Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2019-07-05 09:39:44	ga_ls8c_ard_3-1-0_094071_2019-07-05_final
2019-07-05 09:40:08	ga_ls8c_ard_3-1-0_094072_2019-07-05_final
2019-07-05 09:40:32	ga_ls8c_ard_3-1-0_094073_2019-07-05_final
2019-07-05 09:40:56	ga_ls8c_ard_3-1-0_094074_2019-07-05_final
2019-07-05 09:41:20	ga_ls8c_ard_3-1-0_094075_2019-07-05_final
2019-07-05 09:41:44	ga_ls8c_ard_3-1-0_094076_2019-07-05_final
2019-07-07 09:30:59	ga_ls8c_ard_3-1-0_092080_2019-07-07_final
2019-07-07 09:31:23	ga_ls8c_ard_3-1-0_092081_2019-07-07_final
2019-07-07 09:31:47	ga_ls8c_ard_3-1-0_092082_2019-07-07_final
2019-07-07 09:32:11	ga_ls8c_ard_3-1-0_092083_2019-07-07_final
2019-07-07 09:32:34	ga_ls8c_ard_3-1-0_092084_2019-07-07_final
2019-07-07 09:32:58	ga_ls8c_ard_3-1-0_092085_2019-07-07_final
2019-10-02 09:35:36	ga_ls8c_ard_3-1-0_093075_2019-10-02_final
2019-10-02 09:36:00	ga_ls8c_ard_3-1-0_093076_2019-10-02_final
2019-10-02 09:36:24	ga_ls8c_ard_3-1-0_093077_2019-10-02_final
2019-10-02 09:36:48	ga_ls8c_ard_3-1-0_093078_2019-10-02_final
2019-10-02 09:37:12	ga_ls8c_ard_3-1-0_093079_2019-10-02_final
2019-10-02 09:37:36	ga_ls8c_ard_3-1-0_093080_2019-10-02_final
2019-10-02 09:37:59	ga_ls8c_ard_3-1-0_093081_2019-10-02_final
2019-10-04 09:26:26	ga_ls8c_ard_3-1-0_091083_2019-10-03_final
2019-10-04 09:26:50	ga_ls8c_ard_3-1-0_091084_2019-10-03_final
2019-10-04 09:27:14	ga_ls8c_ard_3-1-0_091085_2019-10-03_final
2019-10-04 09:27:38	ga_ls8c_ard_3-1-0_091086_2019-10-03_final
2019-10-04 09:28:02	ga_ls8c_ard_3-1-0_091087_2019-10-03_final
2019-10-04 09:28:26	ga_ls8c_ard_3-1-0_091088_2019-10-03_final
2019-10-04 09:28:50	ga_ls8c_ard_3-1-0_091089_2019-10-03_final
2022-01-25 09:46:10	ga_ls8c_ard_3-2-1_095071_2022-01-25_final
2022-01-25 09:46:34	ga_ls8c_ard_3-2-1_095072_2022-01-25_final
2022-02-21 09:31:05	ga_ls8c_ard_3-2-1_092080_2022-02-21_final
2022-02-21 09:31:29	ga_ls8c_ard_3-2-1_092081_2022-02-21_final
2022-02-21 09:31:53	ga_ls8c_ard_3-2-1_092082_2022-02-21_final
2022-02-21 09:32:17	ga_ls8c_ard_3-2-1_092083_2022-02-21_final
2022-02-21 09:32:41	ga_ls8c_ard_3-2-1_092084_2022-02-21_final
2022-02-21 09:33:05	ga_ls8c_ard_3-2-1_092085_2022-02-21_final
2022-02-23 09:22:19	ga_ls8c_ard_3-2-1_090089_2022-02-22_final
2022-02-23 09:22:43	ga_ls8c_ard_3-2-1_090090_2022-02-22_final
2022-02-26 09:46:02	ga_ls8c_ard_3-2-1_095071_2022-02-26_final
2022-02-26 09:46:26	ga_ls8c_ard_3-2-1_095072_2022-02-26_final
2022-05-03 09:35:03	ga_ls8c_ard_3-2-1_093075_2022-05-03_final
2022-05-03 09:35:27	ga_ls8c_ard_3-2-1_093076_2022-05-03_final
2022-05-03 09:35:51	ga_ls8c_ard_3-2-1_093077_2022-05-03_final
2022-05-03 09:36:15	ga_ls8c_ard_3-2-1_093078_2022-05-03_final
2022-05-03 09:36:39	ga_ls8c_ard_3-2-1_093079_2022-05-03_final
2022-05-03 09:37:03	ga_ls8c_ard_3-2-1_093080_2022-05-03_final
2022-05-03 09:37:27	ga_ls8c_ard_3-2-1_093081_2022-05-03_final
