UAS-based soil carbon mapping using VIS-NIR (480-1000 nm) multi-spectral imaging: Potential and limitations

Geoderma

Volumn 275, Issue , 2016, Pages 55-66

  Aldana Jague, Emilien ^a   Heckrath, Goswin ^b   Macdonald, Andy ^c   van Wesemael, Bas ^a   Van Oost, Kristof ^a,d  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^b DANISH INSTITUTE OF AGRICULTURAL SCIENCES   (Denmark)

^c ROTHAMSTED RESEARCH   (United Kingdom)

^d FNRS   (Belgium)

Author keywords

Mapping; Multi spectral; Remote sensing; Soil organic carbon; Soil spectra; UAS

Indexed keywords

AGRICULTURE; CALIBRATION; MAPPING; ORGANIC CARBON; PHOTOMAPPING; REMOTE SENSING; SPECTROSCOPY; UNMANNED AERIAL VEHICLES (UAV);

HIGH SPATIAL RESOLUTION; MULTI-SPECTRAL; MULTI-SPECTRAL CAMERAS; MULTI-SPECTRAL IMAGERY; PRECISION AGRICULTURE; SOIL ORGANIC CARBON; SUPPORT VECTOR MACHINE REGRESSIONS; UNMANNED AERIAL SYSTEMS;

SOILS;

AERIAL PHOTOGRAPHY; AGRICULTURAL SOIL; MAPPING; MULTISPECTRAL IMAGE; ORGANIC CARBON; REMOTE SENSING; SAMPLING; SOIL CARBON; SOIL MANAGEMENT; SOIL PROPERTY; SPATIAL RESOLUTION; SUPPORT VECTOR MACHINE; UNMANNED VEHICLE;

HORDEUM;

EID: 84966293673     PISSN: 00167061     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.geoderma.2016.04.012     Document Type: Article

References (70)

1. Aldana Jague E., Sommer M., Saby N.P.A., Cornelis J.-T., Van Wesemael B., Van Oost K. High resolution characterization of the soil organic carbon depth profile in a soil landscape affected by erosion. Soil Tillage Res. 2016, 156:185-193.
2. Amundson R. The carbon budget in soil. Annu. Rev. Earth Planet. Sci. 2001, 29:535-562.
3. Anderson K., Kuhn N.J. Variations in soil structure and reflectance during a controlled crusting experiment. Int. J. Remote Sens. 2008, 29:3457-3475.
4. Anon Rothamsted Long-term Experiments - Guide to the Classical and Other Long-term Experiments, Datasets and Sample Archive 2006, 31-34. http://www.rothamsted.ac.uk.
5. Arrouays D., Jolivet C., Boulonne L., Bodineau G., Saby N., Grolleau E. A new initiative in France: a multi-institutional soil quality monitoring network. C. R. Acad Agric. Fr. 2002, 88(5):93-105.
6. Baluja J., Diago M.P., Balda P., Zorer R., Meggio F., Morales F., Tardaguila J. Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). Irrig. Sci. 2012, 30:511-522.
7. Bartholomeus H., Kooistra L., Stevens A., van Leeuwen M., van Wesemael B., Ben-Dor E., Tychon B. Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy. Int. J. Appl. Earth Obs. Geoinf. 2011, 13:81-88.
8. Bellon-Maurel V., Fernandez-Ahumada E., Palagos B., Roger J.M., McBratney A. Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy. TrAC Trends Anal. Chem. 2010, 29:1073-1081.
9. Brus D.J., Heuvelink G.B.M. Optimization of sample patterns for universal kriging of environmental variables. Geoderma 2007, 138:86-95.
10. Bull I.D., van Bergen P.F.R., Poulton P., Evershed R.P. Organic geochemical studies of soils from the Rothamsted Classical Experiments-II, soils from the Hoosfield Spring Barley Experiment treated with different quantities of manure. Org. Geochem. 1998, 28:11-26.
11. Cambou A., Cardinael R., Kouakoua E., Villeneuve M., Durand C., Barthès B.G. Prediction of soil organic carbon stock using visible and near infrared reflectance spectroscopy (VNIRS) in the field. Geoderma 2016, 261:151-159.
12. Chang C.C., Lin C.J. LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2011, 2:27:1-27:27. (Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm).
13. Chen F., Kissel D.E., West L.T., Adkins W. Field-scale mapping of surface soil organic carbon using remotely sensed imagery. Soil Sci. Soc. Am. J. 2000, 64:746.
14. Croft H., Anderson K., Kuhn N.J. Characterizing soil surface roughness using a combined structural and spectral approach. Eur. J. Soil Sci. 2009, 60:431-442.
15. Croft H., Kuhn N.J., Anderson K. On the use of remote sensing techniques for monitoring spatio-temporal soil organic carbon dynamics in agricultural systems. Catena 2012, 94:64-74.
16. Dlugoß V., Fiener P., Schneider K. Layer-specific analysis and spatial prediction of soil organic carbon using terrain attributes and erosion modeling. Soil Sci. Soc. Am. J. 2010, 74:922.
17. Doetterl S., Stevens A., Van Oost K., van Wesemael B. Soil organic carbon assessment at high vertical resolution using closed-tube sampling and vis-NIR spectroscopy. Soil Sci. Soc. Am. J. 2013, 77:1430.
18. Glendining M.J., Poulton P.R., Powlson D.S., Jenkinson D.S. Fate of 15 N-labelled fertilizer applied to spring barley on soils of contrasting nutrient status. Plant Soil 1997, 195:83-98.
19. Goidts E., Van Wesemael B., Van Oost K. Driving forces of soil organic carbon evolution at the landscape and regional scale using data from a stratified soil monitoring. Glob. Chang. Biol. 2009, 15:2981-3000.
20. Gomez C., Viscarra Rossel R.A., McBratney A.B. Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: an Australian case study. Geoderma 2008, 146:403-411.
21. Govers G., Merckx R., Van Oost K., van Wesemael B. Managing Soil Organic Carbon for Global Benefits: A STAP Technical Report 2013, 70.
22. Grandjean G. Integrated system of data collection technologies for mapping soil properties. Digisoil Report 2011, (58 pp.).
23. Johnston A.E., Poulton P.R., Coleman K. Chapter 1 soil organic matter: its importance in sustainable agriculture and carbon dioxide fluxes. Adv. Agron. 2009, 101:1-57.
24. Kalbermatten M., Van De Ville D., Turberg P., Tuia D., Joost S. Multiscale analysis of geomorphological and geological features in high resolution digital elevation models using the wavelet transform. Geomorphology 2012, 138:352-363.
