Google Earth Engine ——数据全解析专辑(全球人类改变数据集（gHM）以1千米的分辨率数据集)

The global Human Modification dataset (gHM) provides a cumulative measure of human modification of terrestrial lands globally at 1 square-kilometer resolution. The gHM values range from 0.0-1.0 and are calculated by estimating the proportion of a given location (pixel) that is modified, the estimated intensity of modification associated with a given type of human modification or "stressor". 5 major anthropogenic stressors circa 2016 were mapped using 13 individual datasets:

• human settlement (population density, built-up areas)
• agriculture (cropland, livestock)
• transportation (major, minor, and two-track roads; railroads)
• mining and energy production
• electrical infrastructure (power lines, nighttime lights)

Please see the paper for additional methodological details. This asset was re-projected to WGS84 for use in Earth Engine.

代码：

全球人类改变数据集（gHM）以1平方公里的分辨率提供了全球人类改变陆地的累积测量。gHM值的范围是0.0-1.0，通过估计一个给定的位置（像素）被修改的比例，估计与给定类型的人类修改或 "压力源 "有关的修改强度来计算。使用13个单独的数据集绘制了2016年左右的5个主要人类活动压力源。

人类住区（人口密度、建筑区
农业（耕地、牲畜
运输（主要、次要和双轨公路；铁路
采矿和能源生产
电力基础设施（电线、夜间照明）。
更多方法细节请见本文。该资产被重新投影到WGS84，以便在地球引擎中使用。

Dataset Availability

2016-01-01T00:00:00 - 2016-12-31T00:00:00

Dataset Provider

Conservation Science Partners

Collection Snippet

ee.ImageCollection("CSP/HM/GlobalHumanModification")

Resolution

1000 meters

Bands Table

  

   

    

     

    
    

     

      var dataset = ee.ImageCollection('CSP/HM/GlobalHumanModification');
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      var visualization = {
     
    
   

    

     

    
    

     
  bands: ['gHM'],
     
    
   

    

     

    
    

     
  min: 0.0,
     
    
   

    

     

    
    

     
  max: 1.0,
     
    
   

    

     

    
    

     
  palette: ['0c0c0c', '071aff', 'ff0000', 'ffbd03', 'fbff05', 'fffdfd']
     
    
   

    

     

    
    

     

      };
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      Map.centerObject(dataset);
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      Map.addLayer(dataset, visualization, 'Human modification');
     
    
  
 

数据引用：

Kennedy, C.M., J.R. Oakleaf, D.M. Theobald, S. Baurch-Murdo, and J. Kiesecker. 2019. Managing the middle: A shift in conservation priorities based on the global human modification gradient. Global Change Biology 00:1-16. https://doi.org/10.1111/gcb.14549

文章来源: blog.csdn.net，作者：此星光明2021年博客之星云计算Top3，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/qq_31988139/article/details/120188759