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Characterization of Forested Landscapes from Remotely Sensed Data Using Fractals and Spatial Autocorrelation

Auteur(s):



Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2012
Page(s): 1-14
DOI: 10.1155/2012/945613
Abstrait:

The characterization of forested landscapes is frequently required in civil engineering practice. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions (FDs), along with a simple spatial autocorrelation technique (Moran’sI), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results indicate that when smaller trees do not dominate the landscape (<50%), forested areas can be differentiated according to breast sizes and thus important flood plain characteristics such as ratio of obstructed area to total area can be estimated from remotely sensed data using the studied indices. This would facilitate the estimation of hydraulic roughness coefficients for computation of flood profiles needed for bridge design. FD and Moran’sIremained fairly constant around the values of 2.7 and 0.9 (resp.) for samples with either greater than 50% saplings or less than 50% sawtimber and with ranges of 2.7–2.9 and 0.6–0.9 as the saplings decreased or the sawtimber increased. Those indices can also distinguish hardwood and softwood species facilitating forested landscapes mapping for preliminary environmental impact analysis.

Copyright: © 2012 Mohammad Z. Al-Hamdan et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 3.0 (CC-BY 3.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée.

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  • Reference-ID
    10176953
  • Publié(e) le:
    07.12.2018
  • Modifié(e) le:
    11.07.2019