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WorldView-2 Satellite Imagery and Airborne LiDAR Data for Object-Based Forest Species Classification in a Cool Temperate Rainforest Environment

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Developments in Multidimensional Spatial Data Models

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

High resolution spatial data including airborne LiDAR data and newly available WorldView-2 satellite imagery provide opportunities to develop new efficient ways of solving conventional problems in forestry. Those responsible for monitoring forest changes over time relevant to timber harvesting and native forest conservation realize the potential for improved documentation from using such data. Proper use of high spatial resolution data with object-based image analysis approach and nonparametric classification method such as decision trees offers an alternative to aerial photograph interpretation in support of forest classification and mapping. This study explored ways of processing airborne LiDAR data and WorldView-2 satellite imagery for object-based forest species classification using decision trees in the Strzelecki Ranges, one of the four major Victorian areas of cool temperate rainforest in Australia. The effectiveness of variables derived from different data sets, in particular, the four new bands of WorldView-2 imagery was examined. The results showed that using LiDAR data alone or four conventional bands only, the overall accuracies achieved were 61.39 and 61.42 % respectively, but the overall accuracy increased to 82.35 % when all eight bands and the LiDAR data were used. This study demonstrated that the integration of airborne LiDAR and eight WorldView-2 bands significantly improved the classification accuracy.

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Authors and Affiliations

  1. Australian Centre for Sustainable Catchments, and Faculty of Engineering and Surveying, University of Southern Queensland, Toowoomba, QLD, 4350, Australia

    Zhenyu Zhang & Xiaoye Liu

  2. Centre for GIS, School of Geography and Environmental Science, Monash University, Clayton, VIC, 3800, Australia

    Zhenyu Zhang

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  1. Zhenyu Zhang
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  2. Xiaoye Liu
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Correspondence to Zhenyu Zhang .

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Editors and Affiliations

  1. , Faculty of Geoinformation, Universiti Teknologi Malaysia, Johor, Skudai, 81310, Malaysia

    Alias Abdul Rahman

  2. , Faculty of Geoinformation, Universiti Teknologi Malaysia, Johor, Skudai, 81310, Malaysia

    Pawel Boguslawski

  3. , Faculty of Geoinformation, Universiti Teknologi Malaysia, Johor, Skudai, 81310, Malaysia

    Christopher Gold

  4. , Faculty of Geoinformation, Universiti Teknologi Malaysia, Johor, Skudai, 81310, Malaysia

    Mohamad Nor Said

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Zhang, Z., Liu, X. (2013). WorldView-2 Satellite Imagery and Airborne LiDAR Data for Object-Based Forest Species Classification in a Cool Temperate Rainforest Environment. In: Abdul Rahman, A., Boguslawski, P., Gold, C., Said, M. (eds) Developments in Multidimensional Spatial Data Models. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36379-5_7

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