{"id":32796,"date":"2020-05-19T20:47:41","date_gmt":"2020-05-19T20:47:41","guid":{"rendered":"https:\/\/www.bgs.ac.uk\/?post_type=research_project&#038;p=32796"},"modified":"2020-08-17T13:47:07","modified_gmt":"2020-08-17T13:47:07","slug":"mapping-with-machine-learning","status":"publish","type":"research_project","link":"https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/mapping-with-machine-learning\/","title":{"rendered":"Mapping with machine learning"},"content":{"rendered":"\t\t\t<section class=\"hero-section hero-section-with-social\">\n\t\t\t\t\t\t\t\t<div class=\"hero-info-wrap\">\n\t\t\t\t\t<div class=\"container\">\n\t\t\t\t\t\t<div class=\"row\">\n\t\t\t\t\t\t\t<div class=\"col-12\">\n\t\t\t\t\t\t\t\t<div class=\"hero-info\">\n\t\t\t\t\t\t\t\t\t<h1>Mapping with machine learning<\/h1>\n\t\t\t\t\t\t\t\t\t<p>BGS Research &mdash; Product development<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"social-wrap social-wrap-inline-them\">\n\t\t\t\t<div class=\"sea-background-f\">\n\t\t\t\t\t<span>Share this article<\/span><a target=\"_blank\"  href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/mapping-with-machine-learning\/\"><span class=\"icon-facebook\"><span class=\"hidden\">Facebook<\/span><\/span><\/a><a target=\"_blank\"  href=\"https:\/\/twitter.com\/intent\/tweet?text=Mapping%20with%20machine%20learning&#038;url=https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/mapping-with-machine-learning\/\"><span class=\"icon-twitter\"><span class=\"hidden\">Twitter<\/span><\/span><\/a><a   onclick=\"javascript:void( (function() {var e=document.createElement('script' );e.setAttribute('type','text\/javascript' );e.setAttribute('charset','UTF-8' );e.setAttribute('src','\/\/assets.pinterest.com\/js\/pinmarklet.js?r='+Math.random()*99999999);document.body.appendChild(e)})());\"  href=\"javascript:void(0);\"><span class=\"icon-pinterest\"><span class=\"hidden\">Pinterest<\/span><\/span><\/a><a target=\"_blank\"  href=\"https:\/\/wa.me?text=https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/mapping-with-machine-learning\/\"><span class=\"icon-whatsapp\"><span class=\"hidden\">WhatsApp<\/span><\/span><\/a><a   href=\"mailto:?subject=Mapping%20with%20machine%20learning&#038;body=Recently%20there%20has%20been%20a%20trend%20towards%20the%20collection%20of%20ever-more%20quantitative%20data,%20as%20exemplified%20by%20the%20Tellus%20projects.%20(https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/mapping-with-machine-learning\/)\"><span class=\"icon-mail\"><span class=\"hidden\">Email<\/span><\/span><\/a><a href=\"#\" data-copy=\"https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/mapping-with-machine-learning\/\" class=\"copy-url-on-click\"><span class=\"icon-link\"><span class=\"hidden\">Copy Link<\/span><\/span><\/a><\/div><\/div>\t\t\t\t\t\t\t<\/section>\n\t\t\t\n\n\n<section class=\"wp-block-bgs-blocks-content-container content-section\"><div class=\"container\"><div class=\"row\"><div class=\"col-12\">\n<p>In recent years, there has been a trend towards the collection of ever-more quantitative data, a movement that has so far been exemplified by the Tellus projects in&nbsp;<a aria-label=\"undefined (opens in a new tab)\" href=\"https:\/\/www.bgs.ac.uk\/gsni\/Tellus\/\" target=\"_blank\" rel=\"noreferrer noopener\">Northern Ireland<\/a>&nbsp;and&nbsp;<a rel=\"noreferrer noopener\" href=\"http:\/\/www.tellusgb.ac.uk\/\" target=\"_blank\">south-west England<\/a>. These projects consisted of series of surveys collecting both geochemical and geophysical data through combined ground and air surveys. The beauty and utility of these multidisciplinary surveys is uncovered not in the independent analysis of individual variables, of which there are many, but in the treatment of the large, multivariate datasets as a single system: a fully quantitative representation of the geo-environment as a whole.<\/p>\n\n\n\t\t\t\t<div  class=\"owl-carousel carousel-primary-color carousel owl-theme thumbs-carousel-js\">\n\t\t\t\t\t<div class=\"item\"><figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Cornwall_join-to-Northern-Ireland.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Regression-tree ensemble model of three compositional components of Cornwall\u2013Devon soil chemistry. BGS \u00a9 UKRI.&lt;\/p&gt;\n\" data-gallery=\"gallery_56209\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Cornwall_join-to-Northern-Ireland.jpg\" class=\"attachment-medium size-medium\" alt=\"Regression tree for Cornwall - Devon\" \/><\/a><figcaption class=\"caption \">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Regression-tree ensemble model of three compositional components of Cornwall\u2013Devon soil chemistry. BGS \u00a9 UKRI.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Cornwall_join-to-Northern-Ireland.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Regression-tree ensemble model of three compositional components of Cornwall\u2013Devon soil chemistry. BGS \u00a9 UKRI.&lt;\/p&gt;\n\" data-gallery=\"gallery_56209\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure><\/div><div class=\"item\"><figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Northern_Ireland_link_to_cornwall.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Regression-tree ensemble model of three compositional components of Northern Ireland&#8217;s soil chemistry. BGS \u00a9 UKRI.&lt;\/p&gt;\n\" data-gallery=\"gallery_56209\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Northern_Ireland_link_to_cornwall.jpg\" class=\"attachment-medium size-medium\" alt=\"Northern Ireland soil chemistry\" \/><\/a><figcaption class=\"caption \">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Regression-tree ensemble model of three compositional components of Northern Ireland&#8217;s soil chemistry. BGS \u00a9 UKRI.