Geographical Information Systems: A Picture is Worth More Than a Thousand Datasets
February 7, 2020
A little more than a year ago, my colleague from the Program Assurance Team wrote a blog about the importance of knowing the location of ASC certified farms. What has become of this project, and where will it go in the future?
By Laura Guthschmidt, GIS Coordinator
Last year we had the intention of collecting more accurate coordinate data to create a ‘certification map’. As a Geographical Information System (GIS) person, this wasn’t enough for me. The ASC species standards allow for far more interesting data to be captured than just precise coordinates.
If we truly want to make use of the possibilities that geospatial data offers, then we have to get access to more descriptive farm data; this is where polygons come in.
A polygon doesn’t look like much more than a bunch of lines covering an area, but in reality you can use these lines to systematically analyze the surroundings of a farm.
In the case of ASC this means we can track the boundaries of certified farms to verify compliance with some of the standard indicators, we can measure farm growth over time, and we can calculate production area versus production volume if the data quality allows it. A simple coordinate point would not offer this capability.
In the image above, a (fictive) farm location is displayed using only coordinates (in yellow). It appears to show that the farm is not sited in the Protected Area (in green) – and is around 82 metres away. Compare this with the fuller picture provided by polygons below.
In the above image, polygons (blue lines) make it possible to calculate exact overlap between the fictive farm boundaries and the Protected Area. The additional detail given by the polygons reveal that the farm does in fact overlap with the protected area.
In order for ASC to become a more data-driven organisation, many processes have to be automated. Ensuring the standardisation of data collection is a first step in this process. From there, the data becomes usable for analyses, and therefore more valuable.
The standardisation of incoming geospatial data plays a big role in ensuring that ASC can meet our GIS goals.
From February 5 this year, farms will be required to submit spatial data as part of their annual audit process.
To enable the collection of polygon data that meets our requirements, we have developed a GIS Online Portal that includes an app with all our certified ASC farm coordinates on it. Farmers can now go to this app and draw their farm boundaries to form a polygon according to guidelines that can be found on the portal as well.
The ASC GIS app also contains a number of geospatial data layers that are either directly or indirectly related to one of our species standards – these range from a World Database on Protected Areas to data on indigenous peoples’ land boundaries.
Even though we try to have the best possible data available, as with all geospatial data it is reliant on a number of other factors such as coverage, resolution, accurate time range, how it was acquired, the source, and the copyright. A metadata table on our GIS portal covers these values for each layer in the GIS app.
All ASC farms undergo surveillance audits at least once a year, which means we will have polygon data for all ASC certified farms in just 12 months’ time – February 5 2021! Then we can begin the fun part of analyzing.
Of course, we want to make this process as simple and straightforward as possible, and all Conformity Assessment Bodies (that’s the auditors) and certificate holders (that’s the farms) have been notified of this requirement, and the reasons behind it, via email and a series of webinars.
From the beginning, ASC has worked according to a Theory of Change that supports a transparency ethos, by providing free and unrestricted access to all audit reports, as well as status of sites within our program, through the ASC website.
This project supports the greater aim of transparency and accountability, improvement of services and the creation of new environmental and social value of data. If you want to know more about this project, see our Storymap!