This dataset contains atmospherically corrected surface reflectance and land surface temperature derived from the data produced by the Landsat TM sensor. These images contain 4 visible and near-infrared (VNIR) bands and 2 short-wave infrared (SWIR) bands processed to orthorectified surface reflectance, and one thermal infrared (TIR) band processed to orthorectified surface temperature. They also contain intermediate bands used in calculation of the ST products, as well as QA bands.
Landsat 4 and 5 SR products are created with the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) algorithm (version 3.4.0). All Collection 2 ST products are created with a single-channel algorithm jointly created by the Rochester Institute of Technology (RIT) and National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL).
Strips of collected data are packaged into overlapping "scenes" covering approximately 170km x 183km using a standardized reference grid.
Some assets have only SR data, in which case ST bands are present but empty. For assets with both ST and SR bands, 'L1_PROCESSING_LEVEL' is set to 'L2SP'. For assets with only SR bands, 'L1_PROCESSING_LEVEL' is set to 'L2SR'.
Additional documentation and usage examples.
Data provider notes:
- Data products must contain both optical and thermal data to be successfully processed to surface temperature, as ASTER NDVI is required to temporally adjust the ASTER GED product to the target Landsat scene. Therefore, night time acquisitions cannot be processed to surface temperature.
- A known error exists in the surface temperature retrievals relative to clouds and possibly cloud shadows. The characterization of these issues has been documented by Cook et al., (2014).
该数据集包含从Landsat TM传感器产生的数据中提取的大气校正表面反射率和地表温度。这些图像包含4个可见光和近红外（VNIR）波段和2个短波红外（SWIR）波段，被处理成正射的表面反射率，以及一个热红外（TIR）波段，被处理成正射的表面温度。它们还包含用于计算ST产品的中间波段，以及QA波段。
Landsat 4和5的SR产品是用Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)算法（3.4.0版）制作的。所有的2号卫星产品都是用罗切斯特理工学院（RIT）和美国国家航空航天局（NASA）喷气推进实验室（JPL）联合创建的单通道算法创建的。
收集的数据条被打包成重叠的 "场景"，使用标准化的参考网格，覆盖大约170公里x183公里。
一些资产只有SR数据，在这种情况下，ST波段是存在的，但却是空的。对于既有ST波段又有SR波段的资产，"L1_PROCESSING_LEVEL "被设置为 "L2SP"。对于只有SR带的资产，'L1_PROCESSING_LEVEL'被设置为'L2SR'。
其他文件和使用例子。
数据提供者说明。
数据产品必须包含光学和热数据，才能成功处理成表面温度，因为ASTER NDVI需要在时间上调整ASTER GED产品与目标Landsat场景。因此，夜间采集的数据不能被处理成地表温度。
在相对于云和可能的云影的表面温度检索中存在一个已知的错误。库克等人（2014）已经记录了这些问题的特征。
Dataset Availability
1982-08-22T00:00:00 - 1993-12-14T00:00:00
Dataset Provider
USGS
Collection Snippet
Copied
ee.ImageCollection("LANDSAT/LT04/C02/T1_L2")
Resolution
30 meters
Bands Table
Name | Description | Min | Max | Units | Wavelength | Scale | Offset |
|---|---|---|---|---|---|---|---|
SR_B1 | Band 1 (blue) surface reflectance | 1 | 65455 | 0.45-0.52 μm | 0.0000275 | -0.2 | |
SR_B2 | Band 2 (green) surface reflectance | 1 | 65455 | 0.52-0.60 μm | 0.0000275 | -0.2 | |
SR_B3 | Band 3 (red) surface reflectance | 1 | 65455 | 0.63-0.69 μm | 0.0000275 | -0.2 | |
SR_B4 | Band 4 (near infrared) surface reflectance | 1 | 65455 | 0.77-0.90 μm | 0.0000275 | -0.2 | |
SR_B5 | Band 5 (shortwave infrared 1) surface reflectance | 1 | 65455 | 1.55-1.75 μm | 0.0000275 | -0.2 | |
