Next Article in Journal / Special Issue
An Object-Based Classification of Mangroves Using a Hybrid Decision Tree—Support Vector Machine Approach
Previous Article in Journal
Evaluating Spectral Indices for Assessing Fire Severity in Chaparral Ecosystems (Southern California) Using MODIS/ASTER (MASTER) Airborne Simulator Data
Previous Article in Special Issue
Machine Learning Comparison between WorldView-2 and QuickBird-2-Simulated Imagery Regarding Object-Based Urban Land Cover Classification
Remote Sens. 2011, 3(11), 2420-2439; doi:10.3390/rs3112420

Object-Based Image Analysis of Downed Logs in Disturbed Forested Landscapes Using Lidar

Department of Environmental Sciences, Policy, and Management, College of Natural Resources, University of California at Berkeley, Berkeley, CA 94720, USA
* Author to whom correspondence should be addressed.
Received: 20 September 2011 / Revised: 9 November 2011 / Accepted: 10 November 2011 / Published: 16 November 2011
(This article belongs to the Special Issue Object-Based Image Analysis)
View Full-Text   |   Download PDF [1984 KB, uploaded 19 June 2014]   |   Browse Figures


Downed logs on the forest floor provide habitat for species, fuel for forest fires, and function as a key component of forest nutrient cycling and carbon storage. Ground-based field surveying is a conventional method for mapping and characterizing downed logs but is limited. In addition, optical remote sensing methods have not been able to map these ground targets due to the lack of optical sensor penetrability into the forest canopy and limited sensor spectral and spatial resolutions. Lidar (light detection and ranging) sensors have become a more viable and common data source in forest science for detailed mapping of forest structure. This study evaluates the utility of discrete, multiple return airborne lidar-derived data for image object segmentation and classification of downed logs in a disturbed forested landscape and the efficiency of rule-based object-based image analysis (OBIA) and classification algorithms. Downed log objects were successfully delineated and classified from lidar derived metrics using an OBIA framework. 73% of digitized downed logs were completely or partially classified correctly. Over classification occurred in areas with large numbers of logs clustered in close proximity to one another and in areas with vegetation and tree canopy. The OBIA methods were found to be effective but inefficient in terms of automation and analyst’s time in the delineation and classification of downed logs in the lidar data.
Keywords: lidar; Object-Based Image Analysis (OBIA); downed logs; downed dead wood lidar; Object-Based Image Analysis (OBIA); downed logs; downed dead wood
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote |
MDPI and ACS Style

Blanchard, S.D.; Jakubowski, M.K.; Kelly, M. Object-Based Image Analysis of Downed Logs in Disturbed Forested Landscapes Using Lidar. Remote Sens. 2011, 3, 2420-2439.

View more citation formats

Related Articles

Article Metrics

For more information on the journal, click here


[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert