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Con los últimos avances en el campo del Big Data, el uso, análisis e interpretación de los datos cobra una especial relevancia en la definición y ajuste de la estrategia de muchas empresas. En este contexto, se identifica la necesidad de introducir en el perfil de los ingenieros y titulados en empresariales, el uso de herramientas de análisis y visualización de datos. Este artículo presenta un caso de diseño de una actividad práctica de sistemas de información basado en aprendizaje experiencial, que combina el uso de un ERP con herramientas de gestión y análisis de datos. La práctica persigue fomentar habilidades ligadas al uso de estas herramientas además de transmitir la importancia de su integración para generar valor en las empresas.

espanolCada vez es mayor la integracion entre ensenanza virtual y presencial. Esto esta pro-duciendo un incremento de la ensenanza mixta o blended-learning. Dada la creciente tendencia de integracion de la ensenanza virtual en la formacion presencial, surge la necesidad de reutilizar componentes entre dichas estrategias en interes de la eficiencia. Adicionalmente, la gran disponibilidad de software de codigo abierto facilita la cons-truccion de actividades docentes sin incurrir en costes de licencias, las cuales que pue-den formar parte de distintos cursos de formacion. La reutilizacion de estas actividades docentes en la ensenanza virtual y mixta puede requerir impor-tantes esfuerzos de adaptacion de las mismas si previamente no se ha tenido en cuenta esta posibilidad en su diseno. Estas labores pueden simplificarse mediante la adopcion de arquitecturas y metodologias que favorezcan la flexibilidad y la reutilizacion, tal como se propone en este trabajo. Adicionalmente, se presenta un caso de reutilizacion de actividades do-centes de un MOOC de la plataforma edX dedicado a Sistemas de Informacion, en el que actividades docentes son reutilizadas en otros cursos de distinta modalidad: online, hibridos y presenciales. EnglishThe integration between virtual and face-to-face (ftf) classroom learning is increasing. This is leading to an increase in mixed learning or blended-learning. Due to this growing trend there is a need to reuse course components between these strategies in the interest of efficiency. Additionally, the wide availability of open source software facilitates the construction of learning activities without incurring in licences expenses; activities which can then also be included in other courses. The reuse of these learning activities between virtual, ftf and mixed education may require significant efforts to adapt them if this possibility has not been considered in advance. Adoption of certain architectures and methodologies, that facilitate flexibility and reuse, can simplify this process, as proposed in this paper. A case study is presented on reusing learning activities on Management Information Systems (MIS) developed for either ftf instruction or for an edX MOOC, that are reused in courses in various learning modes: online, blended learning and face-to-face.

Research Highlights: This study advances the effort to accurately estimate the biomass of trees in peatlands, which cover 13% of Canada’s land surface. Background and Objectives: Trees remove carbon from the atmosphere and store it as biomass. Terrestrial laser scanning (TLS) has become a useful tool for modelling forest structure and estimating the above ground biomass (AGB) of trees. Allometric equations are often used to estimate individual tree AGB as a function of height and diameter at breast height (DBH), but these variables can often be laborious to measure using traditional methods. The main objective of this study was to develop allometric equations using TLS-measured variables and compare their accuracy with that of other widely used equations that rely on DBH. Materials and Methods: The study focusses on small black spruce trees (&lt, 5 m) located in peatland ecosystems of the Taiga Plains Ecozone in the Northwest Territories, Canada. Black spruce growing in peatlands are often stunted when compared to upland black spruce and having models specific to them would allow for more precise biomass estimates. One hundred small trees were destructively sampled from 10 plots and the dry weight of each tree was measured in the lab. With this reference data, we fitted biomass models specific to peatland black spruce using DBH, crown diameter, crown area, height, tree volume, and bounding box volume as predictors. Results: Our best models had crown size and height as predictors and outperformed established AGB equations that rely on DBH. Conclusions: Our equations are based on predictors that can be measured from above, and therefore they may enable the plotless creation of accurate biomass reference data for a prominent tree species in a common ecosystem (treed peatlands) in North America’s boreal.

