Login | Request Account (DAF staff only)

Drone-Based Environmental Monitoring and Image Processing Approaches for Resource Estimates of Private Native Forest

View Altmetrics

Srivastava, S. K., Seng, K. P., Ang, L. M., Pachas, A. N. A. and Lewis, T. (2022) Drone-Based Environmental Monitoring and Image Processing Approaches for Resource Estimates of Private Native Forest. Sensors, 22 (20). p. 7872. ISSN 1424-8220


Article Link: https://doi.org/10.3390/s22207872

Publisher URL: https://www.mdpi.com/1424-8220/22/20/7872


This paper investigated the utility of drone-based environmental monitoring to assist with forest inventory in Queensland private native forests (PNF). The research aimed to build capabilities to carry out forest inventory more efficiently without the need to rely on laborious field assessments. The use of drone-derived images and the subsequent application of digital photogrammetry to obtain information about PNFs are underinvestigated in southeast Queensland vegetation types. In this study, we used image processing to separate individual trees and digital photogrammetry to derive a canopy height model (CHM). The study was supported with tree height data collected in the field for one site. The paper addressed the research question “How well do drone-derived point clouds estimate the height of trees in PNF ecosystems?” The study indicated that a drone with a basic RGB camera can estimate tree height with good confidence. The results can potentially be applied across multiple land tenures and similar forest types. This informs the development of drone-based and remote-sensing image-processing methods, which will lead to improved forest inventories, thereby providing forest managers with recent, accurate, and efficient information on forest resources.

Item Type:Article
Business groups:Horticulture and Forestry Science
Keywords:digital photogrammetry; drone-based monitoring; forest resource estimation; image analysis; private native forests; remote sensing; agtech; agritech
Subjects:Agriculture > Agriculture (General) > Farm machinery and farm engineering
Forestry > Research. Experimentation
Forestry > Conservation and protection
Live Archive:15 Nov 2022 04:22
Last Modified:08 Feb 2023 03:25

Repository Staff Only: item control page


Downloads per month over past year

View more statistics