tag on yout theme's header.php
Read the detailed step-by-step at https://humbertosilva.com/visual-composer-infinite-image-carousel/
*/
// auxiliary code to create triggers for the add and remove class for later use
(function($){
$.each(["addClass","removeClass"],function(i,methodname){
var oldmethod = $.fn[methodname];
$.fn[methodname] = function(){
oldmethod.apply( this, arguments );
this.trigger(methodname+"change");
return this;
}
});
})(jQuery);
// main function for the infinite loop
function vc_custominfiniteloop_init(vc_cil_element_id){
var vc_element = '#' + vc_cil_element_id; // because we're using this more than once let's create a variable for it
window.maxItens = jQuery(vc_element).data('per-view'); // max visible items defined
window.addedItens = 0; // auxiliary counter for added itens to the end
// go to slides and duplicate them to the end to fill space
jQuery(vc_element).find('.vc_carousel-slideline-inner').find('.vc_item').each(function(){
// we only need to duplicate the first visible images
if (window.addedItens < window.maxItens) {
if (window.addedItens == 0 ) {
// the fisrt added slide will need a trigger so we know it ended and make it "restart" without animation
jQuery(this).clone().addClass('vc_custominfiniteloop_restart').removeClass('vc_active').appendTo(jQuery(this).parent());
} else {
jQuery(this).clone().removeClass('vc_active').appendTo(jQuery(this).parent());
}
window.addedItens++;
}
});
// add the trigger so we know when to "restart" the animation without the knowing about it
jQuery('.vc_custominfiniteloop_restart').bind('addClasschange', null, function(){
// navigate to the carousel element , I know, its ugly ...
var vc_carousel = jQuery(this).parent().parent().parent().parent();
// first we temporarily change the animation speed to zero
jQuery(vc_carousel).data('vc.carousel').transition_speed = 0;
// make the slider go to the first slide without animation and because the fist set of images shown
// are the same that are being shown now the slider is now "restarted" without that being visible
jQuery(vc_carousel).data('vc.carousel').to(0);
// allow the carousel to go to the first image and restore the original speed
setTimeout("vc_cil_restore_transition_speed('"+jQuery(vc_carousel).prop('id')+"')",100);
});
}
// restore original speed setting of vc_carousel
function vc_cil_restore_transition_speed(element_id){
// after inspecting the original source code the value of 600 is defined there so we put back the original here
jQuery('#' + element_id).data('vc.carousel').transition_speed = 600;
}
// init
jQuery(document).ready(function(){
// find all vc_carousel with the defined class and turn them into infine loop
jQuery('.vc_custominfiniteloop').find('div[data-ride="vc_carousel"]').each(function(){
// allow time for the slider to be built on the page
// because the slider is "long" we can wait a bit before adding images and events needed
var vc_cil_element = jQuery(this).prop("id");
if (window.innerWidth <= 480) {
// jQuery(vc_element).attr('data-per-view',1);
jQuery('.vc_item').each(function(){
this.style.width = '25%'
this.style.height = 'auto'
})
} else {
setTimeout("vc_custominfiniteloop_init('"+vc_cil_element+"')",2000);
}
});
});
(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);
})(window,document,'script','dataLayer','GTM-TZHJ474');
var interval1 = setInterval(function(){
//console.log('ou no interval');
jQuery('.box-news .vc_gitem-zone-a').each(function() {
if((!jQuery(this).css('background-image').includes('vc_gitem_image'))) {
jQuery(this).css('background-image','none')
}
})
jQuery('.box-news .vc_gitem-zone-a a').each(function() {
jQuery(this).attr('data-hover','Leia mais')
})
}, 1000);
setTimeout(function() {
clearInterval(interval1);
},5000);
@font-face {
font-family: "FontAwesome";
src: url("/local/fonts/fa-brands-400.eot"),
url("/local/fonts/fa-brands-400.eot?#iefix") format("embedded-opentype"),
url("/local/fonts/fa-brands-400.woff2") format("woff2"),
url("/local/fonts/fa-brands-400.woff") format("woff"),
url("/local/fonts/fa-brands-400.ttf") format("truetype"),
url("/local/fonts/fa-brands-400.svg#fontawesome") format("svg");
}
@font-face {
font-family: "FontAwesome";
src: url("/local/fonts/fa-solid-900.eot"),
url("/local/fonts/fa-solid-900.eot?#iefix") format("embedded-opentype"),