Research Highlights: This is the most comprehensive analysis to date of the accuracy of height estimates for individual conifer seedlings derived from drone-based image point clouds (DIPCs). We provide insights into the effects on accuracy of ground sampling distance (GSD), phenology, ground determination method, seedling size, and more. Background and Objectives: Regeneration success in disturbed forests involves costly ground surveys of tree seedlings exceeding a minimum height. Here we assess the accuracy with which conifer seedling height can be estimated using drones, and how height errors translate into counting errors in stocking surveys. Materials and Methods: We compared height estimates derived from DIPCs of different GSD (0.35 cm, 0.75 cm, and 3 cm), phenological state (leaf-on and leaf-off), and ground determination method (based on either the DIPC itself or an ancillary digital terrain model). Each set of height estimates came from data acquired in up to three linear disturbances in the boreal forest of Alberta, Canada, and included 22 to 189 surveyed seedlings, which were split into two height strata to assess two survey scenarios. Results: The best result (root mean square error (RMSE) = 24 cm, bias = &minus, 11 cm, R2 = 0.63, n = 48) was achieved for seedlings &gt, 30 cm with 0.35 cm GSD in leaf-off conditions and ground elevation from the DIPC. The second-best result had the same GSD and ground method but was leaf-on and not significantly different from the first. Results for seedlings &le, 30 cm were unreliable (nil R2). Height estimates derived from manual softcopy interpretation were similar to the corresponding DIPC results. Height estimation errors hardly affected seedling counting errors (best balance was 8% omission and 6% commission). Accuracy and correlation were stronger at finer GSDs and improved with seedling size. Conclusions: Millimetric (GSD &lt, 1 cm) DIPC can be used for estimating the height of individual conifer seedlings taller than 30 cm.

[ES] La enseñanza de Sistemas de Información Gerencial (SIG) precisa una metodología activa en la que el alumno utilice y experimente con estos sistemas en entornos similares a la realidad empresarial. Ahora bien, el diseño y desarrollo de prácticas de laboratorio con estos sistemas exige como prerrequisito disponer del correspondiente software, cargado con un conjunto de datos apropiado. En los últimos años, el auge de los sistemas de código abierto y el movimiento hacia la computación en la nube, hacen habitual, por una parte, encontrar en internet “demos” online de libre acceso, o sistemas de prueba con distintos grados de usabilidad, de aplicaciones empresariales. Por otra parte, los sistemas de código abierto permiten, si se dispone de los conocimientos y las plataformas hardware adecuadas, su descarga, instalación y configuración en modo local sin incurrir en coste de licencias. Esto abre un abanico de opciones en cuanto a la arquitectura a utilizar para el diseño de actividades educativas basadas en aplicaciones software, con diferentes ventajas, inconvenientes y requerimientos de recursos. Desde el simple acceso en modo visualización a “demos” existentes en la nube a la descarga y personalización del software en local, pasando por opciones híbridas que combinan estos enfoques en la misma práctica docente. Así, en este trabajo se presentan posibles arquitecturas híbridas para la implantación de actividades docentes de prácticas de laboratorio basadas en la combinación de tareas realizadas en sistemas de libre acceso en la nube y en sistemas implantados localmente. Estos conceptos se ilustran con una experiencia de aplicación de estas arquitecturas híbridas en el diseño de una práctica de laboratorio de la Universidad Carlos III de Madrid basada en aplicaciones de código abierto. Esta experiencia combina un entorno implantado localmente y aplicaciones online en la nube, partiendo del mismo juego de datos en ambos entornos.

The oil and gas industry has grown significantly throughout the boreal and arctic ecosystems of North America. A major feature of the ecological footprint of oil and gas exploration is seismic lines—narrow corridors used to transport and deploy geophysical survey equipment. These lines, which traverse forests, tundra, uplands, and peatlands, were historically up to 10 m wide. Over the past decade, seismic lines have decreased in width (in some cases down to 1.75–3 m); however, their density has increased drastically and their construction is expected to continue in regions of Canada and the United States that are rich in oil and gas resources. We examine the literature related to the environmental impacts of, and restoration and reclamation efforts associated with, seismic lines in the boreal and arctic ecosystems of North America. With respect to conventional seismic lines, numerous studies report significant and persistent environmental changes along these lines and slow recovery of vegetation that translates into a lasting fragmentation of the landscape. This fragmentation has many ramifications for biodiversity and ecosystem processes, including significant implications for threatened woodland caribou herds. While modern, low-impact seismic lines have comparatively lower ecological effects at the site-level, their high density and associated potential edge effects suggest that their actual environmental impact may be underestimated. Seismic line restoration is a critical aspect of future integrated landscape management in hydrocarbon-rich regions of the boreal-arctic, and if widely applied, has the potential to benefit a wide range of species and maintain or re-establish key ecosystem services such as carbon sequestration and biodiversity.

Background: Intensive-care unit (ICU) patients are prone to healthcare-associated infections which are often recurrent. Such infections are influenced by previous occurrences and hence correlation between events needs to be taken into account when modelling the risk of infection recurrence. Objective: To compare five different survival-time models, the Cox proportional hazards model (CPH) and three of its extensions to recurrent event data: Andersen-Gill (AG), Prentice-Williams-Peterson (PWP) and Frailty models. Methods: The models were empirically assessed by direct application to data from a cohort study of 550 patients with ICU-acquired infections. Covariate data included patients sex, age, Glasgow, Apache-II and comorbidity scores, and exposures to medical devices, treatment appropriateness and infection site and resistance to carbapenems. Models were compared using accuracy criteria and goodness-of-fit statistics. Results: 180/550 (33%) patients had infection recurrence, of whom 128 had a first, 40 a second and 12 a third recurrence. All models agreed in the direction of effect for all covariates. However, the CPH model for the risk of first recurrence disregarded data on 64 (26%) of infections, produced the more pronounced hazard ratio estimates, and presented the poorest data fit and accuracy measures. Model fit and accuracy improved in all extended models, with PWP performing best in terms of log-likelihood, Akaike and Bayesian information criteria. Conclusion: The PWP model is based on plausible assumptions in the context of modelling the risk of infection recurrence and was shown in this study to outperform alternative extensions for modelling recurrent events.

Los MOOC (Massive Open Online Courses) son un recurso docente potencialmente muy valioso, bien como instrumento en sí o como complemento de la docencia presencial. Uno de sus principales inconvenientes es la dedicación y esfuerzo requerido para el desarrollo de un MOOC de calidad. El número de MOOC que una institución educativa desarrolla con temáticas similares, personalizados para distintas audiencias y contextos se incrementa cada año. Por tanto, cobra importancia la oportunidad de reutilizar componentes de los MOOC ya desarrollados para disminuir el coste y el tiempo de producción de los nuevos MOOC. Dado que es un fenómeno relativamente reciente, no es infrecuente que las instituciones, se planteen esta necesidad de reutilización únicamente a posteriori, cuando surgen las necesidades de nuevos MOOC relacionados o de variantes del inicial. Esto les enfrenta a importantes dificultades, que podrían haberse paliado con un diseño orientado desde el principio a la flexibilidad y la reutilización, adoptando metodologías como las propuestas en este trabajo. Esta orientación a la reutilización puede inspirarse en metodologías desarrolladas en otros ámbitos con ese mismo propósito, como la programación estructurada, la programación modular y más concretamente la programación orientada a objetos. Los componentes de los MOOC cuyo desarrollo consume más recursos son normalmente los vídeos y los test de evaluación. En este trabajo se revisan buenas prácticas de diseño de estos componentes que facilitan su reutilización de forma eficiente. Este trabajo presenta el caso de reutilización de diversos componentes de un MOOC de la plataforma edX dedicado a Sistemas de Información, inicialmente diseñado para una gran diversidad de participantes, cuyos componentes son reutilizados para desarrollar otros dos cursos virtuales: un SPOC (Small Private Online Course) específico para alumnos de ingeniería y un segundo sobre la toma de decisiones empresariales dirigido a personal de administración y servicios de Naciones Unidas (UN).

Coarse woody debris (CWD, large parts of dead trees) is a vital element of forest ecosystems, playing an important role in nutrient cycling, carbon storage, fire fuel, microhabitats, and overall forest structure. However, there is a lack of effective tools for identifying and mapping both standing (snags) and downed (logs) CWD in complex natural settings. We applied a random forest machine learning classifier to detect CWD in centimetric aerial imagery acquired over a 270-hectare study area in the boreal forest of Alberta, Canada. We used a geographic object-based image analysis (GEOBIA) approach in the classification with spectral, spatial, and LiDAR (light detection and ranging)-derived height predictor variables. We found CWD to be detected with great accuracy (93.4 &plusmn, 4.2% completeness and 94.5 &plusmn, 3.2% correctness) when training samples were located within the application area, and with very good accuracy (84.2 &plusmn, 5.2% completeness and 92.2 &plusmn, 3.2% correctness) when training samples were located outside the application area. The addition of LiDAR-derived variables did not increase the accuracy of CWD detection overall (&lt, 2%), but aided significantly (p &lt, 0.001) in the distinction between logs and snags. Foresters and researchers interested in CWD can take advantage of these novel methods to produce accurate maps of logs and snags, which will contribute to the understanding and management of forest ecosystems.