25. Karhu K., Auffret M.D., Dungait J.A.J., Hopkins D.W., Prosser J.I., Singh B.K., Subke J.-A., Wookey P.A., Ågren G.I., Sebastià M.-T., Gouriveau F., Bergkvist G., Meir P., Nottingham A.T., Salinas N., Hartley I.P. Temperature sensitivity of soil respiration rates enhanced by microbial community response. Nature 2014, 513:81-84.
26. Kelcey J., Lucieer A. Sensor correction of a 6-band multispectral imaging sensor for UAV remote sensing. Remote Sens. 2012, 4:1462-1493.
27. Kempen B., Brus D.J., Stoorvogel J.J. Three-dimensional mapping of soil organic matter content using soil type-specific depth functions. Geoderma 2011, 162:107-123.
28. Kennard R.W., Stone L.A. Computer aided design of experiments. Technometrics 1969, 11:137-148.
29. Knadel M., Thomsen A., Schelde K., Greve M.H. Soil organic carbon and particle sizes mapping using vis-NIR, EC and temperature mobile sensor platform. Comput. Electron. Agric. 2015, 114:134-144.
30. Kühnel A., Bogner C., Huwe B. In situ prediction of soil chemical properties with visible and near infrared spectroscopy in an african savannah. GlobalSoilMap: Basis of the Global Spatial Soil Information System - Proceedings of the 1st GlobalSoilMap Conference 2014, 409-413.
31. Lacoste M., Minasny B., McBratney A., Michot D., Viaud V., Walter C. High resolution 3D mapping of soil organic carbon in a heterogeneous agricultural landscape. Geoderma 2014, 213:296-311.
32. Lal R. Soil carbon sequestration impacts on global climate change and food security. Science 2004, 304:1623-1627.
33. Malone B.P., McBratney A.B., Minasny B., Laslett G.M. Mapping continuous depth functions of soil carbon storage and available water capacity. Geoderma 2009, 154:138-152.
34. McBratney A., Stockmann U., Angers D., Minasny B., Field D. Challenges for soil organic carbon research. Soil Carbon 2014, 3-16. Springer, New York. A.E. Hartemink, K. McSweeney (Eds.).
35. Meersmans J., van Wesemael B., De Ridder F., Van Molle M. Modelling the three-dimensional spatial distribution of soil organic carbon (SOC) at the regional scale (Flanders, Belgium). Geoderma 2009, 152:43-52.
36. Meyer D., Dimitriadou E., Hornik K., Weingessel A., Leisch F. e1071: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien. R package version 1 2015, 6-7. (http://CRAN.R-project.org/package=e1071).
37. Minasny B., McBratney A.B. A conditioned Latin hypercube method for sampling in the presence of ancillary information. Comput. Geosci. 2006, 32:1378-1388.
38. Morgan C.L.S., Waiser T.H., Brown D.J., Hallmark C.T. Simulated in situ characterization of soil organic and inorganic carbon with visible near-infrared diffuse reflectance spectroscopy. Geoderma 2009, 151:249-256.
39. Mouazen A.M., Maleki M.R., De Baerdemaeker J., Ramon H. On-line measurement of some selected soil properties using a VIS-NIR sensor. Soil Tillage Res. 2007, 93:13-27.
40. Nelson D.W., Sommers L.E. Total carbon, organic carbon, and organic matter. Part 3. SSSA Book Ser. 5. SSSA, Madison, WI 1996, 961-1010. R.W. Weaver (Ed.).
41. Nichol J., Lee C.M. Urban vegetation monitoring in Hong Kong using high resolution multispectral images. Int. J. Remote Sens. 2005, 26(5):903-918.
42. Nocita M., Stevens A., Noon C., van Wesemael B. Prediction of soil organic carbon for different levels of soil moisture using Vis-NIR spectroscopy. Geoderma 2013, 199:37-42.
43. Nocita M., Stevens A., van Wesemael B., Aitkenhead M., Bachmann M., Barthès B., Ben Dor E., Brown D.J., Clairotte M., Csorba A., Dardenne P., Demattê J.A.M., Genot V., Guerrero C., Knadel M., Montanarella L., Noon C., Ramirez-Lopez L., Robertson J., Sakai H., Soriano-Disla J.M., Shepherd K.D., Stenberg B., Towett E.K., Vargas R., Wetterlind J. Chapter four - soil spectroscopy: an alternative to wet chemistry for soil monitoring. Adv. Agron. 2015, 132:139-159.
44. O' Rourke S.M., Holden N.M. Optical sensing and chemometric analysis of soil organic carbon - a cost effective alternative to conventional laboratory methods?. Soil Use Manag. 2011, 27(2):143-155.
45. Post W.M., Kwon K.C. Soil carbon sequestration and land-use change: processes and potential. Glob. Chang. Biol. 2000, 6:317-327.
