AbstractsGeography &GIS

Leaf orientation and the spectral reflectance of field crops

by Xiaochen Zou

Institution: University of Helsinki
Department: Department of Geosciences and Geography
Year: 2015
Keywords: geography
Record ID: 1134854
Full text PDF: http://hdl.handle.net/10138/154534


Leaf angle distribution (LAD) is one of the most important parameters used to describe the structure of horizontally homogeneous vegetation canopies, such as field crops. LAD affects how incident photosynthetically active radiation is distributed on plant leaves, thus directly affecting plant productivity. However, the LAD of crops is difficult to quantify; usually it is assumed to be spherical. The purpose of this dissertation is to develop leaf angle estimation methods and study their effect on leaf area index (LAI) and chlorophyll a and b content (Cab) measured from optical observation. The study area was located in Viikki agricultural experimental field, Helsinki, Finland. Six crop species, faba bean, narrow-leafed lupin, turnip rape, oat, barley and wheat, were included in this study. A digital camera was used to take photographs outside the plot to record crop LAD. LAI and Cab were determined for each plot. Airborne imaging spectroscopy data was acquired using an AISA Eagle II imaging spectrometer covering the spectral range in visible and near-infrared (400 1000 nm). A recently developed method for the determination of leaf inclination angle was applied in field crops. This method was previously applied only to small and flat leaves of tree species. The error of LAI determination caused by the assumption of spherical LAD varied between 0 and 1.5 LAI units. The highest correlation between leaf mean tilt angle (MTA) and spectral reflectance was found at a wavelength of 748 nm. MTA was retrieved from imaging spectroscopy data using two algorithms. One method was to retrieve MTA from reflectance at 748 nm using a look-up table. The second method was to estimate MTA using the strong dependence of blue (479 nm) and red (663 nm) on MTA. The two approaches provide a new means to determine crop canopy structure from remote sensing data. LAI and MTA effects on Cab sensitive vegetation indices were examined. Three indices (REIP, TCARI/OSAVI and CTR6) showed strong correlations with Cab and similar performance in model-simulated and empirical datasets. However, only two (TCARI/OSAVI and CTR6) were independent from LAI and MTA. These two indices were considered as robust proxies of crop leaf Cab. Keywords: leaf angle; leaf area index; leaf chlorophyll; digital photograph; imaging spectroscopy; PROSAIL model; vegetation indices