GOES satellites are geostationary weather satellites run by NOAA.
The Fire (HSC) product contains four images: one in the form of a fire mask and the other three with pixel values identifying fire temperature, fire area, and fire radiative power.
The ABI L2+ FHS metadata mask assigns a flag to every earth-navigated pixel that indicates its disposition with respect to the FHS algorithm. Operational users who have the lowest tolerance for false alarms should focus on the "processed" and "saturated" categories (mask codes 10, 11, 30, and 31), but within these categories there can still be false alarms.
NOAA provides the following scripts for suggested categories, color maps, and visualizations:
- GOES-16-17_FireDetection.js
- GOES-16-17_FireReclassification.jsGOES卫星是由NOAA运行的地球静止气象卫星。
火灾(HSC)产品包含四张图像:一张是火灾掩码形式,另外三张是确定火灾温度、火灾面积和火灾辐射功率的像素值。
ABI L2+ FHS元数据掩码为每个地球导航的像素分配一个标志,表明其在FHS算法方面的处置。对误报容忍度最低的操作用户应关注 "已处理 "和 "已饱和 "类别(掩码10、11、30和31),但在这些类别中仍可能有误报。
阅读提示
NOAA为建议的类别、彩图和可视化提供了以下脚本。
GOES-16-17_FireDetection.js
GOES-16-17_FireReclassification.js
Dataset Availability
2017-05-24T00:00:00 - 2021-09-30T00:00:00
Dataset Provider
Collection Snippet
ee.ImageCollection("NOAA/GOES/16/FDCC")
Resolution
2000 meters
Bands Table
Name | Description | Min | Max | Units | Scale | Offset |
Area | Fire area | m^2 | 60.98 | 4000 | ||
Temp | Fire temperature | K | 0.05493667 | 400 | ||
Mask | Fire mask categories. Pixel values in the fire mask image identify a fire category and diagnostic information associated with algorithm execution. The six fire categories include: Good quality or temporally filtered good quality fire pixel; Saturated fire pixel or temporally filtered saturated fire pixel; Cloud contaminated or temporally filtered cloud contaminated fire pixel; High probability or temporally filtered high probability fire pixel; Medium probability or temporally filtered high probability fire pixel; Low probability or temporally filtered high probability fire. Temporally filtered fire pixels are those resulting from fire pixels that are in close proximity in both space and time. | 0 | 0 | |||
Power | Fire radiative power | 0 | 200000 | MW | 0 | 0 |
DQF | Data quality flags | 0 | 5 | 0 | 0 |
* = Values are estimated
Class Table: Mask
Value | Color | Color Value | Description |
10 | #red | Processed fire | |
11 | #white | Saturated fire | |
12 | #slategray | Cloud contaminated fire | |
13 | #orange | High probability fire | |
14 | #violet | Medium probability fire | |
15 | #blue | Low probability fire | |
30 | #darkred | Processed fire, filtered | |
31 | #ghostwhite | Saturated fire, filtered | |
32 | #darkslategray | Cloud contaminated fire, filtered | |
33 | #darkorange | High probability fire, filtered | |
34 | #darkviolet | Medium probability fire, filtered | |
35 | #darkblue | Low probability fire, filtered |
Class Table: DQF
Value | Color | Color Value | Description |
0 | #ffffff | Good quality fire | |
1 | #ff00ff | Good quality fire-free land | |
2 | #0000ff | Invalid due to opaque cloud | |
3 | #00ffff | Invalid due to surface type or sunglint or LZA threshold exceeded or off earth or missing input data | |
4 | #ffff00 | Invalid due to bad input data | |
5 | #ff0000 | Invalid due to algorithm failure |
数据使用:
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:
Early characterization of the active fire detection products derived from the next generation NPOESS/VIIRS and GOES-R/ABI instruments. Schroeder, W., Csiszar, I., et al, (2010), Early characterization of the active fire detection products derived from the next generation NPOESS/VIIRS and GOES-R/ABI instruments, paper presented at 2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Honolulu, HI. doi:10.1109/IGARSS.2010.5650863
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:
// NOAA GOES-16同域火灾产品的单一时间片。 var image = ee.Image('NOAA/GOES/16/FDCC/2019297103632900000'); var area = image.select('Area'); var temp = image.select('Temp'); var dqf = image.select('DQF'); var xmin = -145; var ymin = 15; var xmax = -55; var ymax = 54; var geometry = ee.Geometry.Rectangle({ coords: [xmin, ymin, xmax, ymax], geodesic: false}); Map.centerObject(geometry, 3); 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'); // 火灾很小,在整个GOES图像中很难看到它们。 // 整个GOES图像。 根据面积对火灾进行缓冲,使其更加突出。 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(1.4)); }); Map.addLayer(area, {color: 'orange'}, 'area'); // 根据温度进行缓冲发射,以使其脱颖而出。 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(1.27)); }); Map.addLayer(temp, {color: 'red'}, 'temp');
数据集:NOAA/GOES/17/FDCC
代码:
// NOAA GOES-17 conterminous fire product for a single time slice. var image = ee.Image('NOAA/GOES/17/FDCC/2019297090619600000'); var area = image.select('Area'); var temp = image.select('Temp'); var dqf = image.select('DQF'); Map.centerObject(image, 3); var geometry = image.geometry(); 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(1.4)); }); 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');