SR_B7 | Band 7 (shortwave infrared 2) surface reflectance | 1 | 65455 | 2.08-2.35 μm | 0.0000275 | -0.2 | |
ST_B6 | Band 6 surface temperature. | 0 | 65535 | Kelvin | 10.40-12.50 μm | 0.00341802 | 149 |
SR_ATMOS_OPACITY | A general interpretation of atmospheric opacity generated by LEDAPS and based on the radiance viewed over Dark Dense Vegetation (DDV) within the scene. A general interpretation of atmospheric opacity is that values (after scaling by 0.001 is applied) less than 0.1 are clear, 0.1-0.3 are average, and values greater than 0.3 indicate haze or other cloud situations. SR values from pixels with high atmospheric opacity will be less reliable, especially under high solar zenith angle conditions. The SR_ATMOS_OPACITY band is provided for advanced users and for product quality assessment and has not been validated. Most users are advised to instead use the QA_PIXEL band information for cloud discrimination. | 0 | 10000 | 0.001 | 0 | ||
SR_CLOUD_QA | Cloud Quality Assessment | 0 | 0 | ||||
SR_CLOUD_QA Bitmask | Bit 0: Dark Dense Vegetation (DDV)Bit 1: CloudBit 2: Cloud ShadowBit 3: Adjacent to CloudBit 4: SnowBit 5: Water | ||||||
ST_ATRAN | Atmospheric Transmittance. | 0 | 10000 | 0.0001 | 0 | ||
ST_CDIST | Pixel distance to cloud. | 0 | 24000 | km | 0.01 | 0 | |
ST_DRAD | Downwelled Radiance. | 0 | 28000 | W/(m^2*sr*um)/ DN | 0.001 | 0 | |
ST_EMIS | Emissivity estimated from ASTER GED. | 0 | 10000 | 0.0001 | 0 | ||
ST_EMSD | Emissivity standard deviation. | 0 | 10000 | 0.0001 | 0 | ||
ST_QA | Uncertainty of the Surface Temperature band. | 0 | 32767 | K | 0.01 | 0 | |
ST_TRAD | Thermal band converted to radiance. | 0 | 22000 | W/(m^2*sr*um)/ DN | 0.001 | 0 | |
ST_URAD | Upwelled Radiance. | 0 | 28000 | W/(m^2*sr*um)/ DN | 0.001 | 0 | |
QA_PIXEL | Pixel quality attributes generated from the CFMASK algorithm. | 0 | 0 | ||||
QA_PIXEL Bitmask | Bit 0: FillBit 1: Dilated CloudBit 2: UnusedBit 3: CloudBit 4: Cloud ShadowBit 5: SnowBit 6: Clear 0: Cloud or Dilated Cloud bits are set1: Cloud and Dilated Cloud bits are not setBit 7: WaterBits 8-9: Cloud Confidence 0: None1: Low2: Medium3: HighBits 10-11: Cloud Shadow Confidence 0: None1: Low2: Medium3: HighBits 12-13: Snow/Ice Confidence 0: None1: Low2: Medium3: HighBits 14-15: Cirrus Confidence 0: None1: Low2: Medium3: High | ||||||
QA_RADSAT | Radiometric saturation QA | 0 | 0 | ||||
QA_RADSAT Bitmask | Bit 0: Band 1 data saturatedBit 1: Band 2 data saturatedBit 2: Band 3 data saturatedBit 3: Band 4 data saturatedBit 4: Band 5 data saturatedBit 5: Band 6L data saturatedBit 6: Band 7 data saturatedBit 7: UnusedBit 8: Band 6H data saturatedBit 9: Dropped pixel 0: Pixel present1: Detector doesn't have a value | ||||||
- Bit 0: Dark Dense Vegetation (DDV)
- Bit 1: Cloud
- Bit 2: Cloud Shadow
- Bit 3: Adjacent to Cloud
- Bit 4: Snow
- Bit 5: Water
ST_ATRANAtmospheric Transmittance.0100000.00010ST_CDISTPixel distance to cloud.024000km0.010ST_DRADDownwelled Radiance.028000W/(m^2*sr*um)/ DN0.0010ST_EMISEmissivity estimated from ASTER GED.0100000.00010ST_EMSDEmissivity standard deviation.0100000.00010ST_QAUncertainty of the Surface Temperature band.032767K0.010ST_TRADThermal band converted to radiance.022000W/(m^2*sr*um)/ DN0.0010ST_URADUpwelled Radiance.028000W/(m^2*sr*um)/ DN0.0010QA_PIXELPixel quality attributes generated from the CFMASK algorithm.00QA_PIXEL Bitmask
