Integration of in situ measured soil status and remotely sensed hyperspectral data to improve plant production system monitoring: Concept, perspectives and limitations

Remote Sensing of Environment

Volumn 128, Issue , 2013, Pages 197-211

  Tits, Laurent ^a   Somers, Ben ^b   Stuckens, Jan ^c   Farifteh, Jamshid ^a   Coppin, Pol ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b FLEMISH INSTITUTE FOR TECHNOLOGICAL RESEARCH VITO   (Belgium)

^c Researchpark Haasrode   (Belgium)

Author keywords

Agriculture; Chlorophyll; Citrus; Leaf Area Index; Look up table; Radiative transfer; Soil moisture; Spectral Mixture Analysis; Vegetation index; Water

Indexed keywords

CITRUS; LEAF AREA INDEX; LOOK-UP-TABLE; SPECTRAL MIXTURE ANALYSIS; VEGETATION INDEX;

AGRICULTURE; CHLOROPHYLL; CROPS; DIGITAL STORAGE; FORESTRY; MIXTURES; RADIATIVE TRANSFER; REMOTE SENSING; SOIL MOISTURE; VEGETATION; WATER;

GEOLOGIC MODELS;

ALGORITHM; BIOPHYSICS; CHLOROPHYLL; CROP PRODUCTION; DATA SET; FRUIT; IN SITU MEASUREMENT; INTEGRATED APPROACH; LEAF AREA INDEX; MONITORING; PIXEL; RADIATIVE TRANSFER; SOIL ANALYSIS; SOIL MOISTURE; VEGETATION INDEX;

CITRUS;

EID: 84868575093     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2012.10.006     Document Type: Article

References (62)

1. Adams J.B., Smith M.O., Gillespie A.R. Imaging spectroscopy: Interpretation based on spectral mixture analysis. Remote geochemical analysis: Elemental and mineralogical composition 7 1993, 145-166. Cambridge University Press, New York. C.M. Pieters, P. Englert (Eds.).
2. Asner G.P., Heidebrecht K.B. Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: Comparing multispectral and hyperspectral observations. International Journal of Remote Sensing 1992, 23:3939-3958.
3. Baret F., Guyot G. Potentials and limits of vegetation indexes for LAI and APAR assessment. Remote Sensing of Environment 1991, 35:161-173.
4. Bateson C.A., Asner G.P., Wessman C.A. Endmember bundles: A new approach to incorporating endmember variability into spectral mixture analysis. IEEE Transactions on Geoscience and Remote Sensing 2000, 38:1083-1094.
5. Biliouris D., Van der Zande D., Verstraeten W.W., Stuckens J., Muys B., Dutré Ph, et al. RPV model parameters based on hyperspectral bidirectional reflectance measurements of Fagus sylvatica L. leaves. Remote Sensing 2009, 1:92-106.
6. Borel C., Gerstl S. Nonlinear spectral mixing models for vegetative and soil surfaces. Remote Sensing of Environment 1994, 47:403-416.
7. Brown L. A survey of image registration techniques. Computing Surveys 1992, 24:325-376.
8. Clevers J.G.P.W., van der Heijden G.W.A.M., Verzakov S., Schaepman M.E. Estimating grassland biomass using SVM band shaving of hyperspectral data. Photogrammetric Engineering and Remote Sensing 2007, 73:1141-1148.
9. Delalieux S., Somers B., Hereijgers S., Verstraeten W.W., Keulemans W., Coppin P. A near-infrared narrow-waveband ratio to determine Leaf Area Index in orchards. Remote Sensing of Environment 2008, 112:3762-3772.
10. Dinguirard M., Slater P.N. Calibration of space-multispectral imaging sensors: A review. Remote Sensing of Environment 1999, 68:194-205.
11. Dorigo W., Zurita-Milla R., de Wit A., Brazile J., Singh R., Schaepman M. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling. International Journal of Applied Earth Observation and Geoinformation 2007, 9:165-193.
12. Dzikiti S., Verreynne J.S., Stuckens J., Strever A., Verstraeten W.W., Swennen R., et al. Determining the water status of Satsuma mandarin trees [Citrus unshiu Marcovitch] using spectral indices and by combining hyperspectral and physiological data. Agricultural And Forest Meteorology 2010, 150:369-379.
13. Eitel J., Gessler P., Smith A., Robberecht R. Suitability of existing and novel spectral indices to remotely detect water stress in Populus spp. Forest Ecology and Management 2006, 229:170-182.
14. Environmental Mapping and Analysis Program Available online:, Accessed last on June 20th 2012. http://www.enmap.org.
15. FAO FAO, world reference base for soil resources. World soil resource report no 84 1998, Food and Agriculture Organization of the United Nations, Rome.
16. Fitzgerald G.J., Pinter P.J., Hunsaker D.J., Clarke T.R. Multiple shadow fractions in spectral mixture analysis of a cotton canopy. Remote Sensing of Environment 2005, 97:526-539.
17. Gao B. NDWI - A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment 1996, 58:257-266.
18. Gitelson A., Merzlyak M. Signature analysis of leaf reflectance spectra: Algorithm development for remote sensing of chlorophyll. Journal of Plant Physiology 1996, 148:494-500.
19. Hansen P., Schjoerring J. 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 2003, 86:542-553.
20. Huete A. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment 1988, 25:295-309.
21. Itten K.I., Meyer P. Geometric and radiometric correction of TM data of mountainous forested areas. IEEE Transactions on Geoscience and Remote Sensing 1993, 31:764-770.
22. Jacquemoud S., Baret F. Prospect-A model of leaf optical properties spectra. Remote Sensing of Environment 1990, 34:75-91.
23. Jacquemoud S., Verhoef W., Baret F., Bacour C., Zarco-Tejada P.J., Asner G.P., et al. PROSPECT + SAIL models: A review of use for vegetation characterization. Remote Sensing of Environment 2009, 113:S56-S66.
24. Jordan C. Derivation of Leaf-Area Index from quality of light on forest floor. Ecology 1969, 50:663-666.
25. Kerr J., Ostrovsky M. From space to species: Ecological applications for remote sensing. Trends In Ecology & Evolution 2003, 18:299-305.
26. Liang S., Fang H., Chen M. Atmospheric correction of Landsat ETM+ land surface imagery - Part I: Methods. IEEE Transactions on Geoscience and Remote Sensing 2001, 39:2490-2498.
27. Liu W., Baret F., Gu X., Tong Q., Zheng L., Zhang B. Relating soil surface moisture to reflectance. Remote Sensing of Environment 2002, 81:238-246.
28. Lobell D., Asner G. Moisture effects on soil reflectance. Soil Science Society of America Journal 2002, 66:722-727.
29. Lobell D., Asner G. Cropland distributions from temporal unmixing of MODIS data. Remote Sensing of Environment 2004, 93:412-422.
30. MDA corporation (2012) [available online: sm.mdacorporation.com]. Accessed last on June 20th 2012.
31. Müller E., Décamps H. Modeling soil moisture-reflectance. Remote Sensing of Environment 2001, 76:173-180.
32. Okin G.S., Roberts D.A., Murray B., Curkendall D.W., Okin W.J. Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments. Remote Sensing of Environment 2001, 77:212-225.
33. Ouillon S., Douillet P., Andrefouet S. Coupling satellite data with in situ measurements and numerical modeling to study fine suspended-sediment transport: A study for the lagoon of New Caledonia. Coral Reefs 2004, 23:109-122.
34. Peddle D.R., Smith A.M. Spectral mixture analysis of agricultural crops: Endmember validation and biophysical estimation in potato plots. International Journal of Remote Sensing 2005, 26:4959-4979.
