Brazilian National Forest Inventory - a landscape scale approach to monitoring and assessing forested landscapes
DOI:
https://doi.org/10.4336/2018.pfb.38e201701493Keywords:
Spatial pattern, Forestry policy, IndicesAbstract
The strategic importance of forest resources, both at the national and global level, as well as the scarcity of reliable qualitative and quantitative information about Brazilian forests are among the motivations that led to the implementation of a new national forest inventory in Brazil (IFN-BR). Beyond traditional field survey through clustered sampling, the IFN-BR incorporates Landscape Sample Units (LSU) as a geospatial component of the inventory. Landscape indicators and indices are generated through the analysis of land use/land cover in the LSUs, which provide information about composition, morphology, mosaic patterns, adjacent habitat similarity, connectivity, fragmentation, and state of riparian zones. In the current study, we describe the indicators selected to assess landscape using pilot LSUs established in Paraná State, as well as the calculation and composition of indices and scores.Downloads
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References
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Riitters, K. H. et al. National land-cover pattern data. Ecology, v. 81, n. 604, p.1-15. 2000. DOI: 10.1890/0012-9658(2000)081[0604:NLCPD]2.0.CO;2.
Saura, S. Effects of remote sensor spatial resolution and data aggregation on selected fragmentation indices. Landscape Ecology, v. 19, n. 2, p. 197-209, 2004. DOI: 10.1023/B:LAND.0000021724.60785.65.
Saura, S. Evaluating forest landscape connectivity through conefor sensinode 2.2. In: Lafortezza, R. et al. (Ed.). Patterns and processes in forest landscapes: multiple use and sustainable management. [S.l.]: Springer, 2006. p. 403-422.
Serviço Florestal Brasileiro. Florestas do Brasil em resumo: 2013: dados de 2007-2012. Brasília, DF, 2013. 186 p.
Soille, P. & Vogt, P. Morphological segmentation of binary patterns. Pattern Recognition Letters, v. 30, n. 4, p. 456-459. 2009. DOI: 10.1016/j.patrec.2008.10.015.
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Vogt, P. User guide of guidos toolbox. Ispra: European Commission, 2016. 33 p.
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Wickham, J. D. & Norton, D. J. Mapping and analyzing landscape patterns. Landscape Ecology, v. 9, n. 1, p. 7-23, 1994. DOI: 10.1007/BF00135075.
Wu, J. Effects of changing scale on landscape pattern analysis: Scaling relations. Landscape Ecology, v. 19, n. 2, p. 125-138, 2004. DOI: 10.1023/B:LAND.0000021711.40074.ae.
Yemshanov, D. et al. Assessing land clearing potential in the Canadian agriculture-forestry interface with a multi-attribute frontier approach. Ecological Indicators, v. 54, p. 71-81, 2015. DOI: 1016/j.ecolind.2015.02.019.
Backes, A. Floresta com araucária: importância e usos múltiplos. In: Fonseca, C. R. et al. (Ed.) Floresta com araucária: ecologia, conservação e desenvolvimento sustentável. Ribeirão Preto: Holos, 2009. p. 303-309.
Benson, B. J. & Mackenzie, M. D. Effects of sensor spatial-resolution on landscape structure parameters. Landscape Ecology, v. 10, n. 2, p. 113-120, 1995. DOI: 10.1007/BF00153828.
Brasil. Lei nº 12.651, de 25 de maio de 2012. Dispõe sobre a proteção da vegetação nativa; altera as Leis nos 6.938, de 31 de agosto de 1981, 9.393, de 19 de dezembro de 1996, e 11.428, de 22 de dezembro de 2006; revoga as Leis nos 4.771, de 15 de setembro de 1965, e 7.754, de 14 de abril de 1989, e a Medida Provisória no 2.166-67, de 24 de agosto de 2001; e dá outras providências. Available from: <http://www.planalto.gov.br/ccivil_03/_ato2011-2014/2012/lei/L12651compilado.htm>. Access on: 09 Dec. 2016.
Brena, D. A. Proposição de um sistema de inventario florestal nacional para o Brasil. Ciência Florestal, v. 6, n.1, p. 109-127, 1996.