2022-05-05 09:25:55	ga_ls8c_ard_3-2-1_091083_2022-05-04_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-05 09:27:54	ga_ls8c_ard_3-2-1_091088_2022-05-04_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-07 09:16:22	ga_ls8c_ard_3-2-1_089090_2022-05-06_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-27 09:36:12	ga_ls8c_ard_3-2-1_093076_2022-11-27_final
2022-11-27 09:36:36	ga_ls8c_ard_3-2-1_093077_2022-11-27_final
2022-11-27 09:37:00	ga_ls8c_ard_3-2-1_093078_2022-11-27_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-11-27 09:38:12	ga_ls8c_ard_3-2-1_093081_2022-11-27_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-06 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-12-06_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-06 09:33:36	ga_ls8c_ard_3-2-1_092085_2022-12-06_final
2022-12-11 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-12-11_final
2022-12-11 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-12-11_final
2022-12-13 09:35:45	ga_ls8c_ard_3-2-1_093075_2022-12-13_final
2022-12-13 09:36:09	ga_ls8c_ard_3-2-1_093076_2022-12-13_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-13 09:36:57	ga_ls8c_ard_3-2-1_093078_2022-12-13_final
2022-12-13 09:37:21	ga_ls8c_ard_3-2-1_093079_2022-12-13_final
2022-12-13 09:37:45	ga_ls8c_ard_3-2-1_093080_2022-12-13_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-15 09:26:57	ga_ls8c_ard_3-2-1_091084_2022-12-14_final
2022-12-15 09:27:21	ga_ls8c_ard_3-2-1_091085_2022-12-14_final
2022-12-15 09:27:45	ga_ls8c_ard_3-2-1_091086_2022-12-14_final
2022-12-15 09:28:09	ga_ls8c_ard_3-2-1_091087_2022-12-14_final
2022-12-15 09:28:33	ga_ls8c_ard_3-2-1_091088_2022-12-14_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-17 09:16:58	ga_ls8c_ard_3-2-1_089090_2022-12-16_final
2022-12-20 09:40:14	ga_ls8c_ard_3-2-1_094071_2022-12-20_final
2022-12-20 09:40:38	ga_ls8c_ard_3-2-1_094072_2022-12-20_final
2022-12-20 09:41:02	ga_ls8c_ard_3-2-1_094073_2022-12-20_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-20 09:42:14	ga_ls8c_ard_3-2-1_094076_2022-12-20_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-22 09:31:50	ga_ls8c_ard_3-2-1_092081_2022-12-22_final
2022-12-22 09:32:14	ga_ls8c_ard_3-2-1_092082_2022-12-22_final
2022-12-22 09:32:38	ga_ls8c_ard_3-2-1_092083_2022-12-22_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2022-12-22 09:33:26	ga_ls8c_ard_3-2-1_092085_2022-12-22_final
2022-12-29 09:35:39	ga_ls8c_ard_3-2-1_093075_2022-12-29_final
2022-12-29 09:36:03	ga_ls8c_ard_3-2-1_093076_2022-12-29_final
2022-12-29 09:36:27	ga_ls8c_ard_3-2-1_093077_2022-12-29_final
2022-12-29 09:36:51	ga_ls8c_ard_3-2-1_093078_2022-12-29_final
2022-12-29 09:37:15	ga_ls8c_ard_3-2-1_093079_2022-12-29_final
2022-12-29 09:37:39	ga_ls8c_ard_3-2-1_093080_2022-12-29_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years