlands 111-155
20. Major D.J., Baret F., and Guyot G. A ration vegetation index adjusted for soil brightness. International Journal of Remote Sensing 11 5 (1990) 727-740
21. Mutanga O., Skidmore A.K., and Wieren S. Discrimination tropical grass (Cenchrus ciliaris) canopies grown under different nitrogen treatments using spectroradiometry. ISPRS Journal of Photogrammetry and Remote Sensing 57 4 (2003) 263-272
22. Myneni R.B., and Williams D.L. On the relationship between FAFAR and NDVI. Remote Sensing of Environment 49 3 (1994) 200-211
23. Pearson R.L., and Miller L.D. Remote mapping of standing crop biomass for estimation of the productivity of the short-grass prairie, Pawnee National Grasslands, Colorado. Proc. 8th International Symposium on Remote Sensing of Environment, ERIM International, Ann Arbor, Michigan, USA, 2-6 October, 1972 (1972) 1357-1381
24. Plant F.J., Munk D.S., Roberts B.R., Vargas R.L., Rains D.W., TraVI's R.L., and Humacher R.B. Relationships between remotely sensed reflectance data and cotton growth and yield. Transactions of the ASAE 43 3 (2000) 535-546
25. Qi J., Chehbouni A., Huete A.R., Kerr Y.H., and Sorooshian S. A modified soil adjusted vegetation index. Remote Sensing of Environment 48 2 (1994) 119-126
26. Read J.J., Tarpley L., Mckinion J.M., and Reddy K.R. Narrow-waveband reflectance ratios for remote estimation of nitrogen status in cotton. Journal of Environmental Quality 31 5 (2002) 1442-1452
27. Richardson A.J., and Wiegand C.L. Distinguishing vegetation from soil background information. Photogrammetric Engineering and Remote Sensing 43 12 (1977) 1541-1552
28. Rouse J.W., Haas R.H., Schell J.A., Deering D.W., and Harlan J.C. Monitoring the vernal advancement of retrogradation of natural vegetation. NASA/GSFC, Type III, Final Report, Greenbelt, MD, USA (1974) 1-371
29. Serrano L., Filella L., and Peñuelas J. Remote sensing of biomass and yield of winter wheat under different nitrogen supplies. Crop Science 40 3 (2000) 723-731
30. Shanahan J.F., Schepers J.S., Francis D.D., Varvel G.E., Wilhelm W.W., Tringe J.M., Schlemmer M.R., and Major D.J. Use of remote-sensing imagery to estimate corn grain yield. Agronomy Journal 93 3 (2001) 583-589
31. Sims D.A., and Gamon J.A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment 81 2-3 (2002) 331-354
32. Thenkabail P.S., Smith B.B., and De Pauw E. Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sensing of Environment 71 2 (2000) 158-182
33. Tottrup C., and Rasmussen M.S. Mapping long-term changes in savannah crop productivity in Senegal through trend analysis of time series of remote sensing data. Agriculture Ecosystems and Environment 103 3 (2004) 545-560
34. Wu C.S., Xiang Y.Q., Zheng L.F., and Tong Q.X. Estimating chlorophyll density of crop canopies by using hyperspectral data. Journal of Remote Sensing 4 3 (2000) 228-232