Jan 14, 2014 | Citizen Science, Environment
Steffen Fritz has just been awarded an ERC Consolidator Grant to fund a research project on crowdsourcing and ground data collection on land-use and land cover. In this interview he talks about his plans for the new project, CrowdLand.
Farmers in Kenya are one group which the Crowdland Project aims to involve in their data gathering. Photo credit: Neil Palmer, CIAT
What’s the problem with current land cover data?
There are discrepancies between current land cover products, especially in cropland data. It’s all based on satellite data, and in these data, it is extremely difficult to distinguish between cropland and natural vegetation in certain parts of the world if you do not use so-called very high resolution imagery, similar to a picture you take from space. With this high-resolution data you can see structures like fields and so on, which you can then use to distinguish between natural vegetation and cropland. But this is a task where currently people are still better at than computers–and there is a huge amount of data to look at.
In our Geo-Wiki project and related efforts such as the Cropland Capture game, we have asked volunteers to look at these high-resolution images and classify the ground cover as cropland or not cropland. The efforts have been quite successful, but our new project will take this even further.
How will the new project expand on what you’ve already done in Geo-Wiki?
The big addition is to go on the ground. Most of the exercises we currently do are based on the desktop or the phones, or tablets, asking volunteers to classify imagery that they see on a screen.
What this project aims to do is to improve data you collect on the ground, known as in-situ data. You can use photography, GPS sensors, but also your knowledge you have about what you see. We will use volunteers to collect basic land cover data such as tree cover, cropland, and wetlands, but also much more detailed land-use information. With this type of data we can document what crops are grown where, whether they are irrigated, if the fields are fertilized, what exact type of crops are growing, and other crop management information which you cannot see in satellite imagery. And there are some things you can’t even see when you’re on the ground, thus you need to ask the farmer or recruit the farmer as a data provider. That’s an additional element this project will bring, that we will work closely with farmers and people on the ground.
For the study, you have chosen Austria and Kenya. Why these two countries?
In Austria we have much better in situ data. For example, the Land Use Change Analysis System (LUCAS) in Europe collects in situ data according to a consistent protocol. But this program is very expensive, and the agency that runs it, Eurostat, is discussing how to reduce costs. Additionally the survey is only repeated every three years so fast changes are not immediately recorded. Some countries are not in favor of LUCAS and they prefer to undertake their own surveys. Then however you lose the overall consistency and there is no Europe-wide harmonized database which allows for comparison between countries. Our plan is to use gaming, social incentives, and also small financial incentives to conduct a crowdsourced LUCAS survey. Then we will examine what results you get when you pay volunteers or trained volunteers compared to the data collected by experts.
In Kenya, the idea is similar, but in general in the developing world we have very limited information, and the resources are not there for major surveys like in Europe. In order to remedy that the idea is again to use crowdsourcing and use a “bounded crowd” which means people who have a certain level of expertise, and know about land cover and land use, for example people with a surveyor background, university students, or interested citizens who can be trained. But in developing countries in particular it’s important to use financial incentives. Financial incentives, even small ones, could probably help to collect much larger amounts of data. Kenya is a good choice also because it has quite a good internet connection, a 3G network, and a lot of new technologies evolving around mobile phones and smartphone technology.
What will happen with the data you collect during this project?
First, we will analyze the data in terms of quality. One of our research questions is how good are the data collected by volunteers compared to data collected by experts. Another research question is how can imperfect but large data collected by volunteers be filtered and combined so that it becomes useful and fulfills the scientific accuracy requirements.
Then we will use these data and integrate them into currently existing land use and land cover data, and find ways to make better use of it. For example, in order to make projections about future land-use and to better quantify current yield gaps it is crucial to get accurate current information on land-use, including spatially explicit information on crop types, crop management information and other data.
Once we have done some quality checks we will also make these data available for other researchers or interested groups of people.
Crowdsourcing for land cover is in its infancy. There have been lots of crowdsourcing projects in astronomy, archaeology, and biology, for example, but there hasn’t been much on land use, and there is huge potential there. ”We need to not only better understand the quality of the data we collect, but also expand the network of institutions who are working on this topic.”
