Abstract
In this chapter, we describe our method for landscape ecological mapping in support of biodiversity evaluation through the use of airborne laser survey data. Our study areas include the Siretoko Peninsula, well known as a World Natural Heritage area, and the Chugoku mountainous area in the Satoyama Region, Japan. The landscape ecological map consists of the combination of a three dimensional vegetation structure classification derived from a detailed digital surface model (DSM) and a micro landform classification generated from a detailed digital elevation model (DEM). Airborne laser survey data were used to derive micro landforms under forest areas by using the last pulse data in a Fall season. Vegetation classification was generated by using the seasonal difference of the airborne laser survey data acquired in Summer and Fall. An overlay analysis of the vegetation classification and the landform classification indicates that at the Shiretoko Peninsula, three dimensional vegetation structures are more related to terrain elevation rather than micro landforms. And at the Chugoku mountainous area, some early deciduous high thin crown trees are located in historical mining sites within several micro landform categories such as gentle slope, concave and rough texture.
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Acknowledgments
This study was supported by Environment Research and Technology Development Fund (D-0805: project leader is Mamoru Koarai) from Ministry of Environment, Japan. Several collaborators are listed here: Prof. Ryota Nagasawa, Prof. Yoshiyuki Hioki, Prof. Tsuyoshi Yoshida, Prof. Akio Yamashita, Dr. Takayuki Nakano, Dr. Hiroshi P. Sato, and Mr. Kosei Otoi.
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Koarai, M. (2015). Landscape Ecological Mapping for Biodiversity Evaluation Using Airborne Laser Scanning Data. In: Li, J., Yang, X. (eds) Monitoring and Modeling of Global Changes: A Geomatics Perspective. Springer Remote Sensing/Photogrammetry. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-9813-6_7
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DOI: https://doi.org/10.1007/978-94-017-9813-6_7
Publisher Name: Springer, Dordrecht
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