Retrieval of wheat leaf area index from AWiFS multispectral datausing canopy radiative transfer simulation

International Journal of Applied Earth Observation and Geoinformation

Volumn 32, Issue 1, 2014, Pages 173-185

  Nigam, Rahul ^a   Bhattacharya, Bimal K ^a   Vyas, Swapnil ^a   Oza, Markand P ^a  

^a INDIAN SPACE RESEARCH ORGANISATION   (India)

Author keywords

Canopy radiative transfer; Crop; LAI retrieval; Satellite

Indexed keywords

CANOPY; COMPUTER SIMULATION; CROP PLANT; EMPIRICAL ANALYSIS; LEAF AREA INDEX; MULTISPECTRAL IMAGE; RADIATIVE TRANSFER; REMOTE SENSING; WHEAT;

EID: 84904462848     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2014.04.003     Document Type: Article

References (63)

1. Allen, WA, Gausman, H.W., Richardson, A.J., Thomas, J.R., 1969. Interaction of isotropic light with a compact plant leaf. J. Opt. Soc. Am. 59,1376-1379.
2. Asner, G.P., 1998. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens. Environ. 64, 234-253.
3. Barker, D.M., Huang, W., Guo, Y.R., Bourgeois, A.J., Xiao, Q.N., 2004. A three dimensional variational data assimilation system for MM5: implementation and initial results. Mon. Weather Rev. 132, 897-914.
4. Baret, F., Guyot, G., 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environ. 35,161-173.
5. Baret, F., Hagolle, O., Geiger, B., Bicheron, P., Miras, B., Huc, M., Berthelot, B., Nono, F., Weiss, M., Samain, O., Roujean, J.L., Leroy, M., 2007. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm. Remote Sens. Environ. 110, 275-286.
6. Bhattacharya, B.K., Mallick, K., Nigam, R., Dakore, K., Shekh, A.M., 2011. Efficiency based wheat yield prediction in a semi-arid climate using surface energy budgeting with satellite observations. Agric. For. Meteorol. 151,1394-1408.
7. Bilagi, S.A., Jirali, D.I., Chetti, M.B., Hiremath, S.M., Patil, B.N., 2008. Biophysical, biochemical parameters and their association with yield in Dicocumm wheat genotype. KarnatakaJ. Agric. Sci. 21,176-180.
8. Bonan, G.B., 1991. Atmosphere-biosphere exchange of carbon dioxide in boreal forests. J. Geophys. Res. 96, 7301-7312.
9. Botha, E.J., Leblon, B., Zebarth, B., Watmough,J., 2007. Non-destructive estimation of potato leaf chlorophyll from canopy hyperspectral reflectance using the inverted PROSAIL model. Int.J. Appl. Earth Obs. Geoinf. 9,360-374.
10. Chaurasia, S., Bhattacharya, B.K., Dadhwal, V.K., Parihar, J.S., 2006. Field-scale Leaf Area Index estimation using IRS-1D LISS-III data. Int.J. Remote Sens. 27,637-644.
11. Chaurasia, S., Nigam, R., Bhattacharya, B.K., Sridhar, V.N., Mallick, K., Vyas, S.P., Patel, N.K., Mukherjee, J., Shekhar, C, Kumar, D., Singh, K.P.S., Bairagi, G.D., Purohit, N.L., Parihar, J.S., 2011. Development of regional wheat VI-LAI models using RESOURCESAT-1 AWiFS data. J. Earth Syst. Sci. 120, 1113-1125.
12. Chen, D., Huang, J., Jackson, T.J., 2005. Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands. Remote Sens. Environ. 98, 225-236.
13. Chen, B., Chen, J.M., Mo, G., Yuen, C, Margolis, H., Higuchi, K., Chan, D., 2007. Modeling and scaling coupled energy, water, and carbon fluxes based on remote sensing: an application to Canada's landmass. J. Hydrometeorol. 8,123-143.
14. Colombo, R., Bellingeri, D., Fasolini, D., Marino, CM., 2003. Retrieval of leaf area index in different vegetation types using high resolution satellite data. Remote Sens. Environ. 86,120-131.
15. Combal, B., Baret, F., Weiss, M., Trubuil, A., Macé, D., Pragnère, A., Myneni, R., Knyazikhin, Y., Wang, L, 2002. Retrieval of canopy biophysical variables from bidirectional reflectance using prior information to solve the ill-posed inverse problem. Remote Sens. Environ. 84,1-15.
16. Danson, F.M., Rowland, C.S., Baret, F., 2003. Training a neural network with a canopy reflectance model to estimate crop leaf area index. Int. J. Remote Sens. 24, 4891-4905.
17. Department of Agriculture and Cooperation, Ministry of Agriculture, Govt. of India, 2011. Annual report 2010-11.
18. Eva, H., Lambin, E.F., 1998. Burnt area mapping in central Africa using ASTER data. Int.J. Remote Sens. 19,3437-3497.