- Bit 0: Fill
- Bit 1: Dilated Cloud
- Bit 2: Unused
- Bit 3: Cloud
- Bit 4: Cloud Shadow
- Bit 5: Snow
- Bit 6: Clear
- 0: Cloud or Dilated Cloud bits are set
- 1: Cloud and Dilated Cloud bits are not set
- Bit 7: Water
- Bits 8-9: Cloud Confidence
- 0: None
- 1: Low
- 2: Medium
- 3: High
- Bits 10-11: Cloud Shadow Confidence
- 0: None
- 1: Low
- 2: Medium
- 3: High
- Bits 12-13: Snow/Ice Confidence
- 0: None
- 1: Low
- 2: Medium
- 3: High
- Bits 14-15: Cirrus Confidence
- 0: None
- 1: Low
- 2: Medium
- 3: High
QA_RADSATRadiometric saturation QA00QA_RADSAT Bitmask
- Bit 0: Band 1 data saturated
- Bit 1: Band 2 data saturated
- Bit 2: Band 3 data saturated
- Bit 3: Band 4 data saturated
- Bit 4: Band 5 data saturated
- Bit 5: Band 6L data saturated
- Bit 6: Band 7 data saturated
- Bit 7: Unused
- Bit 8: Band 6H data saturated
- Bit 9: Dropped pixel
- 0: Pixel present
- 1: Detector doesn't have a value
影像属性：
Name | Type | Description |
|---|---|---|
ALGORITHM_SOURCE_SURFACE_REFLECTANCE | String | Name and version of the surface reflectance algorithm. |
ALGORITHM_SOURCE_SURFACE_TEMPERATURE | String | Name and version of the surface temperature algorithm. |
CLOUD_COVER | Double | Percentage cloud cover (0-100), -1 = not calculated. |
CLOUD_COVER_LAND | Double | Percentage cloud cover over land (0-100), -1 = not calculated. |
COLLECTION_CATEGORY | String | Scene collection category, "T1" or "T2". |
DATA_SOURCE_AIR_TEMPERATURE | String | Air temperature data source. |
DATA_SOURCE_ELEVATION | String | Elevation data source. |
DATA_SOURCE_OZONE | String | Ozone data source. |
DATA_SOURCE_PRESSURE | String | Pressure data source. |
DATA_SOURCE_REANALYSIS | String | Reanalysis data source. |
DATA_SOURCE_WATER_VAPOR | String | Water vapor data source. |
DATE_PRODUCT_GENERATED | Double | Timestamp of the date when the product was generated. |
EARTH_SUN_DISTANCE | Double | Earth-Sun distance (AU). |
EPHEMERIS_TYPE | Identifier to inform the user of the orbital ephemeris type used: "DEFINITIVE" or "PREDICTIVE". If the field is not present, the user should assume "PREDICTIVE". | |
GEOMETRIC_RMSE_MODEL | Double | Combined RMSE (Root Mean Square Error) of the geometric residuals (meters) in both across-track and along-track directions. |
GEOMETRIC_RMSE_MODEL_X | Double | RMSE (Root Mean Square Error) of the geometric residuals (meters) measured on the GCPs (Ground Control Points) used in geometric precision correction in the across-track direction. |
GEOMETRIC_RMSE_MODEL_Y | Double | RMSE (Root Mean Square Error) of the geometric residuals (meters) measured on the GCPs (Ground Control Points) used in geometric precision correction in the along-track direction. |
GROUND_CONTROL_POINTS_MODEL | Double | Number of GCPs used in the precision correction process. This parameter is only present if the PROCESSING_LEVEL is L1TP. |
