Comparing mobile and static assessment of biomass in heterogeneous grassland with a multi-sensor system

Journal of Sensors and Sensor Systems

Volumn 5, Issue 2, 2016, Pages 301-312

  Safari, Hanieh ^a   Fricke, Thomas ^a   Reddersen, Björn ^a   Möckel, Thomas ^a   Wachendorf, Michael ^a  

^a UNIVERSITY OF KASSEL   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURE; FORECASTING; MOBILE COMPUTING; PREDICTIVE ANALYTICS;

MOBILE APPLICATIONS; MOBILE SENSOR SYSTEMS; MULTI-SENSOR SYSTEMS; PREDICTION ACCURACY; PREDICTION MODEL; SENSOR COMBINATIONS; STATIC MEASUREMENTS; VEHICLE MOVEMENTS;

BIOMASS;

EID: 84982703214     PISSN: 21948771     EISSN: 2194878X     Source Type: Journal    
DOI: 10.5194/jsss-5-301-2016     Document Type: Article

References (44)

1. Adamchuk, V. I., Hummel, J. V., Morgan, M. T., and Upadhyaya, S. K. On-The-go soil sensors for precision agriculture, Comp. Elect. Agric., 44, 71-91, 2004
2. Biewer, S., Fricke, T., and Wachendorf, M. Determination of Dry Matter Yield from Legume-Grass Swards by Field Spectroscopy, Crop Sci., 49, 1927-1936, doi: 10.2135/cropsci2008.10.0608, 2009a.
3. Biewer, S., Fricke, T., and Wachendorf, M. Development of Canopy Reflectance Models to Predict Forage Quality of Legume-Grass Mixtures, Crop Sci., 49, 1917-1926, doi: 10.2135/cropsci2008.11.0653, 2009b
4. Blüthgen, N., Dormann, C. F., Prati, D., Klaus, V. H., Kleinebecker, T., Hölzel, N., Alt, F., Boch, S., Gockel, S., Hemp, A., Müller, J., Nieschulze, J., Renner, S. C., Schöning, I., Schumacher, U., Socher, S. A., Wells, K., Birkhofer, K., Buscot, F., Oelmann, Y., Rothenwöhrer, C., Scherber, C., Tscharntke, T., Weiner, C. N., Fischer, M., Kalko, E. K. V., Linsenmair, K. E., Schulze, E.-D., and Weisser, W. W. A quantitative index of land-use intensity in grasslands: Integrating mowing, grazing and fertilization, Basic Appl. Ecol., 13, 207-220, 2012
5. Castle, M. E. A simple disc instrument for estimating herbage yield, J. Br. Grassl. Soc., 31, 37-40, doi: 10.1111/j.1365-2494.1976.tb01113.x, 1976
6. Cozzolino, D., Porker, K., and Laws, M. An Overview on the Use of Infrared Sensors for in Field, Proximal and at Harvest Monitoring of Cereal Crops, Agriculture 2015, 5, 713-722, doi: 10.3390/agriculture5030713, 2015
7. Diaconis, P. and Efron, B. Computer-intensive methods in statistics, Sci. Am., 248, 96-108, 1983
8. Duan, M., Gao, Q., Wan, Y., Li, Y., Guo, Y., and Ganzhu, Z. Biomass estimation of alpine grasslands under different grazing intensities using spectral vegetation indices, Can. J. Remote Sens., 37, 413-421, doi: 10.5589/m11-050, 2014
9. Farooque, A. A., Chang, Y. K., Zaman, Q. U., Groulx, D., Schumann, A. W., and Esau, T. J. Performance evaluation of multiple ground based sensors mounted on a commercial wild blueberry harvester to sense plant height, fruit yield and topographic features in real-Time, Comput. Electron. Agr., 91, 135-144, doi: 10.1016/j.compag.2012.12.006, 2013
10. Fava, F., Colombo, R., Bocchi, S., Meroni, M., Sitzia, M., Fois, N., and Zucca, C. Identification of hyperspectral vegetation indices for Mediterranean pasture characterization, Int. J. Appl. Earth Obs., 11, 233-243, doi: 10.1016/j.jag.2009.02.003, 2009
11. Fricke, T. and Wachendorf, M. Combining ultrasonic sward height and spectral signatures to assess the biomass of legume-grass swards, Comput. Electron. Agr., 99, 236-247, doi: 10.1016/j.compag.2013.10.004, 2013
12. Fricke, T., Richter, F., and Wachendorf, M. Assessment of forage mass from grassland swards by height measurement using an ultrasonic sensor, Comput. Electron. Agr., 79, 142-152, doi: 10.1016/j.compag.2011.09.005, 2011
13. Goel, N. S. Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data, Remote Sens., 4, 1-212, doi: 10.1080/02757258809532105, 1988
14. Gottfried, T., Auerswald, K., and Ostler, U. Mobile correction for a spatial offset between sensor and position data in on-The-go sensor applications, Comput. Electron. Agr., 84, 76-84, 2012
15. Hakl, J., Hrevušová, Z., Hejcman, M., and Fuksa, P. The use of a rising plate meter to evaluate Lucerne (Medicago sativa L. height as an important agronomic trait enabling yield estimation, Grass Forage Sci., 67, 589-596, 2012
16. Himstedt, M., Fricke, T., and Wachendorf, M. Determining the contribution of legumes in legume-grass mixtures using digital image analysis, Crop Sci., 49, 1910-1916, doi: 10.2135/cropsci2008.11.0636, 2009
17. Inoue, Y., Penuelas, J., Miyata, A., and Mano, M. Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice, Remote Sens. Environ., 112, 156-172, doi: 10.1016/j.rse.2007.04.011, 2008
18. Isselstein, J., Jeangros, B., and Pavlu, V. Agronomic aspects of biodiversity targeted management of temperate grasslands in Europe-A review, Agr. Res., 3, 139-151, 2005
19. Kawamura, K., Betteridge, K., Sanches, I. D., Tuohy, Mike P., Costall, D., and Inoue, Y. Field radiometer with canopy pasture probe as a potential tool to estimate and map pasture biomass and mineral components: A case study in the Lake Taupo catchment, New Zealand, New Zeal. J. Agr. Res., 52, 417-434, doi: 10.1080/00288230909510524, 2009
20. Kristensen, T., Søegaard, K., and Kristensen, I. S. Management of grasslands in intensive dairy livestock farming, Livest Prod Sci., 96, 61-73, doi: 10.1016/j.livprodsci.2005.05.024, 2005
21. Lan, Y., Zhang, H., Lacey, R., Hoffmann, W. C., and Wu, W. Development of an Integrated Sensor and Instrumentation System for Measuring Crop Conditions, Agricultural Engineering International: the CIGR E Journal, Manuscript IT 08 1115, Vol. XI, April, 2009
22. Muñoz-Huerta, R. F., Guevara-Gonzalez, R. G., Contreras-Medina, L. M., Torres-Pacheco, I., Prado-Olivarez, J., and Ocampo-Velazquez, R. V. A Review of Methods for Sensing the Nitrogen Status in Plants: Advantages, Disadvantages and Recent Advances, Sensors, 13, 10823-10843, doi: 10.3390/s130810823, 2013
23. Nagasaka, Y., Umeda, N., Kanetai, Y., Taniwaki, K., and Sasaki Y. Autonomous guidance for rice transplanting using global positioning and gyroscopes, Comput. Electron. Agr., 43, 223-234, 2004
24. Nelder, J. A. The statistics of linear models: back to basics, Stat Comput., 4, 221-234, doi: 10.1007/BF00156745, 1994
25. Numata, I., Roberts, D., Chadwick, O., Schimel, J., Galvao, L., and Soares, J. Evaluation of hyperspectral data for pasture estimate in the Brazilian Amazon using field and imaging spectrometers, Remote Sens. Environ., 112, 1569-1583, doi: 10.1016/j.rse.2007.08.014, 2008
26. Oudshoorn, F. W., Cornou, C., Hellwing, A. L. F., Hansen, H. H., Munksgaard, L., Lund, P., and Kristensen, T. Estimation of grass intake on pasture for dairy cows using tightly and loosely mounted di- and tri-Axial accelerometers combined with bite count, Comput. Electron. Agr., 99, 227-235, doi: 10.1016/j.compag.2013.09.013, 2013
27. Pepperl, F. Sensors for the factory automation - Overview Standard Sensors, PepperlCFuchs ENU Part No. 200237, available from: http://www.pepperl-fuchs.us/usa/downloads-USA/Sensing-your-needs-2010-01-EN.pdf, 2010
