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By Linda See and Ian McCallum, IIASA Ecosystems Services and Management Program, Earth Observation Team
Land cover is of fundamental importance for environmental research. It serves as critical baseline information for many large-scale models, for example in developing future scenarios of land use and climate change. However, current land cover products are not accurate enough for many applications and to improve them we need better and more accessible validation data. We recently argued this point in a Nature correspondence, and here we take the opportunity to expand on our brief letter.
In the last decade, multiple global land cover data products have been developed. But when these products are compared, there are significant amounts of spatial disagreement across land cover types. Where one map shows cropland, another might show forest domains. These discrepancies persist even when you take differences in the legend definitions into account. The reasons for this disagreement include the use of different satellite sensors, different classification methodologies, and the lack of sufficient data from the ground, which are needed to train, calibrate, and validate land cover maps.
An artist’s illustration of the NASA Landsat Data Continuity Mission spacecraft, one of the many satellites that collects data about Earth’s surface. Credit: NASA/GSFC/Landsat
A recent Comment in Nature (Nature, 513, 30-31; 2014) argued that freely available satellite imagery will improve science and environmental-monitoring products. Although we fully agree that greater open access and sharing of satellite imagery is urgently needed, we believe that this plea neglects a crucial component of land cover generation: the data required to calibrate and validate these products.
At present, remotely sensed global land cover is not accurate enough for monitoring biodiversity loss and ecosystem dynamics or for many of the other applications for which baseline land cover and change over time are critical inputs. When Sentinel-2–a new Earth observation satellite to be launched in 2015 by the European Space Agency–comes online, it will be possible to produce land cover maps at a resolution of 10 meters. Although this has incredible potential for society as a whole, these products will only be useful if they represent the land cover more accurately than the current products available. To improve accuracy, more calibration and validation data are required. Although more investment is clearly needed in ground-based measurements, there are other, complementary solutions to this problem.
Map showing cropland disagreement between two different land cover maps, GlobCover and GLC2000: all colors represent disagreement. Credit: Geo-Wiki.org, Google Earth
Not only should governments and research institutes be urged to share imagery, they should also share their calibration and validation data. Some efforts have been made by the Global Observation for Forest Cover and Land Dynamics (GOFC-GOLD) in this direction, but there is an incredible amount of data that remains locked within institutes and agencies. The atmospheric community shares their data much more readily than the Earth Observation (EO) community, even though we would only benefit by doing so.
Crowdsourcing of calibration and validation data also has real potential for vastly increasing the amount of data available to improve classification algorithms and the accuracy of land cover products. The IIASA Geo-Wiki project is one example of a growing community of crowdsourcing applications that aim to improve the mapping of the Earth’s surface.
New apps developed by IIASA’s Earth Observation Team aim to involve people around the world in on-the-ground data validation efforts.
Geo-Wiki is a platform which provides citizens with the means to engage in environmental monitoring of the earth by providing feedback on existing spatial information overlaid on satellite imagery or by contributing entirely new data. Data can be input via the traditional desktop platform or mobile devices, with campaigns and games used to incentivize input. Resulting data are available without restriction.
Another major research projects we are using to address many of these issues identified above is the ERC Project Crowdland .
Note: This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
At IIASA in Laxenburg this week, renowned mathematician Don Saari laid out a challenge for the Institute’s scientists: to better understand complex systems, he said, researchers must find better ways to model the interactions between different factors.
“In a large number of models, we use climate change or other factors as a variable. What we’re doing is throwing in these variables, rather than representing interactions—like how does energy affect population?” said Saari, a longtime IIASA collaborator and council member, and newly elected IIASA Council Chair, a position he will take up in November. “The great challenge of systems analysis is figuring out how to connect all the parts.”
“Whenever you take any type of system and look at parts and how you combine parts, you’re looking at a reductionist philosophy. We all do that in this room,” said Saari. “It is the obvious way to address a complex problem: to break it down into solvable parts.”
The danger of reductionism, Saari said, is that it can turn out completely incorrect solutions—without any indication that they are incorrect. He said, “The whole may be completely different than the sum of its parts.”
Take a Rubik’s cube as an example: Saari said “If you try to solve it by first doing the red side, then the green, then the blue, you will end up with a mess. What happens on one side is influenced by what’s happening on all the other sides.”
In the same way, the world’s great systems of energy, water, climate all influence each other. During the discussions, IIASA Deputy Director Nebojsa Nakicenovic noted that current work to extend the findings of the Global Energy Assessment to include water resources could narrow the potential number of sustainable scenarios identified for energy futures by more than half.
Saari pointed out that many of the world’s great scientists—including Nobel Prize winner Tom Schelling and Kyoto prize winner Simon Levin, both IIASA alumni—reached their groundbreaking ideas by elucidating the connections between two different fields.
