izpis_h1_title_alt

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

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URLURL - Izvorni URL, za dostop obiščite https://www.mdpi.com/1999-4907/11/11/1148 Povezava se odpre v novem oknu
URLURL - Izvorni URL, za dostop obiščite https://doi.org/10.3390/f11111148 Povezava se odpre v novem oknu

Izvleček
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 m2/ha. However, Bayes factors (BF10) suggest there is only moderate evidence for the difference in N (BF10 = 4.061) and anecdotal evidence for the difference in G (BF10 = 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.

Jezik:Angleški jezik
Ključne besede:forest inventory, mobile applications, bitterlich relascope, private forest owners, Bayesian informative hypotheses, accuracy, forest management planning
Vrsta gradiva:Članek v reviji (dk_c)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:BF - Biotehniška fakulteta
Leto izida:2020
Št. strani:16 str.
Številčenje:article 1148, iss. 11
UDK:630*6
ISSN pri članku:1999-4907
DOI:10.3390/f11111148 Povezava se odpre v novem oknu
COBISS.SI-ID:38901763 Povezava se odpre v novem oknu
Število ogledov:84
Število prenosov:295
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
 
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Gradivo je del revije

Naslov:Forests
Skrajšan naslov:Forests
Založnik:MDPI
ISSN:1999-4907
COBISS.SI-ID:3872166 Povezava se odpre v novem oknu

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Številka projekta:P4-0059
Naslov:Gozd, gozdarstvo in obnovljivi gozdni viri

Financer:EC - European Commission
Program financ.:ERA-NET Sumforest
Številka projekta:2330-17-000077
Naslov:Forests and extreme weather events
Akronim:FOREXCLIM

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:11.12.2020

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:gozdna inventura, zasebni gozdovi, gozdnogospodarsko načrtovanje

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