Archive for the ‘computer models’ Category

Necessity of ABMs?

Saturday, January 28th, 2012

Agent-based models are an interesting concept, with much potential, and as O’Sullivan describes, many limitations.  As exciting as they are, they have not gained the popularity in geography one may have expected, either.  Several reasons for this stood out to me amid the papers and class discussion.

First, agent-based models of increasing complexity are expensive, but if we want them to put out detailed results, they require this commitment of time and money to collect and input extensive amounts of data.  How many companies can afford the required commitment?

Second, as O’Sullivan mentioned, ABMs “frequently violate one of the most common tenets of practical science, the imperative to prefer simplicity over elaboration”.  This, combined with the fact that complex results can sometimes be just as hard to fathom as the complex data entered into the models, can be off-putting.

Third, and I would argue, most relevant, is the current availability of real-time data.  In class, we discussed how a lot of the results ABMs are attempting to discover can currently be monitored in real-time.  If we can have access to real people outputting results, as opposed to agents endowed with real qualities, why would we not choose the former?  Surely they can best model the complexities and counter-intuitive nature of real life?

All that being said, ABMs seem incredibly exciting, and an interesting way to model problems that we don’t have answers and data for already.  With continued improvements into the future, they seem like a technology to watch, maybe for emergence in unexpected ways.


O’Sullivan, David. “Geographical Information Science: Agent-Based Models.” Progress in Human Geography. 32.4 (2008): 541-550. Print.

O’Sullivan reading and Conceptualizing Agents and Environments

Saturday, January 28th, 2012

I would like to respond and build on to sidewalk ballet’s post about the contextual limitations of abstract Agent Based Models (ABMs). While your critique may be levelled at abstract ABMs specifically, I believe that ABMs are capable of capturing the complex specificities of any local area. Coming at a computational cost, I would imagine users of ABM would typically tailor their models to accurately reflect their situation. Another thing to consider is that an ABM’s environment does not need to represent a physical location. ABM can be used with environments that are very common to many agents, such as time or virtual environments like the stock market. I think of it as a way to model simultaneous decision-making, game theorying. In these types of non-place specific environments, more generalized ABMs may still be appropriate.

An important reminder is that agents need not be individuals as well. Frankly, I find this a more challenging concept for ABM. O’Sullivan touches on this point as well; how do we represent agents that are not individuals and who are also mobile? Is it ever appropriate to assume an entire family is one agent when a census tracks movement of the population? Can we assume a pride of lions in the savannah is one agent since it is clearly led by the dominant male? Tackling these issues of generalization and how to represent their movements allows for reduced computation cost and a scaling up of these models.

O’Sullivan, David. (2008). “Geographical information science: agent-based models.” Progress in Human Geography, 32(4) 541-550.

– Madskiier_JWong

Bonabeau reading and acknowledging limitations of Agent Based Modeling

Saturday, January 28th, 2012

Bonabeau’s article goes to great lengths to illustrate the advantages of Agent Based Modeling (ABM). He provides a quick overview of the approach which consists of agents that independently make decisions towards their goals and a shared environment. The novelty of this approach is that it captures emergent behaviour and often counter-intuitive results by analyzing at the individual agent level (which is often highly heterogeneous). Bonabeau explains this modeling has been applied to many fields such as transportation, supermarket design, and stock markets.

Despite this broad applicability of ABM, it must be approached cautiously. I believe that there is a large gap between seeing a simulation of an emergent phenomenon and whether it can be validated as representative of reality. The accuracy of these simulations depends on the inputted parameters, which often must reflect difficult-to-quantify behaviours. An uncritical acceptance of ABM’s results can risk large sums of money, public trust, and lives.  

Furthermore, it is important to use ABM to its full potential. Users of this tool should not focus solely on running this model until they get a desired result. There is room for geographic analysis of unexpected emergent interactions to better explain conclusions. There is also a need for a deep understanding of the limited spatial analysis each agent is capable of, and how the agents’ perception of their spatial surroundings affects their behaviour.   

Bonabeau, Eric. “Agent-based Modeling: Methods and Techniques for Simulating Human Systems.” Proceedings of the National Academy of Sciences of the United States of America. 99.10 (2002): 7280-7287. Print.

– Madskiier_JWong

Problems with Basic ABMs

Friday, January 27th, 2012

Multiple, differing agent-based models, being “simulation[s] that [use] agents to represent actors in the real world,” (O’Sullivan, 542), can produce results “that would match with empirical observations equally well” (546). Many basic, abstract models can reach the same conclusion, but how well can these be applied to specific occurrences in different locations?

In geography we know about the importance of locational specificity; the particular environmental, social, economic, political etc. factors that influence—and ultimately shape—the place. Abstract ABMs disregard any detail of real world situations, and therefore the emergent phenomena is incredibly abstract itself—making it impractical for it be applied to a wide variety of different places. Things occurring in one space cannot be blindly applied to a different one without acknowledging the different factors which comprise and inhabit the space. The substitutability of space is an inherent problem.

Abstract ABMs may not be seeking to generate results explaining phenomena for a particular location, but then what is their use in GIScience? Without incorporating any specific spatial entities, micro-level factors cannot be discerned and, ultimately, the phenomena cannot be explained. In the real world, the local has a great influence on agent behavior and interactions which is being overlooked in abstract ABMs. ABMs focus on the heterogeneity of individual agents, but basic models don’t consider the heterogeneity of different environments and how it influences agent behavior.

From a GIScience perspective, it seems that basic models don’t hold much weight in the explanation of phenomena for specific locations. Knowing that circumstances change in different areas, the behaviour depicted in abstract ABMs is incredibly superficial without model concerns for the particular.

O’Sullivan, David. (2008). “Geographical information science: agent-based models.” Progress in Human Geography, 32(4) 541-550.

-sidewalk ballet

Agent-Based Modeling: Computation and Cost?

Thursday, January 26th, 2012

Agent-based modeling (ABM) can do ANYTHING — the basic claim being made by Eric Bonabeau in his article, Agent-based modeling: Methods and techniques for simulating human systems.  And indeed, it does appear that ABM is quite useful, particularly when examining heterogeneous populations, as we can see in “virtually every example in this article”, to quote the author himself.  While I still wonder about the validity of ABM in certain situations, and can’t help but feel unsure about the authors’ exuberant claims in his writing, there was one thing particularly that I found missing from this article: computation and cost.

While Bonabeau does devote one or two sentences at the very end of the article to the high level of computational power required for these types of models, he does not, in my opinion, adequately express not only how important this one factor may be, but also all the additional factors inherent with data-heavy models such as this.  For example, he makes no reference to the amount of data collection that must go into creating these models.  Even a basic GIS user understands that a superficial layer of data is not interesting, but anything more than that requires a lot of commitment to collecting data.  In this case, working with human systems, to me that implies surveying people about their behaviours, how they make decisions, and so on.  This means time and monetary commitment.  And this leads to my larger criticism: the most telling aspect was how the companies he referred to were primarily established, and I would assume, wealthy, companies or organizations who could afford to use ABMs to make better management decisions.  Despite this, nowhere does he discuss cost.  Surely this technology does not come cheap?  And if it does, wouldn’t that make it even more desirable, and worthwhile to include?

With this knowledge, the reader (and potential user) could make a more informed decision about if ABM is not only useful, but at all possible, for them.  In the end, an interesting overview of applications of ABM, but lacking in answers to a few important questions.

Bonabeau, Eric. “Agent-based Modeling: Methods and Techniques for Simulating Human Systems.” Proceedings of the National Academy of Sciences of the United States of America. 99.10 (2002): 7280-7287. Print.


GIS and Coral Reef Management and Conservation on the American Samoa

Wednesday, November 19th, 2008

From another student in Intro GIS.

The independent state of Samoa, located in the South Pacific Ocean, possesses an incredible rich coral reef system. However, the reef is in poor shape because of environmental catastrophes and anthrogenic effects. The reef was damaged not only by the two large hurricanes (Ofa and Val) in the early 1990s, but also by a subsequent infestation of starfish and by coral bleaching. Human impacts–there’s a large footprint in terms of mining, construction, agriculture and sewerage–are also harming the coral reef.

