Google Earth Engine ——（COPERNICUS/S5P/OFFL/L3系列——CH4/CO/CLOUD/CO/HCHO/NO2/O3/SO2）数据集

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发布于 2024-02-02 09:00:29

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发布于 2024-02-02 09:00:29

数据介绍：

Sentinel-5 Precursor

Sentinel-5 Precursor is a satellite launched on 13 October 2017 by the European Space Agency to monitor air pollution. The onboard sensor is frequently referred to as Tropomi (TROPOspheric Monitoring Instrument).

All of the S5P datasets, except CH4, have two versions: Near Real-Time (NRTI) and Offline (OFFL). CH4 is available as OFFL only. The NRTI assets cover a smaller area than the OFFL assets, but appear more quickly after acquisition. The OFFL assets contain data from a single orbit (which, due to half the earth being dark, contains data only for a single hemisphere).

Because of noise on the data, negative vertical column values are often observed in particular over clean regions or for low SO2 emissions. It is recommended not to filter these values except for outliers, i.e. for vertical columns lower than -0.001 mol/m^2.

The original Sentinel 5P Level 2 (L2) data is binned by time, not by latitude/longitude. To make it possible to ingest the data into Earth Engine, each Sentinel 5P L2 product is converted to L3, keeping a single grid per orbit (that is, no aggregation across products is performed).

Source products spanning the antimeridian are ingested as two Earth Engine assets, with suffixes _1 and _2.

The conversion to L3 is done by the harpconvert tool using the bin_spatial operation. The source data is filtered to remove pixels with QA values less than:

80% for AER_AI
75% for the tropospheric_NO2_column_number_density band of NO2
50% for all other datasets except for O3 and SO2

The O3_TCL product is ingested directly (without running harpconvert).

Sentinel-5 Precursor Sentinel-5 Precursor 是欧洲航天局于 2017 年 10 月 13 日发射的一颗卫星，用于监测空气污染。机载传感器通常被称为 Tropomi（对流层监测仪器）。

除 CH4 外，所有 S5P 数据集都有两个版本：近实时 (NRTI) 和离线 (OFFL)。 CH4 仅作为 OFFL 提供。 NRTI 资产覆盖的区域比 OFFL 资产小，但在收购后出现得更快。 OFFL 资产包含来自单个轨道的数据（由于地球有一半是黑暗的，因此仅包含单个半球的数据）。

由于数据上的噪声，通常会观察到负的垂直列值，尤其是在清洁区域或 SO2 排放量较低的情况下。除了离群值外，建议不要过滤这些值，即对于低于 -0.001 mol/m^2 的垂直列。

原始 Sentinel 5P Level 2 (L2) 数据按时间分档，而不是按纬度/经度分档。为了能够将数据摄取到 Earth Engine，每个 Sentinel 5P L2 产品都转换为 L3，每个轨道保持一个网格（即，不执行跨产品的聚合）。

跨越反子午线的源产品作为两个地球引擎资产被摄取，后缀为 _1 和 _2。

到 L3 的转换由 harpconvert 工具使用 bin_spatial 操作完成。过滤源数据以移除 QA 值小于以下值的像素：

AER_AI 80% NO2 的对流层_NO2_column_number_密度带为 75% 除 O3 和 SO2 外，所有其他数据集为 50% 直接摄取 O3_TCL 产品（不运行 harpconvert）。

数据基本信息：

Dataset Availability

2018-04-30T10:50:26 - 2021-08-22T00:00:00

Dataset Provider

European Union/ESA/Copernicus

Collection Snippet

ee.ImageCollection("COPERNICUS/S5P/OFFL/L3_O3_TCL")

