Identification of hyperspectral vegetation indices for Mediterranean pasture characterization

International Journal of Applied Earth Observation and Geoinformation

Volumn 11, Issue 4, 2009, Pages 233-243

  Fava, F ^a,b   Colombo, R ^b   Bocchi, S ^a   Meroni, M ^b   Sitzia, M ^c   Fois, N ^c   Zucca, C ^d  

^a UNIVERSITY OF MILAN   (Italy)

^b UNIVERSITY OF MILANO BICOCCA   (Italy)

^c AGRIS Sardegna   (Italy)

^d UNIVERSITY OF SASSARI   (Italy)

Author keywords

Biomass; Hyperspectral indices; Leaf area index; Nitrogen; Pasture; Remote sensing

Indexed keywords

AIRBORNE SENSING; BIOMASS; BROADBAND DATA; CANOPY REFLECTANCE; EXPERIMENTAL STUDY; FIELD SURVEY; LEAF AREA INDEX; NDVI; NEAR INFRARED; NITROGEN CYCLE; PASTURE; RADIOMETER; REGRESSION ANALYSIS; SATELLITE DATA; SATELLITE IMAGERY; SPECTRAL ANALYSIS;

MEDITERRANEAN REGION; MEDITERRANEAN SEA;

EID: 67349146321     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2009.02.003     Document Type: Article

References (51)

