加拿大陆地卫星得出的1985-2020年森林采伐扰动情况 本产品所包含的年度森林变化数据是全国性的(整个森林生态系统),代表了加拿大在30米空间分辨率下的墙到墙的采伐特征。信息成果代表了加拿大森林36年的采伐变化,来自一个单一的、一致的、空间明确的数据源,以完全自动化的方式得出。这种在捕捉人类影响的分辨率下描述森林特征的能力,对于从管理和科学的角度建立详细监测森林生态系统的基线至关重要。Landsat数据的时间序列被用来描述1985-2020年期间加拿大6.5亿公顷森林生态系统中由野火和采伐造成的林木替代森林干扰的国家趋势。前言 – 床长人工智能教程
Landsat数据的空间分辨率为30米,因此,变化信息非常详细,而且对自然和人为的变化都有参考价值。这些数据代表了每年更换林分的森林变化。替换林分的干扰类型标记为野火和采伐,置信度较低的野火和采伐,也是共享的。区分和共享较低等级的成员可能性是为了向用户表明,一些变化事件更难被分配到一个变化类型中,但通常被发现属于正确的类别。关于数据、图像处理和应用的时间序列变化检测方法的概述,以及关于数据的独立准确性评估的信息,见(Hermosilla等人,2016)。可用的数据是收获事件的变化年,可以在这里下载https://opendata.nfis.org/downloads/forest_change/CA_Forest_Harvest_1985-2020.zip
免责声明:该数据集的全部或部分描述由作者或其作品提供。
数据集引证
Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Campbell, L.B., 2016. Mass data processing of time series Landsat imagery:
pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054.
Code Snippet¶
var ca_forest_harvest = ee.Image("projects/sat-io/open-datasets/CA_FOREST/CA_Forest_Harvest_1985-2020");
var style = require('users/gena/packages:style')
Map.setCenter(-96.038,54.742,4)
var vis = {min:1985,max:2020,palette:["03071e","370617","6a040f","9d0208","d00000","dc2f02","e85d04","f48c06","faa307","ffba08"]}
style.SetMapStyleGrey()
Map.addLayer(ca_forest_harvest,vis,'Canada Forest Harvest 1985-2020')
var nSteps = 15
// Creates a color bar thumbnail image for use in legend from the given color palette
function makeColorBarParams(palette) {
return {
bbox: [0, 0, nSteps, 1],
dimensions: '200x10',
format: 'png',
min: 0,
max: nSteps,
palette: palette,
};
}
// Create the colour bar for the legend
var colorBar = ui.Thumbnail({
image: ee.Image.pixelLonLat().select(0).int(),
params: makeColorBarParams(vis.palette),
style: {stretch: 'horizontal', margin: '0px 8px', maxHeight: '24px',position:'bottom-left'},
});
// Create a panel with three numbers for the legend
var legendLabels = ui.Panel({
widgets: [
ui.Label(vis.min, {margin: '4px 8px'}),
ui.Label(vis.max, {margin: '4px 8px', textAlign:'right',stretch:'horizontal'})
],
layout: ui.Panel.Layout.flow('horizontal')
});
// Legend title
var legendTitle = ui.Label({
value: 'Year',
style: {fontWeight: 'bold',position:'bottom-left'}
});
// Add the legendPanel to the map
var legendPanel = ui.Panel([legendTitle, colorBar, legendLabels]);
legendPanel.style().set({
position: 'bottom-left',
shown: true
});
Map.add(legendPanel);
Sample Code: https://code.earthengine.google.com/?scriptPath=users/sat-io/awesome-gee-catalog-examples:agriculture-vegetation-forestry/CA-FOREST-HARVEST-1985-2020
License¶
This work is licensed under and freely available to the public Open Government Licence - Canada.
Created by: Hermosilla et al. 2016
Curated in GEE by : Samapriya Roy
keywords: Forest Harvest, Forest inventory, Land cover, Landsat, Machine learning
Last updated on GEE: 2023-01-28