{"version":"1.0","provider_name":"MAAP","provider_url":"https:\/\/www.maapprogram.org\/pt-br\/","author_name":"MAAP Consultants","author_url":"https:\/\/www.maapprogram.org\/pt-br\/author\/maapconsultants\/","title":"MAAP #65: Pontos cr\u00edticos de desmatamento em 2017 na Amaz\u00f4nia peruana - MAAP","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"l5YUN3oYtF\"><a href=\"https:\/\/www.maapprogram.org\/pt-br\/maap-65-portugues\/\">MAAP #65: Pontos cr\u00edticos de desmatamento em 2017 na Amaz\u00f4nia peruana<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/www.maapprogram.org\/pt-br\/maap-65-portugues\/embed\/#?secret=l5YUN3oYtF\" width=\"600\" height=\"338\" title=\"&#8220;MAAP #65: Pontos cr\u00edticos de desmatamento em 2017 na Amaz\u00f4nia peruana&#8221; &#8212; MAAP\" data-secret=\"l5YUN3oYtF\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!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);\n\/\/# sourceURL=https:\/\/www.maapprogram.org\/wp-includes\/js\/wp-embed.min.js\n\/* ]]> *\/\n<\/script>\n","description":"Em um relat\u00f3rio anterior,\u00a0MAAP #40\u00a0, destacamos o poder de combinar alertas GLAD* de alerta precoce com an\u00e1lises de imagens de sat\u00e9lite de alta resolu\u00e7\u00e3o (por exemplo, da empresa\u00a0Planet\u00a0), como parte de um sistema abrangente de monitoramento de desmatamento\u00a0quase em tempo real\u00a0. No relat\u00f3rio atual, analisamos os alertas GLAD do primeiro semestre de 2017 (at\u00e9 17 [&hellip;]","thumbnail_url":"https:\/\/www.maapprogram.org\/wp-content\/uploads\/2017\/08\/MAAP_Kernel_2017_O_v1_en.jpg"}