Comparison of different regression models and validation techniques for the assessment of wheat leaf area index from hyperspectral data

International Journal of Remote Sensing

Volumn 36, Issue 18, 2015, Pages 4519-4534

  Siegmann, Bastian ^a   Jarmer, Thomas ^a  

^a UNIVERSITY OF OSNABRÜCK   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CROPS; DECISION TREES; LEAST SQUARES APPROXIMATIONS; PLANTS (BOTANY); REFLECTION; REMOTE SENSING;

LEAVE-ONE-OUT CROSS VALIDATIONS; PARTIAL LEAST SQUARES REGRESSIONS (PLSR); QUANTITATIVE ASSESSMENTS; REFLECTANCE SPECTRUM; SPATIAL TRANSFERABILITY; SPECTRAL INFORMATION; STATISTICAL REGRESSION MODEL; SUPPORT VECTOR REGRESSION (SVR);

REGRESSION ANALYSIS;

LEAF AREA INDEX; MODEL VALIDATION; REGRESSION ANALYSIS; REMOTE SENSING; SPECTRAL REFLECTANCE; WHEAT;

TRITICUM AESTIVUM;

EID: 84943406365     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2015.1084438     Document Type: Article

References (63)

1. J.Arenas-Garcia,, and G.Camps-Valls. 2008. “Efficient Kernel Orthonormalized PLS for Remote Sensing Applications.” IEEE Transactions on Geoscience and Remote Sensing 46 (10): 2872–2881. doi:10.1109/TGRS.2008.918765.
2. G.P.Asner,, J.M.Scurlock, and J.A.Hicke. 2003. “Global Synthesis of Leaf Area Index Observations: Implications for Ecological and Remote Sensing Studies.” Global Ecology and Biogeography 12 (3): 191–205. doi:10.1046/j.1466-822X.2003.00026.x.
3. C.Atzberger,, M.Guérif, F.Baret, and W.Werner. 2010. “Comparative Analysis of Three Chemometric Techniques for the Spectroradiometric Assessment of Canopy Chlorophyll Content in Winter Wheat.” Computers and Electronics in Agriculture 73 (2): 165–173. doi:10.1016/j.compag.2010.05.006.
4. M.A.Babyak, 2004. “What You See May Not Be What You Get: A Brief, Nontechnical Introduction to Overfitting in Regression-Type Models.” Psychosomatic Medicine 66 (3): 411–421.
5. C.Bacour,, S.Jacquemoud, M.Leroy, O.Hautecoeur, M.Weiss, L.Prévot, N.Bruguier, and H.Chauki. 2002. “Reliability of the Estimation of Vegetation Characteristics by Inversion of Three Canopy Reflectance Models on Airborne POLDER Data.” Agronomie 22 (6): 555–565. doi:10.1051/agro:2002039.
6. E.Boegh,, H.Soegaard., N.Broge, C.B.Hasager, N.O.Jensen, K.Schelde, and A.Thomsen. 2002. “Airborne Multispectral Data for Quantifying Leaf Area Index, Nitrogen Concentration, and Photosynthetic Efficiency in Agriculture.” Remote Sensing of Environment 81 (2–3): 179–193. doi:10.1016/S0034-4257(01)00342-X.
7. N.J.J.Bréda, 2003. “Ground-Based Measurements of Leaf Area Index: A Review of Methods, Instruments and Current Controversies.” Journal of Experimental Botany 54 (392): 2403–2417. doi:10.1093/jxb/erg263.
8. L.Breiman, 2001. “Random Forests.” Machine Learning 45 (1): 5–32. doi:10.1023/A:1010933404324.
9. N.H.Broge,, and J.V.Mortensen. 2002. “Deriving Green Crop Area Index and Canopy Chlorophyll Density of Winter Wheat from Spectral Reflectance Data.” Remote Sensing of Environment 81 (1): 45–57. doi:10.1016/S0034-4257(01)00332-7.
