Military service (Republic of Korea army) training course


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20190405

Author  :  Moura-Bueno, J. M. Dalmolin, R. S. D. ten Caten, A. Dotto, A. C. Dematte, J. A. M. Year  : 2019 Title  :  Stratification of a local VIS-NIR-SWIR spectral library by homogeneity criteria yields more accurate soil organic carbon predictions Journal  :  Geoderma Comment   :    The aim of this research was to  i) characterize and identify differences among spectra obtained for subtropical soils samples, ii)  evaluate different pre-processing techniques and multivariate methods to propose SOC prediction models from  the spectral data and iii) evaluate the performance of SOC prediction models calibrated from the stratification of  a local library.  Spectral reflectance measurements were performed in the  laboratory with a spectroradiometer in the range of 350–2500 nm. Six pre-processing techniques were applied to  the spectra (including derivatives, normalization and non-linear transformations) and four multivariate calibration  methods, namely, partial least
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20190412

Author  :  Ian A. Smith, Lucy R. Hutyra, Andrew B. Reinmann1, Jonathan R. Thompson, David W. Allen Year  : 2019 Title  :  Evidence for edge enhancements of soil respiration in temperate forests Journal  :  Geophysical Research Letters Comment   :   Forest fragmentation impacts carbon uptake and storage, however, the magnitude and direction of fragmentation impacts on soil respiration remain poorly characterized. They quantify soil respiration rates along edge-to-interior transects in two temperate broad-leaf forests in the eastern US that vary in climate, species composition, and soil type. They observe average soil respiration rates 15-26% higher at the forest edge compared to the interior, corresponding to large gradients in soil temperature.  These results suggest that estimates of soil respiration in the temperate forest region may be underestimating biological emissions of carbon dioxide.
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20181130

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Author  :  Eleanor Hobley, Markus Steffens, Sara L. Bauke & Ingrid Kögel-Knabner Year  : 2018 Title  :  Hotspots of soil organic carbon  storage revealed by laboratory  hyperspectral imaging Journal  :  Scientific Reports Comment   :   They tested the application  of laboratory hyperspectral imaging with a variety of machine learning approaches to predict OC  distribution in undisturbed soil cores.  Despite a  large increase in variance and reduction in OC content with increasing depth, the high resolution of the  images enabled statistically powerful analysis in spatial distribution of OC in the soil cores.  Laboratory hyperspectral imaging enables  powerful, fine-scale investigations of the vertical distribution of soil OC as well as hotspots of OC  storage in undisturbed samples, overcoming limitations of traditional soil sampling campaigns.
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