# DS4G - Environmental Insights Explorer — Data

来源：https://www.kaggle.com/competitions/ds4g-environmental-insights-explorer/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

### Context: 

Current [emissions factors methodologies](https://www.epa.gov/air-emissions-factors-and-quantification/basic-information-air-emissions-factors-and-quantification#About%20Emissions%20Factors) are based on time-consuming data collection and may include errors derived from a lack of access to granular datasets, inability to refresh data on a frequent basis, overly general modeling assumptions, and inaccurate reporting of emissions sources like fuel consumption. We’re challenging the Kaggle community to see if it’s possible to use remote sensing techniques to develop a methodology to calculate an average historical emissions factor of electricity generated for a sub-national region.

### Content:

DATASET SELECTION STARTER PACK 

 - [Global Power Plant database](https://developers.google.com/earth-engine/datasets/catalog/WRI_GPPD_power_plants) by WRI
 - [Sentinel 5P OFFL NO2](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2) by [EU/ESA/Copernicus](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-5p-tropomi/document-library)
 - [Global Forecast System 384-Hour Predicted Atmosphere Data ](https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25) by NOAA/NCEP/EMC
 - [Global Land Data Assimilation System](https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V021_NOAH_G025_T3H) by NASA

Participants may also consider using other public datasets related to trade commodities for fuel types, total fuel consumed, and/or data from the [US Energy Information Agency (EIA)](https://www.eia.gov/state/data.php?sid=RQ#CarbonDioxideEmissions). 

### Dataset Licenses:
 - [Global Power Plant database: ](https://developers.google.com/earth-engine/datasets/catalog/WRI_GPPD_power_plants) [CC 4.0](https://creativecommons.org/licenses/by/4.0/)
 - [Copernicus Sentinel data 2018-2019: ](https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_NO2) 
 [Terms and Conditions](https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice)
 - [Global Forecast System 384-Hour Predicted Atmosphere Data: ](https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25) no restrictions on use and distribution
 - [Global Land Data Assimilation System: ](https://developers.google.com/earth-engine/datasets/catalog/NASA_GLDAS_V021_NOAH_G025_T3H) data from the [GES DISC archive ](https://disc.gsfc.nasa.gov/information/documents?title=data-policy)are available free to the user community
  - Beaudoing, Hiroko and M. Rodell, NASA/GSFC/HSL (2016), GLDAS Noah Land Surface Model L4 monthly 0.25 x 0.25 degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [2/10/2019], 10.5067/SXAVCZFAQLNO