09 August 2012
Owing to the importance of global land cover in disciplines such as climate change, food security and land-use modelling, the creation of a global land cover calibration and validation data set is essential. We established a global sample of validation points which were classified in this competition. Validators were ask to identify the degree of human impact (on a scale from 0 to 100) which is visible from Google Earth imagery. Examples illustrating the concept of human impact across the full spectrum (from areas devoid of influence to urbanized areas with large impervious surfaces) were provided to the volunteers as part of online training materials. Through different Geo-Wiki crowdsourcing competitions, more than 100,000 validation samples of human impact were collected globally.
Rank | Name | Affiliation |
1 | Ujjal Deka Baruah | Gauhati University, Guwahati, Assam, India |
2 | Anup Saikia | Gauhati University, Guwahati, Assam, India |
3 | Kuleswar Singh | Gauhati University, Guwahati, Assam, India |
4 | Sergio de Miguel | University of Eastern Finland, Joensuu, Finland |
5 | Rubul Hazarika | Gauhati University, Guwahati, Assam, India |
6 | Ankita Sarkar | Gauhati University, Guwahati, Assam, India |
7 | Abel Alan Marcarini | AgroParis Tech, Nancy, France |
8 | Mrinal Baruah | Gauhati University, Guwahati, Assam, India |
9 | Dhrubajyoti Sahariah | Gauhati University, Guwahati, Assam, India |
10 | Trishna Changkakati | Gauhati University, Guwahati, Assam, India |
By interpolating the validation samples of human impact points and by using a simplified remoteness concept – which is distance to visible human influence - a map of human impact has been produced (Figure 1).
Comparing the crowdsourced map of human impact with version 2 of the human footprint by Sanderson et al. (2002), there are large differences primarily in areas of agriculture and some desert regions, where human impact is visible from space but which is not picked up using the methodology of Sanderson et al. (2002). Our analysis will undertake a systematic comparison of the two products, use the crowdsourced data to validate the Sanderson map and consider the advantages and disadvantages of a crowdsourcing approach for creating maps of wilderness. Recommendations for how the method can be improved in the future will also be presented.
An abstract of the study has been submitted to the WILD10 Conference "MAKE THE WORLD A WILDER PLACE" taking part from 4-10 October 2013 in Salamanca, Spain.
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Program Director and Principal Research Scholar Strategic Initiatives Program
Principal Research Scholar Novel Data Ecosystems for Sustainability Research Group - Advancing Systems Analysis Program
Principal Research Scholar Novel Data Ecosystems for Sustainability Research Group - Advancing Systems Analysis Program
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