Quantifying the influences of spectral resolution on uncertainty in leaf trait estimates through a Bayesian approach to RTM inversion

Remote Sensing of Environment

Volumn 183, Issue , 2016, Pages 226-238

  Shiklomanov, Alexey N ^a   Dietze, Michael C ^a   Viskari, Toni ^b,c   Townsend, Philip A ^d   Serbin, Shawn P ^b,c  

^a BOSTON UNIVERSITY   (United States)

^b BROOKHAVEN NATIONAL LABORATORY   (United States)

^c STONY BROOK UNIVERSITY   (United States)

^d UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Bayesian statistics; Hyperspectral data; Leaf optical properties; PROSPECT; Radiative transfer modeling; Spectral inversion

Indexed keywords

BAYESIAN NETWORKS; BIODIVERSITY; CLIMATE CHANGE; INFRARED DEVICES; OPTICAL PROPERTIES; PROBABILITY DISTRIBUTIONS; RADIATIVE TRANSFER; REFLECTION; REMOTE SENSING; SPECTRAL RESOLUTION; UNCERTAINTY ANALYSIS; VEGETATION;

BAYESIAN STATISTICS; HYPERSPECTRAL DATA; LEAF OPTICAL PROPERTY; PROSPECT; RADIATIVE TRANSFER MODEL; SPECTRAL INVERSION;

PARAMETER ESTIMATION;

ALGORITHM; BAYESIAN ANALYSIS; CANOPY REFLECTANCE; DATA INVERSION; DATABASE; LEAF MORPHOLOGY; MULTISPECTRAL IMAGE; OPTICAL PROPERTY; RADIATIVE TRANSFER; REMOTE SENSING; SPECTRAL RESOLUTION; UNCERTAINTY ANALYSIS; VEGETATION DYNAMICS;

CONIFEROPHYTA;

EID: 84973351920     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2016.05.023     Document Type: Article

References (84)

1. Allen W.A., Gausman H.W., Richardson A.J., Thomas J.R. Interaction of isotropic light with a compact plant leaf. Journal of the Optical Society of America 1969, 59(10):11-14.
2. Asner G.P., Martin R.E., Anderson C.B., Knapp D.E. Quantifying forest canopy traits: Imaging spectroscopy versus field survey. Remote Sensing of Environment 2015, 158:15-27. (http://doi.org/10.1016/j.rse.2014.11.011).
3. Atzberger C., Richter K. Spatially constrained inversion of radiative transfer models for improved LAI mapping from future sentinel-2 imagery. Remote Sensing of Environment 2012, 120:208-218. (http://doi.org/10.1016/j.rse.2011.10.035).
4. Banskota, A., Wynne, R. H., Serbin, S. P., Kayastha, N., Thomas, V. A, & Townsend, P. A. (2013). Utility of the wavelet transform for LAI estimation using hyperspectral data. Photogrammetric Engineering and Remote Sensing, 79(7), 7907.
5. Banskota A., Serbin S.P., Wynne R.H., Thomas V.A., Falkowski M.J., Kayastha N., Townsend P.A. An LUT-based inversion of DART model to estimate forest LAI from hyperspectral data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2015, 1-14.
6. Blackburn G.A. Hyperspectral remote sensing of plant pigments. Journal of Experimental Botany 2007, 58(4):855-867. 10.1093/jxb/erl123.
7. Blackburn G.A., Ferwerda J.G. Retrieval of chlorophyll concentration from leaf reflectance spectra using wavelet analysis. Remote Sensing of Environment 2008, 112(4):1614-1632. 10.1016/j.rse.2007.08.005.
8. Cheng T., Rivard B., Sánchez-Azofeifa G.A., Feng J., Calvo-Polanco M. Continuous wavelet analysis for the detection of green attack damage due to mountain pine beetle infestation. Remote Sensing of Environment 2010, 114(4):899-910. 10.1016/j.rse.2009.12.005.
9. Cheng T., Rivard B., Sánchez-Azofeifa A.G., Féret J.B., Jacquemoud S., Ustin S.L. Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis. ISPRS Journal of Photogrammetry and Remote Sensing 2014, 87:28-38. 10.1016/j.isprsjprs.2013.10.009.
10. Combal B., Baret F., Weiss M., Trubuil A., Macé D., Pragnère A., Wang L. Retrieval of canopy biophysical variables from bidirectional reflectance using prior information to solve the ill-posed inverse problem. Remote Sensing of Environment 2003, 84(1):1-15. 10.1016/S0034-4257(02)00035-4.
11. Couture J.J., Serbin S.P., Townsend P.A. Spectroscopic sensitivity of real-time, rapidly induced phytochemical change in response to damage. New Phytologist 2013, 198(1):311-319. 10.1111/nph.12159.
12. Cressie N., Calder C.A., Clark J.S., Ver Hoef J.M., Wikle C.K. Accounting for uncertainty in ecological analysis: The strengths and limitations of hierarchical statistical modeling. Ecological Applications 2009, 19(3):553-570. 10.1890/07-0744.1.
13. Croft H., Chen J.M., Zhang Y., Simic A. Modelling leaf chlorophyll content in broadleaf and needle leaf canopies from ground, CASI, Landsat TM 5 and MERIS reflectance data. Remote Sensing of Environment 2013, 133:128-140. 10.1016/j.rse.2013.02.006.
14. Croft H., Chen J.M., Zhang Y. The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures. Ecological Complexity 2014, 17(1):119-130. 10.1016/j.ecocom.2013.11.005.
15. Dawson T.P., Curran P.J., Plummer S.E. LIBERTY - Modeling the effects of leaf biochemical concentration on reflectance spectra. Remote Sensing of Environment 1998, 65(1):50-60. 10.1016/S0034-4257(98)00007-8.
16. Deel L.N., McNeil B.E., Curtis P.G., Serbin S.P., Singh A., Eshleman K.N., Townsend P.a. Relationship of a Landsat cumulative disturbance index to canopy nitrogen and forest structure. Remote Sensing of Environment 2012, 118:40-49. 10.1016/j.rse.2011.10.026.
17. Di Vittorio A.V. Enhancing a leaf radiative transfer model to estimate concentrations and in vivo specific absorption coefficients of total carotenoids and chlorophylls a and b from single-needle reflectance and transmittance. Remote Sensing of Environment 2009, 113(9):1948-1966. 10.1016/j.rse.2009.05.002.
