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Na podlagi simuliranja zgostitve mreže monitoringa gozdov in gozdnih ekosistemov (4 x 4 km) in podatkov za leto 2012 smo prikazali, da bi za manj kot 10 % vzorčne napake pri ocenah lesne zaloge, prirastka in količine odmrle drevnine potrebovali vsaj 2 x 2 km ali celo 2 x 1,4 km mrežo ploskev, ki bi jo lahko poimenovali nacionalna gozdna inventura. Zaradi lažje organiziranosti dela (redne letne naloge zaposlenih na GIS in ZGS) predlagamo uvedbo panelnega inventurnega sistema, v katerem je sistematična mreža vzorčnih ploskev razdeljena v posamezne skupine ti. panele, ki jih kasneje premikamo tako, da je vsak panel na celotni površini države izmerjen v posameznem letu. S tako organizirano kontinuirano NGI bi vzpostavili metodološko statistično utemeljen in kakovosten informacijski sistem o gozdovih za letna poročila o stanju slovenskih gozdov na državni ravni in hkrati bi po enem snemalnem ciklu pridobili dovolj velik vzorec za konsistentna poročila o stanju gozdov na nižjih prostorskih ravneh kot so provenienčna območja, GGO ali statistične regije. Simulating higher grid density of Forest and Forest Ecosystems Condition Survey (4 x 4 km) (FFECS) using data from 2012 survey we showed that, for a sampling error under 10 % in growing stock, growth increment, and dead wood quantity estimations, Slovenia would need at least 2 x 2 km or even 2 x 1.4 km sampling grid of plots we could call national forest inventory. For easier work organization (regular annual tasks of the SFI and SFS) we suggest the implementation of continuous panel inventory system, where the plots on systematic sampling grid are divided into individual groups, the so-called panels, which we later move in such a way, that each panel on the whole country surface is measured in an individual year. With thus organized continual national forest inventory (NFI), we would establish methodologically and statistically well-founded and high-quality information system on forests for annual reports on condition of Slovenian forests on the national level. At the same time, after one recording cycle we would acquire a sufficiently large sample for consistent reports on forest condition on lower spatial levels like provenance areas, forest management areas (FMA), or statistical regions. |
