Next Article in Journal / Special Issue
Comparing Empirical and Semi-Empirical Approaches to Forest Biomass Modelling in Different Biomes Using Airborne Laser Scanner Data
Previous Article in Journal
A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China
Previous Article in Special Issue
Phenology-Based Method for Mapping Tropical Evergreen Forests by Integrating of MODIS and Landsat Imagery
Open AccessArticle

Drones as a Tool for Monoculture Plantation Assessment in the Steepland Tropics

1
ForestGEO, Smithsonian Tropical Research Institute, Balboa, Ancon, 0843-03092 Panama City, Panama
2
Yale School of Forestry & Environmental Studies, New Haven, CT 06511, USA
3
Smithsonian Tropical Research Institute, Balboa, Ancon, 0843-03092 Panama City, Panama
4
Fearless Labs, 8 Market Place, Baltimore, MD 21202, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Christian Ginzler and Lars T. Waser
Forests 2017, 8(5), 168; https://doi.org/10.3390/f8050168
Received: 31 March 2017 / Revised: 2 May 2017 / Accepted: 6 May 2017 / Published: 12 May 2017
(This article belongs to the Special Issue Optimizing Forest Inventories with Remote Sensing Techniques)
Smallholder tree plantations are expanding in the steepland tropics due to demand for timber and interest in ecosystem services, such as carbon storage. Financial mechanisms are developing to compensate vegetation carbon stores. However, measuring biomass—necessary for accessing carbon funds—at small scales is costly and time-intensive. Therefore, we test whether low-cost drones can accurately estimate height and biomass in monoculture plantations in the tropics. We used Ecosynth, a drone-based structure from motion technique, to build 3D vegetation models from drone photographs. These data were filtered to create a digital terrain model (DTM) and digital surface model (DSM). Two different canopy height models (CHMs) from the Ecosynth DSM were obtained by subtracting terrain elevations from the Ecosynth DTM and a LIDAR DTM. We compared height and biomass derived from these CHMs to field data. Both CHMs accurately predicted the height of all species combined; however, the CHM from the LiDAR DTM predicted heights and biomass on a per-species basis more accurately. Height and biomass estimates were strong for evergreen single-stemmed trees, and unreliable for small leaf-off species during the dry season. This study demonstrates that drones can estimate plantation biomass for select species when used with an accurate DTM. View Full-Text
Keywords: drone; LiDAR; point cloud; ecosynth; Panama; plantation; inventory; tropics drone; LiDAR; point cloud; ecosynth; Panama; plantation; inventory; tropics
Show Figures

Figure 1

MDPI and ACS Style

Miller, E.; Dandois, J.P.; Detto, M.; Hall, J.S. Drones as a Tool for Monoculture Plantation Assessment in the Steepland Tropics. Forests 2017, 8, 168.

AMA Style

Miller E, Dandois JP, Detto M, Hall JS. Drones as a Tool for Monoculture Plantation Assessment in the Steepland Tropics. Forests. 2017; 8(5):168.

Chicago/Turabian Style

Miller, Ethan; Dandois, Jonathan P.; Detto, Matteo; Hall, Jefferson S. 2017. "Drones as a Tool for Monoculture Plantation Assessment in the Steepland Tropics" Forests 8, no. 5: 168.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop