Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover

By Steffen Fritz, I. Mccallum, C. Schill, C. Perger, R. Grillmayer, Frédéric Achard, F. Kraxner, Michael Obersteiner. Remote Sensing, 2009

361 citations recorded by the source corpus.

Global land cover is one of the essential terrestrial baseline datasets available for ecosystem modeling, however uncertainty remains an issue. Tools such as Google Earth offer enormous potential for land cover validation. With an ever increasing amount of very fine spatial resolution images (up to 50 cm × 50 cm) available on Google Earth, it is becoming possible for every Internet user (including non remote sensing experts) to distinguish land cover features with a high degree of reliability. Such an approach is inexpensive and allows Internet users from any region of the world to get involved in this global validation exercise. The Geo-Wiki Project is a global network of volunteers who wish to help improve the quality of global land cover maps. Since large differences occur between existing global land cover maps, current ecosystem and land-use science lacks crucial accurate data (e.g., to determine the potential of additional agricultural land available to grow crops in Africa), volunteers are asked to review hotspot maps of global land cover disagreement and determine, based on what they actually see in Google Earth and their local knowledge, if the land cover maps are correct or incorrect. Their input is recorded in a database, along with uploaded photos, to be used in the future for the creation of a new and improved hybrid global land cover map.

Subfields: Ecological Modeling, Ecology, Geography, Planning and Development

View Paper: https://www.semanticscholar.org/paper/5085e9ebce09e0797e445591eb7f684139eff52f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. John M. Cinnamon
2. Nadine Schuurman
3. Clement Atzberger
4. Pascal Neis
5. Alexander Zipf

In Ecology

1. Clement Atzberger
2. Jun Xiong
3. M. Gumma
4. Prasad S. Thenkabail
5. Russ Congalton
6. Kamini Yadav
7. Pardhasaradhi Teluguntla

In Geography, Planning and Development

1. Pascal Neis
2. Alexander Zipf
3. John M. Cinnamon
4. Nadine Schuurman
5. Dennis Zielstra
6. Geoff Boeing

Citations in the corpus

• Automated cropland mapping of continental Africa using Google Earth Engine cloud computing (2017, methodology): “A webbased system for supporting classification have been used in the past for general land cover (Fritz et al., 2009; Tsendbazar et al., 2015).”
• Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs (2013, background): “Interesting attempts are, for example, GeoWiki [148]) and JECAM [149]; • Space agencies and sensor developers spend huge amounts of money for precise radiometric calibration of the deployed instruments.”
• Confronting the data-divide in a time of spatial turns and volunteered geographic information (2013, background): “Also, Fritz et al. (2009) describe www.geo-wiki.org, a Web site that allows distributed users to interact with Google Earth imagery to contribute to a global land classification project.”
• The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007-2011 (2011, background): “The successful development of user generated content in recent years had an increasing impact on a variety of research fields and particularly OSM has been the focus of many new developments such as routing applications, 3D city models and Location-Based Services (LBS) [20–23].”