Abstract:Resumo: Este artigo apresenta uma proposta de abordagem dos sistemas complexos considerando sua engenharia e definindo medidas cujas evoluções temporais proporcionam indicativos de necessidade de ações preventivas nas fases de projeto, execução e operação de grandes obras.
“…In Portuguese, the term corresponding to window is ‘janela’, which has its root in the word ‘Janus’. ‘ CompPlex Janus ’ is a tribute to Prof. Dr. Sérgio Mascarenhas de Oliveira, the Brazilian scientist who was an enthusiast of Engineering of Complexity and remains a scientific benchmark even after his recent demise [ 53 ]. Both scripts were developed in the Python language, to be executed as plugins in the open-source geographic information system QGIS.…”
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.
“…In Portuguese, the term corresponding to window is ‘janela’, which has its root in the word ‘Janus’. ‘ CompPlex Janus ’ is a tribute to Prof. Dr. Sérgio Mascarenhas de Oliveira, the Brazilian scientist who was an enthusiast of Engineering of Complexity and remains a scientific benchmark even after his recent demise [ 53 ]. Both scripts were developed in the Python language, to be executed as plugins in the open-source geographic information system QGIS.…”
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.
Background: Complexity theory (CT) has been used in response to the need for a different mindset than the classical engineering paradigm. The engineering education research (EER) community may benefit from the knowledge of how CT has been used in the field.Purpose: Aiming to provide a broad view of CT in EER, the following research questions guided the study: How has CT been applied in EER, and how does it contribute to addressing the challenges of classical engineering education? What are the different complexity engineering approaches, and how can they be integrated into the context of EER?Method: A systematic literature review was conducted. The review process was divided into three stages: planning, conducting, and reporting. Fifty-eight journal articles and five book chapters were submitted to an iterative process of organization, categorization, analysis, and synthesis. Results: Complexity schools of thought were integrated into EER. The research was organized into thematic categories: epistemological and ontological perspectives; complex thinking and competences; pedagogical approaches; complexity, sustainability, and transdisciplinarity interdependence; engineering axiology; and systemic transformation of engineering education. For each category, main contributions were integrated, and gaps were identified.Different meanings of complexity engineering were discussed and related to complexity schools of thought.Conclusions: Defining the type of complexity approach used is essential to advance knowledge, as there are fundamental epistemological, ontological, and methodological differences. Thematic categories help future researchers position theoretical contributions and be precise about how their findings contribute to understanding complexity applications in EER. Overcoming the limits of classical engineering requires a paradigmatic discussion, and CT proves valuable for this.
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