Comparative analysis of IKONOS, SPOT, and ETM+ data for leaf area index estimation in temperate coniferous and deciduous forest stands

Remote Sensing of Environment

Volumn 102, Issue 1-2, 2006, Pages 161-175

  Soudani, Kamel ^a   François, Christophe ^a   le Maire, Guerric ^a   Le Dantec, Valérie ^b   Dufrêne, Eric ^a  

^a UNIVERSITÉ PARIS SUD   (France)

^b CNES   (France)

Author keywords

Forest; IKONOS; LAI; Landsat ETM+; Leaf area index; NDVI; PROSPECT; SAIL; SPOT 4 HRVIR

Indexed keywords

COMPUTER SIMULATION; MATHEMATICAL MODELS; REMOTE SENSING; VEGETATION;

IKONOS; LAI; LANDSAT ETM+; LEAF AREA INDEX; NDVI; PROSPECT; SAIL; SPOT-4 HRVIR;

FORESTRY;

ATMOSPHERE; CALIBRATION; CANOPY; CANOPY REFLECTANCE; LEAF AREA INDEX; RADIOMETRIC SURVEY; REMOTE SENSING;

FORESTRY; PLANTS; REMOTE SENSING;

EID: 33646130407     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2006.02.004     Document Type: Article

References (84)

1. Asner G.P., Scurlock J.M., and Hicke J.A. Global synthesis of leaf area index observations: Implications for ecological and remote sensing studies. Global Ecology and Biogeography 12 (2003) 91-205
2. Baret F., and Guyot G. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sensing of Environment 35 (1991) 161-173
3. Black T.A., Lee X., and Sagar R.M. Characteristics of shortwave and longwave irradiances under a Douglas-fir forest stand. Canadian Journal of Forest Research 21 (1991) 1020-1028
4. Blackburn G.A., and Milton E.J. Seasonal variations in the spectral reflectance of deciduous tree canopies. International Journal of Remote Sensing 16 4 (1995) 709-720
5. Breda N.J.J. Ground-based measurements of leaf area index: A review of methods, instruments and current controversies. Journal of Experimental Botany 54 392 (2003) 2403-2417
6. Bricaud A., Bosc E., and Antoine D. Algal biomass and sea surface temperature in the Mediterranean basin: Intercomparison of data from various satellite sensors, and implications for primary production estimates. Remote Sensing of Environment 81 (2002) 163-178
7. Brivio P.A., Giardino C., and Zilioli E. Determination of chlorophyll concentration changes in Lake Garda using an image-based radiative transfer code for Landsat TM images. International Journal of Remote Sensing 22 (2001) 487-502
8. 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 (2001) 156-172
9. Brown L., Chen J.M., Leblanc S.G., and Cihlar J. A shortwave infrared modification to the simple ratio for LAI retrieval in boreal forests: An image and model analysis. Remote Sensing of Environment 71 (2000) 16-25
10. Chavez P.S. An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment 24 (1988) 459-479
11. Chavez P.S. Image-based atmospheric corrections revisited and revised. Photogrammetric Engineering and Remote Sensing 62 (1996) 1025-1036
12. Chen J.M., Rich P.M., Gower S.T., Norman J.M., and Plummer S. Leaf area index of boreal forests: Theory, techniques and measurements. Journal of Geophysical Research. Atmospheres 102 (1997) 429-443
13. Chen X., Vierling L., Rowell E., and DeFelice T. Using lidar and effective LAI data to evaluate IKONOS and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest. Remote Sensing of Environment 91 (2004) 14-26
14. Cohen W.B., Maiersperger T.K., Zhiqiang Y., Gower S.T., Turner D.P., Ritts W.D., et al. Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: A quality assessment of 2000/2001 provisional MODIS products. Remote Sensing of Environment 88 (2003) 233-255
15. Colombo R., Bellingeri D., Fasolini D., and Marino C.M. Retrieval of leaf area index in different vegetation types using high resolution satellite data. Remote Sensing of Environment 86 (2003) 120-131
16. Coyea M.R., and Margolis H.A. The historical reconstruction of growth efficiency and its relationship to tree mortality in balsam fir ecosystems affected by spruce budworm. Canadian Journal of Forest Research 24 (1994) 2208-2221
17. Cutini A., Matteucci G., and Mugnozza G.S. Estimation of leaf area index with the Li-Cor LAI 2000 in deciduous forests. Forest Ecology and Management 105 (1998) 55-65
18. Davidson E.A., Savage K., Bolstad P., Clark D.A., Curtis P.S., Ellsworth D.S., et al. Belowground carbon allocation in forests estimated from litterfall and IRGA-based soil respiration measurements. Agricultural and Forest Meteorology 113 (2002) 39-54
19. Dufrêne E., and Breda N. Estimation of deciduous forest leaf area index using direct and indirect methods. Oecologia 104 (1995) 156-162
20. Eklundh L., Harrie L., and Kuusk A. Investigating relationships between Landsat ETM+ sensor data and leaf area index in a boreal conifer forest. Remote Sensing of Environment 78 (2001) 239-251
21. Fournier R.A., Daniel M., Walter J.-M.N., and Soudani K. Measurement of forest structure. In: Wulder M., and Franklin S. (Eds). Methods and applications for remote sensing for forests: Concepts and case studies (2003), Kluwer Academic Publishers, Dordrecht 77-113
22. Fournier R.A., Rich P.M., and Landry R. Hierarchical characterization of canopy architecture for boreal forest. Journal of Geophysical Research 102 (1997) 445-454
23. Franklin S.E., Wulder M.A., and Gerylo G.R. Texture analysis of IKONOS panchromatic data for Douglas-fir forest age class separability in British Columbia. International Journal of Remote Sensing 22 (2001) 2627-2632
24. Gamon J.A., Field C.B., Goulden M., Griffin K., Hartley A., Joel G., et al. Relationships between NDVI, canopy structure, and photosynthetic activity in three Californian vegetation types. Ecological Applications 5 (1995) 28-41
25. Gond V., de Pury D.G.G., Veroustraete F., and Ceulemans R. Seasonal variation of leaf-area index, leaf chlorophyll and water content scaled up to fAPAR to estimate the carbon balance of a temperate multi-layer, multi-species forest. Tree Physiology 19 (1999) 673-679
26. Goward S.N., Davis P.E., Fleming D., Miller L., and Townshend J.R. Empirical comparison of Landsat 7 and IKONOS multispectral measurements for selected Earth Observation System (EOS) validation sites. Remote Sensing of Environment 88 (2003) 80-99
27. Granier A., Ceshia E., Damesin C., Dufrêne E., Epron D., Gross P., et al. The carbon balance of a young Beech forest. Functional Ecology 14 (2000) 312-325
