Google Earth Engine——EOSDIS下产生或收集的海洋颜色和卫星海洋生物数据

This level 3 product includes ocean color and satellite ocean biology data produced or collected under EOSDIS.

This dataset may be used for studying the biology and hydrology of coastal zones, changes in the diversity and geographical distribution of coastal marine habitats, biogeochemical fluxes and their influence in Earth's oceans and climate over time, and finally the impact of climate and environmental variability and change on ocean ecosystems and the biodiversity they support.

Scale factor and offset are already applied.

Documentation:

• Ocean Color Forum

• Chlorophyll Forum

• Algorithm Theoretical Basis Document (Chlorophyll)

• Algorithm Theoretical Basis Document (Fluorescence Line Height)

• Algorithm Theoretical Basis Document (Particulate Organic Carbon)

• Algorithm Theoretical Basis Document (Remote-Sensing Reflectance)

• Processing History

这个3级产品包括在EOSDIS下产生或收集的海洋颜色和卫星海洋生物学数据。

这个数据集可用于研究沿海地区的生物学和水文学、沿海海洋生境的多样性和地理分布的变化、生物地球化学通量及其在地球海洋和气候中的影响，以及最后研究气候和环境变异和变化对海洋生态系统及其支持的生物多样性的影响。

已经应用了比例因子和抵消。

文件。

海洋色彩论坛

叶绿素论坛

算法的理论基础文件（叶绿素

算法理论基础文件(荧光线高度)

算法理论基础文件（颗粒有机碳）。

算法理论基础文件(遥感反射率)

Dataset Availability

2002-07-04T00:00:00 - 2021-06-30T00:00:00

Dataset Provider

NASA OB.DAAC at NASA Goddard Space Flight Center

Collection Snippet

ee.ImageCollection("NASA/OCEANDATA/MODIS-Aqua/L3SMI")

Resolution

4616 meters

Bands Table

* = Values are estimated

影像属性：

数据引用：

NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group. Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua Ocean Color Data, NASA OB.DAAC, Greenbelt, MD, USA.

NASA Ocean Color

NASA Ocean Color

NASA Ocean Color

NASA Ocean Color

https://doi.org/10.5067/GHMDA-2PJ19

代码：

  

   

    

     

    
    

     

      var dataset = ee.ImageCollection('NASA/OCEANDATA/MODIS-Aqua/L3SMI')
     
    
   

    

     

    
    

     

                        .filterDate('2016-01-01', '2016-01-31');
     
    
   

    

     

    
    

     

      var remoteSensingReflectance =
     
    
   

    

     

    
    

     

          dataset.select(['Rrs_645', 'Rrs_555', 'Rrs_443']);
     
    
   

    

     

    
    

     

      var remoteSensingReflectanceVis = {
     
    
   

    

     

    
    

     
  min: 0.0,
     
    
   

    

     

    
    

     
  max: 0.011,
     
    
   

    

     

    
    

     

      };
     
    
   

    

     

    
    

     

      Map.setCenter(-52.12, -46.13, 4);
     
    
   

    

     

    
    

     

      Map.addLayer(
     
    
   

    

     

    
    

     

          remoteSensingReflectance, remoteSensingReflectanceVis,
     
    
   

    

     

    
    

     
    'Remote Sensing Reflectance');
     
    
  
 

 terra星：

  

   

    

     

    
    

     

      var dataset = ee.ImageCollection('NASA/OCEANDATA/MODIS-Terra/L3SMI')
     
    
   

    

     

    
    

     

                        .filterDate('2016-01-01', '2016-01-31');
     
    
   

    

     

    
    

     

      var remoteSensingReflectance =
     
    
   

    

     

    
    

     

          dataset.select(['Rrs_645', 'Rrs_555', 'Rrs_443']);
     
    
   

    

     

    
    

     

      var remoteSensingReflectanceVis = {
     
    
   

    

     

    
    

     
  min: 0.0,
     
    
   

    

     

    
    

     
  max: 0.02,
     
    
   

    

     

    
    

     

      };
     
    
   

    

     

    
    

     

      Map.setCenter(-52.12, -46.13, 4);
     
    
   

    

     

    
    

     

      Map.addLayer(
     
    
   

    

     

    
    

     

          remoteSensingReflectance, remoteSensingReflectanceVis,
     
    
   

    

     

    
    

     
    'Remote Sensing Reflectance');
     
    
  
 

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/120576103