Estos son los últimos bosques vírgenes que aún persisten en Europa

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Aunque parezca mentira, aún quedan bosques vírgenes en Europa,vergeles salvajes en los que no se aprecia la mano del hombre. Un equipo internacional de investigadores, dirigidos por la Universidad de Humboldt en Berlín, ha elaborado un estudio y un mapa que muestran el sorprendente número de esos bosques antiguos que se mantienen en el continente. En España, están situados principalmente en Pirineos y la cornisa cantábrica.

«Lo que hemos mostrado en este estudio es que, aunque la superficie total del bosque no es grande en Europa, quedan muchos más de estos bosques vírgenes o primarios de lo que se pensaba anteriormente, y están ampliamente distribuidos», afirma Bill Keeton, ecólogo forestal en Vermont. «Y donde hay, proporcionan valores ecológicos y un hábitat excepcionalmente únicos para la biodiversidad», señalan.

El mapa identifica 13.800 km cuadrados en 34 países europeos. «No es que estos bosques nunca hayan sido tocados por el hombre. Esto sería difícil de creer en Europa», explica Francesco Maria Sabatini, autor principal del estudio (aquí puede consultar su blog, muy recomendable). «Aún así, estos son bosques donde no hay indicaciones claramente visibles de actividades humanas. Tal vez sea porque han estado borrosas por décadas de no intervención, donde los procesos ecológicos siguen una dinámica natural».

Los científicos han mantenido la ubicación exacta de muchos de estos bosques de forma confidencial. «Son ecosistemas muy delicados, que pueden verse gravemente dañados por el turismo excesivo. Algunos, también se encuentran dentro de áreas estrictamente protegidas, por lo que el acceso normalmente solo se concede después del permiso explícito de las autoridades competentes», apunta Sabatini a ABC. Sin embargo, en España sí puede mencionar «un par de bosques famosos»: el Hayedo de Montejo de la Sierra, en el macizo de Ayllón, y la reserva Natural de Muniellos, en Asturias, o la preciosa Selva de Irati, en el Valle de Salazar, Navarra.

La compilación del mapa fue una tarea enorme. «Contactamos a cientos de científicos forestales, expertos y activistas de ONG de toda Europa que pedían compartir información sobre dónde encontrar esos bosques en su país», dice Sabatini, investigador postdoctoral en Humboldt. «Sin su participación directa, nunca hubiéramos podido construir nuestra base de datos, que es la más completa jamás compilada para Europa».

Remotos y fragmentados

El estudio destaca que los bosques primarios en Europa son generalmente muy raros, ubicados en áreas remotas y fragmentados en pequeños parches. «El paisaje europeo es el resultado de milenios de actividades humanas, por lo que no es sorprendente que solo una pequeña fracción de nuestros bosques aún no haya sido perturbada», explica Tobias Kuemmerle, director del Laboratorio de Biogeografía de Conservación de la Universidad de Humbolt y autor principal de el estudio. «Aunque esos bosques solo corresponden a una pequeña fracción del área total de bosques en Europa -dice-, son absolutamente excepcionales en términos de su valor ecológico y de conservación».

Los bosques primarios suelen ser el único hogar que les queda a muchas especies en peligro de extinción, y los científicos los consideran laboratorios naturales para comprender el impacto de las personas en los ecosistemas forestales. «Saber dónde están estos bosques raros es, por lo tanto, extremadamente importante, pero, hasta este estudio, no existía un mapa unificado para Europa».

En peligro

Aunque estás zonas están por lo general bien protegidas, el nuevo estudio también muestra que la preservación no puede darse por sentada. La mayoría de estos bosques son pequeños y están intercalados en paisajes dominados por humanos, lo que los hace particularmente propensos a la perturbación humana. Esto significa que, al menos en algunos países europeos, la extracción de madera o la tala pueden poner en peligro su naturaleza salvaje.

«Se están talando parcelas amplias de bosque primario en muchas áreas de montaña, por ejemplo en Rumania y Eslovaquia y en algunos países de los Balcanes», dice Miroslav Svoboda, científico de la Universidad de Ciencias de la Vida de Praga y coautor del estudio. «Una creciente demanda de bioenergía, junto con altas tasas de tala ilegal, están llevando a la destrucción de este patrimonio natural irremplazable, a menudo sin siquiera entender que el bosque que se corta es primario». Los científicos confían en que el nuevo mapa pueda ayudar a proteger los bosques antiguos de Europa.

