Browsing by Subject "Resolution"

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  • Riihimäki, Henri; Luoto, Miska; Heiskanen, Janne (2019)
    Fractional cover of green vegetation (FCover) is a key variable when observing Arctic vegetation under a changing climate. Vegetation changes over large areas are traditionally monitored by linking plot-scale measurements to satellite data. However, integrating field and satellite data is not straightforward. Typically, the satellite data are at a much coarser scale in comparison to field measurements. Here, we studied how Unmanned Aerial Systems (UASs) can be used to bridge this gap. We covered three 250 m x 250 m sites in Fennoscandian tundra with varying productivity ana FCover, ranging from barren vegetation to shrub tundra. The UAS sites were then used to train satellite data-based FCover models. First, we created a binary vegetation classification (absent, present) by using UAS-derived RGB-orthomosaics and logistic regression. Secondly, we used the classification to calculate FCover to Planet CubeSat (3 m), Sentinel-2A MSI (10 m, 20 m), and Landsat 8 OLI (30 m) grids, and examined how well FCover is explained by various spectral vegetation indices (VI) derived from satellite data. The overall classification accuracies for the UAS sites were >= 90%. The UAS-FCover were strongly related to the tested VIs (D-2 89% at best). The explained deviance was generally higher for coarser resolution data, indicating that the effect of data resolution should be taken into account when comparing results from different sensors. VIs based on red-edge (at 740 nm, 783 nm), or near-infrared and shortwave infrared (SWIR) had the highest performance. We recommend wider inspection of red-edge and SWIR bands for future Arctic vegetation research. Our results demonstrate that UASs can be used for observing FCover at multiple scales. Individual UAS sites can serve as focus areas, which provide information at the finest resolution (e.g. individual plants), whereas a sample of several UAS sites can be used to train satellite data and examine vegetation over larger extents.
  • Cai, Runlong; Jiang, Jingkun; Mirme, Sander; Kangasluoma, Juha (2019)
    Measuring aerosol size distributions accurately down to similar to 1 nm is a key to nucleation studies, and it requires developments and improvements in instruments such as electrical mobility spectrometers in use today. The key factors characterizing the performance of an electrical mobility spectrometer for sub-3 nm particles are discussed in this study. A parameter named as Pi is proposed as a figure of merit for the performance of an electrical mobility spectrometer in the sub-3 nm size range instead of the overall detection efficiency. Pi includes the overall detection efficiency, the measurement time in each size bin, the aerosol flow rate passing through the detector, and the aerosol-to-sheath flow ratio of the differential mobility analyzer. The particle raw count number recorded by the detector can be estimated using Pi at a given aerosol size distribution function, dN/dlogd(p)( ). The limit of detection for the spectrometer and the statistical uncertainty of the measured aerosol size distribution can also be readily estimated using Pi. In addition to Pi, the size resolution of an electrical mobility analyzer is another factor characterizing the systematic errors originated from particle sizing. Four existing electrical mobility spectrometers designed for measuring sub-3 nm aerosol size distributions, including three scanning/differential mobility particle spectrometers and one differential mobility analyzer train, are examined. Their optimal performance is evaluated using Pi and the size resolution. For example, the Pi value and the size resolution of a diethylene-glycol differential mobility particle spectrometer for 1.5 nm particles are 8.0 x 10(-4) cm(3) and 5.7, respectively. The corresponding relative uncertainty of the measured size distribution is approximately 9.6% during an atmospheric new particle formation event with a dN/dlogd(p) of 5 x 10(5) cm(-3) . Assuming an adjustable sheath flow rate of the differential mobility analyzer, the optimal size resolution is approximately 5-9 when measuring atmospheric new particle formation events.