Clerici, N. et al. Riparian zones where green and blue networks meet: pan-European zonation modelling based on remote sensing and GIS. Luxembourg: Publications Office of the European Union, 2011. (European Union. JRC Scientific and Technical Reports, 24774). DOI: 10.2788/80271. Available from: < https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/riparian-zones-where-green-and-blue-networks-meet-pan-european-zonation-modelling-based>. Access on: 18 Dec. 2016.
Clerici, N. & Vogt, P. Ranking European regions as providers of structural riparian corridors for conservation and management purposes. International Journal of Applied Earth Observation and Geoinformation, v. 21, n. 1, p. 477-483, 2013. DOI: 10.1016/j.jag.2012.07.001.
Estreguil, C. et al. A proposal for an integrated modelling framework to characterise habitat pattern. Environmental Modelling & Software, v. 52, p.176-191, 2014. DOI: https://doi.org/10.1016/j.envsoft.2013.10.011.
Estreguil, C. et al. Habitat landscape pattern and connectivity indices. Wageningen. 2012. Available from: <http://www.researchgate.net/ publication/236024557_Habitat_landscape_pattern_and_connectivity_indices_used_at_varying_spatial_scales_for_harmonized_reporting_in_the_EBONE_project/file/72e7e515d7f91be397.pdf>. Access on: 19 Oct. 2017.
Estreguil, C. & Mouton, C. Measuring and reporting on forest landscape pattern, fragmentation and connectivity in Europe: methods and indicators. Luxembourg: Office for Official Publications of the European Communities, 2009. 69 p. (JRC Scientific and Technical Reports Office for Official). Available from: <https://core.ac.uk/download/pdf/38615393.pdf>. Access on: 19 Oct. 2017.
FAO. Global Forest Assessment 2015: desk reference. Roma, 2015. Available from: < www.fao.org/3/a-i4808e.pdf>. Access on: 19 Oct. 2017.
Freitas, J. V. de et al. Brazil. In: Tomppo, E. et al. (Ed.) National forest inventories: pathways for common reporting. [S. l.]: European Science Foundation, 2010. p. 541-553.
Freitas, J. V. de et al. Brazil. In: Vidal, C. et al. (Ed.). National forest inventories: assessment of wood availability and use. [S. l.]: Springer, 2016. p. 197-212.
Freitas, J. V. de et al. The New Brazilian National Forest Inventory. In: McRoberts, R. E. et al. (Ed.) Proceedings of the eighth annual forest inventory and analysis symposium, 2006 Monterey, CA. Monterey: USDA Forest Service, 2006. p. 9-12.
García-Gigorro, S. & Saura, S. Forest fragmentation estimated from remotely sensed data: Is comparison across scales possible? Forest Science, v. 51, n. 1, p. 51-63, 2005. DOI: 10.1093/forestscience/51.1.51
Haynes, R. W. Forest management in the 21st century: changing numbers, changing context. Journal of Forestry, v. 100, n. 2, p. 38-43, 2002. DOI: 10.1093/jof/100.2.38
Holmgren, P. & Persson, R. Evolution and prospects of global forest assessments. Unasylva, v. 53, n. 210, p. 3-9, 2002. Available from: www.fao.org/docrep/005/y4001e/y4001e02.htm . Access on: 19 Oct. 2017.
Ivits, E. et al. Estimating the ecological status and change of riparian zones in Andalusia assessed by multi-temporal AVHHR datasets. Ecological Indicators, v. 9, n. 3, p. 422-431. 2009. DOI: 10.1016/j.ecolind.2008.05.013.
Jenerette, G. D. & Wu, J. On the definitions of scale. Bulletin of the Ecological Society of America, v. 81, n. 1, p. 104-105, 1997.
Jesus, J. B. & Souza, B. B. Methodology for automatically delimiting permanent preservation areas along water courses: the use of GIS in the hydrological basin of the Sergipe River, Brazil. Revista Árvore, v. 40, n. 2, p. 229-234, 2016. DOI: 10.1590/0100-67622016000200005.
Levin, S. A. The problem of pattern and scale in ecology: the Robert H. MacArthur Award Lecture. Ecology, v. 73, p. 1943-1967, 1992. DOI: 10.2307/1941447.
