image missingTrue Value Metrics (TVM)
Meaningful Metrics for a Smart Society
image missing Navigation ... HOME
SiteNav SitNav (1) SitNav (2) SitNav (3) SitNav (4) SitNav (5) SitNav (6) SitNav (7) SitNav (8)
Date: 2020-02-25 Page is: DBtxt001.php txt00009955

Good but not good enough

Can You Use Big Data to Track an Elephant Poacher?

This is an interesting article but it should be read with caution. I am an advocate for technology but am very aware of its limitations. With technology like this more people are able to know something about the state of elephant poaching, but what about fixing the problem of elephant poaching. Knowing, talking, is one thing. Actually doing something effective to fix the problem is another thing, and they should not be confused. From what I know of the problem we are losing the battle and all we have succeeded in doing with technology is to tell more people that we are losing the battle. Something beyond technology is needed to win this battle ... and I don't see anything happening to change the terrible trajectory of this problem.

Peter Burgess
Peter Burgess

Can You Use Big Data to Track an Elephant Poacher?

Why looking at a map of news headlines could help us see critical patterns and trends in wildlife crime.

Can You Use Big Data to Track an Elephant Poacher?

By many accounts, 2013 was the year wildlife crime jumped to global prominence. The illicit trade in wildlife products doubled over the preceding four years to become what the World Wildlife Fund argues is now the “fifth-most profitable illicit trade in the world.” The uptick in wildlife poaching has also become a growing threat to the stability of central Africa, with proceeds increasingly funding terrorist organizations. Upwards of 40 percent of al-Shabab’s operating costs, for example, allegedly stem from the ivory trade.

Yet, despite growing interest and media coverage of its impact, there are still significant information gaps in understanding its reach, scale, and enablers. For example, the USAID-supported Wildlife Crime Tech Challenge seeks “innovative solutions to detect, monitor, and predict illicit transit routes,” while the United Nations noted in March the need to “improve the data and evidence base for interventions.”

What kind of story about poaching in Africa would we be able to piece together if we could use “big data” to sift through global news reporting of wildlife and environmental crime over the last three months to create a map of its scale as sifted through the lens of the international media? Using the Global Database of Events, Language, and Tone (GDELT) Project, which monitors local media around the world (and live-translates it from 65 languages, along with Google’s BigQuery system and CartoDB’s online mapping platform), the map offers a glimpse through the nearly 30,000 articles relating to wildlife and environmental crime monitored by GDELT from Feb. 19 through June 2. Each dot on the map represents a location mentioned alongside wildlife crime during that period — clicking on a dot will display a list of monitored coverage mentioning that location. A separate live-updating map refreshes every hour and provides a real-time glimpse of the most recent coverage.

Globally mapping the news involves enormous technical challenges — meaning there will be inevitable false positives in the map above, as a result of headlines with language like “poached eggs” and “poached executives,” translation difficulties, errant “breaking news updates” or information boxes, and dead links. But overall the map should reflect a reasonable view of global media coverage of wildlife crime over the past three months.

So what does the map actually tell us? By arranging the world’s news reporting on wildlife crime geographically, we are able to see how actions in one part of the globe affect another, how the wildlife trade impacts almost every country, the range of plants and animals affected, and its human cost. It would be difficult for a single person to read all 30,000 news reports in 65 languages, yet computers can do so within a matter of minutes, making it possible to look across all of those reports to paint a picture of the trade’s global impact. Perhaps most striking is that by using the map, we can see that wildlife crime is not something that only affects a handful of game preserves in Africa — it is a global phenomenon that affects almost every country.

The numbers of animals affected by wildlife crime can be staggering: By some estimates, upwards of 73 million sharks are killed each year for their fins alone to create shark fin soup. Given that Texas serves as the gateway for over half the shark fin trade in the United States, the Texas legislature passed a new bill last month formally banning the trade.

National Geographic reported that in Africa, more than 100,000 elephants were killed by humans between 2010 and 2012, with the population declining more than 64 percent in central Africa over just the last decade (the article sites a study published in Proceedings of the National Academy of Sciences). This increase is, perhaps, in large part a result of the availability of modern weaponry, which then increases poachers’ ability to maximize fatalities. In one particularly violent incident, poachers armed with AK-47 machine guns and grenades slaughtered more than 300 elephants in a single attack. In the Itapagipe Peninsula in Brazil, illegal fishermen are resorting to dynamite and explosives to kill and catch large numbers of fish at once, simultaneously causing damage to houses along the coast.

Yet, modern technology is also providing solutions to help deter poaching, especially drones. In Africa, drones are increasingly being used both to monitor elephants and even to herd them out of harm’s way. In Jamaica, drones are being tested to monitor fishing activity via live video feeds. Social media has also been used in anti-trafficking campaigns, with a recent effort in India claiming to reach over 1.4 million people.

It is not just animals that are illegally caught and sold. The 2013 theft of more than 1,000 Venus’ flytraps in Wilmington, North Carolina, led to a new law making theft of the plants a felony punishable by up to two years in prison. Yet, even with the threat of jail time, in January of this year four men were caught with 970 of the poached plants, representing 3 percent of the entire natural population. In California, redwood forests are increasingly grappling with poachers targeting the redwood burls that are critical to the trees’ health.

Clashes between legitimate hunters or fishermen and poachers can become violent. In one confrontation between Sri Lankan fishermen and alleged poachers, “three fishermen were injured and fishing nets and a boat damaged when Indian fishermen threw petrol bombs, pelted stones and sharp objects” at them. Violent confrontations with security services can also result. When 100 red sandalwood poachers were confronted by police in Seshachalam forest in India in April, they first “attacked policemen with sickles and axes and pelted stones on them,” followed by a “heavy exchange of gunfire from both sides” in which 20 of the poachers were killed.

Poaching can have a terrible human cost, with human trafficking sometimes used to provide the necessary labor force. This past March global headlines focused on nearly 4,000 foreign fishermen trapped on remote Indonesian islands after the government began cracking down on illegal fishing boats. Some had previously been forced into slavery and “beaten and locked in cages” with their illegal catch sold in American grocery stores.

Through the emerging lens of big data, we are able to transform a bulleted list of tens of thousands of news articles into a holistic visualization that highlights geographic patterns. We can hopefully make it possible to find new ways of understanding global trends in wildlife crime, publicize its local impacts, and better communicate to the public its impact on society. Perhaps this is big data’s greatest potential today: not as a crystal ball seeing into the future, but as a mapmaker that transforms chaos into cartography.


JUNE 12, 2015
The text being discussed is available at

Amazing and shiny stats
Blog Counters Reset to zero January 20, 2015
TrueValueMetrics (TVM) is an Open Source / Open Knowledge initiative. It has been funded by family and friends plus donations from well wishers who understand the importance of accountability and getting the management metrics right. TVM is a 'big idea' that has the potential to be a game changer leveling the playing field so the wealth and power is shared on a more reasonable basis between people who work for a living and those that own the economy and the levers of power. In order to be effective, it cannot be funded in the conventional way with a for profit business plan, but absolutely must remain an open access initiative.

The information on this website may only be used for socio-enviro-economic performance analysis, personal information, education and limited low profit purposes
Copyright © 2005-2019 Peter Burgess. All rights reserved.