Matches in SemOpenAlex for { <https://semopenalex.org/work/W3088215358> ?p ?o ?g. }
- W3088215358 abstract "Abstract Background The local pivotal method (LPM) utilizing auxiliary data in sample selection has recently been proposed as a sampling method for national forest inventories (NFIs). Its performance compared to simple random sampling (SRS) and LPM with geographical coordinates has produced promising results in simulation studies. In this simulation study we compared all these sampling methods to systematic sampling. The LPM samples were selected solely using the coordinates (LPMxy) or, in addition to that, auxiliary remote sensing-based forest variables (RS variables). We utilized field measurement data (NFI-field) and Multi-Source NFI (MS-NFI) maps as target data, and independent MS-NFI maps as auxiliary data. The designs were compared using relative efficiency (RE); a ratio of mean squared errors of the reference sampling design against the studied design. Applying a method in NFI also requires a proven estimator for the variance. Therefore, three different variance estimators were evaluated against the empirical variance of replications: 1) an estimator corresponding to SRS; 2) a Grafström-Schelin estimator repurposed for LPM; and 3) a Matérn estimator applied in the Finnish NFI for systematic sampling design. Results The LPMxy was nearly comparable with the systematic design for the most target variables. The REs of the LPM designs utilizing auxiliary data compared to the systematic design varied between 0.74–1.18, according to the studied target variable. The SRS estimator for variance was expectedly the most biased and conservative estimator. Similarly, the Grafström-Schelin estimator gave overestimates in the case of LPMxy. When the RS variables were utilized as auxiliary data, the Grafström-Schelin estimates tended to underestimate the empirical variance. In systematic sampling the Matérn and Grafström-Schelin estimators performed for practical purposes equally. Conclusions LPM optimized for a specific variable tended to be more efficient than systematic sampling, but all of the considered LPM designs were less efficient than the systematic sampling design for some target variables. The Grafström-Schelin estimator could be used as such with LPMxy or instead of the Matérn estimator in systematic sampling. Further studies of the variance estimators are needed if other auxiliary variables are to be used in LPM." @default.
- W3088215358 created "2020-10-01" @default.
- W3088215358 creator A5040106841 @default.
- W3088215358 creator A5043285353 @default.
- W3088215358 creator A5067373226 @default.
- W3088215358 creator A5068180174 @default.
- W3088215358 creator A5076291197 @default.
- W3088215358 creator A5089612595 @default.
- W3088215358 date "2020-09-24" @default.
- W3088215358 modified "2023-10-16" @default.
- W3088215358 title "Comparison of the local pivotal method and systematic sampling for national forest inventories" @default.
- W3088215358 cites W1272693108 @default.
- W3088215358 cites W1842700253 @default.
- W3088215358 cites W1877183157 @default.
- W3088215358 cites W1905902179 @default.
- W3088215358 cites W1965710338 @default.
- W3088215358 cites W1968554898 @default.
- W3088215358 cites W2003644107 @default.
- W3088215358 cites W2017253904 @default.
- W3088215358 cites W2029685080 @default.
- W3088215358 cites W2033003748 @default.
- W3088215358 cites W2046735139 @default.
- W3088215358 cites W2050038074 @default.
- W3088215358 cites W2083358939 @default.
- W3088215358 cites W2103549993 @default.
- W3088215358 cites W2103884260 @default.
- W3088215358 cites W2109758583 @default.
- W3088215358 cites W2120575449 @default.
- W3088215358 cites W2169765847 @default.
- W3088215358 cites W2288393565 @default.
- W3088215358 cites W2335375293 @default.
- W3088215358 cites W2403035479 @default.
- W3088215358 cites W2495953580 @default.
- W3088215358 cites W2552199498 @default.
- W3088215358 cites W2558332400 @default.
- W3088215358 cites W2584446210 @default.
- W3088215358 cites W2616917210 @default.
- W3088215358 cites W2752326225 @default.
- W3088215358 cites W2782548987 @default.
- W3088215358 cites W2798144068 @default.
- W3088215358 cites W2802945275 @default.
- W3088215358 cites W2911801323 @default.
- W3088215358 cites W2915861510 @default.
- W3088215358 cites W4232575550 @default.
- W3088215358 cites W4236261977 @default.
- W3088215358 cites W2229012373 @default.
- W3088215358 doi "https://doi.org/10.1186/s40663-020-00266-9" @default.
- W3088215358 hasPublicationYear "2020" @default.
- W3088215358 type Work @default.
- W3088215358 sameAs 3088215358 @default.
- W3088215358 citedByCount "8" @default.
- W3088215358 countsByYear W30882153582021 @default.
- W3088215358 countsByYear W30882153582022 @default.
- W3088215358 crossrefType "journal-article" @default.
- W3088215358 hasAuthorship W3088215358A5040106841 @default.
- W3088215358 hasAuthorship W3088215358A5043285353 @default.
- W3088215358 hasAuthorship W3088215358A5067373226 @default.
- W3088215358 hasAuthorship W3088215358A5068180174 @default.
- W3088215358 hasAuthorship W3088215358A5076291197 @default.
- W3088215358 hasAuthorship W3088215358A5089612595 @default.
- W3088215358 hasBestOaLocation W30882153581 @default.
- W3088215358 hasConcept C105795698 @default.
- W3088215358 hasConcept C106131492 @default.
- W3088215358 hasConcept C118248890 @default.
- W3088215358 hasConcept C121955636 @default.
- W3088215358 hasConcept C129848803 @default.
- W3088215358 hasConcept C139945424 @default.
- W3088215358 hasConcept C140779682 @default.
- W3088215358 hasConcept C144024400 @default.
- W3088215358 hasConcept C144133560 @default.
- W3088215358 hasConcept C149923435 @default.
- W3088215358 hasConcept C165646398 @default.
- W3088215358 hasConcept C185429906 @default.
- W3088215358 hasConcept C185592680 @default.
- W3088215358 hasConcept C191393472 @default.
- W3088215358 hasConcept C192489979 @default.
- W3088215358 hasConcept C196083921 @default.
- W3088215358 hasConcept C198531522 @default.
- W3088215358 hasConcept C2908647359 @default.
- W3088215358 hasConcept C31972630 @default.
- W3088215358 hasConcept C33923547 @default.
- W3088215358 hasConcept C41008148 @default.
- W3088215358 hasConcept C43617362 @default.
- W3088215358 hasConcept C75373757 @default.
- W3088215358 hasConceptScore W3088215358C105795698 @default.
- W3088215358 hasConceptScore W3088215358C106131492 @default.
- W3088215358 hasConceptScore W3088215358C118248890 @default.
- W3088215358 hasConceptScore W3088215358C121955636 @default.
- W3088215358 hasConceptScore W3088215358C129848803 @default.
- W3088215358 hasConceptScore W3088215358C139945424 @default.
- W3088215358 hasConceptScore W3088215358C140779682 @default.
- W3088215358 hasConceptScore W3088215358C144024400 @default.
- W3088215358 hasConceptScore W3088215358C144133560 @default.
- W3088215358 hasConceptScore W3088215358C149923435 @default.
- W3088215358 hasConceptScore W3088215358C165646398 @default.
- W3088215358 hasConceptScore W3088215358C185429906 @default.
- W3088215358 hasConceptScore W3088215358C185592680 @default.
- W3088215358 hasConceptScore W3088215358C191393472 @default.
- W3088215358 hasConceptScore W3088215358C192489979 @default.
- W3088215358 hasConceptScore W3088215358C196083921 @default.