How Matterport Helps Optimising BIM Modelling in Revit

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Optimise BIM Modelling in Revit for Complex Construction Projects, Reduce Time Spent on Measurements and As-Builts

(This story is brought to you by Matterport)

Hand measuring the boiler room - from wall to pipe, from pipe to pipe, floor to ceiling, floor to pipe, etc. - would take 4-5 hours for a contractor to accomplish, and 4-5 days for an engineer to model in Revit, as well as potential additional follow on site-visits.

Bergman also knew traditional laser scanning (e.g. with a Leica system) in such a complicated and tight space would require a large number of scan positions. Laser scanning would also take longer than manual measurements in addition to the time required to register the point clouds and still require hand modelling. Finally, acquiring a laser scanner would add a significant unnecessary, expense to his budget.

So he began searching for new tools which would make modeling the MEP room more efficient, without adding additional time or cost to the budget.

Key considerations:

• Manual measurements for modelling as builts represent a significant time expense per project
• New tool needed to simplify and expedite the modelling process
• New tool required to sync with current Revit/ReCap workflow

The solution

Matterport Scanning 60% Faster than Hand Measuring, Point Clouds Speed Revit Modeling by 40%

With the Matterport Pro 3D Camera, Bergman was able to capture a medium-density single registered point cloud (200 MB) of the MEP room in under an hour. Because he wanted to double check the accuracy of the point cloud, he still took the time to manually hand-measure the MEP room, which took him approximately 2-3 hours to accomplish. Once he had the point cloud, he was able to upload and index it in ReCap to view 3D model. He did this to retain the colorization of the point clouds, as importing Matterport point clouds directly into Revit can remove the colorization of the points.

From there, Bergman saved the ReCap file and imported it directly into Revit to model on top of the 3D structure. When he compared the point cloud data to his hand-taken measurements, he found they were accurate up to the centimetre. With similar projects, modelling in Revit with hand measurements would have taken 4-5 days to trace over the as built. With the point cloud, it took him 2. Due to the accuracy of the point cloud, measuring in the future will be minimized, cutting his time spent measuring by 60%. And since the point cloud is delivered from Matterport as a single, fully registered point cloud there is no time spent manually registering the data to get a final point cloud.

Modelling time in Revit was decreased by 40% which was also expedited by his 24/7 access to perfect, immersive visual references to the job site. This reference material is immediately at hand without having to manage any image files. And modelling with both an accurate point cloud and visuals is the key to modelling efficiency.

Bergman frequently will go back to the job site to visually confirm that the Revit model matches reality. With the Matterport 3D Showcase he no longer has a need to go back on site to confirm that the existing conditions were modelled correctly, removing as much as a day’s travel from his schedule.

• Scan space using the Matterport Pro 3D Camera (30-60min/room)
• Download the pre-registered Matterport point cloud (200 MB)
• Import the point cloud into ReCap (to retain colorization)
• Import ReCap file into Revit
• Trace over 3D point cloud to create BIM model

The results

Field-to-Finish in 50% of the Time Enables TL Circle to Offer Competitive Pricing 30%-40% Below Previous Rate

The typical price for building a BIM model of a MEP boiler project like this would be approximately US$10k, but with the optimized modelling process, the price drops to US$5K-6K. Bergman estimates that the field to finish time for projects is cut in half when compared to projects done with manual or laser system. By expediting the process, Bergman is able to offer more competitive prices, which has opened him up to new markets as well as increase wages for his employees.

Other projects completed without the Matterport system had approximately 70% more inconsistencies with their as builts. With Matterport, that number was reduced to nearly 0.

“Matterport has helped cut my field to finish time in half. I’m excited to leverage this new tool to improve the BIM modeling process.”

Aryn Bergman, Owner of TL Circle

On demand webinar

Fast, Affordable Reality Capture for the Built Environment

AEC professionals from Gilbane, Hensel Phelps, Mortenson, and more are using Matterport’s Pro2 3D Camera and Cloud platform to streamline workflows, minimize labour costs, reduce site visits, and to mitigate risk. Sign up for our live webinar to learn how you can use Matterport’s 3D reality capture solution to make your projects more efficient and cost-effective.

El hombre más rico del mundo propone llevar las fábricas a la Luna para salvar la Tierra

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El hombre más rico del mundo, Jeff Bezos, fundador y director ejecutivo del gigante Amazon, dice que su empresa espacial Blue Origin trabajará con la NASA y la ESA para crear un asentamiento en la Luna.