We present the Change , Aftereffect , and Trend (CAT) transform for visualizing and analyzing landscape dynamics from dense, multi-annual satellite vegetation index (VI) time series. The transform compresses a temporally detailed, multi-annual VI dataset into three new variables capturing change events and trends occurring within that period. First, peak annual greenness is extracted from each year. Then a series of simple calculations generate the three CAT variables: 1) Change : the maximum interannual absolute difference in peak greenness between consecutive years; 2) Aftereffect : the mean peak greenness after Change occurred; and 3) Trend : the slope of a linear regression applied to the entire annual peak greenness time series. We demonstrate the CAT transform by applying it to a MODIS 16-day 250-m normalized difference VI (NDVI) dataset covering the province of Alberta, Canada, for 2001 through 2011. We find that the CAT variables capture much of the non-seasonal change in the original NDVI time series. When displayed as an RGB color composite (the CAT image), the transform provides a striking visualization of both drastic and gradual decadal-scale landscape dynamics. Its application to quantitative analyses is demonstrated by an urban sprawl case study conducted around the city of Calgary, Alberta, where a simple decision-tree-based classification of the CAT transform variables was superior to a bitemporal, image-differencing approach. The simple yet powerful CAT transform is easily applicable to other study areas and datasets, and could foster a wider usage and understanding of the many archived high-temporal-resolution satellite datasets currently available.

Outbreaks of insect pests periodically cause large losses of volume in Canada’s forests. Compounded with climate change, outbreaks create significant challenges for managing the sustainable delivery of ecosystem services. Current methods to monitor damage by these pests involve both field and aerial surveys. While relatively cost effective and timely, aerial survey consistency and spatial coverage may be insufficient for detailed monitoring across Canada’s vast forest-land base. Remote sensing can augment these methods and extend monitoring capabilities in time and space by incorporating knowledge of pest-host interactions and of how damage translates into a remote sensing signal for detection and mapping. This review provides a brief introduction to major forest insect pests in Canada (two bark beetles (Coleoptera: Curculionidae) and six defoliators) and the damage they cause, a synthesis of the literature involving aerial survey and remote sensing, and a discussion of how these two approaches could be integrated into future pest monitoring from a Canadian perspective. We offer some lessons learned, outline roles that remote sensing could serve in a management context, and discuss what ongoing and upcoming technological advances may offer to future forest health monitoring.

Rapid assessment of forest regeneration using unmanned aerial vehicles (UAVs) is likely to decrease the cost of establishment surveys in a variety of resource industries. This research tests the feasibility of using UAVs to rapidly identify coniferous seedlings in replanted forest-harvest areas in Alberta, Canada. In developing our protocols, we gave special consideration to creating a workflow that could perform in an operational context, avoiding comprehensive wall-to-wall surveys and complex photogrammetric processing in favor of an efficient sampling-based approach, consumer-grade cameras, and straightforward image handling. Using simple spectral decision rules from a red, green, and blue (RGB) camera, we documented a seedling detection rate of 75.8 % (n = 149), on the basis of independent test data. While moderate imbalances between the omission and commission errors suggest that our workflow has a tendency to underestimate the seedling density in a harvest block, the plot-level associations with ground surveys were very high (Pearson&rsquo, s r = 0.98, n = 14). Our results were promising enough to suggest that UAVs can be used to detect coniferous seedlings in an operational capacity with standard RGB cameras alone, although our workflow relies on seasonal leaf-off windows where seedlings are visible and spectrally distinct from their surroundings. In addition, the differential errors between the pine seedlings and spruce seedlings suggest that operational workflows could benefit from multiple decision rules designed to handle diversity in species and other sources of spectral variability.