28. Hadjimitsis D.G., Clayton C.R., and Retalis A. On the darkest pixel atmospheric correction algorithm: A revised procedure applied over satellite remotely sensed images intended for environmental applications. In: Manfred E., Hermann J., and Ulrich M. (Eds). Remote sensing for environmental monitoring, GIS applications, and geology. III Proceedings of SPIE vol. 5239 (2004) 464-471
29. Hansen M.C., DeFries R.S., Townshend J.R.G., Marufud L., and Sohlberg R. Development of a MODIS tree cover validation data set for Western Province, Zambia. Remote Sensing of Environment 83 (2002) 320-335
30. Hill J., and Aifadopoulou D. Comparative analysis of Landsat-5 TM and SPOT HRV-1 data for use in multiple sensor approaches. Remote Sensing of Environment 34 (1990) 55-70
31. Holst T., Hauser S., Kircgäßner A., Matzarakis A., Mayer H., and Schindler D. Measuring and modeling plant area index in beech stands. International Journal of Biometeorology 48 (2004) 192-201
32. Huete A.R. A soil adjusted vegetation index (SAVI). Remote Sensing of Environment 25 (1988) 295-309
33. Huete A.R., Justice C., and Liu H. Development of vegetation and soil indices for MODIS-EOS. Remote Sensing of Environment 49 (1994) 224-234
34. Jacquemoud S., and Baret B. PROSPECT: A model of leaf optical properties spectra. Remote Sensing of Environment 34 (1990) 75-91
35. Jarvis P.G., and Leverenz J.W. Productivity of temperate deciduous and evergreen forest. In: Lango O.L., Nobel P.S., Osmond V.B., and Ziegler H. (Eds). Ecosystem processes: Mineral cycling, productivity and man's influence (1983), Springer, Berlin 233-280
36. Jordan C.F. Derivation of leaf area index from quality of light on the forest floor. Ecology 50 (1969) 663-666
37. Kalácska M., Sanchez-Azofeifa G.A., Rivard B., Calvo-Alvarado J.C., Journet A.R.P., Arroyo-Mora J.P., et al. Leaf area index measurements in a tropical moist forest: A case study from Costa Rica. Remote Sensing of Environment 91 (2004) 134-152
38. Kaufman Y.J. The atmospheric effect on remote sensing and its corrections. In: Asrar G. (Ed). Theory and applications of optical remote sensing (1989), Wiley, New York 336-428
39. Kaufman Y.J., and Tanré D. Atmospherically Resistant Vegetation Index (ARVI) for EOS-MODIS. IEEE Transactions on Geoscience and Remote Sensing 30 (1992) 261-270
40. Kodani E., Awaya Y., Tanaka K., and Matsumara N. Seasonal patterns of canopy structure, biochemistry and spectral reflectance in a broad-leaved deciduous Fagus crenata canopy. Forest Ecology and Management 167 (2002) 233-249
41. Landsat-7 Science Data User's Handbook. (2004). NASA/Goddard Space Flight Center, Greenbelt, MD. http://ltpwww.gsfc.nasa.gov/IAS/handbook/handbook_htmls/chapter11/chapter11.html
42. Leblanc S.G., and Chen J.M. A practical scheme for correcting multiple scattering effects on optical measurements of leaf area index. Agricultural and Forest Meteorology 110 (2001) 125-139
43. Le Dantec V., Dufrêne E., and Saugier B. Interannual and spatial variation in maximum leaf area index of temperate deciduous stands. Forest Ecology and Management 134 (2000) 78-81
44. le Maire G., Davi H., Soudani K., François C., Le Dantec V., and Dufrêne E. Modeling annual production and carbon fluxes of a large managed temperate forest using forest inventories, satellite data and field measurements. Tree Physiology 25 (2005) 859-872
45. Liang S. Narrowband to broadband conversions of land surface albedo: I. Algorithms. Remote Sensing of Environment 76 (2001) 213-238
46. Liang S., Fang H., Chen M., Shuey C.J., Walthall C., Daughtry C., et al. Validating MODIS land surface reflectance and albedo products: Methods and preliminary results. Remote Sensing of Environment 83 (2002) 149-162
47. LI-COR. (1992). LAI-2000 Plant Canopy Analyser. Operating manual. Li-Cor.
48. Linder S. Potential and actual production in Australian forest stands. In: Landsberg J.J., and Parson W. (Eds). Research for forest management (1985), CSIRO, Melbourne 11-35
49. Machado J.-L., and Reich P.B. Evaluation of several measures of canopy openness as predictors of photosynthetic photon flux density in deeply shaded conifer-dominated forest understory. Canadian Journal of Forest Research 29 (1999) 1438-1444
50. Maguire D.A., Brissette J.C., and Gu L. Crown architecture and growth efficiency of red spruce in uneven-aged, mixed species stands in Maine. Canadian Journal of Forest Research 28 (1998) 1233-1240
51. Miura T., Huete A.R., Yoshioka H., and Holben B.N. An error and sensitivity analysis of atmospheric resistant vegetation indices derived from dark target-based atmospheric correction. Remote Sensing of Environment 78 (2001) 284-298
52. Moorthy, I., Miller, J. R., Noland, T. L., Nielsen, U., & Zarco-Tejada, P.J. (2003). Needle chlorophyll content estimation of boreal conifers using hyperspectral remote sensing. International Geoscience and Remote Sensing Symposium, IGARSS'03, ISBN 0-7803-7929-2-0-7803-7930-6, Toulouse (France), 21-25/7/2004.
53. Myneni R.B., Maggion S., Iaquinta J., Privette J.L., Gobron N., Pinty B., et al. Optical remote sensing of vegetation: Modelling, caveats and algorithms. Remote Sensing of Environment 51 (1995) 169-188
54. Myneni R.B., and Williams D.L. On the relationship between FAPAR and NDVI. Remote Sensing of Environment 49 (1994) 200-211
55. Nilson T. A theoretical analysis of the frequency of gaps in plant stands. Agricultural and Forest Meteorology 8 (1971) 25-38
56. Nilson T. Inversion of gap frequency data in forest stands. Agricultural and Forest Meteorology 8 (1999) 25-38
57. Olthof I., and King D.J. Development of a forest health index using multispectral airborne digital camera imagery. Canadian Journal of Remote Sensing 26 (2000) 166-176
58. Plummer S.E. Perspectives on combining ecological process models and remotely sensed data. Ecological Modelling 129 (2000) 169-186
59. Reichstein M., Rey A., Freibauer A., Tenhunen J., Valentini R., Banza J., et al. Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices. Global Biogeochemical Cycles 17 (2003) 1104
60. Roberts D.A., Ustin S.L., Ogunjemiyo S., Greenberg J., Dobrowski S.Z., Chen J., et al. Spectral and structural measures of Northwest forest vegetation at leaf to landscape scales. Ecosystems 7 (2004) 545-562
61. Rouse J.W., and Haas R.H. Monitoring vegetation systems in the great plain with ERTS. Third ERTS Symposium vol. 1 (1973), NASA, Washington, DC 309-317
62. Song C., Woodcock C.E., Seto K.C., Lenney P., and Macomber S.A. Classification and change detection using Landsat TM data. When and how to correct atmospheric effects?. Remote Sensing of Environment 75 (2001) 230-244
63. Soudani K., Trautmann J., and Walter J.M. Comparison of optical methods for estimating canopy openness and leaf area index in broad-leaved forests. Comptes Rendus de l'Académie des Sciences (France) 324 (2001) 381-392
64. Soudani K., Trautmann J., and Walter J.-M.N. Leaf area index and canopy stratification in Scots pine (Pinus sylvestris L.) stands. International Journal of Remote Sensing 18 (2003) 3605-3618
65. Spanner M.A., Pierce L.L., Peterson D.L., and Running S.W. Remote sensing of temperate coniferous forest leaf area index: The influence of canopy closure, understory vegetation and background reflectance. International Journal of Remote Sensing 11 (1990) 95-111
66. Stenberg P., Rautiainen M., Manninen T., Voipio P., and Smolander H. Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands. Silva Fennica 38 1 (2004) 3-14
67. Steven M.D., Malthus T.J., Baret F., Xu H., and Chopping M.J. Intercalibration of vegetation indices from different sensor systems. Remote Sensing of Environment 88 4 (2003) 412-422
68. Tcherkez, G. (personal communication). Laboratoire d'Ecologie Systématique et Evolution, Université Paris Sud Orsay (Guillaume.tcherkez@ese.u-psud.fr). Author of-Flowers: Evolution of the floral architecture of angiosperms. Enfield, NH : Science Publishers. 182 pp.
69. Thenkabail P.S. Inter-sensor relationships between IKONOS and Landsat-7 ETM+ NDVI data in three ecoregions of Africa. International Journal of Remote Sensing 25 (2004) 389-408
70. Thenkabail P.S., Enclona E.A., Ashton M.S., Legg C., and Jean De Dieu M. Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests. Remote Sensing of Environment 90 (2004) 23-43
71. Thenkabail P.S., Hall J., Lin T., Ashton M.S., Harris D., and Enclona E.A. Detecting floristic structure and pattern across topographic and moisture gradients in a mixed species Central African forest using IKONOS and Landsat-7 ETM+ images. International Journal of Applied Earth Observation and Geoinformation 4 (2003) 255-270
72. Teillet P.M., and Fedosejevs G. On the dark target approach to atmospheric correction of remotely sensed data. Canadian Journal of Remote Sensing 21 (1995) 374-387
73. Teillet P.M., Staenz K., and Williams D.J. Effects of spectral spatial and radiometric characteristics of remote sensing vegetation indices of forested regions. Remote Sensing of Environment 61 (1997) 139-149
74. Turner D.P., Ritts W.D., Cohen W.B., Gower S.T., Zhao M., Running S.W., et al. Scaling gross primary production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation. Remote Sensing of Environment 88 (2003) 256-270
75. Vargas L.A., Andersen M.N., Jensen C.R., and Jørgensen U. Estimation of leaf area index, light interception and biomass accumulation of Miscanthus sinensis 'Goliath' from radiation measurements. Biomass and Bioenergy 22 (2002) 1-14
76. Vose J.M., and Allen H.L. Leaf area, stemwood growth and nutrition relationships in loblolly pine. Forest Science 34 (1988) 546-563
77. Vose J.M., Dougherty P.M., Long J.N., Smith F.W., Gholz H.L., and Curran P.J. Factors influencing the amount and distribution of leaf area of pine stands. Ecological Bulletins 43 (1994) 102-114
78. Verhoef W. Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model. Remote Sensing of Environment 16 (1984) 125-141
79. Wang Y., Woodcock C.E., Buermann W., Stenberg P., Voipio P., Smolander H., et al. Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland. Remote Sensing of Environment 91 (2004) 114-127
80. Welles J.M., and Norman J.M. Instrument for indirect measurement of canopy architecture. Agronomy Journal 83 (1991) 818-825
81. White J.D., Running S.W., Nemani R., Keane R.E., and Ryan K.C. Measurement and remote sensing of LAI in rocky mountain Montana ecosystems. Canadian Journal of Forest Research 27 (1997) 1714-1727
82. Williams D.L. A comparison of spectral reflectance properties at the needle, branch and canopy level for selected conifer species. Remote Sensing of Environment 35 (1991) 79-93
83. van Dijk A., and Bruijnzeel L.A. Modelling rainfall interception by vegetation of variable density using an adapted analytical model: Part 1. Model description. Journal of Hydrology 247 (2001) 230-238
84. Zarco-Tejada P.J., Miller J.R., Harro J., Hu B., Noland T.L., Goel N., et al. Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies. Remote Sensing of Environment 89 (2004) 189-199