46. Powlson D.S., Bhogal A., Chambers B.J., Coleman K., Macdonald A.J., Goulding K.W.T., Whitmore A.P. The potential to increase soil carbon stocks through reduced tillage or organic material additions in England and Wales: a case study. Agric. Ecosyst. Environ. 2012, 146:23-33.
47. Primicerio J., Di Gennaro S.F., Fiorillo E., Genesio L., Lugato E., Matese A., Vaccari F.P. A flexible unmanned aerial vehicle for precision agriculture. Precis. Agric. 2012, 13:517-523.
48. R Core Team R: A Language and Environment for Statistical Computing 2015, R Foundation for Statistical Computing, Vienna, (Austria. URL http://www.R-project.org/).
49. R Development Core Team R: A language and environment for statistical computing 2014, R Foundation for Statistical Computing, (http://www.r-project.org).
50. Roberts C.A., Workman J., Reeves J.B., Malley D.F., Martin P.D., Ben-Dor E. Application in analysis of soils. Near-infrared Spectroscopy in Agriculture, American Society of Agronomy, Crop Science Society of America 2004, 44:729-784. Madison, USA. 10.2134/agronmonogr44.c26. C. Roberts, J. Workman, J. Reeves (Eds.).
51. Rothamsted Research Details of the Classical and Other Long-term Experiments, Datasets and Sample Archive, Harpenden 2006, (52 pp.).
52. Rumpel C., Kögel-Knabner I. Deep soil organic matter-a key but poorly understood component of terrestrial C cycle. Plant Soil 2011, 338:143-158.
53. Selige T., Böhner J., Schmidhalter U. High resolution topsoil mapping using hyperspectral image and field data in multivariate regression modeling procedures. Geoderma 2006, 136:235-244.
54. Sherrod L.A., Dunn G., Peterson G.A., Kolberg R.L. Inorganic carbon analysis by modified pressure-calcimeter method. Soil Sci. Soc. Am. J. 2002, 66:299-305.
55. Sørensen L.K., Dalsgaard S. Determination of clay and other soil properties by near infrared spectroscopy. Soil Sci. Soc. Am. J. 2005, 69:159.
56. Stevens A., van Wesemael B., Vandenschrick G., Touré S., Tychon B. Detection of carbon stock change in agricultural soils using spectroscopic techniques. Soil Sci. Soc. Am. J. 2006, 70:844.
57. Stevens A., van Wesemael B., Bartholomeus H., Rosillon D., Tychon B., Ben-Dor E. Laboratory, field and airborne spectroscopy for monitoring organic carbon content in agricultural soils. Geoderma 2008, 144:395-404.
58. Stevens A., Miralles I., van Wesemael B. Soil organic carbon predictions by airborne imaging spectroscopy: comparing cross-validation and validation. Soil Sci. Soc. Am. J. 2012.
59. Tate N.J., Brunsdon C., Charlton M., Fotheringham A.S., Jarvis C.H. Smoothing/filtering LiDAR digital surface models. Experiments with loess regression and discrete wavelets. J. Geogr. Syst. 2005, 7:273-290.
60. Turner D., Lucieer A., Wallace L. Direct georeferencing of ultrahigh-resolution UAV imagery. IEEE Trans. Geosci. Remote Sens. 2014, 52:2738-2745.
61. Vašát R., Heuvelink G.B.M., Borůvka L. Sampling design optimization for multivariate soil mapping. Geoderma 2010, 155:147-153.
62. Viscarra Rossel R.A.V., Behrens T. Using data mining to model and interpret soil diffuse reflectance spectra. Geoderma 2010, 158:46-54.
63. Viscarra Rossel R.A.V., Webster R. Predicting soil properties from the Australian soil visible-near infrared spectroscopic database. Eur. J. Soil Sci. 2012, 63:848-860.
64. Vohland M., Ludwig M., Thiele-Bruhn S., Ludwig B. Determination of soil properties with visible to near- and mid-infrared spectroscopy: effects of spectral variable selection. Geoderma 2014, 223-225:88-96.
65. Warren R.G., Johnston A.E. Hoosfield continuous Barley. Rothamsted Experimental Station Report for 1966 1967, 320-338.
66. Wenjun J., Zhou S., Jingyi H., Shuo L. In situ measurement of some soil properties in paddy soil using visible and near-infrared spectroscopy. PLoS One 2014, 9:e105708.
67. West T.O., Post W.M. Soil organic carbon sequestration rates by tillage and crop rotation. Soil Sci. Soc. Am. J. 2002.
68. Witcher B. Waveslim a R package, version 1.7.5 2015.
69. Zarco-Tejada P.J., Berni J.A.J., Suárez L., Sepulcre-Cantó G., Morales F., Miller J.R. Imaging chlorophyll fluorescence with an airborne narrow-band multispectral camera for vegetation stress detection. Remote Sens. Environ. 2009, 113:1262-1275.
70. Zhang C., Kovacs J.M. The application of small unmanned aerial systems for precision agriculture: a review. Precis. Agric. 2012, 13:693-712.