Yliopiston etusivulle Suomeksi På svenska In English Helsingin yliopisto

RACS driven Cox process and its application to forest regeneration monitoring

Show simple item record

dc.contributor Helsingin yliopisto, Matematiikan ja tilastotieteen laitos (Valtiotieteellinen tiedekunta) fi
dc.contributor University of Helsinki, Mathematics and Statistics (Faculty of Social Sciences) en
dc.contributor Helsingfors universitet, Matematik och statistik, Institutionen för (Statsvetenskapliga fakulteten) sv
dc.contributor.author Niemi, Aki
dc.date.accessioned 2009-09-08T09:25:42Z
dc.date.available 2009-09-08T09:25:42Z
dc.date.issued 2003-02-13 en
dc.identifier.uri http://hdl.handle.net/10138/10257
dc.description Endast avhandlingens sammandrag. Pappersexemplaret av hela avhandlingen finns för läsesalsbruk i Statsvetenskapliga biblioteket (Unionsgatan 35). Dessa avhandlingar fjärrutlånas endast som microfiche. sv
dc.description Abstract only. The paper copy of the whole thesis is available for reading room use at the Library of Social Sciences (Unioninkatu 35) . Microfiche copies of these theses are available for interlibrary loans. en
dc.description Vain tiivistelmä. Opinnäytteiden sidotut arkistokappaleet ovat luettavissa HY:n keskustakampuksen valtiotieteiden kirjastossa (Unioninkatu 35). Opinnäytteitä lainataan ainoastaan mikrokortteina kirjaston kaukopalvelun välityksellä fi
dc.description.abstract Statistical methodology for forest regeneration monitoring is presented. The objectives are to construct spatial point process models for saplings, and to develop theory for model-based sampling from these processes. The main components affecting the early-stage spatial pattern of saplings are site-preparation (soil treatment) and regeneration method. The effect of site-preparation is predominant. First, planting and sowing take place in the treated tracks. Second, the density of naturally regenerated saplings is higher within the tracks than outside. The RACS driven Cox process, a new class of spatial point processes, enables one to model the spatial pattern of site-preparation tracks and to incorporate a higher sapling density inside the tracks than outside. In this hierarchical model, the distribution of site-preparation tracks is modelled by a random closed set (RACS). The classical theory of spatial sampling deals with estimation of the mean value of a realisation of a stationary, continuous-parameter random field. This theory utilises the covariance function of the random field, assuming that it is monotonically decreasing and positive definite. In forest regeneration monitoring, the estimation of the sapling density is performed by plot sampling where the number of saplings is counted from sample plots placed in the regeneration area. The statistical problem is that the classical sampling theory is not directly applicable. The problem is solved via a transformation from the observation of a stationary point process, to a stationary continuous-parameter random field. Further, the covariance function of the resulting random field is derived. The formula is a function of the intensity and the pair correlation function of the point process, and the size of the sample plot. In the empirical part, two RACS driven Cox process models are constructed according to authoritative instructions on site-preparation. One model is for a mounded regeneration area and another for a disc trenched area. Comparison with data shows that the models describe reasonably well the spatial pattern of the saplings. References: Matern, B. (1960). Spatial variation. Meddelanden fran Statens Skogsforskningsinstitut 49(5). Stoyan, D. & Kendall, W. S. & Mecke, J. (1995). Stochastic Geometry and Its Applications, 2nd edition. Wiley, Chichester. en
dc.language.iso en en
dc.subject spatial point process en
dc.subject random closed set en
dc.subject RACS driven Cox process en
dc.subject spatial sampling en
dc.subject covariance function en
dc.subject forest regeneration en
dc.title RACS driven Cox process and its application to forest regeneration monitoring en
dc.identifier.laitoskoodi 710 en
dc.type.ontasot Licentiate thesis en
dc.type.ontasot Lisensiaatintyö fi
dc.type.ontasot Licentiatsavhandling sv

Files in this item

Files Description Size Format View/Open
abstract.pdf 49.93Kb PDF View/Open
This item appears in the following Collection(s)

Show simple item record

Search Helda


Advanced Search

Browse

My Account