10. G.A.Carter, 1994. “Ratios of Leaf Reflectances in Narrow Wavebands as Indicators of Plant Stress.” International Journal of Remote Sensing 15 (3): 697–703. doi:10.1080/01431169408954109.
11. -C.-C.Chang,, and C.-J.Lin. 2011. “LIBSVM: A Library for Support Vector Machines.” ACM Transactions on Intelligent Systems and Technology 2 (3): 1–27. doi:10.1145/1961189.
12. J.M.Chen,, and T.A.Black. 1992. “Defining Leaf-Area Index for Non-Flat Leaves.” Plant, Cell & Environment 15 (4): 421–429. doi:10.1111/pce.1992.15.issue-4.
13. W.B.Cohen,, T.K.Maiersperger, S.T.Gower, and D.P.Turner. 2003. “An Improved Strategy for Regression of Biophysical Variables and Landsat ETM+ Data.” Remote Sensing of Environment 84 (4): 561–571. doi:10.1016/S0034-4257(02)00173-6.
14. S.Cox, 2002. “Information Technology: The Global Key to Precision Agriculture and Sustainability.” Computers and Electronics in Agriculture 36 (2–3): 93–111. doi:10.1016/S0168-1699(02)00095-9.
15. P.J.Curran, 1994. “Imaging Spectrometry.” Progress in Physical Geography 18 (2): 247–266. doi:10.1177/030913339401800204.
16. R.Darvishzadeh,, A.Skidmore, M.Schlerf, C.Atzberger, F.Corsi, and M.Cho. 2008. “Estimation of Leaf Area Index and Chlorophyll for a Mediterranean Grassland Using Hyperspectral Data.” In Proceedings of The International Archives of Photogrammetry, Remote Sensing and Spatial Information Science, Vol. XXXVII, Beijing, July3–11, Part B7, 471–478. Beijing: ISPRS.
17. C.S.T.Daughtry,, K.P.Gallo, S.N.Goward, S.D.Prince, and W.P.Kustas. 1992. “Spectral Estimates of Absorbed Radiation and Phytomass Production in Corn and Soybean Canopies.” Remote Sensing of Environment 39 (2): 141–152. doi:10.1016/0034-4257(92)90132-4.
18. B.Duchemin,, R.Hadriab, S.Errakib, G.Bouleta, P.Maisongrandea, A.Chehbouni, R.Escadafal, J.Ezzaharb, J.C.B.Hoedjesa, M.H.Kharroud, S.Khabbab, B.Mougenot, A.Oliosoe, J.-C.Rodriguez, and V.Simonneauxa. 2006. “Monitoring Wheat Phenology and Irrigation in Central Morocco: On the Use of Relationships between Evapotranspiration, Crops Coefficients, Leaf Area Index and Remotely-Sensed Vegetation Indices.” Agricultural Water Management 79 (1): 1–27. doi:10.1016/j.agwat.2005.02.013.
19. B.W.Dunn,, H.G.Beecher, G.D.Batten, and S.Ciavarella. 2002. “The Potential of Near-Infrared Reflectance Spectroscopy for Soil Analysis: A Case Study from the Riverine Plain of South-Eastern Australia.” Australian Journal of Experimental Agriculture 42 (5): 607–614. doi:10.1071/EA01172.
20. B.Efron, 1983. “Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation.” Journal of the American Statistical Association 78 (382): 316–331. doi:10.1080/01621459.1983.10477973.
21. H.L.Fang,, S.L.Liang, and A.Kuusk. 2003. “Retrieving Leaf Area Index Using a Genetic Algorithm with a Canopy Radiative Transfer Model.” Remote Sensing of Environment 85 (3): 257–270. doi:10.1016/S0034-4257(03)00005-1.
22. J.Gray,, and C.Song. 2012. “Mapping Leaf Area Index Using Spatial, Spectral and Temporal Information from Multiple Sensors.” Remote Sensing of Environment 119: 173–183. doi:10.1016/j.rse.2011.12.016.
