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Issue Date: March 21st 2019
Last modified: March 21st 2019
Learning

Urban Forests on the UN Global Platform Methods Service

Over the past six weeks the UN Global Platform has been collaborating with the UK’s Data Science Campus to develop an implementation of the Urban Forest project onto the cloud-based platform. The Urban Forests project aims to create an index of vegetation through taking Google street view images around the road network and classifying the amount of vegetation in each image.

Documentation Link: http://joe.peskett.projects.officialstatistics.org/ungp_blog/jekyll/update/2018/11/13/Urban-Forests-on-UNGP.html

Partner: Office for National Statistics

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Over the past six weeks the UN Global Platform has been collaborating with the UK’s Data Science Campus to develop an implementation of the Urban Forest project onto the cloud-based platform. The Urban Forests project aims to create an index of vegetation through taking Google street view images around the road network and classifying the amount of vegetation in each image. High level information on the project is available here, and a full report can be read here.

Largely, the process of implementeing this on the platform has involved development of a series of algorithms in the methods service. The methods service allows for methods to be written in a range of languages (R, Python, Java) which can then be called from a wide range of languages. This allows for a combination of languages to easily be used in a single pipeline. Each part of the pipeline is contained within it’s own algorithm, allowing them to be called independtly of one another. This post will walk through the creation of a number of these algorithms, how these have been combined to form a pipeline and how this could be reused.

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