Nonparametric and probabilistic classification using NN-balls with environmental and remote sensing applications
2011 (English)In: Advances in Directional and Linear Statistics: A Festschrift for Sreenivasa Rao Jammalamadaka / [ed] M.T. Wells & A. Sengupta, Heidelberg: Physica Verlag, 2011, 201-216 p.Chapter in book (Refereed)
National and international policies today require environmental follow-upsystems that detect, in a quality assured way, changes over time in land use and landscape indicators. Questions related to environmental health and spatial patterns call for new statistical tools.We present in this chapter some new developments on the classification of land use by using multispectral and multitemporal satellite images, based on techniques of nearest neighbour balls. The probabilistic classifiers introduced are useful for measuring uncertainty at pixel level and obtaining reliable area estimates locally. Also some theoretical considerations for the reference sample plotmethod (today named k-NN method in natural resource applications) are presented.
Place, publisher, year, edition, pages
Heidelberg: Physica Verlag, 2011. 201-216 p.
Probability Theory and Statistics
Research subject Mathematical Statistics
IdentifiersURN: urn:nbn:se:umu:diva-63687DOI: 10.1007/978-3-7908-2628-9_14ISI: 000284726800014ISBN: 978-3-7908-2627-2ISBN: 978-3-7908-2628-9OAI: oai:DiVA.org:umu-63687DiVA: diva2:582324