Note: This article gives the views of the interviewee, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Jan 7, 2014 | IIASA Network, Systems Analysis
On October 15, 2012, a young man from Bangladesh named Quazi Mohammad Rezwanul Ahsan Nafis parked next to New York Federal Reserve Bank in a van with what he believed was a 1000-pound bomb, walked a few blocks away, and then attempted to detonate the bomb by mobile phone.
In fact, the bomb was a fake, supplied by undercover agents for the United States FBI. The agents, posing as radical jihadists, had led Nafis along for months, allowing him to believe they were fellow terrorists and gathering information about his plot. The cover was maintained until the moment when his bomb failed to detonate, and Nafis was arrested. Disaster averted.
Researchers at IIASA study many risks to society, from floods, hurricanes, and natural disasters, to the impacts of climate change on future generations. They use models that can help disentangle the costs and benefits of different policies that could help prevent damage or deaths, or mitigate the impacts of global problems like climate change and air pollution. Could the same techniques apply to the dangers of terrorism and jihadists attacks? Could systems analysis help inform intelligence agencies in order to stop more terrorist attacks?
Could systems analysis techniques help guide policies to prevent terrorist attacks? Image Credit: Vjeran Pavic
Yale University Professor Ed Kaplan has done just that in work that he presented at IIASA in late December 2013. His research, which has intersected with IIASA in the past through collaborations with former IIASA Directors Howard Raiffa and Detlof von Winterfeldt, uses operations research to find ways to improve intelligence operations so as to catch more terrorists, before an attack can take place.
Kaplan, an expert on counterterrorism research, refined a simple economic model of customer service, known as a “queuing model” to instead represent the evolution of terror plots by terrorists, and interaction between the terrorists and the undercover agents who are working to uncover those plots.
“The best way to stop an attack is to know it’s about to happen beforehand,” says Kaplan. That means, in large part, having enough agents in the right places to detect attacks. But how many agents is the right number?
At IIASA, Kaplan described his terrorist “queuing model,” which can be applied to show how much a given number of agents would be likely to decrease attacks. Queuing models are an operations research method used to understand waiting times in lines, such as what happens at restaurants, offices, telephone queues or even internet servers.
But in the standard model, customers want to be served, and the servers know who the customers are. In Kaplan’s terrorist model, the terrorists – customers –don’t want to be served, and the servers—the agents—don’t know where their customers are. By modifying the model to account for those differences, Kaplan can answer some tricky questions about the best way for intelligence agencies to fight terrorism.
“Even if you don’t know how many terrorists there are or where they are, you can make it more likely that they will show themselves, you can make it more difficult for them to carry out an attack,” says Kaplan.
Kaplan’s method provides estimates of the numbers of undetected terrorist plots, as well as what it would take to increase detection rates.
Using data from court records of terrorism cases, Kaplan refined his models to include the average time that a terror plot is active – that is, the time from when a terrorist group first starts a plot, to the time that they are either caught, or the attack takes place. Based on the data, he could then calculate how many terror plots were likely to be in progress at any one time. He could also estimate the probability of detecting those plots, and how much that probability could be increased by employing more agents. For example, the model calculates that by increasing FBI agents by a factor of two would increase the detection rate from 80% to 89%.
But the data also point to one disturbing conclusion: A 100% detection rate is impossible. As the number of agents increases, the detection rate increases in ever smaller increments. Kaplan says, “We have to decide how safe is safe enough. When should we stop putting money into Homeland Security, and start putting more back into education and health?”
Download Kaplan’s IIASA presentation (PDF, 2.8 KB)
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Dec 19, 2013 | Air Pollution, Demography, Environment
By Erich Striessnig, Research Assistant, IIASA World Population Program
We have all heard about the terrible air pollution in India’s cities. Average concentrations of particulate pollution exceed World Health Organization guidelines through most of India, most of the time. So why hasn’t anything been done? Is it really too expensive?
