1.0Center for Geospatial Analyticshttps://www.clarku.edu/geospatial-analyticsCarol D'Onofriohttps://www.clarku.edu/geospatial-analytics/author/cdonofrio-s/rich600338<blockquote class="wp-embedded-content" data-secret="ysWq4vbO2p"><a href="https://www.clarku.edu/geospatial-analytics/projects/risk-mapping-for-redd/">Risk Mapping for REDD (Collaboration with Verra and TerraCarbon)</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.clarku.edu/geospatial-analytics/projects/risk-mapping-for-redd/embed/#?secret=ysWq4vbO2p" width="600" height="338" title="“Risk Mapping for REDD (Collaboration with Verra and TerraCarbon)” — Center for Geospatial Analytics" data-secret="ysWq4vbO2p" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! 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); //# sourceURL=https://www.clarku.edu/geospatial-analytics/wp-includes/js/wp-embed.min.js </script> https://www.clarku.edu/geospatial-analytics/wp-content/uploads/sites/117/thumbnail_verra_4_500-1-png.avif500500Since 2022, Clark Labs, in partnership with TerraCarbon, has worked with Verra to develop a methodology for the predictive mapping of the risk of unplanned deforestation in tropical jurisdictions containing REDD projects. This has now been accepted as the VT0007 Unplanned Deforestation Allocation (UDef-A) tool. The methodology provides a benchmark modeling approach that establishes a spatially and quantitatively explicit mapping of expected future deforestation for jurisdictions that may contain multiple REDD projects. A jurisdiction is typically a country, or a state or province for large countries. The tool also provides the means for incorporating alternative empirical models and for their evaluation against the benchmark. Work continues with the development and testing of an open-source software implementation (UDef-ARP) and toolboxes for ArcGIS and QGIS.