Research to improve the health of the ecosystem are crucial. One big problem of Samoa is its remote location that makes data collection difficult. Researchers at the Oregon State University are currently working on the creation of benthic maps, web-based information System and education modules on GIS for the population of Samoa.

In a presentation, Dr. Dawn Wright, from the Oregon State, explains the use of geospatial technologies on Samoa and their usefulness for reef coral conservation and management. The first important technology is a multibeam investigation to figure out the bathymetry of the coral reef communities. The second technology is GIS, which would permit, as said before, the mapping of resources to improve management and decision-making.

Many reasons promote further research in mapping technologies on Samoa. Researchers like Dr. Wright want not only to identify the geological characteristics of the ocean floor, but also to identify the organisms that live in the Samoan coral reefs environment. Also, an algae bloom was identified in 1996, implying a nutrient boost in the coral reef environment that needs to be identified and monitored. Moreover, it is important to identify which sites are of high importance to prioritize their conservation.

Paving the way for further discussions, Dr. Wright explains that GIS is important because it permits the study of the structure, the change and the function of the coral reefs. This allows for real-time management because of the ability to follow the physical modifications on a regular basis. She also explains that other scientists in other regions were able to analyze coral reef ecology using GIS.

The US Center for Coastal Management and Assessment is tasked with advancing research on coastal and marine ecosystems. (The CCMA is part of NOAA’s National Centers for Coastal Ocean Science (NCCOS)). Its biogeography branch is tasked with gathering information about living marine habitats, including reefs. The CCMA Biogeography Branch decided in 2004 to map the coral reef and other benthic habitats’ distributions in American Samoa. The project includes a CD-ROM with maps, satellite imagery and GIS technologies. The most recent completed work is impressively precise and detailed. It includes 34 benthic zones with 51 square miles of ocean floor maps.

John Snow revisited

Sunday, November 16th, 2008

From another student in the Intro to GIS course.

Isn’t it strange how everything seems to go full circle? Arguably John Snow’s work using maps to figure out the source of the 1854 Broad Street cholera outbreak in London was the birth of using spatial analysis/maps for anything but figuring out where you are going. Actually, for much of history, maps weren’t even used for navigation by Europeans, the focus only shifting from the sky to the earth in the 1500’s (there is an interesting podcast on this, as well as some pretty obscure, but nonetheless highly interesting alternative uses for the mapping process). But despite this late start to mapping, humans have come incredibly far incredibly rapidly: from John Snow collecting cholera data by going door to door, and mapping by hand, to using Google Earth to predict where an existing outbreak might spread next, and now to predicting outbreaks before they even begin.

Rita Colwell and colleagues at the University of Maryland are working on using geospatial data from satellites to predict cholera outbreaks, even before they occur. This is based on preexisting satellite data on the temperature, height, and chlorophyll concentrations of seawater. The hope that soon satellites will also collect salinity and oxygen saturation, among other variables, which may help improve the model. It is known that as waters warm, phytoplankton flourish, and this is associated with increased outbreaks of cholera. But just how great of a correlation, and how predictions could be bettered, is where GIS comes into play. Colwell correlated the satellite data to cholera case statistics, with the hope of developing a model strong enough to predict up to six weeks of the future.

But as advanced as we may have become, in collecting and projecting data, we still face many of the same problems as John Snow did all those years ago. Back in the days of John Snow, there was no agency collecting outbreak locations, let alone the Internet on which to post them. But despite the fact that we are lucky enough to have such services available to us via the Internet, even if not physically going door to door, researchers have to write letters and emails in order to track down people. And of course there is the always the problem of data integrity: how much can we trust the data from a government disease agency? At least John Snow was collecting the data himself, and thus could trust it as much as he could trust humans to answer faithfully. So it is quite odd how both one of the earliest and one of the latest applications of GIS involves mapping cholera outbreaks, one looking backwards, one looking forwards, and yet we face many of the same problems.

It’s the circle of GIS life.

