USGS Landsat 5 Level 2, Collection 2, Tier 1

Dataset Availability: 1984-03-16T16:18:01Z–2012-05-05T17:54:06Z
Dataset Provider: USGS
Earth Engine Snippet: ee.ImageCollection("LANDSAT/LT05/C02/T1_L2")

Revisit Interval: 16 Days
Tags: cfmask cloud fmask global landsat lasrc lst lt05 reflectance sr tm usgs

Description

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, 'PROCESSING_LEVEL' is set to 'L2SP'. For assets with only SR bands, '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).
ASTER GED contains areas of missing mean emissivity data required for successful ST product generation. If there is missing ASTER GED information, there will be missing ST data in those areas.
The ASTER GED dataset is created from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. While this dataset has a global spatial extent, there are areas missing mean emissivity information due to persistent cloud contamination in the ASTER measurements.
The USGS further screens unphysical values (emissivity < 0.6) in ASTER GED to remove any emissivity underestimation due to undetected clouds. For any given pixel with no ASTER GED input or unphysical emissivity value, the resulting Landsat ST products have missing pixels. The missing Landsat ST pixels will be consistent through time (1982-present) given the static nature of ASTER GED mean climatology data. For more information refer to landsat-collection-2-surface-temperature-data-gaps-due-missing

Bands

Resolution
30 meters

Bands

Name	Units	Min	Max	Scale	Offset	Wavelength	Description
`SR_B1`		1	65455	2.75e-05	-0.2	0.45-0.52 μm	Band 1 (blue) surface reflectance
`SR_B2`		1	65455	2.75e-05	-0.2	0.52-0.60 μm	Band 2 (green) surface reflectance
`SR_B3`		1	65455	2.75e-05	-0.2	0.63-0.69 μm	Band 3 (red) surface reflectance
`SR_B4`		1	65455	2.75e-05	-0.2	0.77-0.90 μm	Band 4 (near infrared) surface reflectance
`SR_B5`		1	65455	2.75e-05	-0.2	1.55-1.75 μm	Band 5 (shortwave infrared 1) surface reflectance
`SR_B7`		1	65455	2.75e-05	-0.2	2.08-2.35 μm	Band 7 (shortwave infrared 2) surface reflectance
`SR_ATMOS_OPACITY`		0	10000	0.001			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.
`SR_CLOUD_QA`							Cloud Quality Assessment
Bitmask for SR_CLOUD_QA 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_B6`	K	0	65535	0.00341802	149	10.40-12.50 μm	Band 6 surface temperature. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_ATRAN`		0	10000	0.0001			Atmospheric Transmittance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_CDIST`	km	0	24000	0.01			Pixel distance to cloud. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_DRAD`	W/(m^2srum)/ DN	0	28000	0.001			Downwelled Radiance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_EMIS`		0	10000	0.0001			Emissivity estimated from ASTER GED. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_EMSD`		0	10000	0.0001			Emissivity standard deviation. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_QA`	K	0	32767	0.01			Uncertainty of the Surface Temperature band. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_TRAD`	W/(m^2srum)/ DN	0	22000	0.001			Thermal band converted to radiance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`ST_URAD`	W/(m^2srum)/ DN	0	28000	0.001			Upwelled Radiance. If 'PROCESSING_LEVEL' is set to 'L2SR', this band is fully masked out.
`QA_PIXEL`							Pixel quality attributes generated from the CFMASK algorithm.
Bitmask for QA_PIXEL 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_RADSAT`							Radiometric saturation QA
Bitmask for QA_RADSAT 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

Image Properties

Image Properties

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	STRING	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. This parameter is only present if the L1_PROCESSING_LEVEL is L1TP.
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. This parameter is only present if the L1_PROCESSING_LEVEL is L1TP.
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. This parameter is only present if the L1_PROCESSING_LEVEL is L1TP.
GROUND_CONTROL_POINTS_MODEL	DOUBLE	Number of GCPs used in the precision correction process. This parameter is only present if the L1_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 L1_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.

Terms of Use

Terms of Use

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.

Explore with Earth Engine

Code Editor (JavaScript)

var dataset = ee.ImageCollection('LANDSAT/LT05/C02/T1_L2')
    .filterDate('2000-06-01', '2000-07-01');

// Applies scaling factors.
function applyScaleFactors(image) {
  var opticalBands = image.select('SR_B.').multiply(0.0000275).add(-0.2);
  var thermalBand = image.select('ST_B6').multiply(0.00341802).add(149.0);
  return image.addBands(opticalBands, null, true)
              .addBands(thermalBand, null, true);
}

dataset = dataset.map(applyScaleFactors);

var visualization = {
  bands: ['SR_B3', 'SR_B2', 'SR_B1'],
  min: 0.0,
  max: 0.3,
};

Map.setCenter(-114.2579, 38.9275, 8);

Map.addLayer(dataset, visualization, 'True Color (321)');

Python setup

See the Python Environment page for information on the Python API and using geemap for interactive development.

import ee
import geemap.core as geemap

Colab (Python)

dataset = ee.ImageCollection('LANDSAT/LT05/C02/T1_L2').filterDate(
    '2000-06-01', '2000-07-01'
)


# Applies scaling factors.
def apply_scale_factors(image):
  optical_bands = image.select('SR_B.').multiply(0.0000275).add(-0.2)
  thermal_bands = image.select('ST_B6').multiply(0.00341802).add(149.0)
  return image.addBands(optical_bands, None, True).addBands(
      thermal_bands, None, True
  )


dataset = dataset.map(apply_scale_factors)

visualization = {
    'bands': ['SR_B3', 'SR_B2', 'SR_B1'],
    'min': 0.0,
    'max': 0.3,
}

m = geemap.Map()
m.set_center(-114.2579, 38.9275, 8)
m.add_layer(dataset, visualization, 'True Color (321)')
m

Open in Code Editor

USGS Landsat 5 Level 2, Collection 2, Tier 1

LANDSAT/LT05/C02/T1_L2, cfmask,cloud,fmask,global,landsat,lasrc,lst,lt05,reflectance,sr,tm,usgs

1984-03-16T16:18:01Z/2012-05-05T17:54:06Z

Google Earth Engine

https://developers.google.com/earth-engine/datasets