HwangRyuKimmEtAl2016

Référence

Hwang, Y., Ryu, Y., Kimm, H., Jiang, C., Lang, M., Macfarlane, C., Sonnentag, O. (2016) Correction for light scattering combined with sub-pixel classification improves estimation of gap fraction from digital cover photography. Agricultural and Forest Meteorology, 222:32-44. (Scopus )

Résumé

Digital cover photography (DCP) has emerged as an indirect method to measure gap fraction of vegetation canopies. However, as with other photographic methods, determining camera relative exposure value (REV) and threshold for pixel classification, cause substantial uncertainties in gap fraction estimates. Here we propose a new method to improve the measurement of gap fraction under various solar zenith angles (SZAs), sky conditions, and canopy structures. This method computes gap fractions of ambiguous vegetation or sky pixels using an unsaturated raw image from DCP and a reconstructed sky image from the raw image, thus taking full advantage of the potential of raw image processing. This is combined with pre-classification of pixels that are unambiguously canopy and sky to greatly reduce light scattering effects that are likely to be present within the canopy. To test the sensitivity of the new method, we acquired images at one-hour intervals between 20 and 85° of SZAs under closed, half-closed, and open canopies with REV settings from 0 to -5. The new method showed little variation in gap fractions across the diverse SZAs in closed, half-closed, and open canopies. A perforated panel experiment, which was used to test the accuracy of the estimated gap fractions, confirmed that the new method accurately estimated gap fractions across a range of hole size, gap fractions and SZAs. We conclude that the new method opens new opportunities to estimate gap fractions accurately regardless of solar positions from open to closed canopies, and is a significant advance for accurate and precise monitoring of canopy cover and leaf area index (LAI), and for calibrating and evaluating satellite remote sensing LAI products. © 2016 Elsevier B.V.

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@ARTICLE { HwangRyuKimmEtAl2016,
    AUTHOR = { Hwang, Y. and Ryu, Y. and Kimm, H. and Jiang, C. and Lang, M. and Macfarlane, C. and Sonnentag, O. },
    TITLE = { Correction for light scattering combined with sub-pixel classification improves estimation of gap fraction from digital cover photography },
    JOURNAL = { Agricultural and Forest Meteorology },
    YEAR = { 2016 },
    VOLUME = { 222 },
    PAGES = { 32-44 },
    NOTE = { cited By 6 },
    ABSTRACT = { Digital cover photography (DCP) has emerged as an indirect method to measure gap fraction of vegetation canopies. However, as with other photographic methods, determining camera relative exposure value (REV) and threshold for pixel classification, cause substantial uncertainties in gap fraction estimates. Here we propose a new method to improve the measurement of gap fraction under various solar zenith angles (SZAs), sky conditions, and canopy structures. This method computes gap fractions of ambiguous vegetation or sky pixels using an unsaturated raw image from DCP and a reconstructed sky image from the raw image, thus taking full advantage of the potential of raw image processing. This is combined with pre-classification of pixels that are unambiguously canopy and sky to greatly reduce light scattering effects that are likely to be present within the canopy. To test the sensitivity of the new method, we acquired images at one-hour intervals between 20 and 85° of SZAs under closed, half-closed, and open canopies with REV settings from 0 to -5. The new method showed little variation in gap fractions across the diverse SZAs in closed, half-closed, and open canopies. A perforated panel experiment, which was used to test the accuracy of the estimated gap fractions, confirmed that the new method accurately estimated gap fractions across a range of hole size, gap fractions and SZAs. We conclude that the new method opens new opportunities to estimate gap fractions accurately regardless of solar positions from open to closed canopies, and is a significant advance for accurate and precise monitoring of canopy cover and leaf area index (LAI), and for calibrating and evaluating satellite remote sensing LAI products. © 2016 Elsevier B.V. },
    AFFILIATION = { Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, South Korea; Interdisciplinary Program in Agricultural and Forest Meteorology, Seoul National University, South Korea; Interdisciplinary Program in Landscape Architecture, Seoul National University, South Korea; Research Institute of Agriculture and Life Sciences, Seoul National University, South Korea; Tartu Observatory, 61602 Tõravere, Tartumaa, Estonia; CSIRO Land and Water Flagship, Private Bag No. 5, Wembley, WA, Australia; Université de Montréal, Département de géographie, Montréal, QC, Canada },
    AUTHOR_KEYWORDS = { Digital cover photography; Gap fraction; Leaf area index; Light exposure; Remote sensing },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1016/j.agrformet.2016.03.008 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960865853&doi=10.1016%2fj.agrformet.2016.03.008&partnerID=40&md5=5f6b7a613237d403a1e5f801decd0bab },
}

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