Abstract
Abstract. To integrate the multi-spectral imagery and laser scanning data for forest management, a low-cost multisensory UAV system, named Kylin Cloud, is introduced in this paper. The Kylin Cloud is composed several low-cost sensors (i.e., GNSS receiver, IMU, global shutter camera, multispectral camera, and laser scanner), providing the fusion of the imagery and laser scanning data for reliable forest inventory. Experiments were undertaken in a forest park in Wuhan. Results showed that the registration error of the multispectral Digital Orthophoto Map (DOM) and laser scanning data is about one pixel, demonstrating a high potential of the proposed low-cost system.
Highlights
Forest management relies on accurate spectral and geometrical characteristics of trees
The proposed method achieved an accurate registration between the laser scanning points and the multispectral Digital Orthophoto Map (DOM)
The selected feature points should be recognized both in image and laser scanning points, and evenly distributed in the study sites
Summary
Forest management relies on accurate spectral and geometrical characteristics of trees. The detailed information of trees is acquired through field inventory, which is labor-intensive, time-consuming (Dai et al, 2018; Wang et al, 2016; Yang et al, 2016). In these years, many efforts focused on the fusion of the imagery and laser scanning data and achieved effective improvement in the forest applications, i.e., species identification (Puttonen et al, 2010), habitat modeling (García et al, 2011), and land cover classification (Tooke et al, 2009). Forestry decisions are made based on the remote sensing surveys
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