Evaluation of three spatial interpolation methods to estimate forest volume in the municipal forest of the Greek island Skyros

dc.contributor.author	Kalivas, DP	en
dc.contributor.author	Kollias, VJ	en
dc.contributor.author	Apostolidis, EH	en
dc.date.accessioned	2014-06-06T06:52:31Z
dc.date.available	2014-06-06T06:52:31Z
dc.date.issued	2013	en
dc.identifier.issn	10095020	en
dc.identifier.uri	http://dx.doi.org/10.1080/10095020.2013.766398	en
dc.identifier.uri	http://62.217.125.90/xmlui/handle/123456789/6055
dc.subject	Autocorrelation	en
dc.subject	Forest modeling	en
dc.subject	Geostatistics	en
dc.subject	Spatial prediction	en
dc.subject.other	autocorrelation	en
dc.subject.other	forest	en
dc.subject.other	geostatistics	en
dc.subject.other	interpolation	en
dc.subject.other	kriging	en
dc.subject.other	modeling	en
dc.subject.other	prediction	en
dc.subject.other	spatial analysis	en
dc.subject.other	Aegean Islands	en
dc.subject.other	Central Greece	en
dc.subject.other	Euboea	en
dc.subject.other	Greece	en
dc.subject.other	Skyros	en
dc.subject.other	Sporades [Aegean Islands]	en
dc.title	Evaluation of three spatial interpolation methods to estimate forest volume in the municipal forest of the Greek island Skyros	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/10095020.2013.766398	en
heal.publicationDate	2013	en
heal.abstract	Forest volume is of great interest to forest managers. Plot observations of forest volume are available from planning reports. For managers, however, what is relevant are forest volume surfaces. In this study, three interpolation methods were employed to construct continuous surfaces for the evaluation of forest volume at positions for which no measurements are available. For the Municipal Forest of Skyros Island, we compared spatial predictions derived from Inverse Distance Weighting (IDW), Block Kriging (BK), and Block Co-Kriging (BCK) interpolation methods, as applied to data from 120 sample plots. The existence of spatial autocorrelation in the data was identified using correlograms of Moran's I index. Spatial outliers were identified and excluded from the analysis using the local Moran's I index. Only slope, of the examined environmental factors, showed an acceptable correlation with forest volume and was used as an auxiliary variable for BCK. The performance of the three methods was evaluated, using an independent validation set and comparing these indices: mean error (ME) and root mean square error. Additionally, for BK and BCK, the indices, standardized ME, average standard error, and the standardized root-mean-square error were used. For the three interpolation methods, the BK method gave the more accurate results; BCK is the next more accurate method and IDW the third. © 2013 Wuhan University.	en
heal.journalName	Geo-Spatial Information Science	en
dc.identifier.issue	2	en
dc.identifier.volume	16	en
dc.identifier.doi	10.1080/10095020.2013.766398	en
dc.identifier.spage	100	en
dc.identifier.epage	112	en