数据属性：

Name	Type	Description
ALGORITHM_VERSION	String	The algorithm version used in L2 processing. It's separate from the processor (framework) version, to accommodate different release schedules for different products.
BUILD_DATE	String	The date, expressed as milliseconds since 1 Jan 1970, when the software used to perform L2 processing was built.
HARP_VERSION	Int	The version of the HARP tool used to grid the L2 data into an L3 product.
INSTITUTION	String	The institution where data processing from L1 to L2 was performed.
L3_PROCESSING_TIME	Int	The date, expressed as milliseconds since 1 Jan 1970, when Google processed the L2 data into L3 using harpconvert.
LAT_MAX	Double	The maximum latitude of the asset (degrees).
LAT_MIN	Double	The minimum latitude of the asset (degrees).
LON_MAX	Double	The maximum longitude of the asset (degrees).
LON_MIN	Double	The minimum longitude of the asset (degrees).
ORBIT	Int	The orbit number of the satellite when the data was acquired.
PLATFORM	String	Name of the platform which acquired the data.
PROCESSING_STATUS	String	The processing status of the product on a global level, mainly based on the availability of auxiliary input data. Possible values are "Nominal" and "Degraded".
PROCESSOR_VERSION	String	The version of the software used for L2 processing, as a string of the form "major.minor.patch".
PRODUCT_ID	String	Id of the L2 product used to generate this asset.
PRODUCT_QUALITY	String	Indicator that specifies whether the product quality is degraded or not. Allowed values are "Degraded" and "Nominal".
SENSOR	String	Name of the sensor which acquired the data.
SPATIAL_RESOLUTION	String	Spatial resolution at nadir. For most products this is `3.5x7km2`, except for `L2__O3__PR`, which uses `28x21km2`, and `L2__CO____` and `L2__CH4___`, which both use `7x7km2`. This attribute originates from the CCI standard.
TIME_REFERENCE_DAYS_SINCE_1950	Int	Days from 1 Jan 1950 to when the data was acquired.
TIME_REFERENCE_JULIAN_DAY	Double	The Julian day number when the data was acquired.
TRACKING_ID	String	UUID for the L2 product file.

数据集代码：

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CH4')
  .select('CH4_column_volume_mixing_ratio_dry_air')
  .filterDate('2019-06-01', '2019-07-16');

var band_viz = {
  min: 1750,
  max: 1900,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P CH4');
Map.setCenter(0.0, 0.0, 2);

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CLOUD')
  .select('cloud_fraction')
  .filterDate('2019-06-01', '2019-06-02');

var band_viz = {
  min: 0,
  max: 0.95,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P Cloud');
Map.setCenter(-58.14, -10.47, 2);

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_CO')
  .select('CO_column_number_density')
  .filterDate('2019-06-01', '2019-06-11');

var band_viz = {
  min: 0,
  max: 0.05,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P CO');
Map.setCenter(-25.01, -4.28, 4);

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_HCHO')
  .select('tropospheric_HCHO_column_number_density')
  .filterDate('2019-06-01', '2019-06-06');

var band_viz = {
  min: 0.0,
  max: 0.0003,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P HCHO');
Map.setCenter(0.0, 0.0, 2);

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_NO2')
  .select('tropospheric_NO2_column_number_density')
  .filterDate('2019-06-01', '2019-06-06');

var band_viz = {
  min: 0,
  max: 0.0002,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P N02');
Map.setCenter(65.27, 24.11, 4);

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3')
  .select('O3_column_number_density')
  .filterDate('2019-06-01', '2019-06-05');

var band_viz = {
  min: 0.12,
  max: 0.15,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P O3');
Map.setCenter(0.0, 0.0, 2);

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_O3_TCL')
  .select('ozone_tropospheric_vertical_column')
  .filterDate('2019-06-01', '2019-07-01');

var band_viz = {
  min: 0,
  max: 0.02,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P O3');
Map.setCenter(0.0, 0.0, 2);

var collection = ee.ImageCollection('COPERNICUS/S5P/OFFL/L3_SO2')
  .select('SO2_column_number_density')
  .filterDate('2019-06-01', '2019-06-11');

var band_viz = {
  min: 0.0,
  max: 0.0005,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};

Map.addLayer(collection.mean(), band_viz, 'S5P SO2');
Map.setCenter(0.0, 0.0, 2);