1. Asner G.P. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens. Environ. 65 (1998) 225-226
2. Asner G.P., Townsend A.R., and Bustamante M.M.C. Spectrometry of pasture condition and biogeochemistry in the Central Amazon. Geophys. Res. Lett. 26 (1999) 2769-2772
3. Asner G.P., Townsend A.R., Bustamante M.M.C., Nardoto G.B., and Olander L.P. Pasture degradation in the central Amazon: linking changes in carbon and nutrient cycling with remote sensing. Glob. Change Biol. 10 (2004) 844-862
4. Bailey D.W., Gross J.E., Laca E.A., Rittenhouse L.R., Coughenour M.B., Swift D.M., and Sims P.L. Mechanisms that result in large herbivore grazing distribution patterns. J. Range Manage. 49 (1996) 386-400
5. Ball D., Collins M., Lacefield G., Martin N., Mertens D., Olson K., Putnam D., Undersander D., and Wolf M. Understanding Forage Quality. American Farm Bureau Federation Publication 1-01 (2001), American Farm Bureau Federation, Park Ridge, IL
6. Beeri O., Phillips R., Hendrickson J., Frank A.B., and Kronberg S. Estimating forage quantity and quality using aerial hyperspectral imagery for northern mixed-grass prairie. Remote Sens. Environ. 110 (2007) 216-225
7. Blackburn G.A. Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leaves. Int. J. Remote Sens. 19 (1998) 657-675
8. Boschetti M., Bocchi S., and Brivio P.A. Assessment of pasture production in the Italian Alps using spectrometric and remote sensing information. Agric. Ecosyst. Environ. 118 (2007) 267-272
9. Bowyer P., and Danson F.M. Sensitivity of spectral reflectance to variation in live fuel moisture content at leaf and canopy level. Remote Sens. Environ. 92 (2004) 297-308
10. 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 Sens. Environ. 76 (2001) 156-172
11. Cho M.A., and Skidmore A. A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method. Remote Sens. Environ. 101 (2006) 181-193
12. Cho M.A., Skidmore A., Corsi F., van Wieren S.E., and Sobhan I. Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression. Int. J. Appl. Earth Observ. Geoinform. 9 (2007) 414-424
13. Corrall A.J., and Fenlon J.S. A comparative method for describing the seasonal distribution of production from grasses. J. Agric. Sci., UK 91 (1978) 61-67
14. d'Angelo M., Enne G., Madrau S., Percich L., Previtali F., Pulina G., and Zucca C. Mitigating land degradation in Mediterranean agro-silvo-pastoral systems: a GIS-based approach. Catena 40 (2000) 37-49
15. Danson F.M., and Plummer S.E. Red-edge response to forest leaf-area index. Int. J. Remote Sens. 16 (1995) 183-188
16. Darvishzadeh R., Skidmore A., Schlerf M., Atzberger C., Corsi F., and Cho M. LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements. ISPRS-J. Photogramm. Remote Sens. 63 (2008) 409-426
17. Darvishzadeh R., Skidmore A., Schlerf M., and Atzberger C. Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland. Remote Sens. Environ. 112 (2008) 2592-2604
18. Darvishzadeh R., Skidmore A., Atzberger C., and van Wieren S. Estimation of vegetation LAI from hyperspectral reflectance data: Effects of soil type and plant architecture. Int. J. Appl. Earth Observ. Geoinform. 10 (2008) 358-373
19. Daughtry C.S.T., Walthall C.L., Kim M.S., de Colstoun E.B., and McMurtrey J.E. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sens. Environ. 74 (2000) 229-239
20. Elvidge C.D., and Chen Z.K. Comparison of broad-band and narrow-band red and near-infrared vegetation indexes. Remote Sens. Environ. 54 (1995) 38-48
21. Everitt J., Richardson A.J., and Gausman H.V. Leaf reflectance-nitrogen-chlorophyll relations in buffelgrass. Photogramm. Eng. Remote Sens. 51 (1985) 463-466
22. FAO/ISRIC/ISSS, 1998. World Reference Base for Soil Resources. World Soil Resources Report 84. FAO, Rome, p. 90.
23. Feng W., Yao X., Zhu Y., Tian Y.C., and Cao W. Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. Eur. J. Agron. 28 (2008) 394-404
24. Gianelle D., and Guastella F. Nadir and off-nadir hyperspectral field data: strengths and limitations in estimating grassland biophysical characteristics. Int. J. Remote Sens. 28 (2007) 1547-1560
25. Gianelle D., and Vescovo L. Determination of green herbage ratio in grasslands using spectral reflectance. Methods and ground measurements. Int. J. Remote Sens. 28 (2007) 931-942
26. Green R.N., Trowbridge R.L., and Klinka K. Towards a taxonomic classification of humus forms. Forest Sci. 39 (1993) 1-49
27. Haboudane D., Miller J.R., Tremblay N., Zarco-Tejada P.J., and Dextraze L. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sens. Environ. 81 (2002) 416-426
28. 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 Sens. Environ. 86 (2003) 542-553
29. He Y., Guo X.L., and Wilmshurst J. Studying mixed grassland ecosystems I: suitable hyperspectral vegetation indices. Can. J. Remote Sens. 32 (2006) 98-107
30. Hinzman L.D., Bauer M.E., and Daughtry C.S.T. Effects of nitrogen fertilization on growth and reflectance characteristics of winter-wheat. Remote Sens. Environ. 19 (1986) 47-61
31. Hoffer, R.M., 1978. Biological and physical considerations in applying computer-aided analysis techniques to remote sensor data. In Remote Sensing: The quantitative approach edited by P.H. Swain and S.M. Davis (New York: McGraw-Hill), pp. 227-289.
32. Hunt E.R., Everitt J.H., Ritchie J.C., Moran M.S., Booth D.T., Anderson G.L., Clark P.E., and Seyfried M.S. Applications and research using remote sensing for rangeland management. Photogramm. Eng. Remote Sens. 69 (2003) 675-693
33. 2 flux measurements in rice. Remote Sens. Environ. 112 (2008) 156-172
34. Jordan C.F. Derivation of leaf area index from quality of light on the forest floor. Ecology 50 (1969) 663-666
35. Lamb D.W., Steyn-Ross M., Schaare P., Hanna M.M., Silvester W., and Steyn-Ross A. Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: theoretical modelling and experimental observations. Int. J. Remote Sens. 23 (2002) 3619-3648
36. Lee K.S., Cohen W.B., Kennedy R.E., Maiersperger T.K., and Gower S.T. Hyperspectral versus multispectral data for estimating leaf area index in four different biomes. Remote Sens. Environ. 91 (2004) 508-520
37. Mutanga O., and Skidmore A.K. Narrow band vegetation indices overcome the saturation problem in biomass estimation. Int. J. Remote Sens. 25 (2004) 3999-4014
38. Mutanga O., Skidmore A.K., and Prins H.H.T. Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features. Remote Sens. Environ. 89 (2004) 393-408
39. Numata I., Roberts D.A., Chadwick O.A., Schimel J., Sampaio F.R., Leonidas F.C., and Soares J.V. Characterization of pasture biophysical properties and the impact of grazing intensity using remotely sensed data. Remote Sens. Environ. 109 (2007) 314-327
40. Numata I., Roberts D.A., Chadwick O.A., Schimel J., Galvao J., and Soares J.V. Evaluation of hyperspectral data for pasture estimate in the Brazilian Amazon using field and imaging spectrometers. Remote Sens. Environ. 112 (2008) 1569-1583
41. Rouse, J.W., Hass, R.H., Shell, J.A., Deering, D.W., 1974. Monitoring vegetation systems in the Great Plains with ERTS-1. In: Proceedings of the 3rd Earth Resources Technology Satellite Symposium 1, 309-317.
42. Rundquist B.C. The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie. Remote Sens. Environ. 81 (2002) 129-135
43. Senft R.L., Rittenhouse L.R., and Woodmansee R.G. Factors influencing patterns of cattle grazing behaviour on shortgrass steppe. J. Range Manage. 38 (1984) 82-87
44. Starks P.J., Zhao D.L., Phillips W.A., and Coleman S.W. Development of canopy reflectance algorithms for real-time prediction of bermudagrass pasture biomass and nutritive values. Crop Sci. 46 (2006) 927-934
45. Starks P.J., Zhao D., Phillips W.A., and Coleman S.W. Herbage mass, nutritive value and canopy spectral reflectance of bermudagrass pastures. Grass Forage Sci. 61 (2006) 101-111
46. Thenkabail P.S., Smith R.B., and De Pauw E. Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sens. Environ. 71 (2000) 158-182
47. Todd S.W., Hoffer R.M., and Milchunas D.G. Biomass estimation on grazed and ungrazed rangelands using spectral indices. Int. J. Remote Sens. 19 (1998) 427-438
48. Van Leeuwen W.J.D., and Huete A.R. Effects of standing litter on the biophysical interpretation of plant canopies with spectral indices. Remote Sens. Environ. 55 (1996) 123-138
49. Vescovo L., and Gianelle D. Mapping the green herbage ratio of grasslands using both aerial and satellite-derived spectral reflectance. Agric. Ecosyst. Environ. 115 (2006) 141-149
50. Zarco-Tejada P.J., Miller J.R., Noland T.L., Mohammed G.H., and Sampson P.H. Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data. IEEE Trans. Geosci. Remote Sens. 39 (2001) 1491-1507
51. Zhao D.H., Li J.L., and Qi J.G. Identification of red and NIR spectral regions and vegetative indices for discrimination of cotton nitrogen stress and growth stage. Comput. Electron. Agric. 48 (2005) 155-169