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Bayesian evaluation of smartphone applications for forest inventories in small forest holdings
ID
Ficko, Andrej
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(3,30 MB)
MD5: E86A258812EEC22E6DBE4B90BAB12D12
URL - Izvorni URL, za dostop obiščite
https://www.mdpi.com/1999-4907/11/11/1148
Galerija slik
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 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.
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
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
BF - Biotehniška fakulteta
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2020
Št. strani:
16 str.
Številčenje:
Vol. 11, iss. 11, art. 1148
PID:
20.500.12556/RUL-122443
UDK:
630*6
ISSN pri članku:
1999-4907
DOI:
10.3390/f11111148
COBISS.SI-ID:
38901763
Datum objave v RUL:
11.12.2020
Število ogledov:
1296
Število prenosov:
500
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
Forests
Skrajšan naslov:
Forests
Založnik:
MDPI
ISSN:
1999-4907
COBISS.SI-ID:
3872166
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:
01.11.2020
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
gozdna inventura
,
zasebni gozdovi
,
gozdnogospodarsko načrtovanje
Projekti
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
Republic of Slovenia, Ministry of Agriculture, Forestry, and Food
Številka projekta:
2330-17-000077
Akronim:
FOREXCLIM
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P4-0059
Naslov:
Gozd, gozdarstvo in obnovljivi gozdni viri
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