Lindenmayer, D. et al. A checklist for ecological management of landscapes for conservation. Ecology Letters, v. 11, n. 1, p. 78-91, 2008. DOI: 10.1111/j.1461-0248.2007.01114.x
Luz, N. B. da et al. Developments in forest monitoring under the Brazilian National Forest Inventory: multi-source and hybrid image classification approaches. In: WORLD FORESTRY CONGRESS, 14., 2015, Durban. Forests and people: investing in a sustainable future. Rome: FAO, 2015. p. 7-11.
Machado, S. A. Inventário Florestal Nacional das florestas plantadas nos estados Paraná e Santa Catarina. Brasília, DF: Instituto Brasileiro de Desenvolvimento Florestal, 1984.
Riitters, K. H. et al. An indicator of forest dynamics using a shifting landscape mosaic. Ecological Indicators, v. 9, n. 1, p. 1-14. 2009a. DOI: 10.3097/LO.200913.
Riiters, K. H. et al. Evaluating anthropogenic risk of grassland and forest habitat degradation using land-cover data. Landscape Online, v. 13, n. 1, p.1-14. 2009b. DOI: 10.3097/LO.200913.
Riitters, K. H. et al. National land-cover pattern data. Ecology, v. 81, n. 604, p.1-15. 2000. DOI: 10.1890/0012-9658(2000)081[0604:NLCPD]2.0.CO;2.
Saura, S. Effects of remote sensor spatial resolution and data aggregation on selected fragmentation indices. Landscape Ecology, v. 19, n. 2, p. 197-209, 2004. DOI: 10.1023/B:LAND.0000021724.60785.65.
Saura, S. Evaluating forest landscape connectivity through conefor sensinode 2.2. In: Lafortezza, R. et al. (Ed.). Patterns and processes in forest landscapes: multiple use and sustainable management. [S.l.]: Springer, 2006. p. 403-422.
Serviço Florestal Brasileiro. Florestas do Brasil em resumo: 2013: dados de 2007-2012. Brasília, DF, 2013. 186 p.
Soille, P. & Vogt, P. Morphological segmentation of binary patterns. Pattern Recognition Letters, v. 30, n. 4, p. 456-459. 2009. DOI: 10.1016/j.patrec.2008.10.015.
Turner, M. G. et al. Landscape ecology in theory and practice: pattern and process. New York: Springer, 2001. 406 p.
Vogt, P. User guide of guidos toolbox. Ispra: European Commission, 2016. 33 p.
Wickham, J. D. et al. A national assessment of green infrastructure and change for the conterminous United States using morphological image processing. Landscape and Urban Planning, v. 94, n. 3-4, p.186-195, 2010. DOI: 10.1016/j.landurbplan.2009.10.003
Wickham, J. D. & Norton, D. J. Mapping and analyzing landscape patterns. Landscape Ecology, v. 9, n. 1, p. 7-23, 1994. DOI: 10.1007/BF00135075.
Wu, J. Effects of changing scale on landscape pattern analysis: Scaling relations. Landscape Ecology, v. 19, n. 2, p. 125-138, 2004. DOI: 10.1023/B:LAND.0000021711.40074.ae.
Yemshanov, D. et al. Assessing land clearing potential in the Canadian agriculture-forestry interface with a multi-attribute frontier approach. Ecological Indicators, v. 54, p. 71-81, 2015. DOI: 1016/j.ecolind.2015.02.019.
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Published
2018-06-29
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DA LUZ, Naíssa Batista; GARRASTAZU, Marilice Cordeiro; ROSOT, Maria Augusta Doetzer; MARAN, Jéssica Caroline; DE OLIVEIRA, Yeda Maria Malheiros; FRANCISCON, Luziane; CARDOSO, Denise Jeton; DE FREITAS, Joberto Veloso. Brazilian National Forest Inventory - a landscape scale approach to monitoring and assessing forested landscapes. Pesquisa Florestal Brasileira, [S. l.], v. 38, 2018. DOI: 10.4336/2018.pfb.38e201701493. Disponível em: https://pfb.sede.embrapa.br/pfb/article/view/1493. Acesso em: 19 apr. 2025.
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