Using GIS to Model International Water Disputes

Friday, November 14th, 2008

From another student in Intro to GIS

GIS offers powerful tools for compiling, visualizing and analyzing potential indicators of international water resource conflict, because it has the capability to incorporate biological, physical and socioeconomic data. (Yoffe & al, 2004: 5)

Since its invention and particularly in the two last decades, GIS usages have increasingly turned toward social applications, examples being the use of GIS for census and market analysis. One very interesting social application has been the recent use of GIS to model current and possible future conflicts around transboundary waters. The scale of the issue is such that concrete empirical data over international water conflicts have been totally absent until very lately; the area of conflicts is usually perceived as pertaining to political/human sciences more than to applicable sciences. Fortunately, Yoffe & al. (2004) were able to combine both topics intelligently. Integrating temporality by looking at past conflicts over time, they joined physical data (climatology/precipitations and local versus international basins delineation by overlaying them to nations) to sociological ones (institutional capacity, internal disputes, international treaties ratified). These data were gathered in the Transboundary Freshwater Dispute Database (TFDD) and its Transboundary Freshwater Spatial Database. From there, the scholars were able to analyze and model probable conflicts around international watersheds.

However, some challenges remain for such modeling to be truly representative. The first challenge is very common to new GIS topics; it is the lack of hydropolitical and watershed data. As Yoffe & al. mentions, the only available hydropolitical data – provided by the Data Development International Research (DDIR) and other databases – only concern past conflicts, not past cooperative situations. Moreover, available data on conflicts are not specific to water but rather refer to general military issues (Yoffe & al., 2004: 3). Therefore, many data used to build the TFDD and draw conclusions regarding water conflicts are not primary; instead, they are derived from primary and even from secondary data. Indeed, while they were compiled with care, this kind of data leads to a lot of uncertainty regarding analysis. This uncertainty could be problematic in the eventuality that such modeling is used in institutional decision-making and interventions to prevent conflicts.

A second problem lies in the technical limitations of the TFDD website, which does not allow interactive consultation of the data. For instance, it is impossible to overlay spatial data to the tabular ones and to the hydropolitical data on the website. Therefore, for the TFDD to be used at its full potential, it would be pertinent to develop a user-friendly interactive tool that would let users to enter some spatial and attribute data, and would allow them to interpret and use data.

Still, the biggest problem probably lies in the little interest around the issue of international waters. However, this will be corrected most likely within the next 25 years as water scarcity is expected to increase and so are conflicts around the resource.

In sum, from this article, it appears obvious that GIS has large potential to help finding locally adapted solutions to global problems of water scarcity. Other possible areas of GIS research relating to water scarcity could be the modeling of virtual water (water traded through food importations) or of soil water (water available to plant through soils). Virtual and soil waters are also recent concerns and, again, data are almost nonexistent. For instance, in addition to knowing soils type in different regions, determining soil water at a global scale would more importantly require knowing soils volume, and modeling erosion and soils displacements over time, among other things. Obviously, these issues are complex. However, if challenges can be overcome, a geospatial analysis and modeling of virtual or soil waters could help determining which areas are the most sustainable ones for agricultural purposes from a water scarcity perspective. Once again, it would probably allow avoiding some conflicts over water.

For more information on GIS and international water conflicts:
Yoffe, S., G. Fiske, M. Giordano, M. Giordano, K. Larson, K. Stahl, and A. T. Wolf (2004), Geography of International Water Conflict and Cooperation: Data Sets and Applications, Water Resources Research, 40.

Wolf, A. T., S. B. Yoffe and M. Giordano. (2003) International waters: identifying basins at risk. Water Policy 5: 29–60.

For more information on virtual water and soil water:
Allan, J.A. (2007). Beyond the Watershed: Avoiding the Dangers of Hydro-Centricity and Informing Water Policy. In Hillel Shuval & Hassan Dweik (Eds.), Water Resources in the Middle East:Israel-Palestinian Water Issues – From Conflict to Cooperation. Heidelberg, Germany: Springer, pp. 33-39.

For more information about the use of GIS for water resources:
David R. Maidment (2002). ArcHydro: GIS for Water Resources, available as a Google Book.

Notes from the Where 2.0 conference

Tuesday, May 13th, 2008

I’m currently at Where 2.0 2008, where neogeographer entrepreneurs meet We 2.0 and I’ll post interesting talks, links as they come up.

Jack Dangermond of ESRI mentioned a cool application, which is a joint venture between The Nature Conservancy and U Washington that shows impacts on habitats and species over time as temperature increases and precipitation patterns change.