18. Di Vittorio A.V. Pigment-based identification of ozone-damaged pine needles as a basis for spectral segregation of needle conditions. Journal of Environmental Quality 2009, 38(3):855-867. 10.2134/jeq2008.0260.
19. Di Vittorio A.V., Biging G.S. Spectral identification of ozone-damaged pine needles. International Journal of Remote Sensing 2009, 30(12):3041-3073. 10.1080/01431160802558725.
20. Dietze M.C., Moorcroft P.R. Tree mortality in the eastern and Central United States: Patterns and drivers. Global Change Biology 2011, 17(11):3312-3326. 10.1111/j.1365-2486.2011.02477.x.
21. Dietze M.C., Lebauer D.S., Kooper R. On improving the communication between models and data. Plant, Cell and Environment 2013, 36(9):1575-1585. 10.1111/pce.12043.
22. Fassnacht F.E., Stenzel S., Gitelson A.A. Non-destructive estimation of foliar carotenoid content of tree species using merged vegetation indices. Journal of Plant Physiology 2015, 176:210-217. 10.1016/j.jplph.2014.11.003.
23. Feret J.B., François C., Asner G.P., Gitelson A.A., Martin R.E., Bidel L.P.R., Jacquemoud S. PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment 2008, 112(6):3030-3043. 10.1016/j.rse.2008.02.012.
24. Féret J.-B., François C., Gitelson A., Asner G.P., Barry K.M., Panigada C., Jacquemoud S. Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling. Remote Sensing of Environment 2011, 115(10):2742-2750. 10.1016/j.rse.2011.06.016.
25. Ferreira M.P., Grondona A.E.B., Rolim S.B.A., Shimabukuro Y.E. Analyzing the spectral variability of tropical tree species using hyperspectral feature selection and leaf optical modeling. Journal of Applied Remote Sensing 2013, 7(1):073502. 10.1117/1.JRS.7.073502.
26. Fourty T., Baret F., Jacquemoud S., Schmuck G., Verdebout J. Leaf optical properties with explicit description of its biochemical composition: Direct and inverse problems. Remote Sensing of Environment 1996, 56(2):104-117. 10.1016/0034-4257(95)00234-0.
27. Friedl M.A., McIver D.K., Hodges J.C.F., Zhang X., Muchoney D., Strahler A.H., Schaaf C. Global land cover mapping from MODIS: Algorithms and early results. Remote Sensing of Environment 2002, 83:287-302. 10.1016/S0034-4257(02)00078-0.
28. Ganapol B.D., Johnson L.F., Hammer P.D., Hlavka C.A., Peterson D.L. LEAFMOD: A new within-leaf radiative transfer model. Remote Sensing of Environment 1998, 63(2):182-193. 10.1016/S0034-4257(97)00134-X.
29. Gelman A., Rubin D.B. Inference from iterative simulation using multiple sequences. Statistical Science 1992, 7:457-511.
30. Grant L. Diffuse and specular characteristics of leaf reflectance. Remote Sensing of Environment 1987, 22:309-322. 10.1016/0034-4257(87)90064-2.
31. Haario H., Saksman E., Tamminen J. An adaptive metropolis algorithm. Bernoulli 2001, 7(2):223-242. 10.2307/3318737.
32. Haboudane D., Miller J.R., Tremblay N., Zarco-Tejada P.J., Dextraze L. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment 2002, 81(2-3):416-426. 10.1016/S0034-4257(02)00018-4.
33. Hansen M.C., Stehman S.V., Potapov P.V. Quantification of global gross forest cover loss. Proceedings of the National Academy of Sciences of the United States of America 2010, 107(19):8650-8655. 10.1073/pnas.0912668107.
34. Houborg R., Fisher J.B., Skidmore A.K. Advances in remote sensing of vegetation function and traits. International Journal of Applied Earth Observation and Geoinformation 2015, 10.1016/j.jag.2015.06.001.
35. Huete A., Didan K., Miura T., Rodriguez E.P., Gao X., Ferreira L.G. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment 2002, 83(1-2):195-213. 10.1016/S0034-4257(02)00096-2.
