DSpace Unitus DSpace

Unitus DSpace >
Dipartimento di Scienze dell'Ambiente Forestale e delle sue Risorse >
DiSAFRi - Archivio della produzione scientifica >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/2661

Title: Use of geographically weighted regression to enhance the spatial features of forest attribute maps
Authors: Maselli, Fabio
Chiesi, Marta
Corona, Piermaria
Keywords: Growing stock
Geographically weighted regression
Landsat Thematic Mapper
Issue Date: 2014
Publisher: Society of Photo-Optical Instrumentation Engineers
Citation: Maselli, F. et al. 2014. Use of geographically weighted regression to enhance the spatial features of forest attribute maps. "Journal of Applied Remote Sensing" 8: 083533- 1-083533-13
Abstract: Geographically weighted regression (GWR) procedures can be adapted to enhance the spatial features of low spatial resolution maps based on higher resolution remotely sensed imagery. This operation relies on the assumption that the GWR models developed at low resolution can be proficiently applied to higher resolution data. An example of such an application is presented for downscaling a forest growing stock map which has been recently produced over the Italian national territory. GWR was appli
...more
DOI: 10.1117/1.JRS.8.083533
URI: http://hdl.handle.net/2067/2661
ISSN: 1931-3195
Appears in Collections:DiSAFRi - Archivio della produzione scientifica

Files in This Item:

File Description SizeFormat
JARS_maselli_GWR_1.pdf300.94 kBAdobe PDFView/Open


This item is protected by original copyright

Recommend this item

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! Unitus DSpace  © 2005 Università degli Studi della Tuscia - Feedback