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Registro Completo |
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
09/03/2022 |
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Data da última atualização: |
09/03/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MATTOS, S. H. V. L. de; VICENTE, L. E.; KOGA-VICENTE, A.; BIELENKI JUNIOR, C.; PIQUEIRA, J. R. C. |
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Afiliação: |
SÉRGIO HENRIQUE VANNUCCHI LEME DE MATTOS, UFSCar; LUIZ EDUARDO VICENTE, CNPMA; ANDREA KOGA-VICENTE; CLÁUDIO BIELENKI JUNIOR, UFSCar; JOSÉ ROBERTO CASTILHO PIQUEIRA, POLI-USP. |
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Título: |
Metrics based on information entropy applied to evaluate complexity of landscape patterns. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Plos One, v. 17, n.1, e0262680, 2022. |
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Páginas: |
23 p. |
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ISSN: |
1932-6203 |
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DOI: |
https://doi.org/10.1371/journal.pone.0262680 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Landscape is an ecological category represented by a complex system formed by interactions between society and nature. Spatial patterns of different land uses present in a landscape reveal past and present processes responsible for its dynamics and organisation. Measuring the complexity of these patterns (in the sense of their spatial heterogeneity) allows us to evaluate the integrity and resilience of these complex environmental systems. Here, we show how landscape metrics based on information entropy can be applied to evaluate the complexity (in the sense of spatial heterogeneity) of patches patterns, as well as their transition zones, present in a Cerrado conservation area and its surroundings, located in south-eastern Brazil. The analysis in this study aimed to elucidate how changes in land use and the consequent fragmentation affect the complexity of the landscape. The scripts CompPlex HeROI and CompPlex Janus were created to allow calculation of information entropy (He), variability (He/Hmax), and López-Ruiz, Mancini, and Calbet (LMC) and Shiner, Davison, and Landsberg (SDL) measures. CompPlex HeROI enabled the calculation of these measures for different regions of interest (ROIs) selected in a satellite image of the study area, followed by comparison of the complexity of their patterns, in addition to enabling the generation of complexity signatures for each ROI. CompPlex Janus made it possible to spatialise the results for these four measures in landscape complexity maps. As expected, both for the complexity patterns evaluated by CompPlex HeROI and the complexity maps generated by CompPlex Janus, the areas with vegetation located in a region of intermediate spatial heterogeneity had lower values for the He and He/Hmax measures and higher values for the LMC and SDL measurements. So, these landscape metrics were able to capture the behaviour of the patterns of different types of land use present in the study area, bringing together uses linked to vegetation with increased canopy coverage and differentiating them from urban areas and transition areas that mix different uses. Thus, the algorithms implemented in these scripts were demonstrated to be robust and capable of measuring the variability in information levels from the landscape, not only in terms of spatial datasets but also spectrally. The automation of measurement calculations, owing to informational entropy provided by these scripts, allows a quick assessment of the complexity of patterns present in a landscape, and thus, generates indicators of landscape integrity and resilience. MenosAbstract: Landscape is an ecological category represented by a complex system formed by interactions between society and nature. Spatial patterns of different land uses present in a landscape reveal past and present processes responsible for its dynamics and organisation. Measuring the complexity of these patterns (in the sense of their spatial heterogeneity) allows us to evaluate the integrity and resilience of these complex environmental systems. Here, we show how landscape metrics based on information entropy can be applied to evaluate the complexity (in the sense of spatial heterogeneity) of patches patterns, as well as their transition zones, present in a Cerrado conservation area and its surroundings, located in south-eastern Brazil. The analysis in this study aimed to elucidate how changes in land use and the consequent fragmentation affect the complexity of the landscape. The scripts CompPlex HeROI and CompPlex Janus were created to allow calculation of information entropy (He), variability (He/Hmax), and López-Ruiz, Mancini, and Calbet (LMC) and Shiner, Davison, and Landsberg (SDL) measures. CompPlex HeROI enabled the calculation of these measures for different regions of interest (ROIs) selected in a satellite image of the study area, followed by comparison of the complexity of their patterns, in addition to enabling the generation of complexity signatures for each ROI. CompPlex Janus made it possible to spatialise the results for these four measures in landscape c... Mostrar Tudo |
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Thesagro: |
Cerrado; Ecossistema; Floresta; Sensoriamento Remoto; Uso da Terra. |
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Thesaurus Nal: |
Entropy; Forests; Remote sensing. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/232278/1/Vicente-Metrics-based-2021.pdf
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Marc: |
LEADER 03456naa a2200301 a 4500
001 2140699
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008 2022 bl uuuu u00u1 u #d
022 $a1932-6203
024 7 $ahttps://doi.org/10.1371/journal.pone.0262680$2DOI
100 1 $aMATTOS, S. H. V. L. de
245 $aMetrics based on information entropy applied to evaluate complexity of landscape patterns.$h[electronic resource]
260 $c2022
300 $a23 p.
520 $aAbstract: Landscape is an ecological category represented by a complex system formed by interactions between society and nature. Spatial patterns of different land uses present in a landscape reveal past and present processes responsible for its dynamics and organisation. Measuring the complexity of these patterns (in the sense of their spatial heterogeneity) allows us to evaluate the integrity and resilience of these complex environmental systems. Here, we show how landscape metrics based on information entropy can be applied to evaluate the complexity (in the sense of spatial heterogeneity) of patches patterns, as well as their transition zones, present in a Cerrado conservation area and its surroundings, located in south-eastern Brazil. The analysis in this study aimed to elucidate how changes in land use and the consequent fragmentation affect the complexity of the landscape. The scripts CompPlex HeROI and CompPlex Janus were created to allow calculation of information entropy (He), variability (He/Hmax), and López-Ruiz, Mancini, and Calbet (LMC) and Shiner, Davison, and Landsberg (SDL) measures. CompPlex HeROI enabled the calculation of these measures for different regions of interest (ROIs) selected in a satellite image of the study area, followed by comparison of the complexity of their patterns, in addition to enabling the generation of complexity signatures for each ROI. CompPlex Janus made it possible to spatialise the results for these four measures in landscape complexity maps. As expected, both for the complexity patterns evaluated by CompPlex HeROI and the complexity maps generated by CompPlex Janus, the areas with vegetation located in a region of intermediate spatial heterogeneity had lower values for the He and He/Hmax measures and higher values for the LMC and SDL measurements. So, these landscape metrics were able to capture the behaviour of the patterns of different types of land use present in the study area, bringing together uses linked to vegetation with increased canopy coverage and differentiating them from urban areas and transition areas that mix different uses. Thus, the algorithms implemented in these scripts were demonstrated to be robust and capable of measuring the variability in information levels from the landscape, not only in terms of spatial datasets but also spectrally. The automation of measurement calculations, owing to informational entropy provided by these scripts, allows a quick assessment of the complexity of patterns present in a landscape, and thus, generates indicators of landscape integrity and resilience.
650 $aEntropy
650 $aForests
650 $aRemote sensing
650 $aCerrado
650 $aEcossistema
650 $aFloresta
650 $aSensoriamento Remoto
650 $aUso da Terra
700 1 $aVICENTE, L. E.
700 1 $aKOGA-VICENTE, A.
700 1 $aBIELENKI JUNIOR, C.
700 1 $aPIQUEIRA, J. R. C.
773 $tPlos One$gv. 17, n.1, e0262680, 2022.
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Embrapa Meio Ambiente (CNPMA) |
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