研究目的
To assess the contribution of UAV and ALS data to the precision of the inventory estimates and to determine which type of UAV auxiliary data leads to the most precise estimates for small forest properties.
研究成果
The use of UAV auxiliary data can effectively support precision forestry practices for small-forest owners by providing advanced data analytics. UAV-SfMDTM data yielded some of the most precise estimates, highlighting the relevance of using UAV photogrammetric data for estimation of key forest variables.
研究不足
The study was conducted in a relatively homogenous forest stand, which may limit the generalizability of the findings to more diverse forest types. The UAV-LS sensor used had limitations in canopy penetration and only provided single returns, which may affect the characterization of some biophysical parameters.
1：Experimental Design and Method Selection:
The study compared the precision of estimates using plot data alone under a design-based inference with model-based estimates that include plot data and four types of auxiliary data from UAVs and ALS.
2：Sample Selection and Data Sources:
A total of 30 bounded circular
3：06 ha slope-adjusted ?eld plots were measured in a 40 ha Pinus radiata plantation. List of Experimental Equipment and Materials:
UAVs equipped with laser scanning sensors, RGB imagery, and photogrammetric equipment were used alongside ALS data.
4：Experimental Procedures and Operational Workflow:
Field plot measurements included diameter at breast height and height for a sub-sample of trees. UAV and ALS data were processed to extract explanatory variables.
5：Data Analysis Methods:
Linear regression models were fitted for different combinations of biophysical parameters and explanatory variables. The precision of estimates was compared using design-based and model-based inference frameworks.
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