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ACQUISITION AND AUTOMATED RECTIFICATION OF HIGH-RESOLUTION RGB AND NEAR-IR AERIAL PHOTOGRAPHS TO ESTIMATE PLANT BIOMASS AND SURFACE TOPOGRAPHY IN ARID AGRO-ECOSYSTEMS

  • PETER SELSAM (a1), WOLFGANG SCHAEPER (a2), KATJA BRINKMANN (a3) and ANDREAS BUERKERT (a3)
Summary

Increasing image resolution and shrinking camera size facilitates easy mounting of digital cameras on Unmanned Aerial Vehicles (UAVs) to collect large amounts of high-resolution aerial photos for soil surface and vegetation monitoring. Major challenges remain geo-referencing of these images, reliable stitching (mosaicking), elimination of geometric image distortions and compensation of limited image quality and high cost of the equipment. In this study, we report upon the design and field-testing of a custom-made, cost-effective mini-UAV allowing the acquisition of RGB and near-IR images covering areas of 1–2 km2 in each flight and the development of a software tool to automatically combine the geo-referenced images into a seamless image mosaic. Object-orientated image classification was used to estimate plant biomass. The images allowed to determine the distribution and biomass of selected plant species and other landscape features such as field borders and settlement patterns as well as to construct a simple 3D model of the topography of the surveyed area. The setup facilitates the cost-effective acquisition, mosaicking and classification of hundreds of RGB and near-IR images with a spatial resolution of 5–10 cm.

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Corresponding author
Corresponding author. Email: tropcrops@uni-kassel.de
References
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Böhm, B., Böhm, C., Buschmann, M., Chmara, S., Flügel, W. A., Krüger, L., Neumann, M., Püls, A., Reinhold, M., Sagischewski, H., Selsam, P., Vörsmann, P. and Wilkens, C. S. (2010). ANDROMEDA Anwendung Drohnen-basierter Luftbilder – Mosaikierung, Entzerrung und Daten-Auswertung, Abschlussbericht des Verbundprojekts, 31. 12. 2010, FKZ IN6041 (BMWi), Germany.
Böhm, B., Böhm, C., Chmara, S., Flügel, W. A., Krüger, T., Neumann, M., Reinhold, M., Sagischewski, H., Selsam, P., Vörsmann, P. and Wilkens, S. (2008). ANDROMEDA – Drohnenbasierte Erfassung von Forstkalamitäten – von der Vision zum produktiven Verfahren. Forst und Holz 63:3742.
Buerkert, A., Mahler, F. and Marschner, H. (1996). Soil productivity management and plant growth in the Sahel: Potential of an aerial monitoring technique. Plant and Soil 180:2938.
Everitt, J. H., Summy, K. R., Escobar, D. E. and Davis, M. R. (2003). An overview of aircraft remote sensing in integrated pest management. Subtropical Plant Science 55:5967.
Gérard, B., Buerkert, A., Hiernaux, P. and Marschner, H. (1997). Non-destructive measurement of plant growth and nitrogen status of pearl millet with low-altitude aerial photography. Soil Science and Plant Nutrition 43:993998.
Hattenberger, G., Bronz, M. and Gorraz, M. (2014). Using the Paparazzi UAV system for scientific research. In International Micro Air Vehicle (IMAV) Conference and Competition 2014, 247252. Delft, The Netherlands: Delft University of Technology.
Hunt, E.R., Cavigelli, M., Daughtry, C. S. T., McMurtrey, J. E., Walthall, C. L. (2005). Evaluation of digital photography from model aircraft for remote sensing of crop biomass and nitrogen status. Precision Agriculture 6:359–378.
Hunt, E. R., Hively, W. D., Fujikawa, S. J., Linden, D. S., Daughtry, C. S. T. and McCarty, G. W. (2010). Acquisition of NIR-green-blue digital photographs from unmanned aircraft for crop monitoring. Remote Sensing 2:290305.
Kralisch, S., Böhmm, B., Böhmm, C. and Buschm, C., Fink, M., Fischer, C., Schwartze, C., Selsam, P., Zander, F. and Flügel, W.-A. (2012). ILMS – a software platform for integrated environmental management. In International Congress on Environmental Modelling and Software, Managing Resources of a Limited Planet, Sixth Biennial Meeting, Leipzig, Germany, 2012, Seppelt, R., Voinov, A.A., Lange, S., Bankamp, D. (Eds.) pp 28642871. International Environmental Modelling and Software Society (iEMSs) http://www.iemss.org/society/index.php/iemss-2012-proceedings.
Laliberte, A. S., Herrick, J. E., Rango, A. and Winters, C. (2010). Acquisition, orthorectification, and object-based classification of unmanned aerial vehicle (UAV) imagery for rangeland monitoring. Photogrammetric Engineering and Remote Sensing 76:661672.
Lowe, D. G. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60 (2):91110.
Mayer, S. (2011). Application and improvement of the unmanned aerial system SUMO for atmospheric boundary layer studies. PhD Thesis University of Bergen, Norway.
Reinhold, M., Selsam, P. and Matejka, E. (2008). A software tool for object-based image analysis and the evaluation of its segmentation capabilities. In Proceedings EARSeL Joint Workshop: Remote Sensing - New Challenges of High Resolution, 5–7 March, 287297 (Ed Jürgens, C.). Bochum, Germany.
Ries, J. B. and Marzolff, I. (1997). Identification of sediment sources by large-scale aerial photography taken from a monitoring blimp. Physics and Chemistry of the Earth 22 (3–4):295302.
Ries, J. B. and Marzolff, I. (2003). Monitoring of gully erosion in the Central Ebro Basin by large scale aerial photography taken from a remotely controlled blimp. Catena 50 (2–4):309328.
Schaeper, W. (2006). Telescopic eyeglasses and model airplanes. Innovation, 17:5257.
Siebert, S., Gries, D., Zhang, X., Runge, M. and Buerkert, A. (2004). Non-destructive dry matter estimation of Alhagi sparsifolia vegetation in a desert oasis of NW China. Journal of Vegetation Science 15:365372.
Singh, D., Sao, R. and Singh, K. P. (2007). A remote sensing assessment of pest infestation on sorghum. Advances in Space Research 39 (1):155163.
Wilkens, C. S., Krüger, T., Martin, T., Scholtz, A., Vörsmann, P., Reinhold, M. and Selsam, P. (2010). Project ANDROMEDA: Automated generation of area photographs with unmanned aircraft systems. European Journal of Navigation 8 (3):3238.
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Experimental Agriculture
  • ISSN: 0014-4797
  • EISSN: 1469-4441
  • URL: /core/journals/experimental-agriculture
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