Terrestrial Laser Scanning of Agricultural Crops

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 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. * Corresponding author.