KEYWORDS: Remote sensing, Ecosystems, Visualization, Vegetation, Detection and tracking algorithms, Data modeling, Algorithm development, LIDAR, Clouds, RGB color model
The hotspot of biodiversity in the Andes of Southern Ecuador has been severely threatened by climate change and unsustainable land use. The high biodiversity requires strategies for conservation and management of natural resources to be developed at both individual and area-wide levels. In this paper we focus on the development of an automatic treecrown detection and classification approach, which is in line individual-based investigations in the tropical mountain environment. Airborne laser scanning of discrete type was used with a very high granularity (<10 returns per square meter). The individual tree crown detection reached an accuracy of 51% while supervised classification of palm-trees reached an accuracy of 69%. Accuracy measurements are given in the paper. The detection and characterization of individual tree crowns is the first step in the development of a monitoring approach for the tropical mountain forest.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.