36. Hunt E.R.J., Wang L., Qu J.J., Hao X. Remote sensing of fuel moisture content from canopy water indices and normalized dry matter index. Journal of Applied Remote Sensing 2012, 6. 10.1117/1.JRS.6.061705.
37. Jacquemoud S., Baret F. PROSPECT: A model of leaf optical properties spectra. Remote Sensing of Environment 1990, 34(2):75-91. 10.1016/0034-4257(90)90100-Z.
38. Jacquemoud S., Baret F., Andrieu B., Danson F.M., Jaggard K. Extraction of vegetation biophysical parameters by inversion of the PROSPECT + SAIL models on sugar beet canopy reflectance data. Application to TM and AVIRIS sensors. Remote Sensing of Environment 1995, 52(3):163-172. 10.1016/0034-4257(95)00018-V.
39. Jacquemoud S., Verhoef W., Baret F., Bacour C., Zarco-Tejada P.J., Asner G.P., Ustin S.L. PROSPECT + SAIL models: A review of use for vegetation characterization. Remote Sensing of Environment 2009, 113(Suppl. 1):S56-S66. 10.1016/j.rse.2008.01.026.
40. Knyazikhin Y., Martonchik J.V., Diner D.J., Myneni R.B., Verstraete M., Pinty B., Gobron N. Estimation of vegetation canopy leaf area index and fraction from atmosphere-corrected MISR data. Journal of Geophysical Research 1998, 103:239-256.
41. Knyazikhin Y., Schull M.A., Stenberg P., Mõttus M., Rautiainen M., Yang Y., Marshak A., Carmona P.L., Kaufmann R.K., Lewis P., et al. Hyperspectral remote sensing of foliar nitrogen content. Proceedings of the National Academy of Sciences of the United States of America 2013, 110(3):E185-E192. 10.1073/pnas.1210196109.
42. Kobayashi H., Baldocchi D.D., Ryu Y., Chen Q., Ma S., Osuna J.L., Ustin S.L. Modeling energy and carbon fluxes in a heterogeneous oak woodland: A three-dimensional approach. Agricultural and Forest Meteorology 2012, 152:83-100.
43. Kuusk A. A two-layer canopy reflectance model. Journal of Quantitative Spectroscopy and Radiative Transfer 2001, 71(1):1-9. 10.1016/S0022-4073(01)00007-3.
44. Laurent V.C.E., Schaepman M.E., Verhoef W., Weyermann J., Chávez R.O. Bayesian object-based estimation of LAI and chlorophyll from a simulated sentinel-2 top-of-atmosphere radiance image. Remote Sensing of Environment 2014, 140:318-329. 10.1016/j.rse.2013.09.005.
45. Lauvernet C., Baret F., Hascoët L., Buis S., Le Dimet F.X. Multitemporal-patch ensemble inversion of coupled surface-atmosphere radiative transfer models for land surface characterization. Remote Sensing of Environment 2008, 112(3):851-861. 10.1016/j.rse.2007.06.027.
46. Le Maire G., François C., Dufrêne E. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment 2004, 89(1):1-28. 10.1016/j.rse.2003.09.004.
47. LeBauer D.S., Wang D., Richter K.T., Davidson C.S., Dietze M.C. Facilitating feedbacks between field measurements and ecosystem models. Ecological Monographs 2013, 83(2):133-154.
48. Lepine L.C., Ollinger S.V., Ouimette A.P., Martin M.E. Examining spectral reflectance features related to foliar nitrogen in forests: Implications for broad-scale nitrogen mapping. Remote Sensing of Environment 2016, 173:174-186. 10.1016/j.rse.2015.11.028.
49. Leprieur C., Verstraete M.M., Pinty B. Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data. Remote Sensing Reviews 1994, 10(4):265-284. 10.1080/02757259409532250.
50. Li P., Wang Q. Retrieval of leaf biochemical parameters using PROSPECT inversion: A new approach for alleviating ill-posed problems. IEEE Transactions on Geoscience and Remote Sensing 2011, 49(7):2499-2506. 10.1109/TGRS.2011.2109390.
51. Li P.H., Wang Q. Retrieval of chlorophyll for assimilating branches of a typical desert plant through inversed radiative transfer models. International Journal of Remote Sensing 2013, 34(7):2402-2416. 10.1080/01431161.2012.744859.
52. Liu J., Pattey E., Jégo G. Assessment of vegetation indices for regional crop green LAI estimation from Landsat images over multiple growing seasons. Remote Sensing of Environment 2012, 123:347-358. 10.1016/j.rse.2012.04.002.