Incluso si Blue Origin no puede lograr asociaciones público-privadas, Bezos hará lo que sea necesario para que sea así. Su pronóstico es que la Luna es el 

sitio ideal para descongestionar industrialmente a la Tierra y preservarla como hábitat para los humanos, según explicó durante una charla en la Conferencia Internacional de Desarrollo Espacial, celebrada el pasado fin de semana en Los Ángeles.

En el corto plazo, el objetivo de Blue Origin es reducir el costo de acceso al espacio, inicialmente con su nave espacial suborbital New Shepard y luego con su cohete New Glenn de clase orbital en la década de 2020.

A largo plazo, la visión de Bezos es allanar el camino para que millones de personas trabajen en el espacio. Esas personas simplemente podrían vivir y trabajar en asteroides ahuecados, un concepto que fue propuesto décadas atrás por Gerard K. O'Neill, un físico de Princeton cuyas ideas sobre el asentamiento espacial alimentaron la pasión de Bezos por alcanzar este frontera final.

La forma en que Bezos lo ve, moviendo la industria pesada a puestos espaciales impulsados por energía solar es la única manera de garantizar que nuestro planeta pueda hacer frente a la creciente demanda de energía y al estrés que la población en crecimiento supondrá en el medioambiente de la Tierra.

"Tendremos que dejar este planeta", dijo Bezos, citado por Geek Wire. "Vamos a dejarlo, y va a mejorar este planeta. Vamos a ir y venir, y las personas que quieran quedarse, se quedarán".

La Tierra será dividida en zonas para uso residencial e industrial ligero, mientras que la industria pesada se moverá fuera del planeta y será alimentada por energía solar 24 horas al día, 7 días a la semana, dijo.

"La Tierra no es un muy buen lugar para la industria pesada. Es conveniente para nosotros en este momento", dijo Bezos. "Pero en un futuro no muy lejano, estoy hablando de décadas, quizás 100 años, comenzará a ser más fácil hacer muchas de las cosas que hacemos actualmente en la Tierra en el espacio, porque así tendremos mucha energía".

«Como si alguien lo hubiera preparado»

Durante su intervención, Bezos defendió la utilidad de la Luna para estos planes, porque está convenientemente ubicada, accesible en solo un par de días con el cohete correcto. Los científicos han determinado que tiene depósitos de hielo de agua cerca de los polos que podrían convertirse en agua potable, aire respirable y propulsores para cohetes recargables. "Es casi como si alguien nos hubiera preparado esto", dijo Bezos.

Para facilitar el regreso a la luna, Blue Origin tiene un módulo de aterrizaje lunar en los tableros de dibujo que está diseñado para poder entregar 5 toneladas de carga a la superficie lunar. Eso es lo suficientemente fuerte como para ser utilizado para transportar personas, y con suficiente apoyo, podría comenzar a volar a mediados de la década de 2020.

Blue Origin ha propuesto construir su módulo de aterrizaje Blue Moon bajo los términos de una asociación público-privada con la NASA. "Por cierto, haremos eso, incluso si la NASA no lo hace", dijo Bezos. "Lo haremos eventualmente. Podríamos hacerlo mucho más rápido si hubiera una asociación".

Earth Observation Data and Image Processing for High-level Humanitarian Support

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An Efficient Approach for Estimating Refugee Camp Populations

 

 

 

 

 

Over the past decade, the world has witnessed a steady increase in the number of people forced away from their homes by natural disasters or political unrest. They often end up in camps that hold tens of thousands of refugees. The camps are supported by non-governmental organisations (NGOs) that provide food, shelter and medical assistance. To manage their operations, NGOs and other agencies need to know how many people are in a given camp. This article explains how a combination of high-resolution satellite Earth observation data and image processing software provides an efficient approach for estimating camp populations.

The refugee population is growing rapidly. Recent estimates from the United Nations indicate that nearly 68 million people fled their homes in 2016, up from 64 million in the previous year. Often located near war zones, the largest camps hold more than 200,000 people. When essential services such as food, clean water and sanitation are in short supply, malnutrition and sickness can take hold. Financial and material support is limited, though, and a camp’s infrastructure is often overtaxed. Because of their limited funding, NGOs have become adept at planning and resource allocation. Information on population size and trends for a given camp helps the NGOs to optimise the return on their spending. Producing good data, however, is not easy. Aircraft – including unmanned aerial vehicles (UAVs or ‘drones’) – and satellites can capture aerial images of the camps, but manually extracting reliable population data from these photos can be painfully slow and expensive. Médecins Sans Frontières (MSF), an NGO supporting refugee camps, teamed up with experts at the University of Salzburg’s Department of Geoinformatics (Z_GIS) to find a solution. Z_GIS conducts research into the use of satellite imagery with advanced image processing techniques to monitor populations. One of its key objectives is developing automated approaches to extract population information from satellite images of refugee camps.