Aim/Purpose: The aim of this work is to explore which factors impact on the adoption of the flipped classroom in vocational education to pave the way for the schools which want to apply this model. Background: Although various experiences in the use of the flipped classroom have been reported in recent years in the literature, fewer efforts have been done on how to implement this model from a pedagogical standpoint. The factors that influence its adoption have not been studied in depth, at least not in a global way. These factors include the use of technology and teaching methodologies active in the classroom, the trend towards innovation of teachers and schools, and whether teachers have the necessary ICT training and infrastructures. Moreover, although the results of many experiences in Higher Education have been published, this is not so for other levels of education, such as vocational schools. Methodology: A quantitative research method was used by constructing a questionnaire. The questionnaire included open questions in order to obtain qualitative information, which enriched the results obtained. Descriptive and factor analysis was used to analyze data, within the framework of the project FlipIT!–Flipped Classroom in the European Vocational Education”, ERASMUS+ Strategic Partnership (2015-1-HU01-KA202-013555) funded by the European Union, with the participation of Hungary, the United Kingdom, Ireland, the Czech Republic, and Spain. The research sample includes 625 teachers (434 from Spain, 121 from Hungary and 61 from the Czech Republic) from schools participating or somehow associated to the project. Contribution: An empirically validated framework of the factors influencing the adoption of the flipped classroom approach in schools was obtained. This framework can guide the curriculum design of flipped classroom model courses for vocational education teachers. Findings: Empirically validated factors for the adoption of the flipped classroom in technical schools are presented. In addition, descriptive analysis results from a sample of 625 vocational education teachers confirmed that the countries involved in the survey fulfill the factors needed for the adoption of the flipped classroom in vocational education schools. Another important result is that, according to the surveyed teachers, the flipped classroom is a strongly practice-oriented method very suitable for vocational education. Recommendations for Practitioners: The framework here presented can guide the curriculum design of flipped classroom model courses for vocational and technical education teachers and allow schools to know the factors to review and improve in order to use the model. Recommendation for Researchers: This study is a first step toward determining the factors needed for the adoption of the flipped classroom model in vocational and technical schools. More studies using alternative data sources and methods are needed to obtain a definite model to support this adoption since FC has proved to be a very successful model for motivating students. We hope these results pave the way for schools who want to adopt the FC model and for focusing teaching training on the competences that this work detected. Impact on Society: Recently, we are witnessing an important debate about the future of education at every level. Different innovative methodologies have emerged in a search for more motivating and effective ways to learn, as well as to develop in our students the so-called 21st-century skills such as critical thinking, communication and collaboration, creativity, and information, media and technology skills. The flipped classroom approach can help to improve vocational education by changing traditional classes and teaching students other important soft skills, such as teamwork and collaboration, reflection, digital skills, and self-study. Future Research: The model is currently being implemented in schools in Spain, Hungary, and the Czech Republic using the results obtained here under the framework of the European project “FlipIT!–Flipped Classroom in the European Vocational Education”, ERASMUS+ Strategic Partnership (2015-1-HU01-KA202-013555). After checking the criteria obtained in the framework for each of the participating schools, as a first step, an online course has been created using the competences obtained in this framework, both pedagogical and ICT. Once the course is completed, the teachers will carry out a pilot project to use the model. We hope the framework is useful to other researchers in order to implement the model in other countries and extend it with other criteria to obtain a validated international framework. This study is a first step toward determining the factors needed for the adoption of the flipped classroom model in technical schools. More studies using alternative data sources and methods are needed to obtain a definite model to support this adoption since FC has proved to be a very successful model for motivating students. We hope these results pave the way for schools who want to adopt the FC model and for focusing teacher training on competences.

A critical factor in the effective use of technology to enhance or support teaching and learning (referred to, among other things, as technology enhanced learning, or e-learning) is that the technology itself does not overshadow or substitute good quality teaching. While these developments in technology do offer increased and enhanced educational opportunities, any new approaches to teaching and learning should be complemented by knowledge of lear ning theory and pedagogy. Too often the danger arises that the technology erroneously represents some form of “magic bullet”, which can reduce the workload on teachers and facilitate new and better means of learning for students. This can frequently be the case, but this assumption can often miss the need for effort, structure and discipline on the part of all stakeholders to make sure that the technology appropriately and effectively supports the learning and that it has a clear role to play in the learning process - that the technology, for lack of a better term - “knows its place”. As Beetham and Sharpe (2013) note, while digital tools and technologies provide opportunities for “informal, self-directed, independent learning activities”, this in itself is not education. Beetham & Sharpe (2013) argue: “Pedagogy is about guiding learning, rather than leaving you to finding your own way […] our digital native students may be able to use technologies, but that does not mean they can learn from them. Being able to read and write never meant you could therefore learn from books. Learners need teachers.” . And while teachers may look to incorporate innovative strategies in their teaching and learning, a focus needs to “place students at the heart of the education process, [...] to shift to more student-centred, immersive learning experiences, deep faculty/student relationships and the development of critical thinking capacities which remain risk-free for the student experience” (Mukerjee 2014; Norris et al 2012). It is in this context that, on behalf of the Cork Institute of Technology, we are delighted to help participate in the project "FlipIT! -Flipped Classroom in the European Vocational Education” and to have been involved in the development of this E-book. We hope that the information contained within will be of help to both teachers and students (and potentially to other stakeholders) in helping to guide and support the planning and the implementation of the flipped classroom in their respective classrooms (flipped or not). We would also like to credit the work performed by project managers Mária Hartyányi and Judit Mezei from iTStudy Hungary in bringing the project to successful completion. Proyecto financiado por la Comisión Europea No data (2018) UEM

