000			03301nam a22003735i 4500
001			393922
003			ES-MaUEC
005			20230102123036.0
007			cr nn 008mamaa
008			220907s2022 sz | s |||| 0|eng d
020			_a9783031064050
024	7		_a10.1007/978-3-031-06405-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
100	1		_aSims, Allan _eautor _0(orcid)0000-0003-1312-6940 _1https://orcid.org/0000-0003-1312-6940 _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aPrinciples of National Forest Inventory Methods _bTheory, Practice, and Examples from Estonia _cby Allan Sims
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XI, 162 páginas) _b63 ilustraciones, 47 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aManaging Forest Ecosystems _x2352-3956 _v43
505	0		_aChapter 1. Introduction of NFI and LULUCF -- Chapter 2. Definition and uncertainty of forests -- Chapter 3. Tree and its measurement -- Chapter 4. Design of sample plots methods -- Chapter 5. Forest statistics preparation and calculation -- Chapter 6. Remeasurement of sample plots -- Chapter 7. Remote sensing data and methods in NFI -- Chapter 8. Continuous NFI design of a sample plot -- Chapter 9. NFI as open data method -- Chapter 10. Analysis of forest dynamics with NFI data -- Chapter 11. Sustainable forestry analysis method based on sample plot data.
520			_aThis Monograph explains the statistical theory behind the National Forest Inventory (NFI) data collection and compares different methods for modelling and inventory design. The author also explains how natural uncertainty in measurement and modelling can affects the results. Forests, as dynamic systems, are influenced by many unpredictable factors over time. Therefore, readers can use this book to develop the right framework of expectations, when using NFI data. The chapters give an outlook on traditional methods like sample plots, but also consider newer approaches like remote sensing. By merging these different techniqes, NFI datasets can become more reliable and facetted. One of the most contemporary developments in the field, is the use of continuous plots that offer live data at all times. Whether this data should be open to the public, is another discussion point that the author addresses. Offering a perspective from Estonia, readers will find practical examples for all discussed methods. This bridge from theory to practice, makes the volume a useful resource for scientists and decision makers in the forestry sector. .
776	0	8	_iPrinted edition: _z9783031064043
776	0	8	_iPrinted edition: _z9783031064067
776	0	8	_iPrinted edition: _z9783031064074
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-06405-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_BiomedLife_2022
999			_c393922 _d393922