In a recent publication with fellow IIASA Population Program researcher Warren Sanderson and IIASA Mitigation of Air Pollution and Greenhouse Gases Program researchers Wolfgang Schöpp and Markus Amann, we set to find out. In the study, published in the journal Environmental Science and Technology, we showed that in fact, policy reforms in India targeted at reducing emissions of dangerous fine particulate matter could save thousands of lives, and at the same time save money.
Air pollution in India exceeds World Health Organization limits much of the time, which contributes to health problems and premature deaths. Photo Credit: Mark Danielson via Flickr (Creative Commons License)
Due to their very small size, small particles released by cars, factories, and other combustion can travel very deep down into people’s lungs and cause or worsen all sorts of health issues. In Indian cities, where concentrations of these pollutants are already quite high, the expected increase in economic output over the next two decades will be accompanied by an enormous increase in air pollution, leading to a higher number of sick days or even deaths.
Both of these effects could be prevented or at least reduced if stricter regulations on emission limits – already in place in other countries – were imposed. The new study shows that if India enacted pollution controls as stringent as according to European legislation, by the year 2030, the end of the study period, up to 2.5 million premature deaths would be prevented.
So how do pollution controls save money? Healthier people are more productive because they are sick less often. People who can expect to live longer in a cleaner environment are more likely to make investments which would again create jobs and boost the economy. Our study shows that by 2030 such investments would in fact more than pay for themselves, when the economic benefits of a healthier population are considered.
So why haven’t politicians started doing something already much earlier? One answer might be that such reforms initially only produce costs, whereas the benefits typically don’t crystallize before the next elections. Hopefully, this latest scientific evidence from a collaboration of IIASA population and air pollution researchers can offer these politicians an impetus to act. Read more on the IIASA Web site.
Reference Warren Sanderson, Erich Striessnig, Wolfgang Schoepp, and Markus Amann. 2013. Effects on Well-Being of Investing in Cleaner Air in India. Environmental Science and Technology. 47 (23), pp 13222–13229 DOI: 10.1021/es402867r
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Dec 2, 2013 | Demography, Science and Policy
By Raya Muttarak, Research Scholar, IIASA World Population Program
For many years social scientists have observed a connection between economic downturns and a reduction in both unhealthy behaviors and mortality—a paradigm known as “healthy living in hard times.” One possible explanation for such counterintuitive findings was that people when people lose their jobs, have more spare time to dedicate to physical activities. Moreover, under an increased threat of unemployment, those who were still employed might limit their smoking and alcohol consumption in order to reduce their chances of being laid off. So the general agreement among social scientists has been that we should not worry too much about the impact of an economic crisis on health and mortality.
Our current global economic recession is the worst economic recession in contemporary history, however. And in a new study we found out that in fact, its consequences for health are very different from previous economic downturns. Since 2008, the number of smokers has increased substantially along with the increase in unemployed people.
In the new study, published in the journal Tobacco Control, we analyzed the effects of the current economic crisis on smoking in the United States, using data for around 2 million people from the Center for Disease Control’s Behavioral Risk Factor Surveillance System (BRFSS) survey for 2005 to 2010. In contrast to previous economic literature, we found an estimated increase of around 600,000 smokers due to the economic crisis.
Our study took into account the increase of the US population, the pre-crisis trends in smoking prevalence and the change in the distribution of population by socio-demographic characteristics.
We did find that “healthy living in hard times” still holds true for the employed individuals. Perhaps for fear of being laid off due to insurance reasons, these people maintain their healthy lifestyle. On the other hand, once without a job, people either started smoking or relapsed, possibly because of stress related to their new economic situation.
In contrast to previous economic literature, the new study finds an estimated increase of around 600,000 smokers due to the economic crisis. © Alexander Babich | Dreamstime.com
Since smoking prevalence by employment status remained more or less the same as before the crisis, a sharp increase in the number of unemployed individuals consequently led to a massive rise in the number of smokers. This has counterbalanced the trend in declining smoking rate among the employed.