While I look for the site, take a look at Big Ideas in Conservation: Harnessing IT.

GIS applied to climate change

Wednesday, December 19th, 2007

(written by Intro to GIS student, N. G.)

These days, many people in the world have at least some knowledge about the process of climate change and the potential consequences we and the planet face if we continue to put greenhouse gases into the atmosphere. One of the many tasks scientists have been working on is the process of predicting changes that could occur to the earth’s surface should the polar ice continue to melt at its present rate. GIS can become a very important tool in many of these climatologists’ efforts to track how rises in sea level will impact specific land masses, and its larger impact on the population in these areas.

The GIS Initiative Program run by the National Center for Atmospheric Research offers various climate change scenarios shown through GIS to registered users. In creating various climate change scenarios for the Intergovernmental Panel on Climate Change for use in research and conferences, such as the climate change meeting taking place in Bali this week, NCAR has decided to make their datasets available for public download. These models, showing various potential future scenarios of the impact of climate change, help to generate interest in the public and GIS community on the importance of climate change with the easy availability of datasets to manipulate.

The Arctic Institute of North America, located at the University of Calgary calls attention to the Beaufort Sea Project for Climate Change, a project that is using GIS to track various impacts of climate change in the northern Arctic. These activities include tracking the impact of climate change on fish and mammals in the Beaufort Sea as they pertain to the survival of the native groups there, changes in hydrology due to the breakup of ice in the Mackenzie River and the spread of water-bone contaminants due to the melting of the sea ice pack. The transformation of this data into GIS makes the relationships between the variables easy to present and communicate across wide audiences, helping to illustrate the impact of climate change in the Arctic.

Although projects such as these help to provide insight into the impact of climate change on the earth, one must keep in mind that these are only models meant to give predictions to what might happen due to shifts in our climate. Much more study and analysis will need to be done before more accurate statements can be made.

sustainable management by local people

Monday, December 17th, 2007

(written by Intro to GIS student, C. N.)

As a GIS student who racks his brain over the quarks and particularities of the current softwares used to display spatial data, I would never have envisioned anyone short of a professional creating official maps. Furthermore, I would never have thought possible to map such intangible elements as cultural heritage, and to use such maps to create sustainable management plans for entire regions. Despite my skepticism, this is exactly what has been done for Fiji’s Ovalau Island.

Ovalau is one of Fiji’s largest islands with a population of 9000 and an area spanning ~10 by 13 kilometers. It is characterized by a rich cultural history dispersed throughout the villages that inhabit the island’s rugged landscape. Due to these conditions, any available spatial and resource data prior to Ovalau’s new mapping initiative, was of poor quality (relative to state’s needs) and only available orally through conversations and stories. In January 2005, an initiative using Participatory 3D modeling (P3DM) was implemented. The goal of the P3DM exercise – a derivative of Participatory GIS – was to create physical 3D relief models based upon local knowledge, and to use these models to propose a resource management plan. This methodology would ensure that the voice of local people was heard. After all, the proposed resource management plan would be based on their 3D model.

This is exactly what was accomplished in 2005. Base maps were constructed based on the consultations of 27 separate villages. Following this, students, teachers, elders and individuals trained in natural resource management, cartography, GIS, and community work got together for the construction of the 3D model. Throughout this construction, youth workers did much of the manual labor while elders spoke of the various resources and tales of the land. Based on the created map, the Vanua ko Ovalau Resource Management Plan was proposed and accepted.

Ovalau’s uses of P3DM show tangible real life implications for GIS, not just for the GIS professional, but also for entire communities. We are approaching the point in the semester in Intro to GIS, where GIS terminology and jargon seems to be taking over our brains, and we are wondering how long it will be before we will ever really understand the intricacies of GIS. Despite this, it is important to remember that GIS is not exclusive to those with thousand dollar programs and perfectly constructed data. Ovalau is a prime example of adaptations of GIS to participation. It demonstrates that the world of GIS is not restricted to a computer lab but can be used in entire communities, and that it is not limited to classifying well ordered numerical data but can handle cultural assets and heritage.

