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TERRESTRIAL LASER SCANNING OF AGRICULTURAL CROPS 
J. Lumme 3 ' *, M. Karjalainen b , H. Kaartinen b , A. Kukko b , J. Hyyppa b , H. Hyyppa 3 , A. Jaakkola 6 , J. Kleemola c 
a Institute of Photogrammetry and Remote Sensing, Helsinki University of Technology, PL 1200, FIN-02015 HUT, 
Finland - (Juho.Lumme, Hannu.Hyyppa)@ tkk.fi 
b Finnish Geodetic Institute, PL 15, FIN-02431 Masala, Finland - (Mika.Karjalainen, Harri.Kaartinen, 
Antero.Kukko, Anttoni.Jaakkola, Juha.Hyyppa)? fgi.fi 
c Kemira GrowHow, PL 44, FIN-02271 Espoo, Finland -jouko.kleemola@kemira-growhow.com 
Commission V, WG V/3 
KEY WORDS: Terrestrial Laser scanning, Lidar, Agriculture, Precision Farming 
ABSTRACT: 
Laser scanning is a new technology that provides accurate and dense 3D measurements from the object. Development of laser 
scanners and techniques has led to several successful applications in the field of land surveying, forestry, industrial design and city 
planning. However, airborne laser scanners have not broken through in the field of agriculture and precision planning due to high 
expenses and insufficient accuracy, where as terrestrial laser scanners on the tripod are considered to be impractical for operational 
use. However, in the future we may have low-cost laser scanners mounted e.g. on UAVs enabling the cost-efficient use of laser 
scanning for precision agriculture as they are presently used in forestry. The goal of this study was to investigate how laser scanners 
and laser point data can be exploited in agriculture and precision farming. Growth height and ear recognition of cultivated plants 
were investigated using laser scanner data. The test area of this study is located in the Kotkaniemi Experimental Station of Kemira 
GrowHow Ltd in Southern Finland. Cereal cultivars were sown in plots of 1.25 m x 10 m on 6 th May 2006. Plots were fertilized at 
various rates corresponding to 0, 40, 80, 120 and 160 kg of N/ha. Three small grain cereals (barley, oat and wheat) with five 
different rates of fertilizer were scanned six times using Faro terrestrial laser scanner during the growing season of 2006. Faro laser 
scanner was mounted on a movable rack specially made for this study. The rack was about 3 meter high and Faro scanner scanned 
the ground beneath it. Test plots were signalled using white plastic disks and their location was measured using tachymeter. Besides, 
digital photographs, soil moisture values and growth height using tape measure were collected from each test plot and 
meteorological station observations were recorded. Growth heights were determined from each test plot using laser scanner data. A 
single test plot was divided into smaller grid cells and growth heights were determined from each cell. Precision harvesting was 
made on the 16th August 2006 with a combined harvester and total fresh weight of grains was weighed. Moisture content of grains 
was determined and fresh grain weight was converted into grain yield value (kg/ha) using grain moisture content and plot area. 
Growth height measures were compared to threshing results and there was strong correlation between measured growth heights and 
grain yield from each studied cultivars. Besides, ears of spring wheat cultivar Picolo were determined. An algorithm was developed 
to automatically recognize ears and estimate their size from laser scanner data. This result also correlates with the grain yield but the 
problem was to find suitable parameters for the algorithm and algorithm provide rather relative than absolute results of grain yield. 
1. INTRODUCTION 
Terrestrial laser scanners are becoming widely used in the field 
of close-range sensing. They are easy to use and they provide 
three-dimensional point cloud from the object surface in a few 
minutes. Spatial resolution of terrestrial laser scanners is high 
and they can measure several thousand or even more points per 
square meter depending on the distance between laser scanner 
and measured object. 
Several image-based remote sensing studies have been made for 
agriculture and precision crop management. Aerial cameras and 
multispectral scanners of remote sensing satellites are proved to 
be useful tools for regional and global area crop management 
(Idso et al. 1980; Moran et al., 1997a; Seelan et al., 2003). Due 
to the development of Synthetic Aperture Radar (SAR) 
instruments and generalization of SAR satellites, several SAR 
studies in the field of agriculture are made (Chakraborty et al., 
1997, 2005; Moran et al., 1997b; Karjalainen et al., 2001, 2002, 
2004a & 2004b). 
Airborne laser scanners are widely used to model terrain 
surfaces and city areas and to measure forest parameters such as 
stem volume and tree height. Unfortunately, airborne laser 
scanners, in general, are not suitable for agricultural 
applications because of their expenses and insufficient accuracy. 
The expenses are high especially when multi-temporal data sets 
are needed. There are only a few studies concerning laser 
scanning and agriculture (Grenier and Blackmore, 2001; 
Schmidt and Persson, 2003) and they are mainly focused on 
modelling field surface. 
Terrestrial laser scanners are accurate enough to obtain very 
detailed information about agricultural crops but they 
considered to be impractical for operational use. However, this 
study is based on the assumption that in future we probably will 
have e.g. low-cost unmanned airborne laser scanners. And 
different crop parameters will be extracted from agricultural 
field point cloud and used in precision farming likewise they 
already do in the field of forestry. 
* Corresponding author.