Bayesian evaluation of smartphone applications for forest inventories in small forest holdings
ID Ficko, Andrej (Author)

.pdfPDF - Presentation file, Download (3,30 MB)
MD5: E86A258812EEC22E6DBE4B90BAB12D12
URLURL - Source URL, Visit https://www.mdpi.com/1999-4907/11/11/1148 This link opens in a new window

There are increasingly advanced mobile applications for forest inventories on the market. Small enterprises and nonprofessionals may find it difficult to opt for a more sophisticated application without comparing it to an established standard. In a small private forest holding (19 ha, 4 stands, 61 standing points), we compared TRESTIMA, a computer vision-based mobile application for stand inventories, to MOTI, a smartphone-based relascope, in measuring the number of stems (N) and stand basal area (G). Using a Bayesian approach, we (1) weighted evidence for the hypothesis of no difference in N and G between TRESTIMA and MOTI relative to the hypothesis of difference, and (2) weighted evidence for the hypothesis of overestimating versus underestimating N and G when using TRESTIMA compared to MOTI. The results of the Bayesian tests were then compared to the results of frequentist tests after the p-values of paired sample t-tests were calibrated to make both approaches comparable. TRESTIMA consistently returned higher N and G, with a mean difference of +305.8 stems/ha and +5.8 m$^2$/ha. However, Bayes factors (BF$_{10}$) suggest there is only moderate evidence for the difference in N (BF$_{10}$ = 4.061) and anecdotal evidence for the difference in G (BF$_{10}$ = 1.372). The frequentist tests returned inconclusive results, with p-values ranging from 0.03 to 0.13. After calibration of the p-values, the frequentist tests suggested rather small odds for the differences between the applications. Conversely, the odds of overestimating versus underestimating N and G were extremely high for TRESTIMA compared to MOTI. In a small forest holding, Bayesian evaluation of differences in stand parameters can be more helpful than frequentist analysis, as Bayesian statistics do not rely on asymptotics and can answer more specific hypotheses.

Keywords:forest inventory, mobile applications, Bitterlich relascope, private forest owners, Bayesian informative hypotheses, accuracy, forest management planning
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:BF - Biotechnical Faculty
Publication status:Published
Publication version:Version of Record
Number of pages:16 str.
Numbering:Vol. 11, iss. 11, art. 1148
PID:20.500.12556/RUL-122443 This link opens in a new window
ISSN on article:1999-4907
DOI:10.3390/f11111148 This link opens in a new window
COBISS.SI-ID:38901763 This link opens in a new window
Publication date in RUL:11.12.2020
Copy citation
Share:Bookmark and Share

Record is a part of a journal

Shortened title:Forests
COBISS.SI-ID:3872166 This link opens in a new window


License:CC BY 4.0, Creative Commons Attribution 4.0 International
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:01.11.2020

Secondary language

Keywords:gozdna inventura, zasebni gozdovi, gozdnogospodarsko načrtovanje


Funder:Other - Other funder or multiple funders
Funding programme:Republic of Slovenia, Ministry of Agriculture, Forestry, and Food
Project number:2330-17-000077

Funder:ARRS - Slovenian Research Agency
Project number:P4-0059
Name:Gozd, gozdarstvo in obnovljivi gozdni viri

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections: