Fehrmann, Lutz

[["dc.bibliographiccitation.firstpage","223"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Environmental and Ecological Statistics"],["dc.bibliographiccitation.lastpage","237"],["dc.bibliographiccitation.volume","18"],["dc.contributor.author","Yang, Haijun"],["dc.contributor.author","Kleinn, Christoph"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Tang, Shouzheng"],["dc.contributor.author","Magnussen, Steen"],["dc.date.accessioned","2017-09-07T11:47:09Z"],["dc.date.available","2017-09-07T11:47:09Z"],["dc.date.issued","2009"],["dc.description.abstract","Adaptive cluster sampling (ACS) is a sampling technique for sampling rare and geographically clustered populations. Aiming to enhance the practicability of ACS while maintaining some of its major characteristics, an adaptive sample plot design is introduced in this study which facilitates field work compared to “standard” ACS. The plot design is based on a conditional plot expansion: a larger plot (by a pre-defined plot size factor) is installed at a sample point instead of the smaller initial plot if a pre-defined condition is fulfilled. This study provides insight to the statistical performance of the proposed adaptive plot design. A design-unbiased estimator is presented and used on six artificial and one real tree position maps to estimate density (number of objects per ha). The performance in terms of coefficient of variation is compared to the non-adaptive alternative without a conditional expansion of plot size. The adaptive plot design was superior in all cases but the improvement depends on (1) the structure of the sampled population, (2) the plot size factor and (3) the critical value (the minimum number of objects triggering an expansion). For some spatial arrangements the improvement is relatively small. The adaptive design may be particularly attractive for sampling in rare and compactly clustered populations with an appropriately chosen plot size factor."],["dc.identifier.doi","10.1007/s10651-009-0129-9"],["dc.identifier.gro","3149274"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/6653"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5933"],["dc.language.iso","en"],["dc.notes.intern","Kleinn Crossref Import"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1352-8505"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","A new design for sampling with adaptive sample plots"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1041"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Remote Sensing"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Pérez-Cruzado, César"],["dc.contributor.author","Kleinn, Christoph"],["dc.contributor.author","Magdon, Paul"],["dc.contributor.author","Álvarez-González, Juan Gabriel"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Nölke, Nils"],["dc.date.accessioned","2021-04-14T08:27:52Z"],["dc.date.available","2021-04-14T08:27:52Z"],["dc.date.issued","2021"],["dc.description.sponsorship","Forest Research Institute of the German Federal State of Rheinland-Pfalz (FAWF) in Trippstadt"],["dc.identifier.doi","10.3390/rs13051041"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/82431"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.publisher","MDPI"],["dc.relation.eissn","2072-4292"],["dc.rights","https://creativecommons.org/licenses/by/4.0/"],["dc.title","The Horizontal Distribution of Branch Biomass in European Beech: A Model Based on Measurements and TLS Based Proxies"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","300"],["dc.bibliographiccitation.issue","4"],["dc.bibliographiccitation.journal","Scandinavian Journal of Forest Research"],["dc.bibliographiccitation.lastpage","312"],["dc.bibliographiccitation.volume","34"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","Fehrmann, Lutz"],["dc.date.accessioned","2020-12-10T18:14:50Z"],["dc.date.available","2020-12-10T18:14:50Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1080/02827581.2019.1599063"],["dc.identifier.eissn","1651-1891"],["dc.identifier.issn","0282-7581"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/74634"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","In search of a variance estimator for systematic sampling"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","279"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Environmental and Ecological Statistics"],["dc.bibliographiccitation.lastpage","299"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Yang, Haijun"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Mundhenk, Philip"],["dc.contributor.author","Kleinn, Christoph"],["dc.date.accessioned","2017-09-07T11:47:12Z"],["dc.date.available","2017-09-07T11:47:12Z"],["dc.date.issued","2016"],["dc.description.abstract","Adaptive cluster sampling (ACS) has the potential of being superior for sampling rare and geographically clustered populations. However, setting up an efficient ACS design is challenging. In this study, two adaptive plot designs are proposed as alternatives: one for fixed-area plot sampling and the other for relascope sampling (also known as variable radius plot sampling). Neither includes a neighborhood search which makes them much easier to execute. They do, however, include a conditional plot expansion: at a sample point where a predefined condition is satisfied, sampling is extended to a predefined larger cluster-plot or a larger relascope plot. Design-unbiased estimators of population total and its variance are derived for each proposed design, and they are applied to ten artificial and one real tree position maps to estimate density (number of trees per ha) and basal area (the cross-sectional area of a tree stem at breast height) per hectare. The performances—in terms of relative standard error (SE%)—of the proposed designs and their non-adaptive alternatives are compared. The adaptive plot designs were superior for the clustered populations in all cases of equal sample sizes and in some cases of equal area of sample plots. However, the improvement depends on: (1) the plot size factor; (2) the critical value (the minimum number of trees triggering an expansion); (3) the subplot distance for the adapted cluster-plots, and (4) the spatial arrangement of the sampled population. For some spatial arrangements, the improvement is relatively small. The adaptive designs may be particularly attractive for sampling in rare and compactly clustered populations with critical value of 1, subplot distance equal to the diameter of initial circular plots, or plot size factor of 2.5 for an initial basal area factor of 2."],["dc.identifier.doi","10.1007/s10651-015-0339-2"],["dc.identifier.gro","3149289"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/5949"],["dc.language.iso","en"],["dc.notes.intern","Kleinn Crossref Import"],["dc.notes.status","final"],["dc.notes.submitter","chake"],["dc.relation.issn","1352-8505"],["dc.title","Two neighborhood-free plot designs for adaptive sampling of forests"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Forest Ecosystems"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","McRoberts, Ronald E."],["dc.contributor.author","Breidenbach, Johannes"],["dc.contributor.author","Nord-Larsen, Thomas"],["dc.contributor.author","Ståhl, Göran"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Schnell, Sebastian"],["dc.date.accessioned","2020-12-10T18:41:26Z"],["dc.date.available","2020-12-10T18:41:26Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1186/s40663-020-00223-6"],["dc.identifier.eissn","2197-5620"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/17215"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/77581"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.intern","Merged from goescholar"],["dc.relation.orgunit","Fakultät für Forstwissenschaften und Waldökologie"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Comparison of estimators of variance for forest inventories with systematic sampling - results from artificial populations"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Forest Ecosystems"],["dc.bibliographiccitation.volume","7"],["dc.contributor.author","Kleinn, Christoph"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","Nölke, Nils"],["dc.contributor.author","Magdon, Paul"],["dc.contributor.author","Álvarez-González, Juan Gabriel"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Pérez-Cruzado, César"],["dc.date.accessioned","2021-04-14T08:31:18Z"],["dc.date.available","2021-04-14T08:31:18Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1186/s40663-020-00268-7"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/17621"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/83552"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.notes.intern","Merged from goescholar"],["dc.relation.eissn","2197-5620"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Improving precision of field inventory estimation of aboveground biomass through an alternative view on plot biomass"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Environmental Monitoring and Assessment"],["dc.bibliographiccitation.volume","191"],["dc.contributor.author","Fehrmann, Lutz"],["dc.contributor.author","Kukunda, Collins B."],["dc.contributor.author","Nölke, Nils"],["dc.contributor.author","Schnell, Sebastian"],["dc.contributor.author","Seidel, Dominik"],["dc.contributor.author","Magnussen, Steen"],["dc.contributor.author","Kleinn, Christoph"],["dc.date.accessioned","2020-12-10T14:11:32Z"],["dc.date.available","2020-12-10T14:11:32Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1007/s10661-018-7152-y"],["dc.identifier.eissn","1573-2959"],["dc.identifier.issn","0167-6369"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/71098"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","A unified framework for land cover monitoring based on a discrete global sampling grid (GSG)"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","169"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","European Journal of Forest Research"],["dc.bibliographiccitation.lastpage","178"],["dc.bibliographiccitation.volume","139"],["dc.contributor.author","Magnussen, S."],["dc.contributor.author","Kleinn, C."],["dc.contributor.author","Fehrmann, L."],["dc.date.accessioned","2020-12-10T14:11:18Z"],["dc.date.available","2020-12-10T14:11:18Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1007/s10342-020-01257-9"],["dc.identifier.eissn","1612-4677"],["dc.identifier.issn","1612-4669"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/71035"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Wood volume errors from measured and predicted heights"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]