35. Pharr M., Humphreys G. Physically based rendering: From theory to implementation 2004, 1056. Morgan Kaufmann Publishers, San Francisco, USA.
36. Pinter P., Hatfield J., Schepers J., Barnes E., Moran M., Daughtry C., et al. Remote sensing for crop management. Photogrammetric Engineering and Remote Sensing 2003, 69:647-664.
37. Qi J., Chehbouni A., Huete A., Kerr Y., Sorooshian S. A modified soil adjusted vegetation index. Remote Sensing of Environment 1994, 48:119-126.
38. Quarmby N.A., Townshend J.R., Settle J.J., White K.H., Milnes M., Hindle T.L., et al. Linear mixture modelling applied to AVHRR data for crop area estimation. International Journal of Remote Sensing 1992, 13:415-425.
39. Reynolds R., Rayner N., Smith T., Stokes D., Wang W. An improved in situ and satellite SST analysis for climate. Journal of Climate 2002, 15:1609-1625.
40. Richter R., Bachmann M., Dorigo W., Muller A. Influence of the adjacency effect on reflectance measurements. IEEE Transactions on Geoscience and Remote Sensing Letter 2006, 3:565-569.
41. Roberts D.A., Gardner M., Church R., Ustin S., Scheer G., Green R.O. Mapping Chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models. Remote Sensing of Environment 1998, 65:267-279.
42. Roberts D.A., Smith M.O., Adams J.B. Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data. Remote Sensing of Environment 1993, 44:255-269.
43. Rondeaux G., Steven M., Baret F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment 1996, 55:95-107.
44. Somers, B. (2009d). Hyperspectral Unmixing for Plant Production Monitoring. PhD Disertation, Arenberg Doctoral School, Katholieke Universiteit Leuven, pp. 208.
45. Somers, B., Asner, G. P. in press. Invasive species mapping in Hawaiian rainforests using multi-temporal Hyperion spaceborne imaging spectroscopy. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, (DOI ). doi:10.1109/JSTARS.2012.2203796.
46. Somers B., Asner G.P., Tits L., Coppin P. Endmember variability in spectral mixture analysis: A review. Remote Sensing of Environment 2011, 115:1603-1616.
47. Somers B., Cools K., Delalieux S., Stuckens J., der Zande D.V., Verstraeten W., et al. Nonlinear hyperspectral mixture analysis for tree cover estimates in orchards. Remote Sensing of Environment 2009, 113:1183-1193.
48. Somers B., Delalieux S., Stuckens J., Verstraeten W.W., Coppin P. A weighted linear spectral mixture analysis approach to address endmember variability in agricultural production systems. International Journal of Remote Sensing 2009, 30:139-147.
49. Somers B., Delalieux S., Verstraeten W.W., Coppin P. A conceptual framework for the simultaneous extraction of subpixel spatial extent and spectral characteristics of crops. Photogrammetric Engineering and Remote Sensing 2009, 75:57-68.
50. Somers B., Gysels V., Verstraeten W.W., Delalieux S., Coppin P. Modelling moisture-induced soil reflectance changes in cultivated sandy soils: A case study in citrus orchards. European Journal of Soil Science 2010, 61:1091-1105.
51. Stuckens, J., Somers, B., Verstraeten, W., & Coppin, P. (2008). Simulation of physiology induced hyperspectral changes in a virtual citrus orchard as detected by medium and high resolution remote sensing platforms, Geophysical Research Abstracts. EGU General Assembly. Vienna, Austria, April 13-18, 2008 European Geosciences Union.
52. Stuckens J., Somers B., Albrigo G.L., Dzikiti S., Verstraeten W.W., Swennen R., et al. Off-nadir viewing for reducing spectral mixture issues in citrus orchards. Photogrammetric Engineering and Remote Sensing 2010, 76:1261-1274.
53. Stuckens J., Somers B., Delalieux S., Verstraeten W.W., Coppin P. The impact of common assumptions on canopy radiative transfer simulations: A case study in citrus orchards. Journal of Qualitative Spectroscopy & Radiative Transfer 2009, 110:1-21.
54. Tits L., Somers B., Coppin P. The potential and limitations of a clustering approach for the improved efficiency of Multiple Endmember Spectral Mixture Analysis in plant production system monitoring. IEEE Transactions on Geoscience and Remote Sensing 2012, 50:2273-2286.
55. Tucker C. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment 1979, 8:127-150.
56. Verbeiren S., Eerens H., Piccard I., Bauwens I., Van Orshoven J. Sub-pixel classification of SPOT-VEGETATION time series for the assessment of regional crop areas in Belgium. International Journal of Applied Earth Observation and Geoinformation 2008, 10:486-497.
57. Verhoef W., Bach H. Coupled soil-leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data. Remote Sensing of Environment 2007, 109:166-182.
58. Weber J., Penn J. Creation and rendering of realistic trees. Proceedings of the 22nd annual conference on computer graphics and interactive techniques 1995, 119-128.
59. Widlowski J.-L., Robustelli M., Disney M., Gastellu-Etchegorry J.-P., Lavergne T., Lewis P., et al. The RAMI on-line model checker (ROMC): A web-based benchmarking facility for canopy reflectance models. Remote Sensing of Environment 2008, 112:1144-1150.
60. Wu C. Normalized spectral mixture analysis for monitoring urban composition using ETM+ imagery. Remote Sensing of Environment 2004, 93:480-492.
61. Zaks D.P.M., Kucharik C.J. Data and monitoring needs for a more ecological agriculture. Environmental Research Letters 2011, 6:1-10.
62. Zarco-Tejada P., Miller J., Morales A., Berjon A., Aguera J. Hyperspectral indices and model simulation for chlorophyll estimations in open canopy tree crops. Remote Sensing of Environment 2004, 90:463-476.