Welcome to the InfoSci Platform
Reference Hub2
Spatial Pattern Mining for Soil Erosion Characterization

Spatial Pattern Mining for Soil Erosion Characterization

Nazha Selmaoui-Folcher, Frédéric Flouvat, Dominique Gay, Isabelle Rouet
Copyright: © 2011 |Volume: 2 |Issue: 2 |Pages: 20
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781613505489|DOI: 10.4018/jaeis.2011070105
Cite Article Cite Article

MLA

Selmaoui-Folcher, Nazha, et al. "Spatial Pattern Mining for Soil Erosion Characterization." IJAEIS vol.2, no.2 2011: pp.73-92. http://doi.org/10.4018/jaeis.2011070105

APA

Selmaoui-Folcher, N., Flouvat, F., Gay, D., & Rouet, I. (2011). Spatial Pattern Mining for Soil Erosion Characterization. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2(2), 73-92. http://doi.org/10.4018/jaeis.2011070105

Chicago

Selmaoui-Folcher, Nazha, et al. "Spatial Pattern Mining for Soil Erosion Characterization," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 2, no.2: 73-92. http://doi.org/10.4018/jaeis.2011070105

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The protection and the maintenance of the exceptional environment of New Caledonia are major goals for this territory. Among environmental problems, erosion has a strong impact on terrestrial and coastal ecosystems. However, due to the volume of data and its complexity, assessment of hazard at a regional scale is time-consuming, costly and rarely updated. Therefore, understanding and predicting environmental phenomenons need advanced techniques of analysis and modelization. In order to improve the understanding of the erosion phenomenon, this paper proposes a spatial approach based on co-location mining and GIS. Considering a set of Boolean spatial features, the goal of co-location mining is to find subsets of features often located together. This system provides useful and interpretable knowledge based on a new interestingness measure for co-locations and a new visualization of the discovered knowledge. The interestingness measure better reflects the importance of a co-location for the experts, and is completely integrated in the mining process. The visualization approach is a simple, concise and intuitive representation of the co-locations that takes into consideration the spatial nature of the underlying objects and the experts practice.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.