23. D.Haboudane,, J.Millera, E.Patteyc, P.Zarco-Tejada, and I.Strachan. 2004. “Hyperspectral Vegetation Indices and Novel Algorithms for Predicting Green LAI of Crop Canopies: Modeling and Validation in the Context of Precision Agriculture.” Remote Sensing of Environment 90 (3): 337–352. doi:10.1016/j.rse.2003.12.013.
24. P.M.Hansen,, and J.K.Schjoerring. 2003. “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): 542–553. doi:10.1016/S0034-4257(03)00131-7.
25. D.M.Hawkins, 2004. “The Problem of Overfitting.” Journal of Chemical Information and Computer Sciences 44 (1): 1–12.
26. I.Herrmann,, A.Pimstein, A.Karnieli, Y.Cohen, V.Alchanatis, and D.J.Bonfil. 2011. “LAI Assessment of Wheat and Potato Crops by Venμs and Sentinel-2 Bands.” Remote Sensing of Environment 115 (8): 2141–2151. doi:10.1016/j.rse.2011.04.018.
27. S.Jacquemoud,, F.Baret, B.Andrieu, F.M.Danson, and K.Jaggard. 1995. “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 52 (3): 163–172. doi:10.1016/0034-4257(95)00018-V.
28. S.Jacquemoud,, S.L.Ustin, J.Verdebout, G.Schmuck, G.Andreoli, and B.Hosgood. 1996. “Estimating Leaf Biochemistry Using the PROSPECT Leaf Optical Properties Model.” Remote Sensing of Environment 56 (3): 194–202. doi:10.1016/0034-4257(95)00238-3.
29. T.Jarmer, 2013. “Spectroscopy and Hyperspectral Imagery for Monitoring Summer Barley.” International Journal of Remote Sensing 34 (17): 6067–6078. doi:10.1080/01431161.2013.793871.
30. A.Karatzoglou,, A.Smola, K.Hornik, and A.Zeileis. 2004. “Kernlab - an S4 Package for Kernel Methods in R.” Journal of Statistical Software 11 (9): 1–20.
31. Y.Karimi,, S.O.Prasher, A.Madani, and S.Kim. 2008. “Application of Support Vector Machine Technology for the Estimation of Crop Biophysical Parameters Using Aerial Hyperspectral Observations.” Canadian Biosystems Engineering 50: 713–720.
32. B.Koetz,, M.Kneubühler, S.Huber, J.Schopfer, and F.Baret. 2007. “LAI Estimation Based on Multi-Temporal CHRIS/PROBA Data and Radiative Transfer Modelling.” In Proceedings of the ENVISAT Symposium 2007, Montreux, April 23–27. Montreux: ESA.
33. W.Koppe,, F.Li, M.L.Gnyp, Y.Miao, L.Jia, X.Chen, F.Zhang, and G.Bareth. 2010. “Evaluating Multispectral and Hyperspectral Satellite Remote Sensing Data for Estimating Winter Wheat Growth Parameters at Regional Scale in the North China Plain.” Photogrammetry, Remote Sensing and Geoinformation Science 2010 (3): 171–182.
34. K.Lee,, W.B.Cohen, R.E.Kennedy, T.K.Maiersperger, and S.T.Gower. 2004. “Hyperspectral versus Multispectral Data for Estimating Leaf Area Index in Four Different Biomes.” Remote Sensing of Environment 91 (3–4): 508–520. doi:10.1016/j.rse.2004.04.010.
35. D.F.Malley,, P.D.Martin, and E.Ben-Dor. 2004. “Application in Analysis of Soils.” In Near-Infrared Spectroscopy in Agriculture, edited by C.A.Roberts, J.WorkmanJr, and J.B.Reeves, III, 729–783. Madison, WI: American Society of Agronomy-Crop Science Society of America-Soil Science Society of America.
36. B.-H.Mevik,, and R.Wehrens. 2007. “The Pls Package: Principal Component and Partial Least Squares Regression in R.” Journal of Statistical Software 18 (2): 1–24.