url("/local/fonts/fa-solid-900.woff2") format("woff2"),
url("/local/fonts/fa-solid-900.woff") format("woff"),
url("/local/fonts/fa-solid-900.ttf") format("truetype"),
url("/local/fonts/fa-solid-900.svg#fontawesome") format("svg");
}
@font-face {
font-family: "FontAwesome";
src: url("/local/fonts/fa-regular-400.eot"),
url("/local/fonts/fa-regular-400.eot?#iefix") format("embedded-opentype"),
url("/local/fonts/fa-regular-400.woff2") format("woff2"),
url("/local/fonts/fa-regular-400.woff") format("woff"),
url("/local/fonts/fa-regular-400.ttf") format("truetype"),
url("/local/fonts/fa-regular-400.svg#fontawesome") format("svg");
unicode-range: U+F004-F005,U+F007,U+F017,U+F022,U+F024,U+F02E,U+F03E,U+F044,U+F057-F059,U+F06E,U+F070,U+F075,U+F07B-F07C,U+F080,U+F086,U+F089,U+F094,U+F09D,U+F0A0,U+F0A4-F0A7,U+F0C5,U+F0C7-F0C8,U+F0E0,U+F0EB,U+F0F3,U+F0F8,U+F0FE,U+F111,U+F118-F11A,U+F11C,U+F133,U+F144,U+F146,U+F14A,U+F14D-F14E,U+F150-F152,U+F15B-F15C,U+F164-F165,U+F185-F186,U+F191-F192,U+F1AD,U+F1C1-F1C9,U+F1CD,U+F1D8,U+F1E3,U+F1EA,U+F1F6,U+F1F9,U+F20A,U+F247-F249,U+F24D,U+F254-F25B,U+F25D,U+F267,U+F271-F274,U+F279,U+F28B,U+F28D,U+F2B5-F2B6,U+F2B9,U+F2BB,U+F2BD,U+F2C1-F2C2,U+F2D0,U+F2D2,U+F2DC,U+F2ED,U+F328,U+F358-F35B,U+F3A5,U+F3D1,U+F410,U+F4AD;
}
jQuery(document).ready(function(){
jQuery('.single-item').slick({
centerMode: true,
centerPadding: '60px',
slidesToShow: 5,
variableWidth: true,
autoplay: true,
autoplaySpeed: 2000,
responsive: [
{
breakpoint: 768,
settings: {
arrows: false,
centerMode: true,
centerPadding: '40px',
slidesToShow: 3
}
},
{
breakpoint: 520,
settings: {
arrows: false,
centerMode: true,
centerPadding: '40px',
slidesToShow: 1
}
}
]
});
});
.single-item img {
-webkit-filter: grayscale(100%);
filter: grayscale(100%);
}
.single-item img:hover {
-webkit-filter: grayscale(0);
filter: grayscale(0);
}
422n14
Mapping Roads in the Brazilian Amazon with Artificial Intelligence and Sentinel-2 6j3z10
Botelho, J., Jr.; Costa, S.C.P.; Ribeiro, J.G.; Souza, C.M., Jr. Mapping Roads in the Brazilian Amazon with Artificial Intelligence and Sentinel-2. Remote Sens. 2022, 14, 3625. https://doi.org/10.3390/
rs14153625
Abstract: This study presents our efforts to automate the detection of unofficial roads (herein, roads) in the Brazilian Amazon using artificial intelligence (AI). In this region, roads are built by loggers, goldminers, and unauthorized land settlements from existing official roads, expanding over pristine forests and leading to new deforestation and fire hotspots. Previous research used visual interpretation, hand digitization, and vector editing techniques to create a thorough Amazon Road Dataset (ARD) from Landsat imagery. The ARD allowed assessment of the road dynamics and impacts on deforestation, landscape fragmentation, and fires and ed several scientific and societal applications. This research used the existing ARD to train and model a modified U-Net algorithm to detect rural roads in the Brazilian Amazon using Sentinel-2 imagery from 2020 in the Azure Planetary Computer platform. Moreover, we implemented a post-AI detection protocol to connect and vectorize the U-Net road detected to create a new ARD.We estimated the recall and precision accuracy using an independent ARD dataset, obtaining 65% and 71%, respectively. Visual interpretation of the road detected with the AI algorithm suggests that the accuracy is underestimated. The reference dataset does not include all roads that the AI algorithm can detect in the Sentinel-2 imagery. We found an astonishing footprint of roads in the Brazilian Legal Amazon, with 3.46 million km of roads mapped in 2020. Most roads are in private lands (~55%) and 25% are in open public lands under land grabbing pressure. The roads are also expanding over forested areas with 41% cut or within 10 km from the roads, leaving 59% of the 3.1 million km2 of the remaining original forest roadless. Our AI and post-AI models fully automated road detection in rural areas of the Brazilian Amazon, making it possible to operationalize road monitoring. We are using the AI road map to understand better rural roads’ impact on new deforestation, fires, and landscape fragmentation and to societal and policy applications for forest conservation and regional planning.