We recently completed the accuracy assessment of a Landsat-derived landcover polygon layer covering the entire province of Alberta 660,000 km2, Canada, for which we gathered reference information for nearly 5000 randomly selected polygons ranging from two hectares to thousands of hectares in size. This gave us the unique opportunity to quantify, for the first time, how the probability of correctly classifying a landcover object varies with its size. Irrespective of whether they are represented as polygons or as sets of connected pixels with the same label, the classification accuracy of landcover objects decreases as their size decreases, steadily for large and medium sizes, and more dramatically when they are within two orders of magnitude of the pixel size of the input image. We show that this size-dependency is bound to occur whenever the size distribution of landcover objects follows an inverse power law. Our results are consistent with previous studies on related issues, confirm the need to account for size when assessing the accuracy of object-based landcover maps, and cast doubts on the validity of 1 recently proposed object-based accuracy estimators, and 2 landscape pattern analyses where the minimum patch size is close to the pixel size.

Conventional forests inventories narrowly focus on timber attributes and often neglect other aspects that may be relevant for other purposes. In an effort to broaden the usefulness of these inventories, we introduce a new protocol based on softcopy photo-interpretation for efficiently capturing both natural and anthropogenic features across a variety of landscapes. Salient aspects of this protocol include (1) the combined use of polygon, point and line feature representation; (2) over 50 fields per attribute table; and (3) semi-automated quality control tools. We show an application example over a 3-km by 7-km sample area in central-eastern Alberta.

Resumen : La funcion de las Sociedades medicas, mas alla de la generacion de conocimiento cientifico y de la actualizacion de habilidades y tratamientos medicos que puedan ser aplicados en la practica clinica diaria, no tendria sentido sin una meditada planificacion y estructuracion que transmita correctamente dichos conocimientos a la poblacion general. De hecho, la comunicacion deberia ser el vehiculo sobre el que se sustenten las acciones de una Sociedad Cientifica. De su relacion con los medios de comunicacion y del uso adecuado de los numerosos canales que divulgacion que permiten las nuevas tecnologias depende que la informacion en salud sea lo mas rigurosa y didactica posible. Con ello, se consigue potenciar la socializacion del saber medico y reforzar la educacion del paciente experto, estableciendo nuevas relaciones entre el medico y el paciente que cuenten con las garantias que ofrece una Sociedad cientifica. Palabras clave : Comunicacion en salud; Sociedad Medica; Medios de comunicacion; Nuevas tecnologias; redes sociales. Abstract : The function of Health Societies, further than the scientific knowledge, actualization of abilities and medical treatments that could be used in the dairy medical use, couldn’t have any sense without a meditated structure planning that could explain properly the know-how to our society. In fact, communication should be the base of all the actions of any Scientific Society. From the relationship with the social media and appropriate use by the different channels that offer us new technologies, depends that health education could be the most serious and didactic as possible only so, we can ensure accessible medical knowledge and maximize the patient education, creating new relationships between doctors and patients that only Health Societies could offer. Key words : Communication in health; Medical Society; Mass media; New technologies; Social media doi: http://dx.doi.org/10.20318/recs.2016.3131

