1.0British Antarctic Surveyhttps://www.bas.ac.ukAI for Earth Observation - British Antarctic Surveyrich600338<blockquote class="wp-embedded-content" data-secret="3w2yw748XV"><a href="https://www.bas.ac.uk/project/ai-for-earth-observation/">AI for Earth Observation</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.bas.ac.uk/project/ai-for-earth-observation/embed/#?secret=3w2yw748XV" width="600" height="338" title="“AI for Earth Observation” — British Antarctic Survey" data-secret="3w2yw748XV" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script type="text/javascript">
/* <![CDATA[ */
/*! This file is auto-generated */
!function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document);
/* ]]> */
</script>
https://www.bas.ac.uk/wp-content/uploads/2024/07/Feature-Image.png360323Recent increases in the spatial coverage and temporal resolution of 40 m resolution Synthetic Aperture Radar (SAR) imagery, is opening new opportunities to rapidly detect environmental observations e.g. ice sheet and iceberg position with greater positional accuracy. Our team are developing supervised and unsupervised machine learning techniques to automatically detect sea ice and iceberg position from Sentinel-1 SAR imagery.