28. Pittman, J. J., Arnall, D. B., Interrante, S. M., Moffet, C. A., and Butler, T. J. Estimation of biomass and canopy height in bermudagrass, alfalfa, and wheat using ultrasonic, laser, and spectral sensors, Sensors, 15, 2920-2943, doi: 10.3390/s150202920, 2015
29. Pullanagari, R. R., Yule, I. J., Hedley, M. J., Tuohy, M. P., Dynes, R. A., and King, W. M. Multi-spectral radiometry to estimate pasture quality components, Precis. Agric., 13, 442-456, doi: 10.1007/s11119-012-9260-y, 2012
30. Psomas, A., Kneubühler, M., Huber, S., Itten, K., and Zimmermann, N. E. Hyperspectral remote sensing for estimating aboveground biomass and for exploring species richness patterns of grassland habitats, Int. J. Remote Sens., 32, 9007-9031, doi: 10.1080/01431161.2010.532172, 2011
31. R Development Core Team, R. A Language and Environment for Statistical Computing, The R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07-0, available at: http://www.R-project.org/, 2013
32. Rahman, M. M., Lamb, D. W., Stanley, J. N., and Trotter, M. G. Use of proximal sensors to evaluate at the sub-paddock scale a pasture growth-rate model based on light-use efficiency, Crop Pasture Sci., 65, 400-409, doi: 10.1071/CP14071, 2014
33. Raymond, H. E. Airborne remote sensing of canopy water thickness scaled from leaf spectrometer data, Int. J. Remote Sens., 12, 643-649, doi: 10.1080/01431169108929679, 1991
34. Reddersen, B., Fricke, T., and Wachendorf, M. A multisensor approach for predicting biomass of extensively managed grassland, Comput. Electron. Agr., 109, 247-260, doi: 10.1016/j.compag.2014.10.011, 2014
35. Rook, A. and Tallowin, J. Grazing and pasture management for biodiversity benefit, Anim. Res., 52, 181-189, doi: 10.1051/animres: 2003014, 2003
36. Ryan, T. P. Modern regression methods, John Wiley & Sons, Vol. 655, 2008
37. Safari, H., Fricke, T., and Wachendorf, M. The potential of ultrasonic and hyperspectral sensor combination for the estimation and mapping of pasture biomass, Mitt. Gesell. Pflanzenbauwissenschaften, 27, 139-142, 2015
38. Safari, H., Fricke, T., and Wachendorf, M. Determination of fibre and protein content in heterogeneous pastures using field spectroscopy and ultrasonic sward height measurements, Comput. Electron. Agr., 123, 256-263, doi: 10.1016/j.compag.2016.03.002, 2016
39. Schellberg, J., Hill, M. J., Gerhards, R., Rothmund, M., and Braun, M. Precision agriculture on grassland: Applications, perspectives and constraints, Eur. J. Agron., 29, 59-71, doi: 10.1016/j.eja.2008.05.005, 2008
40. Silvia Cid, M., Miguel, A., and Bizuela Cid, B. Heterogeneity in tall fescue pastures created and sustained by cattle grazing, Range Manage., 6, 644-649, 1998
41. Suzuki, Y., Okamoto, H., Takahashi, M., Kataoka, T., and Shibata, Y. Mapping the spatial distribution of botanical composition and herbage mass in pastures using hyperspectral imaging, Grassl. Sci., 58, 1-7, doi: 10.1111/j.1744-697X.2011.00239.x, 2012
42. Wrage, N., Strodthoff, J., Cuchillo, H., Isselstein, J., and Kayser, M. Phytodiversity of temperate permanent grasslands: ecosystem services for agriculture and livestock management for diversity conservation, Biodivers. Conserv., 20, 3317-3339, 2011
43. Wrage, N., Sahin Demirbaǧ, N., Hofmann, M., and Isselstein, J. Vegetation height of patch more important for phytodiversity than that of paddock, Agr. Ecosyst. Environ., 155, 111-116, doi: 10.1016/j.agee.2012.04.008, 2012
44. Zhao C., Huang, W., Chen, L., Meng, Z., Wang, Y., and Xu, F. A harvest area measurement system based on ultrasonic sensors and DGPS for yield map correction, Precis Agric., 11, 163-180, 2010