19. Fang, H., Liang, S., Kussk, A., 2003. Retrieving leaf area index using a genetic algorithm with a canopy radiative transfer model. Remote Sens. Environ. 85, 257-270.
20. Gao, B., 1996. NDWI: a Normalized Difference Water Index for remote sensing of vegetation liquid water from space. Remote Sens. Environ. 58, 257-266.
21. Garrigues, S., Allard, D., Baret, F., Weiss, M., 2006. Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data. Remote Sens. Environ. 105, 286-298.
22. Gautam, S., 2011. Dry matter partitioning, grain filling and grain yield in wheat genotypes. Int.J. Agric. Biol. 6,48-63.
23. Gitelson, A.A., Gritz, Y., Merzlyak, M.N., 2003. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. J. Plant Physiol. 160, 271-282.
24. Gitelson, A.A., Kaufman, Y.J., Merzlyak, M.N., 1996. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sens. Environ. 58, 289-298.
25. Gitelson, A.A., Vina, A., Ciganda, V., Rundquist, D.C., 2005. Remote estimation of canopy chlorophyll content in crops. Geophys. Res. Lett. 32, L08403, http://dx.doi.org/10.1029/2005GL022688.
26. Gobron, N., Pinty, B., Verstraete, M.M., 1997. Theoretical limits to the estimation of the leaf area index on the basis of visible and near-infrared remote sensing data. IEEE Trans. Geosci. Remote Sens. 35, 1438-1445.
27. Gonsamo, A., 2011. Normalized sensitivity measures for leaf area index estimation using three-band spectral vegetation indices. Int. J. Remote Sens. 32, 2069-2080.
28. González-Sanpedro, M.C., Toana, T.L., Moreno, J., Kergoat, L., Rubio, E., 2008. Seasonal variations of leaf area index of agricultural fields retrieved from Landsat data. Remote Sens. Environ. 112, 810-824.
29. Hameed, M., Mansoor, U., Aahraf, M., Rehman Rao, A., 2002. Variation in leaf anatomy in wheat germplasm from varying drought-hit habitats. Int. J. Agric. Biol. 4, 12-16.
30. Houborg, R., Anderson, M., Daughtry, C, 2009. Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at the field scale. Remote Sens. Environ. 113, 259-274.
31. Houborg, R., Boegh, E., 2008. Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data. Remote Sens. Environ. 112,186-202.
32. Houborg, R., Soegaard, H., Boegh, E., 2007. Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data. Remote Sens. Environ. 106,39-58.
33. Jackson, R.D., 1986. Remote sensing of biotic and abiotic plant stress. Annu. Rev. Phytopathol. 24, 265-287.
34. Jackson, R.D., Huete, A.R., 1991. Interpreting vegetation indices. Prev. Vet. Med. 11, 185-200.
35. Jacquemoud, S., Verhoef, W., Baret, F., Bacour, C, Zarco-Tejada, P.J., Asner, G.P., Francois, C, Ustin, S.L., 2009. PROSPECT + SAIL models: a review of use for vegetation characterization. Remote Sens. Environ. 113, S56-S66.
36. Jacquemoud, S., Bacour, C, Poilvé, H., Frangi,J.P., 2000. Comparison of four radiative transfer models to simulate plant canopies reflectance: direct and inverse mode. Remote Sens. Environ. 74,471-481.
37. Jacquemoud, S., Baret, F., 1990. PROSPECT: a model of leaf optical properties spectra. Remote Sens. Environ. 34, 75-91.
38. Jacquemoud, S., Baret, F., Andrieu, B., Danson, F.M., Jaggard, K., 1995. Extraction of vegetation biophysical parameters by inversion of the PROSPECT + SAIL model on sugar beet canopy reflectance data - application to TM and AVIRIS sensors. Remote Sens. Environ. 52,163-172.
39. Jacquemoud, S., Ustin, S.L., Verdebout,J., Schmuck, G., Andreoli, G., Hosgood, B., 1996. Estimating leaf biochemistry using the PROSPECT leaf optical properties model. Remote Sens. Environ. 56,194-202.
40. Jordan, C.F., 1969. Derivation of leaf area index from quality of light on the forest floor. Ecology 50, 663-666.
41. Koetz, B., Baret, F., Poilve, H., Hill, J., 2005. Use of coupled canopy structure dynamics and radiative transfer model to estimate biophysical canopy characteristics. Remote Sens. Environ. 95,115-124.
42. Leshno, M.,YaLin,V., Pinkus,A., Shocken, S., 1993. Multilayer feedforward networks with non polynomial activation function can approximate any function. Neural Netw. 6, 861-867.
43. Liu, J., Chen, J.M., Chihlar, J., Park, W.M., 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 62, 158-175.
44. Matsushita, B., Yang, W., Chen, J., Onda, Y., Qiu, G., 2007. Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to topographic effects: a case study in high-density Cypress forest. Sensors 7, 2636-2651.
45. Nayak, S.S., (M.S. thesis) 2005. Thermal Imagery and Spectral Reflectance Based System to Monitor Crop Condition. Texas Tech University.
46. Oza, M.P., Rajak, D.R., Bhagia, N., Dutta, S., Vyas, S.P., Patel, N.K., Parihar, J.S., 2006a. Multiple production forecasts of wheat in India using remote sensing and weather data. SPIE, http://dx.doi.org/10.1117/12.693918,6411 641102-1.
47. Oza, M.P., Rajak, D.R., Bhagia, N., Dutta, S., Vyas, S.P., Bhuyan, M.R., Jadhav, R.S., 2006b. National wheat production forecasting for 2005-06 using multi-date IRS AWiFS and meteorological data. Space Applications Centre (ISRO) Scientific Note, EOAM/SAC/FASAL-TD/SN/24/2006.
48. Pandya, M.R., Singh, R.P., Murali, K.R., Babu, P.N., Kirankumar, A.S., Dadwal, V.K., 2002. Bandpass solar exoatmospheric irradiance and Rayleigh optical thickness for Indian remote sensing satellite sensors onboard IRS-1A, 1B, 1C, 1D and P4. IEEE Trans. Geosci. Remote Sens. 40, 714-718.
49. Price, J.C., Bausch, W.C., 1995. Leaf Area Index estimation from visible and nearinfrared reflectance data. Remote Sens. Environ. 52,55-65.
50. Rahman, H., Dedieu, G., 1994. SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum. Int.J. Remote Sens. 15, 123-143.
51. Rajak, D.R., Bhuyan, M.R., Oza, M.P., Patel, N.K., Parihar, J.S., 2005. Wheat growth characterisation using multi-year RS data. In: ISRS National Symposium on Emergence of Geoinformatics For Development: Trends & Opportunities, BIT, Mesra, Ranchi, India.
52. Rouse, J.W., Has, R.H., Schell, J.A., Deering, D.W., Harlan, J.C., 1974. Monitoring the vernal advancement of retrodgradation of natural vegetation, NASA/GSFC, Type III, Final report, Greenbelt, MD., pp. 371.
53. Saxena, R.K., Srivastava, R., Verma, K.S., 1997. Spectral library of Indian soils. NATP mission mode programme code no. 27(2)/97/NATP/MM-III-2.
54. Schaepman-Strub, G., Schaepman, M.E., Painter, T.H., Dangel, S., Martonchik, J.V., 2006. Reflectance quantities in optical remote sensing - definitions and case studies. Remote Sens. Environ. 103, 27-42.
55. Seller, P.J., Dickinson, R.E., Randall, D.A., Betts, A.K., Hall, F.G., Berry, J.A., Collatz, G.J., Denning, A.S., Mooney, H.A., Nobre, C.A., Sato, N., Field, C.B., Henderson-Sellers, A., 1997. Modeling the exchanges of energy, water, carbon between continents and the atmosphere. Science 275,502-509.
56. Smith, A.M., Nadeau, C, Freemantle, J., When, H., Teillet, P.M., Kehler, I., Daub, N., Bourgeois, G., De Jong, R., 2005. Leaf area index from CHRIS satellite data and applications in plant yield estimation. In: 26th Canadian symposium on Remote Sensing, Wolfville, Nova Scotia.
57. Srinivas, P., Das, B.K., Saibaba, J., Krishnan, R., 2004. Application of Distance Based Vegetation index for agricultural crops discrimination. In: XXth ISPRS Congress. Commission 7, Istanbul, Turkey.
58. Tian, Y., Wang, Y., Zhang, Y., Knyazikhina, Y., Bogaert,J., Myneni, R.B., 2002. Radiative transfer based scaling of LAI/FPAR retrievals from reflectance data of different resolutions. Remote Sens. Environ. 84,143-159.
59. Verhoef, W., 1984. Light scattering by leaf layers with application to canopy reflectance modeling: the SAIL model. Remote Sens. Environ. 16, 125- 141.
60. Verhoef, W., 1985. Earth observation modeling based on layer scattering matrices. Remote Sens. Environ. 17,165-178.
61. Verhoef, W., Bach, H., 2003. Simulation of hyperspectral and directional radiance images using coupled biophysical and atmosphere radiative transfer model. Remote Sens. Environ. 87, 23-41.
62. Welles, J.M., Norman, J.M., 1991. Instrument for indirect measurement of canopy architecture. J. Agron. 83, 818-825.
63. Yi, Y., Yang, D., Huang, J., Chen, D., 2008. Evaluation of MODIS surface reflectance products for wheat leaf area index (LAI) retrieval. ISPRS J. Photo Remote Sens. 63, 661-677.