53. Loveland T.R., Reed B.C., Brown J.F., Ohlen D.O., Zhu Z., Yang L., Merchant J.W. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. International Journal of Remote Sensing 2000, 21(6-7):1303-1330. 10.1080/014311600210191.
54. Malenovský Z., Albrechtová J., Lhotáková Z., Zurita-Milla R., Clevers J.G.P.W., Schaepman M.E., Cudlín P. Applicability of the PROSPECT model for Norway spruce needles. International Journal of Remote Sensing 2006, 27(24):5315-5340. 10.1080/01431160600762990.
55. Medvigy D., Wofsy S.C., Munger J.W., Hollinger D.Y., Moorcroft P.R. Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem demography model version 2. Journal of Geophysical Research: Biogeosciences 2009, 114(1):1-21. 10.1029/2008JG000812.
56. Moorthy I., Miller J.R., Noland T.L. Estimating chlorophyll concentration in conifer needles with hyperspectral data: An assessment at the needle and canopy level. Remote Sensing of Environment 2008, 112(6):2824-2838. 10.1016/j.rse.2008.01.013.
57. Mousivand A., Menenti M., Gorte B., Verhoef W. Multi-temporal, multi-sensor retrieval of terrestrial vegetation properties from spectral-directional radiometric data. Remote Sensing of Environment 2015, 158:311-330. 10.1016/j.rse.2014.10.030.
58. Myneni R.B., Hoffman S., Knyazikhin Y., Privette J.L., Glassy J., Tian Y., Wang Y., Song X., Zhang Y., Smith G.R., et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sensing of Environment 2002, 83(1-2):214-231. 10.1016/S0034-4257(02)00074-3.
59. Ni-Meister W., Yang W., Kiang N.Y. A clumped-foliage canopy radiative transfer model for a global dynamic terrestrial ecosystem model. I: Theory. Agricultural and Forest Meteorology 2010, 150(7-8):881-894. 10.1016/j.agrformet.2010.02.009.
60. Pinty B., Andredakis I., Clerici M., Kaminski T., Taberner M., Verstraete M.M., Widlowski J.-L. Exploiting the MODIS albedos with the two-stream inversion package (JRC-TIP): 1. Effective leaf area index, vegetation, and soil properties. Journal of Geophysical Research: Atmospheres 2011, 116:1-20. 10.1029/2010JD015372.
61. Plummer M., Best N., Cowles K., Vines K., Sarkar D., Almond R. Coda: Output analysis and diagnostics for MCMC https://cran.r-project.org/web/packages/coda/.
62. Poorter H., Niinemets U., Poorter L., Wright I.J., Villar R. Causes and consequences of variation in leaf mass per area (LMA): A meta-analysis. New Phytologist 2009, 182:565-588.
63. Quaife T., Lewis P., De Kauwe M., Williams M., Law B.E., Disney M., Bowyer P. Assimilating canopy reflectance data into an ecosystem model with an ensemble Kalman filter. Remote Sensing of Environment 2008, 112(4):1347-1364. 10.1016/j.rse.2007.05.020.
64. R Development Core Team R: A language and environment for statistical computing 2008, Austria, Vienna.
65. Serbin S.P. Spectroscopic determination of leaf nutritional, morphological, and metabolic traits. PhD dissertation 2012, UW-Madison, Madison, WI, USA.
66. Serbin S.P., Dillaway D.N., Kruger E.L., Townsend P.A. Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature. Journal of Experimental Botany 2012, 63(1):489-502. 10.1093/jxb/err294.
67. Serbin S.P., Singh A., McNeil B.E., Kingdon C.C., Townsend P.A. Spectroscopic determination of leaf morphological and biochemical traits for northern temperate and boreal tree species. Ecological Applications 2014, 24(September). 10.1890/13-2110.1.
68. Singh A., Serbin S.P., McNeil B.E., Kingdon C.C., Townsend P.A. Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties 2015, Ecological Applications.
69. Sullivan F.B., Ollinger S.V., Martin M.E., Ducey M.J., Lepine L.C., Wicklein H.F. Foliar nitrogen in relation to plant traits and reflectance properties of New Hampshire forests. Canadian Journal of Forest Research 2013, 43(1):18-27. 10.1139/cjfr-2012-0324.