37. M.S.Moran,, S.J.Maas, and P.J.PinterJr. 1995. “Combining Remote Sensing and Modeling for Estimating Surface Evaporation and Biomass Production.” Remote Sensing Reviews 12 (3–4): 335–353. doi:10.1080/02757259509532290.
38. D.J.Mulla, 2013. “Twenty Five Years of Remote Sensing in Precision Agriculture: Key Advances and Remaining Knowledge Gaps.” Biosystems Engineering 114 (4): 358–371. doi:10.1016/j.biosystemseng.2012.08.009.
39. H.T.Nguyen,, and B.-W.Lee. 2006. “Assessment of Rice Leaf Growth and Nitrogen Status by Hyperspectral Canopy Reflectance and Partial Least Square Regression.” European Journal of Agronomy 24 (4): 349–356. doi:10.1016/j.eja.2006.01.001.
40. A.L.Nguy-Robertson,, Y.Peng, A.A.Gitelson, T.J.Arkebauer, A.Pimstein, I.Herrmann, A.Karnieli, D.C.Rundquist, and D.J.Bonfil. 2014. “Estimating Green LAI in Four Crops: Potential of Determining Optimal Spectral Bands for a Universal Algorithm.” Agricultural and Forest Meteorology 192-193: 140–148. doi:10.1016/j.agrformet.2014.03.004.
41. A.I.Oredein,, T.O.Olatayo, and A.C.Loyinmi. 2011. “On Validating Regression Models with Bootstraps and Data Splitting Techniques.” Global Journal of Science Frontier Research 11 (6): 1–6.
42. M.Otto, 2007. Chemometrics: Statistics and Computer Application in Analytical Chemistry. New York: Wiley-VCH.
43. S.L.Powell,, W.B.Cohen, S.P.Healey, R.E.Kennedy, G.G.Moisen, K.B.Pierce, and J.L.Ohmann. 2010. “Quantification of Live Aboveground Forest Biomass Dynamics with Landsat Time-Series and Field Inventory Data: A Comparison of Empirical Modeling Approaches.” Remote Sensing of Environment 114 (5): 1053–1068. doi:10.1016/j.rse.2009.12.018.
44. R.Pu, 2012. “Comparing Canonical Correlation Analysis with Partial Least Squares Regression in Estimating Forest Leaf Area Index with Multitemporal Landsat TM Imagery.” GIScience & Remote Sensing 49 (1): 92–116. doi:10.2747/1548-1603.49.1.92.
45. R Core Team. 2014. “R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.” Accessed July 2, 2015. http://www.R-project.org/
46. S.Rännar,, P.Geladi, F.Lidgren, and S.Wold. 1994. “A Pls Kernel Algorithm for Data Sets with Many Variables and Fewer Objects. Part 1: Theory and Algorithm.” Journal of Chemometrics 8 (2): 111–124. doi:10.1002/cem.1180080204.
47. J.K.Schueller, 1992. “A Review and Integrating Analysis of Spatially-Variable Control of Crop Production.” Fertilizer Research 33 (1): 1–34. doi:10.1007/BF01058007.
48. B.Siegmann,, T.Jarmer, T.Selige, H.Lilienthal, N.Richter, and B.Höfle. 2013. “Comparison of Narrow Band Vegetation Indices and Empirical Models from Hyperspectral Remote Sensing Data for the Assessment of Wheat Nitrogen Concentration.” In Proceedings of the 8th EARSeL Workshop on Imaging Spectroscopy, Nantes, April 8–10. Nantes: EARSeL.
49. R.D.Snee, 1977. “Validation of Regression Models: Methods and Examples.” Technometrics 19 (4): 415–428. doi:10.1080/00401706.1977.10489581.
50. E.W.Steyerberg,, F.E.Harrell Jr, G.J.J.M.Borsboom, M.J.C.Eijkemans, Y.Vergouwe, and J.D.F.Habbema. 2001. “Internal Validation of Predictive Models: Efficiency of Some Procedures for Logistic Regression Analysis.” Journal of Clinical Epidemiology 54 (8): 774–781. doi:10.1016/S0895-4356(01)00341-9.