Ovalau’s success has also merited a World Summit Award.

aesop’s fables for a modern age

Wednesday, October 17th, 2007

I had missed this from the May issue of the New Scientist on the 26 myths (or rather misconceptions) of climate change.

I was particularly attracted to the myth about computer models and whether or not we should put our faith in them.

Climate modellers may occasionally be seduced by the beauty of their constructions and put too much faith in them. Where the critics of the models are both wrong and illogical, however, is in assuming that the models must be biased towards alarmism – that is, greater climate change. It is just as likely that these models err on the side of caution.

And I like the following retort to those who see no value in modeling:

Finally, the claim is sometimes made that if computer models were any good, people would be using them to predict the stock market. Well, they are!

I wonder what our fables will be in 100 years time. Will we be telling stories of the little boy or girl who didn’t heed the broad trends shown in the climate change models and that’s why we’re experienced bad weather today? Or perhaps the little girl who was seduced by the beautiful computer model, which explained all the bad (stingy?) choices she subsequently made in her life.

visualizing global warming

Sunday, September 16th, 2007

because people need to see the impacts to believe it.

Architecture 2030 … tries to bring attention to the amount of greenhouse gas emissions that the building sector contributes to global warming through inefficient electricity use, lighting, heating and cooling.

“The building sector is responsible for close to half of all energy consumption in this country and close to half of all greenhouse gas emissions,” [Edward Mazria, Architecture 2030’s founder] said. Buildings are the single largest contributor to global warming, he said, emitting more than even automobiles.

Architecture 2030 has teemed up with Google Earth to show dramatic images of the impacts on U.S. cities of climate change.

See prior post for Canadian examples and step by step instructions for creating your own seal level rise overlays on Google Earth.

Update: One satellite image is worth a thousand words. And hundreds of satellite images?

the European Space Agency said nearly 200 satellite photos this month taken together showed an ice-free passage along northern Canada, Alaska and Greenland, according to news reports. Ice was retreating to its lowest level since such images were first taken in 1978, according to a report from The Associated Press.

Using satellite data and imagery, the U.S. National Snow and Ice Data Center (NSIDC) now estimates the Arctic ice pack to cover 4.24 million square kilometers (1.63 million square miles) — equal to just less than half the size of the United States.

y2k bug in climate change data: how much does it change the results?

Saturday, August 11th, 2007

I’ll let the computer and climate scientists speak for themselves.

I’ve great concern for communicating climate change to the public. Science simply doesn’t work that way that the climate change skeptics demand it to (i.e., someone wins and someone loses). We create falsifiable hypotheses and our data has error bars. Working with complex models means we have trouble asserting causality to individual components. Against the qualifications and uncertainties with which our scientist culture has grown accustomed, the public is buffeted by clear memes of what is accurate or (in the case of the y2k bug) inaccurate about the data. Once again, science doesn’t work that way.

(BTW, environmental students do not enter university accepting uncertainty of data and outcomes. They want the undeniable evidence that their view of the environmental calamity is correct and want us to supply them with the exact tools to fix the planet. Not to say all students are like that but many are dismayed that the world is far more complicated than that.)

Update: James Hansen responds.

abcnews goes green

Thursday, May 10th, 2007

Tonight’s reporting from World News Tonight

* Concern Soars About Global Warming as World’s Top Environmental Threat
* How to Address Global Warming: A Range of Tips
* EPA Carbon Footprint Guidelines
* San Francisco Goes Green
* Shrinking Your Carbon Footprint
* Fixing the Planet for Profit
* Limit Your Impact on the Environment
* Check Your Household’s Carbon Footprint
* Reducing Your Carbon Footprint

take a bite out of climate change

Wednesday, February 28th, 2007

Researchers at the American Association for the Advancement of Science (AAAS) Annual Meeting annouced a new game that allows participants to take a wedge out of global environmental problems (Science 23 February 2007: Vol. 315. no. 5815, pp. 1068-1069).

In a darkened ballroom in the Hilton San Francisco, 413 people tap numbers onto slate-gray keypads, each the size of a thick paperback book. Around them, almost 600 others watch as two screens at the front of the room reveal the results of their manipulations: a selection of strategies for taking wedge-shaped bites out of a graph of projected levels of atmospheric carbon over the next 50 years. Their mission: to whittle future CO2 levels down to a plateau in time to avert intolerable greenhouse warming.

