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
Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades From Landsat 2l2h5r
Friedl MA, Woodcock CE, Olofsson P, Zhu Z, Loveland T, Stanimirova R, Arevalo P, Bullock E, Hu K-T, Zhang Y, Turlej K, Tarrio K, McAvoy K, Gorelick N, Wang JA, Barber and Souza C (2022) Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades From Landsat. Front. Remote Sens. 3:894571. doi: 10.3389/frsen.2022.894571
Abstract: Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.