Google Earth Engine——GOES-16/17 MCMIPC Series ABI Level 2 云层和水分图像产品的分辨率都是2公里数据集

简介: Google Earth Engine——GOES-16/17 MCMIPC Series ABI Level 2 云层和水分图像产品的分辨率都是2公里数据集

GOES satellites are geostationary weather satellites run by NOAA.

The Cloud and Moisture Imagery products are all at 2km resolution. Bands 1-6 are reflective. The dimensionless "reflectance factor" quantity is normalized by the solar zenith angle. These bands support the characterization of clouds, vegetation, snow/ice, and aerosols. Bands 7-16 are emissive. The brightness temperature at the Top-Of-Atmosphere (TOA) is measured in Kelvin. These bands support the characterization of the surface, clouds, water vapor, ozone, volcanic ash, and dust based on emissive properties.

README


GOES卫星是由NOAA管理的地球静止气象卫星。

云层和水分图像产品的分辨率都是2公里。1-6波段是反射的。无尺寸的 "反射系数 "数量是以太阳天顶角为标准的。这些波段支持云、植被、雪/冰和气溶胶的特征。频段7-16是发射型的。大气层顶部(TOA)的亮度温度以开尔文测量。这些波段支持根据发射特性对地表、云层、水汽、臭氧、火山灰和灰尘进行定性。

Dataset Availability

2017-07-10T00:00:00 - 2021-09-30T00:00:00

Dataset Provider

NOAA

Collection Snippet

ee.ImageCollection("NOAA/GOES/16/MCMIPC")

Resolution

2000 meters

Bands Table

Name Description Min Max Units Wavelength
CMI_C01 Visible - Blue Daytime aerosol over land, coastal water mapping. 0 1.3 Reflectance factor 0.45-0.49µm
DQF_C01 Data quality flags 0 4
CMI_C02 Visible - Red Daytime clouds, fog, insolation, winds 0 1.3 Reflectance factor 0.59-0.69µm
DQF_C02 Data quality flags 0 4
CMI_C03 Near-IR - Veggie Daytime vegetation, burn scar, aerosol over water, winds 0 1.3 Reflectance factor 0.846-0.885µm
DQF_C03 Data quality flags 0 4
CMI_C04 Near-IR - Cirrus Daytime cirrus cloud 0 1.3 Reflectance factor 1.371-1.386µm
DQF_C04 Data quality flags 0 4
CMI_C05 Near-IR - Snow/Ice Daytime cloud-top phase and particle size, snow 0 1.3 Reflectance factor 1.58-1.64µm
DQF_C05 Data quality flags 0 4
CMI_C06 Near IR - Cloud Particle Size Daytime land, cloud properties, particle size, vegetation, snow 0 1.3 Reflectance factor 2.225-2.275µm
DQF_C06 Data quality flags 0 4
CMI_C07 Infrared - Shortwave Window Brightness 197.31 411.86 K 3.80-4.00µm
DQF_C07 Data quality flags 0 4
CMI_C08 Infrared - Upper-level water vapor High-level atmospheric water vapor, winds, rainfall Brightness 138.05 311.06 K 5.77-6.6µm
DQF_C08 Data quality flags 0 4
CMI_C09 Infrared - Mid-level water vapor Mid-level atmospheric water vapor, winds, rainfall Brightness 137.7 311.08 K 6.75-7.15µm
DQF_C09 Data quality flags 0 4
CMI_C10 Infrared - Lower-level water vapor Lower-level water vapor, winds, and sulfur dioxide Brightness 126.91 331.2 K 7.24-7.44µm
DQF_C10 Data quality flags 0 4
CMI_C11 Infrared - Cloud-top phase Total water for stability, cloud phase, dust, sulfur dioxide, rainfall Brightness 127.69 341.3 K 8.3-8.7µm
DQF_C11 Data quality flags 0 4
CMI_C12 Infrared - Ozone Total ozone, turbulence, winds 117.49 311.06 K 9.42-9.8µm
DQF_C12 Data quality flags 0 4
CMI_C13 Infrared - \"Clean\" longwave window Surface and clouds Brightness 89.62 341.27 K 10.1-10.6µm
DQF_C13 Data quality flags 0 4
CMI_C14 Infrared - Longwave window Imagery, sea surface temperature, clouds, rainfall Brightness 96.19 341.28 K 10.8-11.6µm
DQF_C14 Data quality flags 0 4
CMI_C15 Infrared \"Dirty\" longwave Total water, volcanic ash, sea surface temperature Brightness 97.38 341.28 K 11.8-12.8µm
DQF_C15 Data quality flags 0 4
CMI_C16 Infrared - CO_2 longwave Air temperature, cloud heights Brightness 92.7 318.26 K 13.0-13.6µm
DQF_C16 Data quality flags 0 4