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Northern_Ireland_link_to_cornwall.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Regression-tree ensemble model of three compositional components of Northern Ireland&#8217;s soil chemistry. BGS \u00a9 UKRI.&lt;\/p&gt;\n\" data-gallery=\"gallery_56209\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure><\/div>\t\t\t\t<\/div>\n\t\t\t\t\n\n\n<p>Thanks to the current global explosion in big data analytics, we have more tools at our disposal than ever before to make sense of such complex data systems. We can use these tools \u2014 machine learning algorithms \u2014 to explore our data and to condense them into meaningful, evidence-based solutions for specific end users.<\/p>\n\n\n\n<p>The maps reveals all the same features as a traditional geological map and more, all with transparent uncertainties and prediction accuracies in excess of traditional interpolation methods (cross-validated R<sup>2<\/sup>s up to 0.9).<\/p>\n\n\n<figure  class=\"img-wrap\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Arsenic_enrichment.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Arsenic enrichment in south-west England, produced using an artificial neural network in the MXNet framework. BGS \u00a9 UKRI.&lt;\/p&gt;\n\" data-gallery=\"gallery_65301\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Arsenic_enrichment-150x150.jpg\" class=\"lazy-blur\" alt=\"Arsenic enrichment SW England\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Arsenic_enrichment.jpg\" \/><\/a><figcaption class=\"caption \">\n\t\t\t\t\t<div class=\"caption-icon\">\n\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/info-caption.svg\" alt=\"Information icon\">\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div class=\"caption-text\"><p>Arsenic enrichment in south-west England, produced using an artificial neural network in the MXNet framework. BGS \u00a9 UKRI.<\/p>\n<\/div>\n\t\t\t\t\t<div class=\"expand-box expand-box-top\"><a href=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Arsenic_enrichment.jpg\" data-toggle=\"lightbox\" data-footer=\"&lt;p&gt;Arsenic enrichment in south-west England, produced using an artificial neural network in the MXNet framework. BGS \u00a9 UKRI.&lt;\/p&gt;\n\" data-gallery=\"gallery_65301\"><img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/themes\/bgs\/img\/expand.svg\" alt=\"Expand icon\"><\/a><\/div>\n\t\t\t\t<\/figcaption><\/figure>\n\n\n<p>The use of machine learning has so far been focused on modelling and predicting geochemistry; after all, chemical composition is a direct quantification of what a rock or soil actually is and therefore provides an ideal data format through which to port traditional mapping workflows into the digital domain.<\/p>\n\n\n\n<p>As interest grows in improving evidence-based understanding of the behaviour of the rocks beneath our feet, we will need to augment our data systems with measurements of a wider range of geo-properties. For example, in addition to data on chemical composition, we can incorporate data on mechanical properties, hydrological properties and so on in order to provide reliable decision-support tools for a wider user base.<\/p>\n\n\n\n<p>For now, machine learning is successfully allowing us to translate multisensory, airborne-survey data into accurate, high-resolution maps of the chemical composition of the rocks and soils that support the foundations of our society.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Contact<\/h2>\n\n\n\n<p>If you want to discover more then please contact <a href=\"https:\/\/www.bgs.ac.uk\/people\/lawley-russell\/\">Russell Lawley<\/a>. <\/p>\n<\/div><\/div><\/div><\/section>\n\n\n\t\t\t\t\t<section   id=\"latest-content-8862-block_5e7b0d7d9c15e\" class=\"grid-section  primary-background   \" >\n\t\t\t\t\t\t<div class=\"container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"row header-of-section\">\n\t\t\t\t\t\t\t\t<div class=\"col-12\">\n\t\t\t\t\t\t\t\t\t<h2>You may also be interested in<\/h2>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"row grid-wrap\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"col-lg-6 col-12\">\n\t<div class=\"cards cards-orizontal-sm  cards-find-more  cards-bordered\">\n\t\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/\" class=\"media-wrap\">\n\t\t\t<img decoding=\"async\" src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Blueprint_map_feature-150x150.jpg\" class=\"lazy-blur wp-post-image\" alt=\"Blueprint_map_feature\" data-src=\"https:\/\/www.bgs.ac.uk\/wp-content\/uploads\/2020\/05\/Blueprint_map_feature.jpg\" \/>\t\t\t\t\t<\/a>\n\t\t\t\t<div class=\"info-wrap\">\n\t\t\t<div class=\"info\">\n\t\t\t\t<h4><a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/\">Product development<\/a><\/h4>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<p>The properties and resources team publishes a broad range of geological data and information, including digital mapping, for all stakeholders.<\/p>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t<a href=\"https:\/\/www.bgs.ac.uk\/geology-projects\/product-development\/\">Show more<\/a>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"row\">\n\t\t\t\t\t\t\t\t<div class=\"col-12\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/section>\n\t\t\t\t","protected":false},"excerpt":{"rendered":"<p>Recently there has been a trend towards the collection of ever-more quantitative data, as exemplified by the Tellus projects.<\/p>\n","protected":false},"featured_media":32988,"parent":32251,"menu_order":3,"template":"","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"10218,7336,7818,17220,37523,8334","_relevanssi_noindex_reason":""},"tags":[],"region":[],"topic":[],"purpose":[],"area":[],"challenge":[],"challenge_topic":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.3 - 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