![](/images/graphics-bg.png)
Characterization of Forested Landscapes from Remotely Sensed Data Using Fractals and Spatial Autocorrelation
Joint Authors
al-Hamdan, Mohammad Z.
Quattrochi, Dale A.
Rickman, Douglas L.
Cruise, James F.
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-03-21
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
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’s I), 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’s I remained 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.
American Psychological Association (APA)
al-Hamdan, Mohammad Z.& Cruise, James F.& Rickman, Douglas L.& Quattrochi, Dale A.. 2012. Characterization of Forested Landscapes from Remotely Sensed Data Using Fractals and Spatial Autocorrelation. Advances in Civil Engineering،Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-510300
Modern Language Association (MLA)
al-Hamdan, Mohammad Z.…[et al.]. Characterization of Forested Landscapes from Remotely Sensed Data Using Fractals and Spatial Autocorrelation. Advances in Civil Engineering No. 2012 (2012), pp.1-14.
https://search.emarefa.net/detail/BIM-510300
American Medical Association (AMA)
al-Hamdan, Mohammad Z.& Cruise, James F.& Rickman, Douglas L.& Quattrochi, Dale A.. Characterization of Forested Landscapes from Remotely Sensed Data Using Fractals and Spatial Autocorrelation. Advances in Civil Engineering. 2012. Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-510300
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-510300