Modern ecological models often account for the influence of the surrounding environment by using landscape pattern indices (LPIs) as measures of landscape structure. Ideally, the landscape samples from which these LPIs are ex- tracted should be centered on the locations where the response variable was measured. However, in situations where this is not possible due to a lack of adequate full-coverage landcover data, the question arises as to what degree this circumstance creates a bias in the value of the LPIs, thereby obscuring their relation with the response variable. To address this question, we extracted four representative LPIs from 30 rectangular (3 × 6 km) landscape samples evenly distributed across a 10 000 km 2 boreal forest study area. These rectangles were subjected to systematic displacements across a range of distances (0.5 to 2.5 km) and directions, after which we recomputed the LPIs. We found that a 1 km spatial offset led to an average of 15% deviation of original LPI values. Unfortunately, as the offset increased, the range of resulting deviations also widened, making it difficult to predict this effect. Our findings fill a gap in the literature on landscape pattern analysis and suggest that researchers should avoid LPIs extracted from spatially offset landscape samples. Resume : Les modeles ecologiques modernes tiennent souvent compte de l'influence de l'environnement avoisinant en utili- sant des indices paysagers (IP) comme mesure de la structure du paysage. Les regions pour lesquelles ces IP sont extraits devraient idealement provenir du centre des endroits ou la variable etudiee a ete mesuree. Cependant, dans les cas ou cela n'est pas possible du au manque de donnees qui couvrent adequatement toute la couverture terrestre, la question surgit a sa- voir jusqu'a quel point cette situation cree un biais dans la valeur des IP, obscurcissant ainsi leur relation avec la variable etudiee. Pour aborder cette question, nous avons extrait quatre IP representatifs de 30 echantillons rectangulaires (3 × 6 km) de paysage egalement repartis dans une zone d'etude de 10 000 km 2 de foret boreale. Ces rectangles ont ete soumis a des deplacements systematiques sur une serie de distances (0,5 a 2,5 km) et dans differentes directions apres quoi les IP ont ete recalcules. Nous avons trouve qu'un decalage spatial d'un kilometre entrainait une deviation moyenne de 15 % par rapport aux valeurs d'IP originales. Malheureusement, a mesure que le decalage augmente, la dispersion des deviations qui en re- sulte s'accroit, ce qui rend difficile la prediction de cet effet. Nos resultats comblent une lacune dans la litterature et indi- quent que les chercheurs devraient eviter d'extraire des IP a partir d'echantillons decales de paysage. (Traduit par la Redaction)

We introduce an automated change detection and delineation tool for remote sensing images: the Land-cover Change Mapper (LCM). LCM rapidly generates a polygon vector layer (shapefile) of regions deemed to have undergone significant change in land-cover. In its simplest usage, LCM requires two single band or multi-band co-registered images of the same scene acquired at different dates, and as the only user-defined parameter, the minimum size for change regions. The main advantages of this tool are that (a) it is fully unsupervised, (b) it is exceptionally fast, (c) it is robust to geometric misregistration errors and variations in illumination, and (d) it produces visually pleasing outlines that resemble those obtained through manual digitization. We describe how the tool works, illustrate its application to monitoring forest clear-cuts on a 1,000 km 2 area in Western Canada using SPOT imagery, compare it to a commercial tool, and report on its thematic and spatial accuracy. A freeware LCM version is available on the Internet.

We argue that thematic resolution, i.e., the level of categorical detail of a thematic map expressed by the number of classes included in the map legend, is an inherent component of the scale at which a landscape is analyzed. Changing the number of classes can change the configuration of the patch mosaic as much as changing the grain does. We address recent calls in this and other journals to deepen research in this topic. In particular, we report how thematic resolution affects the patchiness of mosaics representing natural landscapes, which have seldom been studied in this respect. We selected seven 50 × 50 km landscapes within national parks, each representative of a world biome. We applied an object-based unsupervised classification to Landsat TM imagery of these landscapes using increasing numbers of classes, between 2 and 50, and derived curves of mean patch size and patch density for each site. Our results are consistent with previous findings in that the patchiness of output mosaics increases monotonically with increasing thematic resolution, with a higher rate of increase up to eight classes that declines until it becomes roughly constant for more than 16 classes. However, this constant rate of increase is still considerable, meaning that, at least for natural landscapes, there is no threshold beyond which the patch-mosaic model is independent of the conceptual filter applied. This dependence on human fiat calls for re-thinking the patch-mosaic paradigm.

High spatial resolution satellite imagery, with pixel sizes of one metre or less, are increasingly available. These data provide an accessible and flexible source of information for forest inventory purposes. In addition, the digital nature of these data provides an opportunity for automated and computer-assisted approaches for forest stand delineation to be considered. Specifically, automation has the potential to realize cost savings by minimizing the time required for manual delineation of forest stands; however, inappropriate automation could result in increased costs due to time-consuming revisions of automated delineations. The aim of this research is to present, through example, investigations of an automated segmentation approach for delineating homogeneous forest stands on high spatial resolution satellite imagery. An evaluation of the suitability of IKONOS 1-m panchromatic data for this application is also presented, along with several key issues that must be considered regarding automated segmentation approaches. Key words: forest inventory, segmentation, automation, IKONOS, high spatial resolution satellite, photo interpretation, stand delineation, object