Class Table: DQF_C01

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C02

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C03

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C04

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C05

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C06

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C07

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C08

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C09

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C10

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C11

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C12

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C13

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C14

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C15

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

Class Table: DQF_C16

Value Color Color Value Description
0 #ffffff Good pixels
1 #ff00ff Conditionally usable pixels
2 #0000ff Out of range pixels
3 #00ffff No value pixels
4 #ffff00 Focal plane temperature threshold exceeded

影像属性:

Name Type Description
CMI_C01_offset Double Offset to add to scaled CMI_C01 values
CMI_C01_scale Double Scale to multiply with raw CMI_C01 values
CMI_C02_offset Double Offset to add to scaled CMI_C02 values
CMI_C02_scale Double Scale to multiply with raw CMI_C02 values
CMI_C03_offset Double Offset to add to scaled CMI_C03 values
CMI_C03_scale Double Scale to multiply with raw CMI_C03 values
CMI_C04_offset Double Offset to add to scaled CMI_C04 values
CMI_C04_scale Double Scale to multiply with raw CMI_C04 values
CMI_C05_offset Double Offset to add to scaled CMI_C05 values
CMI_C05_scale Double Scale to multiply with raw CMI_C05 values
CMI_C06_offset Double Offset to add to scaled CMI_C06 values
CMI_C06_scale Double Scale to multiply with raw CMI_C06 values
CMI_C07_offset Double Offset to add to scaled CMI_C07 values
CMI_C07_scale Double Scale to multiply with raw CMI_C07 values
CMI_C08_offset Double Offset to add to scaled CMI_C08 values
CMI_C08_scale Double Scale to multiply with raw CMI_C08 values
CMI_C09_offset Double Offset to add to scaled CMI_C09 values
CMI_C09_scale Double Scale to multiply with raw CMI_C09 values
CMI_C10_offset Double Offset to add to scaled CMI_C10 values
CMI_C10_scale Double Scale to multiply with raw CMI_C10 values
CMI_C11_offset Double Offset to add to scaled CMI_C11 values
CMI_C11_scale Double Scale to multiply with raw CMI_C11 values
CMI_C12_offset Double Offset to add to scaled CMI_C12 values
CMI_C12_scale Double Scale to multiply with raw CMI_C12 values
CMI_C13_offset Double Offset to add to scaled CMI_C13 values
CMI_C13_scale Double Scale to multiply with raw CMI_C13 values
CMI_C14_offset Double Offset to add to scaled CMI_C14 values
CMI_C14_scale Double Scale to multiply with raw CMI_C14 values
CMI_C15_offset Double Offset to add to scaled CMI_C15 values
CMI_C15_scale Double Scale to multiply with raw CMI_C15 values
CMI_C16_offset Double Offset to add to scaled CMI_C16 values
CMI_C16_scale Double Scale to multiply with raw CMI_C16 values


使用说明:

NOAA data, information, and products, regardless of the method of delivery, are not subject to copyright and carry no restrictions on their subsequent use by the public. Once obtained, they may be put to any lawful use.

数据引用:

Bah, Gunshor, Schmit, Generation of GOES-16 True Color Imagery without a Green Band, 2018. doi:10.1029/2018EA000379

Product User Guide (PUG) Volume 5, L2+ Products.