It may sound like a simple solution to a methodological challenge. However, understanding the connections and influences between complex systems is far from simple. As researcher Tatjana Ermoliova pointed out in the discussion, “In physical systems you can hope to observe and discover the linkages.” But between human, economic, and global environmental systems those linkages are elusive and fraught with uncertainty.
At the end of the lecture, IIASA Director & CEO Prof. Dr. Pavel Kabat turned the challenge towards IIASA scientists, and we now extend it also to our readers: How can scientists better model the connections between systems, and what needs to change in our thinking in order to do so?
By Charlie Wilson and Arnulf Grubler, Tyndall Centre for Climate Change Research and IIASA Transitions to New Technologies Program
Solar-powered flying skateboards: Central to your typical 8-year-old’s vision of a climate-friendly future, but, alas, destined only for the world of science fiction.
But all is not lost. Many other forms of energy technology innovation lie squarely within the realms of science. And scientists working on how to address climate change see innovation as key to addressing climate change.
“The history of energy innovation is littered with over-exuberance…”
The question is how do we innovate successfully? The history of energy innovation is littered with over-exuberance, pipe dreams, and white elephants. But it’s also marked by striking successes, such as the world-leading Danish wind power and Brazilian ethanol industries, or the energy efficiency of Japanese consumer products.
Our new book scours the pages of history to work out what has distinguished past successes from failures. We cast a critical eye on twenty varied innovation histories of energy technologies, from large to small, old to new, and supply to end-use. We are interested both in the technologies that now dominate our landscape as well as technologies that have faded from public view.
Our motivation for the book was to find out: how can we innovate successfully to address climate change? We don’t come up with all the answers, but we do think we can point the way.
A systemic perspective on energy technology innovation
Successful innovation is like a puzzle: you need all the pieces to see the whole picture. But history shows us that innovation policy, research, analysis, and market activity have too frequently focused on a particular piece of the puzzle.
Research and development (R&D) is a good example. Energy-related R&D activities are dominated by private firms. But governments play a crucial role in supporting and investing in R&D with less immediate prospects and less certain pay-offs. When we looked at the history of R&D, we found that public R&D efforts often targeted early and rapid upscaling of promising new technologies. This was particularly the case for energy supply technologies, including wind turbines, solar thermal plants , synthetic fuels, and nuclear power.
Building big can help reduce costs. But cost reductions from upscaling are by no means guaranteed. They depend on all sorts of other things: experimentation and testing, often for prolonged periods; entrepreneurs trying out applications in different market niches; early adopters demonstrating its advantages; underlying investments in skills, training, and human capital; shared expectations around a technology’s prospects; mechanisms to share and exchange knowledge about what works; a consistent market environment without cyclical or stop-start activity that leads to turnover in workforces and the loss of acquired knowledge.
These are just some of the other pieces of the puzzle, elements of the broader innovation system. The cost reductions sought by policymakers and technology developers may be the corner piece that holds the rest together. But it doesn’t make a picture on its own.
This is why advocates of an Apollo program or Manhattan project for low-carbon technologies are wrong. These historical examples of singular science-led R&D programs are poor analogues for what’s needed in today’s energy market environment, with discerning consumers, profit-seeking developers, and cash-poor governments.
We need silver buckshot not silver bullets, diverse portfolios of options not one-shot, large-scale panaceas. Diversity means entrepreneurialism, risk-taking, variety, and experimentation in technology development, learning processes to sustain performance improvements through market deployment, and support for and protection of niche markets by public policy. More and more pieces of the puzzle.
What does it take to bring down the costs of new technologies? A systemic approach to innovation is key.
Learning from history
Our book identifies the hallmarks of historical innovation successes and sets out how we can apply these lessons towards a low-carbon future. We put the puzzle together to reveal the picture of a comprehensive yet simple framework for analyzing energy technology innovation.
An innovation systems perspective makes transparently clear that successful innovation is founded on effectively functioning innovation systems. An inter-dependent mesh of knowledge, institutions, use, and resources that cohere to support new technologies through development and out into the market. With a critical role for consistent, continuous and aligned policy support for all the elements of the energy system.
That corner piece? Well, it’s an important piece of the puzzle … but it’s only a piece.
The book ‘Energy Technology Innovation: Learning from Historical Successes and Failures’ is edited by Arnulf Grubler and Charlie Wilson, and published by Cambridge University Press. It’s also available on Amazon.com.
Note: This article gives the views of the authors, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
“We have to recognize that international approaches to climate change have basically failed. They are not going anywhere, maybe even backwards,” said economist William Nordhaus at a lecture for IIASA staff and young scientists on 23 June. The reason for this failure, he argued, is that international agreements have so far failed to deal with the problem of free riders.