GROUND_CONTROL_POINTS_VERSION | Double | GCP dataset version used in the precision correction process. This parameter is only present if the PROCESSING_LEVEL is L1TP. |
IMAGE_QUALITY | Int | Composite image quality for the bands. 0 = worst, 9 = best, -1 = quality not calculated or assessed. |
L1_DATE_PRODUCT_GENERATED | String | Product generation date for the corresponding L1 product. |
L1_LANDSAT_PRODUCT_ID | String | Landsat Product Identifier for the corresponding L1 product. |
L1_PROCESSING_LEVEL | String | Processing Level for the corresponding L1 product. |
L1_PROCESSING_SOFTWARE_VERSION | String | Processing software version for the corresponding L1 product. |
LANDSAT_PRODUCT_ID | String | Landsat Product Identifier |
LANDSAT_SCENE_ID | String | Short Landsat Scene Identifier |
PROCESSING_LEVEL | String | "L2SP" when both SR and LST bands are present, or "L2SR" when only SR bands are present. |
PROCESSING_SOFTWARE_VERSION | String | The processing software version that created the product. |
SCENE_CENTER_TIME | String | Time of the observations as in ISO 8601 string. |
SENSOR_ID | String | Name of the sensor. |
SPACECRAFT_ID | String | Name of the spacecraft. |
SUN_AZIMUTH | Double | Sun azimuth angle in degrees for the image center location at the image center acquisition time. A positive value indicates angles to the east or clockwise from the north. A negative value indicates angles to the west or counterclockwise from the north. |
SUN_ELEVATION | Double | Sun elevation angle in degrees for the image center location at the image center acquisition time. A positive value indicates a daytime scene. A negative value indicates a nighttime scene. Note: For reflectance calculation, the sun zenith angle is needed, which is 90 - sun elevation angle. |
TEMPERATURE_MAXIMUM_BAND_ST_B6 | Double | Maximum achievable temperature value for Band 6. |
TEMPERATURE_MINIMUM_BAND_ST_B6 | Double | Minimum achievable temperature value for Band 6. |
WRS_PATH | Int | WRS path number of scene. |
WRS_ROW | Int | WRS row number of scene. |
使用说明：
Landsat datasets are federally created data and therefore reside in the public domain and may be used, transferred, or reproduced without copyright restriction.
Acknowledgement or credit of the USGS as data source should be provided by including a line of text citation such as the example shown below.
(Product, Image, Photograph, or Dataset Name) courtesy of the U.S. Geological Survey
Example: Landsat-7 image courtesy of the U.S. Geological Survey
See the USGS Visual Identity System Guidance for further details on proper citation and acknowledgement of USGS products.
Landsat数据集是联邦创建的数据，因此属于公共领域，可以在没有版权限制的情况下使用、转让或复制。
对美国地质调查局作为数据来源的鸣谢或信用，应包括一行文字的引用，如下面的例子。
(产品、图像、照片或数据集名称）由美国地质调查局提供。
例子。Landsat-7图像由美国地质调查局提供
请参阅美国地质调查局视觉识别系统指南，了解有关美国地质调查局产品的正确引用和鸣谢的进一步细节。
代码：
代码语言：javascript复制var dataset = ee.ImageCollection('LANDSAT/LT04/C01/T1_TOA')
.filterDate('1989-01-01', '1992-12-31');
var trueColor321 = dataset.select(['B3', 'B2', 'B1']);
var trueColor321Vis = {
min: 0.0,
max: 0.4,
gamma: 1.2,
};
Map.setCenter(6.746, 46.529, 6);
Map.addLayer(trueColor321, trueColor321Vis, 'True Color (321)');