Accurate Counts

To measure the populations, Z_GIS obtains very-high-resolution (VHR) imagery (less than 1 metre per pixel) from commercial suppliers such as DigitalGlobe and Airbus (Pleiades). The images are processed using Trimble’s eCognition software to produce estimates on the number of physical dwelling units in a camp. The results can be displayed using tools such as ArcGIS or Google Earth to provide geographic context. Teams can then add ground data about the average number of residents per dwelling, enabling them to estimate the size and distribution of the population. The process can be repeated to quantify population change and movement within a camp. The ability to repeat the population analysis quickly is important, since rapid changes can occur in a camp during a crisis.

Rule Sets

Object-based image analysis (OBIA), a method available in eCognition, is used to identify and classify features in an image. According to Dr Dirk Tiede of Z_GIS, OBIA offers greater flexibility and efficiency than pixel-based analysis techniques. Tiede develops customised processes (known as ‘rule sets’) that effectively train eCognition to recognise and classify individual features within an image. The objective is to identify man-made structures and to differentiate dwellings from other camp buildings such as food stations and medical facilities.

The rule sets use edge detection algorithms to delineate camp margins and to classify man-made features. Spatial characteristics of different dwelling types, along with relative spectral differences between objects, enable the rule sets to distinguish light-coloured dwelling structures from darker buildings and fences. The system determines the spectral values in order to separate dwelling types as well as areas with and without vegetation. The comparison is based on specific spectral ranges or vegetation indices such as the Normalised Difference Vegetation Index (NDVI). These values are saved as variables within the rule set and can be combined with other independent spectral parameters. Once a rule set is constructed, it can be transferred and adapted to work in different camps, or at different times in the same camp when the environment has changed.

Hybrid Approach

The initial rule set was developed using archived QuickBird imagery of the Zam Zam camp in Darfur, Sudan. To test transferability, the rule set was applied to a series of QuickBird images taken in the years prior to and following the original dataset. Additional tests used GeoEye-1 imagery at camps in Darfur. During these tests, Z_GIS found that the primary challenges came from varying vegetation at new sites as well as differences in characteristics of various satellite sensors.

Complex situations occur when camps show a very diverse set of structures or several development phases. In addition, local conditions may change the appearance of structures over time. For example, in some camps brightly coloured tents are used, which are relatively easily recognisable. However, when a sandstorm passes over and covers everything in a brownish dust, the given rule set may need to be adapted quickly. Therefore, a hybrid approach was applied that combines the automated solution with manual image interpretation for analysis and quality checking. The tests performed by Z_GIS showed that the rule sets could be adapted successfully using visual inspection on the computer screen and redefining appropriate spectral thresholds for structures and the NVDI for vegetation.

Population Dynamics

Effective population monitoring relies on rapid acquisition and processing of satellite data. Once imagery is acquired, the main bottleneck occurs in image processing. Using more efficient algorithms and faster computing technology (including the distributed computing ability of eCognition Server), it is possible to analyse an entire VHR satellite scene in just a few minutes.

To further reduce the time and staffing level required for analysis, Tiede and his colleagues are working to improve workflows around the automated processes. They are developing applications and solutions with the goal of producing initial data for a camp very quickly. From there, the team can build on the results to produce temporal information on population dynamics.

New Applications

Satellite imagery supports NGOs in more than just population estimates. For example, organisations want to avoid the expensive and risky practice of trucking water to the camps. Using lower-resolution imagery from Sentinel or Landsat satellites, Z_GIS can develop an overview map of a camp’s geohydrological situation to identify possible well sites. Natural disaster aid efforts also benefit from satellite imagery in analysing the extent and nature of damage for first responders and longer-term recovery. After the devastating 2010 earthquake in Haiti, Z_GIS produced a damage map within two days of the event. In emergency situations, the turnaround time is critical. The urgency is usually not as great for refugee camps, but timeliness does matter for highly dynamic situations such as the Rohingya crisis in Bangladesh.

The humanitarian team at Z_GIS continues to work closely with MSF and other NGOs, including the Red Cross movement, SOS Children’s Villages and Action Against Hunger.

Their work has produced a stable, operational service to support humanitarian organisations. It is an illustrative example of the value of Earth observation and image analysis in humanitarian aid. Natural disasters and other crises will continue. Putting advanced tools in the hands of dedicated specialists helps to provide better and faster relief to those in need.