The Kyoto Protocol, for instance, failed as countries dropped out one by one, as soon as mitigation started to become costly. Many countries never even ratified the agreement. Nordhaus explained, “There were no penalties for dropping out.”
Norhaus first introduced the concept of climate clubs at the IIASA 40th Anniversary Conference in 2012.
As the next round of climate talks approach this winter and next in Paris, many researchers say it is time for a new model for international climate change treaties. One new idea, which Nordhaus first proposed at the IIASA 40th Anniversary Conference in 2012, is the concept of “climate clubs.”
Nordhaus said, “Think of the treaty as a club. It’s a voluntary agreement, where members get certain benefits, for a certain cost.” A climate club would work like a free-trade union, such as the EU. It would encourage participation by penalizing non-participants, allowing members of the “climate club” to charge tariffs on all imports of non-participating nations. In his lecture on Monday, Nordhaus expanded on the concept he introduced in 2012, presenting the results of modeling work to determine the tariff rates and carbon prices that would be needed in such an agreement, and how participation would look.
Nordhaus found that more countries were likely to participate when carbon prices were lower. At a carbon price of 25 or 50 dollars, a majority of world regions would participate in the club, while at higher carbon prices of 75 to 100 dollars per ton of carbon dioxide, the highest participation rate would be only about half of that.
At IIASA on Monday. From left: William Nordhaus, IIASA Deputy Director General Nebojsa Nakicenovic, and IIASA Risk Policy and Vulnerability Program Director Joanne Bayer
The high carbon price, Nordhaus explained, would make the cost of participating much higher than the costs of tariffs for non-participants. However, with a lower carbon price, even low penalty tariffs of 3 to 4% could be enough to encourage participation. The idea of tariffs is simpler than previous suggestions of trade penalties based on the carbon emissions impact of specific goods—which in practice are difficult to define, and, as Nordhaus said, “not a big enough stick to induce participation.”
Like any trade agreement, though, Nordhaus’ climate club also means some win and some lose. When he examines the benefits on a regional level, the US, EU, and India appear to gain the most benefits, while Russia and China gain the least. What would it take to get such an agreement off the ground? Nordhaus said that a few key regions would be enough—for example, the EU, the USA, and China.
Watch Nordhaus’ 2012 Lecture at the IIASA Conference
William Nordhaus is Sterling Professor of Economics at Yale University, New Haven, Connecticut, USA. He has a B.A. from Yale University (1963) and a Ph.D. in Economics from MIT (1967). More>>
By Anne Goujon, IIASA World Population Program and Vienna Institute of Demography
How will societies develop in the future? And what environmental, economic, and social factors will influence these changes? Can these problems be analyzed in a scientific way? And if so, what tools should we use? On 13 June, I took part in a workshop for a project aimed at answering these questions.
The workshop took place in Nanterre, France. Photo Credit: Bladsurb via Flickr
I participated in a round table where we discussed how to find tools for forward-looking analysis and how to develop and integrate them to analyze societal change. This implies the integration of different models (economic, territorial, environmental), which can be very challenging. It can be difficult to avoid overlaps between models, and also to account for possible feedback effects between different factors. We discussed how to choose between two overlapping outputs such as two different GDP projections produced by environmental and economic models. Shall we try to validate the models historically by checking which model is best able to reconstruct the past? A nice idea, but most researchers agreed it would be too time and data-intensive to be practical. Another alternative, much less rigorous but easier to implement, would be to compare the results of the two models and decide which one is the best among the FLAGSHIP team. But according to which criteria? The last alternative would be to decide upfront which model should provide which outcome. It is almost a philosophical decision to be made as none is right or wrong.
Innovation seems to be at the core of all models for the future of Europe, encapsulating more than Information and Communication Technologies and Research and Development, but also incorporating other components such organizational capital – the share of a firm at management level. At the moment, FLAGSHIP is envisaging two storylines for the future—namely socio-ecological transition and global growth—which are actually not very far from some of the Shared Socioeconomic Pathway (SSP) scenarios developed by IIASA and others for the 5th assessment of the IPCC . Another IIASA researcher, Samir K.C. presented these scenarios at the meeting as an invited expert.
In a 2011 Science article, IIASA researchers Wolfgang Lutz and Samir KC showed the importance of population heterogeneity, specifically related to age, sex, and level of education, whenever population is an important driver of change. At the workshop, KC talked about the steps involved in the process of developing global demographic and human capital scenarios for the SSPs, with an emphasis on the importance of dialogue, discussion, and interactive iteration between the demographers and the user community in shaping the quality of the product. He recommended more consultation between the demographers and other experts in the FLAGSHIP project to produce consistent and meaningful demographic narratives. He also argued that existing scenarios such as SSPs should be explored and might be useful with some alterations.
Since the project looks at the next 50 years, rather short-term from a demographic point of view, population will possibly enter the whole model with just one scenario.
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