70. Verhoef W. Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model. Remote Sensing of Environment 1984, 16(2):125-141. 10.1016/0034-4257(84)90057-9.
71. Wang Q., Li P. Canopy vertical heterogeneity plays a critical role in reflectance simulation. Agricultural and Forest Meteorology 2013, 169:111-121. 10.1016/j.agrformet.2012.10.004.
72. Wang Z., Skidmore A.K., Wang T., Darvishzadeh R., Hearne J. Applicability of the PROSPECT model for estimating protein and cellulose + lignin in fresh leaves. Remote Sensing of Environment 2015, 168:205-218. 10.1016/j.rse.2015.07.007.
73. Wessels K.J., van den Bergh F., Scholes R.J. Limits to detectability of land degradation by trend analysis of vegetation index data. Remote Sensing of Environment 2012, 125:10-22. 10.1016/j.rse.2012.06.022.
74. Wright I.J., Reich P.B., Westoby M., Ackerly D.D., Baruch Z., Bongers F., Cavender-Bares J., Chapin T., Cornelissen J.H.C., Diemer M., et al. The worldwide leaf economics spectrum. Nature 2004, 428(6985):821-827. 10.1038/nature02403.
75. Yao Y., Liu Q., Liu Q., Li X. LAI retrieval and uncertainty evaluations for typical row-planted crops at different growth stages. Remote Sensing of Environment 2008, 112(1):94-106. 10.1016/j.rse.2006.09.037.
76. Zarco-Tejada P.J., Miller J.R., Harron J., Hu B., Noland T.L., Goel N., Sampson P. Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies. Remote Sensing of Environment 2004, 89(2):189-199. 10.1016/j.rse.2002.06.002.
77. Zarco-Tejada P.J., Guillén-Climent M.L., Hernández-Clemente R., Catalina A., González M.R., Martín P. Estimating leaf carotenoid content in vineyards using high resolution hyperspectral imagery acquired from an unmanned aerial vehicle (UAV). Agricultural and Forest Meteorology 2013, 171-172:281-294. 10.1016/j.agrformet.2012.12.013.
78. Zhang Q., Xiao X., Braswell B., Linder E., Baret F., Moore B. Estimating light absorption by chlorophyll, leaf and canopy in a deciduous broadleaf forest using MODIS data and a radiative transfer model. Remote Sensing of Environment 2005, 99(3):357-371. 10.1016/j.rse.2005.09.009.
79. Zhang Q., Xiao X., Braswell B., Linder E., Ollinger S., Smith M.-L., Minocha R. Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data. Remote Sensing of Environment 2006, 105(3):189-203. 10.1016/j.rse.2006.06.013.
80. Zhang Y., Chen J.M., Miller J.R., Noland T.L. Retrieving chlorophyll content in conifer needles from hyperspectral measurements. Canadian Journal of Remote Sensing 2008, 34(3):296-310.
81. Zhang Q., Middleton E.M., Margolis H.A., Drolet G.G., Barr A.A., Black T.A. Can a satellite-derived estimate of the fraction of PAR absorbed by chlorophyll (FAPARchl) improve predictions of light-use efficiency and ecosystem photosynthesis for a boreal aspen forest?. Remote Sensing of Environment 2009, 113(4):880-888. 10.1016/j.rse.2009.01.002.
82. Zhang Q., Middleton E.M., Gao B.C., Cheng Y.B. Using EO-1 Hyperion to simulate HyspIRI products for a coniferous forest: The fraction of par absorbed by chlorophyll (fAPAR chl) and leaf water content (LWC). IEEE Transactions on Geoscience and Remote Sensing 2012, 50(5 PART 2):1844-1852. 10.1109/TGRS.2011.2169267.
83. Zhang Y., Qu Y., Wang J., Liang S., Liu Y. Estimating leaf area index from MODIS and surface meteorological data using a dynamic Bayesian network. Remote Sensing of Environment 2012, 127:30-43. 10.1016/j.rse.2012.08.015.
84. Zhao F., Guo Y., Huang Y., Reddy K.N., Lee M.A., Fletcher R.S., Thomson S.J. Early detection of crop injury from herbicide glyphosate by leaf biochemical parameter inversion. International Journal of Applied Earth Observation and Geoinformation 2014, 31(1):78-85. 10.1016/j.jag.2014.03.010.