The “Wedge Game,” based on “stabilization wedges”–a concept developed by Robert Socolow and Stephen Pacala of Princeton University (Science, 13 August 2004, p. 968)–was part of a town hall-like session for teachers and students at the AAAS Annual Meeting, held here from 15 to 19 February. The game, designed to convey the scale of the effort needed to stabilize carbon emissions and the pros and cons of possible options, was just one of some 200 sessions, ranging from “Addiction and the Brain” to “Education, Learning, and Public Diplomacy in Virtual Worlds.”

Perhaps influenced by Lovins, the Wedge Gamers voted for a deep-green mix of two parts increased efficiency and one part each solar electricity, wind power, driving less, switching from petroleum to natural gas, and “biostorage” (planting forests to absorb CO2). It’s far from current U.S. energy policy, but it reflects much of the thinking on display at many other sessions at this meeting.

More on The Stabilization Wedge, a concept and a game as well as the teachers’ guide. For those not computer inclined, the Wedge game is also available in colourful paper format.

99 weiße balloons

Tuesday, February 13th, 2007

NYTimes has a video on the use of low cost balloons (only $800US each) to map ozone. It accurately conveys the travails of conducting field research, which doesn’t always proceed as planned. Also it suggests that this field research costs a lot more than $800. The assistants, vehicles (gas, insurance), and supporting hardware (laptops, sensors, tracking devices) adds up quite quickly.

tech for food

Friday, February 2nd, 2007

If you are interested in new technologies for improving agriculture and reducing hunger then you may wish to attend the first International Symposium Tech For Food, which will take place the March 6, 2007, at the International Exhibition of Agriculture in Paris. The Symposium is free in terms of registration but places are limited. The conference and its accompanying site will examine:

all technical means for combating hunger. They are derived from advanced technologies adapted to the agricultural and agribusiness domains: satellite imagery, Internet, wireless communications, portable physical and chemical tests… and others yet to be invented or explored. Aid in land and natural resources management, in the prevention of natural risks, training, information, commercial exchanges: new technologies offer a great many levers for agricultural development and food production, as long as we are able to master their advantages and weaknesses.

More research and development oriented than cell phones for food.

another kind of climate modelling

Thursday, October 26th, 2006

A UK report will be released on Monday that predicts the economic effects of climate change. It was commissioned by the UK Treasury and conducted by Nicholas Stern, who was a chief economist with the World Bank. The message of the report: Climate change will have disasterous effects on the world’s economy. However, the investments now to turn it around are relatively small and will actually boost countries’ ecnonomies.

Speaking at a climate change conference in Birmingham, [David King, the UK government’s chief scientific adviser] said: “All of [Stern’s] detailed modelling out to the year 2100 is going to indicate first of all that if we don’t take global action we are going to see a massive downturn in global economies.” He added: “If no action is taken we will be faced with the kind of downturn that has not been seen since the great depression and the two world wars.” Sir David called the review “the most detailed economic analysis that I think has yet been conducted”.

sensing floods

Wednesday, October 25th, 2006

A “grid” of smart river sensors will be installed in the Ribble River (Yorshire, UK). The sensors will monitor water pressure/depth and flow and will be used to predict impending flooding.

The article likens the network of sensors to grid computing:

Each node is smaller than a human fist and powered by batteries and solar panels. Each is also accompanied by a computer unit about the size of a packet of chewing gum, which contains a processor about as powerful those found in a modern cellphone.

The sensors are positioned within tens of metres of each other and communicate through Wi-Fi and Bluetooth antennas. This enables them to collaborate for data collection and processing tasks, creating a larger community computer. The same “grid computing” approach is used to connect computers at different locations for distributed research projects.

If the river’s behaviour starts to change, the network uses the data collected to run models and predict what will happen next. If a flood seems likely – because it is rapidly rising and moving quickly – the network can send a wireless warning containing the details.

(Hmm but do the people in Yorskshire know that one of their rivers is broadcasting to a lab in Lancashire? The War of the Roses wasn’t that long ago… 😉 )