Browsing by Subject "leaf area index"

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  • Haikarainen, Iina (Helsingfors universitet, 2017)
    Leaf area index (LAI) is an important biophysical variable which helps to estimate vegetation biomass, radiation use efficiency and potential yield. Traditional LAI-determination methods tend to be slow and they require a lot of labor and data processing. Vegetation indices are one way to estimate LAI of the crops, but it is hard to create a vegetation index that would be suitable for all crops, environments and optical occasions. This is caused by saturation of indices under high LAI and differences in structure between various crop species Leaf inclination angle affects spectral reflectance with LAI (Zou et al. 2014, Zou & Mõttus 2015, Zou et al. 2015). The aim of this study was to investigate effects of leaf inclination angle on LAI-sensitive vegetation indices. LAI-sensitive narrow-band vegetation indices were selected from literature and they were calculated based on reflectance of measured field data and simulated model data. After calculation of vegetation indices, regression between vegetation indices and LAI was performed. Regression was performed with both true field data and simulated model data. Finally, simulated data was plotted based on mean leaf tilt angles (20, 30, 40, 50 and 65) and on low, medium and high chlorophyll contents (25-30, 55-60, 95-100). Regression was determined between vegetation indices and LAI based on plotted data. LAI could be estimated from vegetation indices in true field data (R2=0,36-0,52, RMSE 0,65-0,74 m2/m2) and simulated model data (R2=0,25-0,52, RMSE 0,81-1,02 m2/m2) and they acted similarly. When simulated data was plotted, coefficients of determination were higher (R2=0,50-0,99, RMSE 0,12-0,91 m2/m2). The best goodness of fit was found under MTA-levels 40 and 50. Lowest coefficients of determination occurred on highest MTA-level. Chlorophyll amount effected on the way MTA effects on indices performance: variance between MTA-classes seems to be larger under higher chlorophyll levels. As expected, leaf inclination angle affects performance of LAI-sensitive vegetation indices, and chlorophyll amount has effect on this. These observations should be taken into account while choosing index to estimate LAI of crops.
  • Roosjen, Peter, P.J.; Brede, Benjamin; Suomalainen, Juha, M.; Bartholomeus, Harm, M.; Kooistra, Lammert; Clevers, Jan, G.P.W. (2018)
    International Journal of Applied Earth Observation and Geoinformation
    In addition to single-angle reflectance data, multi-angular observations can be used as an additional information source for the retrieval of properties of an observed target surface. In this paper, we studied the potential of multi-angular reflectance data for the improvement of leaf area index (LAI) and leaf chlorophyll content (LCC) estimation by numerical inversion of the PROSAIL model. The potential for improvement of LAI and LCC was evaluated for both measured data and simulated data. The measured data was collected on 19 July 2016 by a frame-camera mounted on an unmanned aerial vehicle (UAV) over a potato field, where eight experimental plots of 30 × 30 m were designed with different fertilization levels. Dozens of viewing angles, covering the hemisphere up to around 30° from nadir, were obtained by a large forward and sideways overlap of collected images. Simultaneously to the UAV flight, in situ measurements of LAI and LCC were performed. Inversion of the PROSAIL model was done based on nadir data and based on multi-angular data collected by the UAV. Inversion based on the multi-angular data performed slightly better than inversion based on nadir data, indicated by the decrease in RMSE from 0.70 to 0.65 m2/m2 for the estimation of LAI, and from 17.35 to 17.29 μg/cm2 for the estimation of LCC, when nadir data were used and when multi-angular data were used, respectively. In addition to inversions based on measured data, we simulated several datasets at different multi-angular configurations and compared the accuracy of the inversions of these datasets with the inversion based on data simulated at nadir position. In general, the results based on simulated (synthetic) data indicated that when more viewing angles, more well distributed viewing angles, and viewing angles up to larger zenith angles were available for inversion, the most accurate estimations were obtained. Interestingly, when using spectra simulated at multi-angular sampling configurations as were captured by the UAV platform (view zenith angles up to 30°), already a huge improvement could be obtained when compared to solely using spectra simulated at nadir position. The results of this study show that the estimation of LAI and LCC by numerical inversion of the PROSAIL model can be improved when multi-angular observations are introduced. However, for the potato crop, PROSAIL inversion for measured data only showed moderate accuracy and slight improvements.
  • Manninen, Terhikki; Stenberg, Pauline (Ilmatieteen laitos - Finnish Meteorological Institute, 2021)
    Raportteja - Rapporter - Reports 2021:5
    Recently a simple analytic canopy bidirectional reflectance factor (BRF) model based on the spectral invariants theory was presented. The model takes into account that the recollision probability in the forest canopy is different for the first scattering than the later ones. Here this model is extended to include the forest floor contribution to the total forest BRF. The effect of the understory vegetation on the total forest BRF as well as on the simple ratio (SR) and the normalized difference (NDVI) vegetation indices is demonstrated for typical cases of boreal forest. The relative contribution of the forest floor to the total BRF was up to 69 % in the red wavelength range and up to 54 % in the NIR wavelength range. Values of SR and NDVI for the forest and the canopy differed within 10 % and 30 % in red and within 1 % and 10 % in the NIR wavelength range. The relative variation of the BRF with the azimuth and view zenith angles was not very sensitive to the forest floor vegetation. Hence, linear correlation of the modelled total BRF and the Ross-thick kernel was strong for dense forests (R2 > 0.9). The agreement between modelled BRF and satellite-based reflectance values was good when measured LAI, clumping index and leaf single scattering albedo values for a boreal forest were used as input to the model.
  • Alekseychik, P. K.; Korrensalo, A.; Mammarella, I.; Vesala, Timo; Tuittila, E. -S. (2017)
    Leaf area index (LAI) is an important parameter in natural ecosystems, representing the seasonal development of vegetation and photosynthetic potential. However, direct measurement techniques require labor-intensive field campaigns that are usually limited in time, while remote sensing approaches often do not yield reliable estimates. Here we propose that the bulk LAI of sedges (LAI(s)) can be estimated alternatively from a micrometeorological parameter, the aerodynamic roughness length for momentum (z(0)). z(0) can be readily calculated from high-response turbulence and other meteorological data, typically measured continuously and routinely available at ecosystem research sites. The regressions of LAI versus z(0) were obtained using the data from two Finnish natural sites representative of boreal fen and bog ecosystems. LAI(s) was found to be well correlated with z(0) and sedge canopy height. Superior method performance was demonstrated in the fen ecosystem where the sedges make a bigger contribution to overall surface roughness than in bogs.