Schmit, T., Griffith, P., et al, (2016), A closer look at the ABI on the GOES-R series, Bull. Amer. Meteor. Soc., 98(4), 681-698.




doi:10.1175/BAMS-D-15-00230.1

代码:

// Band aliases.
var BLUE = 'CMI_C01';
var RED = 'CMI_C02';
var VEGGIE = 'CMI_C03';
var GREEN = 'GREEN';
// 16 pairs of CMI and DQF followed by Bah 2018 synthetic green.
// Band numbers in the EE asset, 0-based.
var NUM_BANDS = 33;
// Skipping the interleaved DQF bands.
var BLUE_BAND_INDEX = (1 - 1) * 2;
var RED_BAND_INDEX = (2 - 1) * 2;
var VEGGIE_BAND_INDEX = (3 - 1) * 2;
var GREEN_BAND_INDEX = NUM_BANDS - 1;
// Visualization range for GOES RGB.
var GOES_MIN = 0.0;
var GOES_MAX = 0.7;  // Alternatively 1.0 or 1.3.
var GAMMA = 1.3;
var goesRgbViz = {
  bands: [RED, GREEN, BLUE],
  min: GOES_MIN,
  max: GOES_MAX,
  gamma: GAMMA
};
var applyScaleAndOffset = function(image) {
  image = ee.Image(image);
  var bands = new Array(NUM_BANDS);
  for (var i = 1; i < 17; i++) {
    var bandName = 'CMI_C' + (100 + i + '').slice(-2);
    var offset = ee.Number(image.get(bandName + '_offset'));
    var scale =  ee.Number(image.get(bandName + '_scale'));
    bands[(i-1) * 2] = image.select(bandName).multiply(scale).add(offset);
    var dqfName = 'DQF_C' + (100 + i + '').slice(-2);
    bands[(i-1) * 2 + 1] = image.select(dqfName);
  }
  // Bah, Gunshor, Schmit, Generation of GOES-16 True Color Imagery without a
  // Green Band, 2018. https://doi.org/10.1029/2018EA000379
  // Green = 0.45 * Red + 0.10 * NIR + 0.45 * Blue
  var green1 = bands[RED_BAND_INDEX].multiply(0.45);
  var green2 = bands[VEGGIE_BAND_INDEX].multiply(0.10);
  var green3 = bands[BLUE_BAND_INDEX].multiply(0.45);
  var green = green1.add(green2).add(green3);
  bands[GREEN_BAND_INDEX] = green.rename(GREEN);
  return ee.Image(ee.Image(bands).copyProperties(image, image.propertyNames()));
};
var collection = 'NOAA/GOES/16/MCMIPC/';
var imageName = '2020211203115800000';
var assetId = collection + imageName;
var image = applyScaleAndOffset(assetId);
Map.addLayer(image, goesRgbViz);

代码:

// NOAA GOES-17 full disk fire product for a single time slice.
var image = ee.Image('NOAA/GOES/17/FDCF/2019275191034100000');
var area = image.select('Area');
var temp = image.select('Temp');
var dqf = image.select('DQF');
var xmin = -205;  // On station as GOES-W
var xmax = xmin + 135;
Map.setCenter((xmin+xmax)/2, 15, 3);
var geometry = ee.Geometry.Rectangle([xmin, -65, xmax, 65], null, true);
var DQFVis = {
  min: 0,
  max: 5,
  palette: [
    'blanchedalmond',  // Good quality fire pixel
    'olive',           // Good quality fire free land
    'teal',            // Opaque cloud
                       // Bad surface type, sunglint, LZA threshold exceeded,
    'darkslateblue',   // off earth, or missing input data
    'lemonchiffon',    // Bad input data
    'burlywood'        // Algorithm failure
  ]};
Map.addLayer(dqf, DQFVis, 'DQF');
// Fires are small enough that they are difficult to see at the scale of
// an entire GOES image.  Buffer fires based on area to make them stand out.
var area = area.reduceToVectors({
  geometry: geometry,
  scale: 2000,
  geometryType: 'centroid',
  labelProperty: 'area',
  maxPixels: 1e10,
}).map(function(feature){
  return feature.buffer(ee.Number(feature.get('area')).add(1).pow(1.5));
});
Map.addLayer(area, {color: 'orange'}, 'area');
// Buffer fires based on temperature to make them stand out.
var temp = temp.reduceToVectors({
  geometry: geometry,
  scale: 2000,
  geometryType: 'centroid',
  labelProperty: 'temp',
  maxPixels: 1e10,
}).map(function(feature){
  return feature.buffer(ee.Number(feature.get('temp')).add(2).pow(1.2));
});
Map.addLayer(temp, {color: 'red'}, 'temp');


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