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 and Spatiotemporal Characterization of Degraded Forests in the Brazilian Amazon through Remote Sensing. 2j5e54
Souza Jr., C. 2005.
Large forested areas have recently been impoverished by degradation caused by selective logging, forest fires and fragmentation in the Amazon region, causing partial change of the original forest structure and composition. As opposed to deforestation that has been monitored with Landsat images since the late 70’s, degraded forests have not been monitored in the Amazon region. In this dissertation, remote sensing techniques for identifying and mapping unambiguously degraded forests with Landsat images are proposed. The test area was the region of Sinop, located in the state of Mato Grosso, Brazil. This region was selected because a gradient of degraded forest environments exist and a robust time-series of Landsat images and forest transect data were available. First, statistical analyses were applied to identify the best set of spectral information extracted from Landsat images to detect several types of degraded forest environments. Fraction images derived from Spectral Mixture Analysis (SMA) were the best type of information for that purpose. A new spectral index based on fraction images – Normalized Difference Fraction Index (NDFI) – was proposed to enhance the detection of canopy damaged areas in degraded forests. Second, a contextual classification algorithm was implemented to separate unambiguously forest degradation caused by anthropogenic activities from natural forest disturbances. These techniques were validated using forest transects and high resolution aerial videography images and proved to be highly accurate. Next, these techniques were applied to a time-series data set of Landsat images, encoming 20 years, to evaluate the relationship between forest degradation and deforestation. The most important finding of the forest change detection analysis was that forest degradation and deforestation are independent events in the study area, making worse the current forest impacts in the Amazon region. Finally, the techniques developed and tested in the Sinop region were successfully applied to forty Landsat images covering other regions of the Brazilian Amazon. Standard fractions and NDFI images were computed for these other regions and both physically and spatially consistent results were obtained. An automated decision tree classification using genetic algorithm was implemented successfully to classify land cover types and sub-classes of degraded forests. The remote sensing techniques proposed in this dissertation are fully automated and have the potential to be used in tropical forest monitoring programs.
Souza Jr., C. 2005.