• Title of article

    Combination of optical and LiDAR satellite imagery with forest inventory data to improve wall-to-wall assessment of growing stock in Italy

  • Author/Authors

    Maselli، نويسنده , , F. and Chiesi، نويسنده , , M. and Mura، نويسنده , , M. A. MARCHETTI and J. P. KRAUSZ، نويسنده , , M. and Corona-Avendaٌo، نويسنده , , P. and Chirici، نويسنده , , G.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    10
  • From page
    377
  • To page
    386
  • Abstract
    The acquisition of information about growing stock is a fundamental step in the framework of forest management planning and scenario modeling, besides being essential for assessing the amount of carbon stored within forest ecosystems. Gallaun et al. (2010) produced a pan-European map of forest growing stock by the combination of ground and remotely sensed data. The first objective of the current paper is to assess the accuracy of this map versus the ground data collected during the latest Italian National Forest Inventory (INFC). Next, a new wall-to-wall estimation of growing stock is obtained by combining ground measurements of four regional forest inventories with the CORINE land cover map of Italy and the global canopy height map derived from Geoscience Laser Altimeter System (GLAS) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. More particularly, the growing stock measurements of the four inventories are stratified by ecosystem type and extended over all Italian forest areas through the application of locally weighted regressions to the GLAS/MODIS canopy height map. When compared to the INFC measurements, the new map shows higher accuracy than that by Gallaun et al., particularly for high growing stock values. The coefficient of determination between estimated and INFC growing stocks is improved by about 0.5, whilst the mean square error is reduced from 90 to 48 m3 ha−1.
  • Keywords
    Forest inventory , Locally weighted regression , CORINE land cover , Glas , MODIS
  • Journal title
    International Journal of Applied Earth Observation and Geoinformation
  • Serial Year
    2014
  • Journal title
    International Journal of Applied Earth Observation and Geoinformation
  • Record number

    2379470