Over the last decade the analysis of Earth observation data has evolved from what were predominantly per-pixel multispectral-based approaches, to the development and application of multiscale object-based methods. To empower users with these emerging object-based approaches, methods need to be intuitive, easy to use, require little user intervention, and provide results closely matching those generated by human interpreters. In an attempt to facilitate this, we present multiscale object-specific segmentation (MOSS) as an integrative object-based approach for automatically delineating image-objects (i.e., segments) at multiple scales from a high-spatial resolution remotely sensed forest scene. We further illustrate that these segments cognitively correspond to individual tree crowns, ranging up to forest stands, and describe how such a tool may be used in computer-assisted forest inventory mapping. MOSS is composed of three primary components: object-specific analysis (OSA), object-specific upscaling (OSU), and a new segmentation algorithm referred to as size constrained region merging (SCRM). The rationale for integrating these methods is that the first two provide the third with object-size parameters that otherwise would need to be specified by a user. Analysis is performed on an IKONOS-2 panchromatic image that represents a highly fragmented forested landscape in the Sooke Watershed on southern Vancouver Island, BC, Canada.

Traditionally, general skills and personal growth have been developed through cognitive processes within academic contexts. Development based on experience may be an alternative route to achieve cognitive knowledge. Enact-learning is based on the biunivocal relationship between knowledge and action. Action is movement. Participants interact with their environment through movement. When participants are aware of this interaction, knowledge is created. First interactions in personal development with the environment are non-verbal. Returning to this concept, we propose work based on creative movement and non- verbal communication. This approach takes into account the multiple intelligences paradigm in order to generate knowledge. This paper seeks to explain a movement development program that has been applied to freshman students studying in different academic areas. The program design is explained in detail. The article demonstrates how the program has helped to develop the participants' body consciousness. The students' reflections are analyzed using a qualitative methodology. A questionnaire focused on the students' perceptions of the connections between general skills and the program rounds out the research results.

Unfortunately, many GIS layers depicting transportation networks do not provide information on the construction year of each line segment in the network. This poses a serious problem when the GIS layer is used as input to historic analyses investigating the growth of the human footprint in an area still being developed, since there is no way of finding out what features already existed at each time lag of the period under analysis. Here we assess the possibility of backdating (a.k.a. retro-fitting) a road network to a reference year (by removing features in the GIS layer whose ground counterparts were not yet built then), using (1) a single Landsat image from the reference year (single date approach); and (2) the latter plus another from a more recent year (multi-date approach). We provide succinct information on the study area, input RS and GIS data, methods, and results; and conclude that full automation of this task is feasible.

Monitoring landscape change is a requisite for sustainable development that should be achievable through the analysis of multitemporal satellite imagery. However, the development of effective methods to analyze these data in a consistent and reliable way is still a challenging issue that demands new approaches. Here we demonstrate the use of a recently developed change detection tool (the Landcover Change Mapper, LCM) for creating a multi-annual disturbance inventory spanning five years in a 10,000 km2 forested area in west-central Alberta, Canada.

Forest monitoring information needs span a range of spatial, spectral and temporal scales. Forest management and monitoring are typically enabled through the collection and interpretation of air photos, upon which spatial units are manually delineated representing areas that are homogeneous in attribution and sufficiently distinct from neighboring units. The process of acquiring, processing, and interpreting air photos is well established, understood, and relatively cost effective. As a result, the integration of other data sources or methods into this work-flow must be shown to be of value to those using forest inventory data. For example, new data sources or techniques must provide information that is currently not available from existing data and/or methods, or it must enable cost efficiencies. Traditional forest inventories may be augmented using digital remote sensing and automated approaches to provide timely information within the inventory cycle, such as disturbance or update information. In particular, image segmentation provides meaningful generalizations of image data to assist in isolating within and between stand conditions, for extrapolating sampled information over landscapes, and to reduce the impact of local radiometric and geometric variability when implementing change detection with high spatial resolution imagery. In this Chapter, we present application examples demonstrating the utility of segmentation for producing forest inventory relevant information from remotely sensed data.

Object-Based Image Analysis (OBIA) has gained considerable impetus over the last decade. However, despite the many newly developed methods and the numerous successful case studies, little effort has been directed towards building the conceptual foundations underlying it. In particular, there are at least two questions that need a clear answer before OBIA can be considered a discipline: i) What is the definition and ontological status of both image objects and geographic objects? And ii) How do they relate to each other? This chapter provides the authors’ tentative response to these questions.

What is Geographic Object-Based Image Analysis (GEOBIA)? To answer this we provide a formal definition of GEOBIA, present a brief account of its coining, and propose a key objective for this new discipline. We then, conduct a SWOT1 analysis of its potential, and discuss its main tenets and plausible future. Much still remains to be accomplished.