Two main lessons can be drawn from our findings. First of all, YES…. this time it is different. The magnitude of the crisis has substantially changed the share of those with and without a job, with the latter being much more likely to engage in risky health behaviors. This in turns reversed most of the conclusions drawn by the previous literature. Second, we should not underestimate the impact of job-related stress factors on healthy behaviors. The idea that joblessness could be seen as a holiday where someone can engage in self-empowering activities is nice and reassuring, but it is meant to fail when unemployment is essentially unexpected and unwanted.
Reference
Gallus S, Ghislandi S, Muttarak R. Effects of the economic crisis on smoking prevalence and number of smokers in the USA. Tob Control. 2013 Aug 16. doi: 10.1136/tobaccocontrol-2012-050856. [Epub ahead of print] PubMed PMID: 23956058.
About the author
Raya Muttarak is a Research Scholar with the World Population (POP) Program. She came to IIASA in September 2011. Her current research covers three broad themes: 1) educational inequality and vulnerability and adaptation to climate change, 2) immigrant integration and ethnic inequality in education, the labor market and climate change adaptation, and 3) socioeconomic determinants of health risks and behaviors. More>>
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Nov 20, 2013 | Citizen Science, Environment, Food & Water
By Linda See, Research Scholar, IIASA Ecosystems Services and Management Program
Researchers estimate we spend 3 billion hours a week on game playing. CC Image courtesy TheErin on Flickr
On a recent rush hour train ride in London I looked around to see just about everybody absorbed in their mobile phone or tablet. This in itself is not that unusual. But when I snooped over a few shoulders, what really surprised me was that most of those people were playing games. I hope this bodes well for our new game, Cropland Capture, introduced last week.
Cropland Capture is a game version of our citizen science project Geo-Wiki, which has a growing network of interested experts and volunteers who regularly help us in validating land cover through our competitions. By turning the idea into a game, we hope to reach a much wider audience.
Playing Cropland Capture is simple: look at a satellite image and tell us if you see any evidence of cropland. This will help us build a better map of where cropland is globally, something that is surprisingly uncertain at the moment. This sort of data is crucial for global food security, identifying where the big gaps in crop yields are, and monitoring crops affected by droughts, amongst many other applications.
Gamification and citizen science
The idea of Cropland Capture is not entirely unique. There are an astonishingly large number of games available for high tech gaming consoles, PCs and increasingly, mobile devices. While the majority of these games are pure entertainment, some are part of an emerging genre known as ”serious games” or ”games with a purpose.” These are games that either have an educational element or through the process of playing them, you can help scientists in doing their research. One of the most successful examples is the game FoldIt, where teams of players work together to decode protein structures. This is not an easy task for a computer to do, but some people are exceptionally talented at seeing these patterns. The result has even led to new scientific discoveries that have been published in high level journals such as Nature.
Jane McGonigal, in her book Reality is Broken (Why Games Make us Better and How They Can Change the World), estimates that we spend 3 billion hours a week alone on game playing, and that the average young person spends more time gaming by the end of their school career than they have actually spent in school. Although these figures may seem alarming, McGonigal argues that there are many positive benefits associated with gaming, including the development of problem-solving skills, the ability to cope better with problems such as depression or chronic pain, and even the possibility that we might live ten years longer if we played games. If people spent just a fraction of this time on “serious games” like FoldIt and Cropland Capture, imagine how much could be achieved.
Since the game started last Friday, 185 players have validated 119,777 square kilometers of land (more than twice the land area of Denmark).
Cropland Capture is easy to play – simply swipe the picture left or right to say whether there is cropland or not.
Get in the game
You can play Cropland Capture on a tablet (iPad or Android) or mobile phone (iPhone or Android). Download the game from the Apple’s App Store or the Google Play Store. For those who prefer an online version, you can also play the game at: http://www.geo-wiki.org/games/croplandcapture/. For more information about the game, check out our videos at: http://www.geo-wiki.org/games/instructions-videos/. During the next six months, we will be providing regular updates on Twitter (@CropCapture) and Facebook.
The game is being played for six months, where the top scorer each week will be crowned the weekly winner. The 25 weekly winners will then be entered into a draw at the end of the competition to win three big prizes: an Amazon Kindle, a smartphone, and a tablet. The game was launched only last week so there is plenty of time to get involved and help scientific research.
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