51. P.S.Thenkabail,, R.B.Smith, and E.De-Pauw. 2000. “Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics.” Remote Sensing of Environment 71 (2): 158–182. doi:10.1016/S0034-4257(99)00067-X.
52. D.Tuia,, J.Verrelst, L.Alonso, F.Perez-Cruz, and G.Camps-Valls. 2011. “Multioutput Support Vector Regression for Remote Sensing Biophysical Parameter Estimation.” IEEE Geoscience and Remote Sensing Letters 8 (4): 804–808. doi:10.1109/LGRS.2011.2109934.
53. M.K.Van Ittersum,, P.A.Leffelaar, H.Van Keulen, M.J.Kropff, L.Bastiaans, and J.Goudriaan. 2003. “On Approaches and Applications of the Wageningen Crop Models.” European Journal of Agronomy 18 (3–4): 201–234. doi:10.1016/S1161-0301(02)00106-5.
54. A.Viña,, A.A.Gitelson, A.L.Nguy-Robertson, and Y.Peng. 2011. “Comparison of Different Vegetation Indices for the Remote Assessment of Green Leaf Area Index of Crops.” Remote Sensing of Environment 115 (12): 3468–3478. doi:10.1016/j.rse.2011.08.010.
55. M.Vohland,, and T.Jarmer. 2008. “Estimating Structural and Biochemical Parameters for Grassland from Spectroradiometer Data by Radiative Transfer Modelling (PROSPECT + SAIL).” International Journal of Remote Sensing 29 (1): 191–209. doi:10.1080/01431160701268947.
56. F.Vuolo,, N.Neugebauer, S.F.Bolognesi, C.Atzberger, and G.D’Urso. 2013. “Estimation of Leaf Area Index Using DEIMOS-1 Data: Application and Transferability of a Semi-Empirical Relationship between Two Agricultural Areas.” Remote Sensing 5 (3): 1274–1291. doi:10.3390/rs5031274.
57. F.-M.Wang,, J.-F.Huang, and Z.-H.Lou. 2011. “A Comparison of Three Methods for Estimating Leaf Area Index of Paddy Rice from Optimal Hyperspectral Bands.” PrecisionAgriculture 12 (3): 439–447. doi:10.1007/s11119-010-9185-2.
58. D.J.Watson, 1947. “Comparative Physiological Studies in the Growth of Field Crops. I. Variation in Net Assimilation Rate and Leaf Area between Species and Varieties, and within and between Years.” Annals of Botany 11 (41): 41–76.
59. M.Weiss,, F.Baret, R.B.Myneni, A.Pragnère, and Y.Knyazikhin. 2000. “Investigation of a Model Inversion Technique to Estimate Canopy Biophysical Variables from Spectral and Directional Data.” Agronomie 20 (1): 3–22. doi:10.1051/agro:2000105.
60. W.Wilhelm,, K.Ruwe, and M.R.Schlemmer. 2000. “Comparison of Three Leaf Area Index Meters in a Corn Canopy.” Crop Science 40 (4): 1179–1183. doi:10.2135/cropsci2000.4041179x.
61. P.Williams, 2011. “Implementation of Near-Infrared Technology.” In Near-Infrared Technology in the Agricultural and Food Industries, edited by P.Williams and K.Norris, 145–169. St. Paul: American Association of Cereal Chemists.
62. K.Yu,, M.L.Gnyp, L.Gao, Y.Miao, X.Chen, and G.Bareth. 2015. “Estimate Leaf Chlorophyll of Rice Using Reflectance Indices and Partial Least Squares.” Journal for Photogrammetry, Remote Sensing and Geoinformation Science 2015 (1): 45–54.
63. G.Zheng,, and L.M.Moskal. 2009. “Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors.” Sensors 9 (4): 2719–2745. doi:10.3390/s90402719.