Volume II-5/W2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5/W2, 295-300, 2013
https://doi.org/10.5194/isprsannals-II-5-W2-295-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5/W2, 295-300, 2013
https://doi.org/10.5194/isprsannals-II-5-W2-295-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  16 Oct 2013

16 Oct 2013

Precise plant height monitoring and biomass estimation with Terrestrial Laser Scanning in paddy rice

N. Tilly1,3, D. Hoffmeister1,3, Q. Cao2,3, V. Lenz-Wiedemann1,3, Y. Miao2,3, and G. Bareth1,3 N. Tilly et al.
  • 1Institute of Geography (GIS & Remote Sensing Group), University of Cologne, 50923 Cologne, Germany
  • 2Department of Plant Nutrition, China Agricultural University, 100193 Beijing, China
  • 3International Center for Agro-Informatics and Sustainable Development (ICASD), Cologne, Germany

Keywords: Agriculture, Crop, Change Detection, Monitoring, Multitemporal, Spatial, TLS

Abstract. Optimizing crop management is a major topic in the field of precision agriculture as the growing world population puts pressure on the efficiency of field production. Accordingly, methods to measure plant parameters with the needed precision and within-field resolution are required. Studies show that Terrestrial Laser Scanning (TLS) is a suitable method to capture small objects like crop plants. In this contribution, the results of multi-temporal surveys on paddy rice fields with the TLS system Riegl LMS-Z420i are presented. Three campaigns were carried out during the key vegetative stage of rice plants in the growing period 2012 to monitor the plant height. The TLS-derived point clouds are interpolated to visualize plant height above ground as crop surface models (CSMs) with a high resolution of 0.01 m. Spatio-temporal differences within the data of one campaign and between consecutive campaigns can be detected. The results were validated against manually measured plant heights with a high correlation (R2 = 0.71). Furthermore, the dependence of actual biomass from plant height was evaluated. To the present, no method for the non-destructive determination of biomass is found yet. Thus, plant parameters, like the height, have to be used for biomass estimations. The good correlation (R2 = 0.66) leads to the assumption that biomass can be estimated from plant height measurements. The results show that TLS can be considered as a very promising tool for precision agriculture.