{"id":2419,"date":"2019-10-02T19:52:06","date_gmt":"2019-10-02T19:52:06","guid":{"rendered":"https:\/\/www.gsnv.org\/shop\/expert-fuzzy-holistic-classifier-applied-to-hyperspectral-data-over-precious-metal-prospects-in-the-swir-2-0-to-2-4-um\/"},"modified":"2020-02-24T18:17:32","modified_gmt":"2020-02-24T18:17:32","slug":"expert-fuzzy-holistic-classifier-applied-to-hyperspectral-data-over-precious-metal-prospects-in-the-swir-2-0-to-2-4-um","status":"publish","type":"product","link":"https:\/\/www.gsnv.org\/shop\/expert-fuzzy-holistic-classifier-applied-to-hyperspectral-data-over-precious-metal-prospects-in-the-swir-2-0-to-2-4-um\/","title":{"rendered":"Expert fuzzy\/holistic classifier applied to hyperspectral data over precious metal prospects in the SWIR (2.0 to 2.4 um)"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"<p>A method is presented for the classification of hyperspectral imagery. The<br \/>\nmethod strives to deliver a product in which a typical user acquires concrete evidence<br \/>\nfor believing the correctness of the classification. We discuss an example using the easiest<br \/>\npossible case so that the presentation is clear: mapping alunite over Cuprite,<br \/>\nNevada, where mineralogical exposures are relatively unobscured and well defined.<br \/>\nThe method brings together in a single package the two main methodologies that have<br \/>\nbeen used to classify images:<br \/>\n\u2022 the holistic approach in which each spectral wavelength is weighted equally, and<br \/>\n\u2022 a feature-based approach in which the identification relies on the presence of<br \/>\nrecognizable spectral absorption features while ignoring the broad characteristics<br \/>\nof the image spectrum.<br \/>\nThe increased availability of hyperspectral imagery using 200 or more narrow<br \/>\nspectral bands permits the increased use of accurate feature-based methods to distinguish<br \/>\nsimilar clay minerals in a way not possible from such imagery as thematic mapper<br \/>\n(TM). While nonexperts can interpret the results of this method, an expert is<br \/>\nrequired for the design of the classification except in the most straightforward cases.<\/p>\n","protected":false},"featured_media":4233,"comment_status":"closed","ping_status":"closed","template":"","meta":{"pmpro_default_level":""},"product_cat":[154],"product_tag":[],"_links":{"self":[{"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/product\/2419"}],"collection":[{"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/comments?post=2419"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/media\/4233"}],"wp:attachment":[{"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/media?parent=2419"}],"wp:term":[{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/product_cat?post=2419"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/www.gsnv.org\/wp-json\/wp\/v2\/product_tag?post=2419"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}