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Title:Monitoring in analiza zaraščanja kraške krajine v GIS okolju
Authors:Hočevar, Milan (Author)
Kušar, Gal (Author)
Cunder, Tomaž (Author)
Language:Slovenian
Tipology:1.01 - Original Scientific Article
Organisation:Logo SciVie - Slovenian Forestry Institute
Abstract:Članek predstavlja raziskavo zaraščanja kraške krajine. Pri analizi smo uporabili tehnike daljinskega zaznavanja, multitemporalne analize satelitskih slik v GIS okolju in statistične regresijske modele. Gozdnatost se je od leta 1935 povečala od 50,4% na 67,9%. Z regresijskim modelom smo pojasnili 71% celotne variabilnosti. Dejavniki, ki so največ prispevali k pojasnitvi zaraščanja so: nadmorska višina, razdalja do gozdnega roba, delež zaraslih površin v predhodnem obdobju, delež kmetijskih zemljišč in dve variabili, ki opisujeta intenzivnost kmetijske rabe. Če se procesi zaraščanja ne bodo bistveno spremenili, lahko do leta 2020 pričakujemo nadaljnje povečevanje gozdnatosti na 72,5%.
Keywords:zaraščanje, GIS, Kras, analiza krajine, daljinsko zaznavanje, Landsat, Ikonos
Year of publishing:2004
COBISS_ID:1436582 Link is opened in a new window
UDC:630*
ISSN on article:0351-3114
OceCobissID:6206978 Link is opened in a new window
URN:URN:NBN:SI:doc-CB7IQOXX
Views:3111
Downloads:1201
Files:.pdf PDF - Presentation file, download (4,99 MB)
 
Journal:Zb. gozd. lesar.
Gozdarski inštitut Slovenije
 
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Secondary language

Language:English
Title:Monitoring and analysis of spontaneous afforestation of Karst landscape in GIS environment
Abstract:This article presents Karst landscape spontaneous afforestation research. Remote sensing techniques, multitemporal analyses of satellite images in the GIS environment and statistical regression models were used in the research. Since 1935, the abundance of forests in this area has increased from 50.4% to 67.9%. About 71% of variability was explained with a regression model. Spontaneous afforestation is strongly influenced by the following factors: altitude, distance to the forest edge, share of afforested area in previous time periods, share of agricultural land, and two variables describing the intensity of agricultural use. Although various demographical, socio-economic and agro-structural factors were analysed in this research study, their influence on the process of spontaneous afforestation could not be established. If there are no significant changes in the processes of spontaneous afforestation in the future,forest abundance can be expected to increase to 72.5% by the year 2020.
Keywords:spontaneous afforestation, GIS, Karst, landscape analysis, remote sensing


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