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
2022-07-05 10:28:19	ga_ls8c_ard_3-2-1_102068_2022-07-05_final
2022-07-06 11:11:58	ga_ls8c_ard_3-2-1_109069_2022-07-06_final
2022-07-08 09:28:43	ga_ls8c_ard_3-2-1_091089_2022-07-07_final
2022-07-11 09:56:48	ga_ls8c_ard_3-2-1_096082_2022-07-11_final
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-24 09:22:49	ga_ls8c_ard_3-2-1_091074_2022-07-23_final
2022-07-25 11:46:10	ga_ls8c_ard_3-2-1_114077_2022-07-25_final
2022-07-25 11:46:58	ga_ls8c_ard_3-2-1_114079_2022-07-25_final
2022-07-29 09:46:12	ga_ls8c_ard_3-2-1_094086_2022-07-29_final
2022-08-02 09:18:44	ga_ls8c_ard_3-2-1_090079_2022-08-01_final
2022-08-06 10:28:56	ga_ls8c_ard_3-2-1_102069_2022-08-06_final
2022-08-11 09:16:37	ga_ls8c_ard_3-2-1_089089_2022-08-10_final
2022-08-14 09:40:44	ga_ls8c_ard_3-2-1_094072_2022-08-14_final
2022-08-14 09:41:08	ga_ls8c_ard_3-2-1_094073_2022-08-14_final
2022-08-16 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-08-16_final
2022-08-20 09:06:52	ga_ls8c_ard_3-2-1_088080_2022-08-19_final
2022-08-31 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-08-31_final
2022-09-06 11:25:27	ga_ls8c_ard_3-2-1_111071_2022-09-06_final
2022-09-09 10:22:17	ga_ls8c_ard_3-2-1_100083_2022-09-09_final
2022-09-10 09:23:05	ga_ls8c_ard_3-2-1_091074_2022-09-09_final
2022-09-11 10:10:20	ga_ls8c_ard_3-2-1_098084_2022-09-11_final
2022-09-11 11:47:14	ga_ls8c_ard_3-2-1_114079_2022-09-11_final
2022-09-12 09:11:56	ga_ls8c_ard_3-2-1_089077_2022-09-11_final
2022-09-17 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-09-17_final
2022-09-19 09:21:44	ga_ls8c_ard_3-2-1_090086_2022-09-18_final
2022-09-21 10:41:29	ga_ls8c_ard_3-2-1_104069_2022-09-21_final
2022-09-26 09:23:08	ga_ls8c_ard_3-2-1_091074_2022-09-25_final
2022-09-28 09:12:46	ga_ls8c_ard_3-2-1_089079_2022-09-27_final
2022-10-03 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-10-03_final
2022-10-03 11:06:10	ga_ls8c_ard_3-2-1_108069_2022-10-03_final
2022-10-03 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-10-03_final
2022-10-04 11:52:37	ga_ls8c_ard_3-2-1_115077_2022-10-04_final
2022-10-05 10:53:24	ga_ls8c_ard_3-2-1_106068_2022-10-05_final
2022-10-07 10:42:13	ga_ls8c_ard_3-2-1_104071_2022-10-07_final
2022-10-10 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-10-10_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-20 11:52:11	ga_ls8c_ard_3-2-1_115076_2022-10-20_final
2022-10-22 09:59:45	ga_ls8c_ard_3-2-1_097073_2022-10-22_final
2022-10-28 11:02:24	ga_ls8c_ard_3-2-1_107075_2022-10-28_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-11-02 11:23:45	ga_ls8c_ard_3-2-1_110082_2022-11-02_final
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-06 09:18:32	ga_ls8c_ard_3-2-1_090078_2022-11-05_final
2022-11-08 10:43:03	ga_ls8c_ard_3-2-1_104073_2022-11-08_final
2022-11-10 10:29:52	ga_ls8c_ard_3-2-1_102071_2022-11-10_final
2022-11-12 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-11-12_final
2022-11-15 09:10:40	ga_ls8c_ard_3-2-1_089074_2022-11-14_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-17 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-11-17_final
2022-11-19 10:23:12	ga_ls8c_ard_3-2-1_101070_2022-11-19_final
2022-11-22 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-11-21_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-12-07 10:11:17	ga_ls8c_ard_3-2-1_099071_2022-12-07_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-13 11:13:26	ga_ls8c_ard_3-2-1_109072_2022-12-13_final
2022-12-15 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-12-14_final
2022-12-16 10:07:01	ga_ls8c_ard_3-2-1_098076_2022-12-16_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-17 09:14:34	ga_ls8c_ard_3-2-1_089084_2022-12-16_final
2022-12-18 11:32:19	ga_ls8c_ard_3-2-1_112073_2022-12-18_final
2022-12-20 09:41:02	ga_ls8c_ard_3-2-1_094073_2022-12-20_final
2022-12-22 09:29:26	ga_ls8c_ard_3-2-1_092075_2022-12-21_final
2022-12-25 11:40:26	ga_ls8c_ard_3-2-1_113078_2022-12-25_final
2022-12-29 09:35:39	ga_ls8c_ard_3-2-1_093075_2022-12-29_final
2022-12-30 10:19:19	ga_ls8c_ard_3-2-1_100076_2022-12-30_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-08 10:11:31	ga_ls8c_ard_3-2-1_099072_2023-01-08_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-16 09:28:46	ga_ls8c_ard_3-2-1_091089_2023-01-15_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-01-19 09:56:04	ga_ls8c_ard_3-2-1_096080_2023-01-19_final
2023-01-23 09:29:48	ga_ls8c_ard_3-2-1_092076_2023-01-22_final
2023-01-24 10:11:53	ga_ls8c_ard_3-2-1_099073_2023-01-24_final
2023-01-24 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-01-24_final
2023-01-30 11:12:07	ga_ls8c_ard_3-2-1_109069_2023-01-30_final
2023-02-01 09:26:51	ga_ls8c_ard_3-2-1_091084_2023-01-31_final
2023-02-09 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-02-09_final
2023-02-09 10:14:16	ga_ls8c_ard_3-2-1_099079_2023-02-09_final
2023-02-11 11:39:10	ga_ls8c_ard_3-2-1_113075_2023-02-11_final
2023-02-17 11:01:36	ga_ls8c_ard_3-2-1_107074_2023-02-17_final
2023-02-22 11:20:26	ga_ls8c_ard_3-2-1_110075_2023-02-22_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-07 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-03-07_final
2023-03-14 09:19:04	ga_ls8c_ard_3-2-1_090081_2023-03-13_final
2023-03-16 09:07:05	ga_ls8c_ard_3-2-1_088082_2023-03-15_final
2023-03-17 11:26:02	ga_ls8c_ard_3-2-1_111074_2023-03-17_final
2023-03-21 09:28:21	ga_ls8c_ard_3-2-1_091089_2023-03-20_final
2023-04-06 11:04:38	ga_ls8c_ard_3-2-1_107083_2023-04-06_final
2023-04-18 11:24:25	ga_ls8c_ard_3-2-1_111071_2023-04-18_final
2023-04-21 10:21:36	ga_ls8c_ard_3-2-1_100084_2023-04-21_final
2023-04-25 09:52:06	ga_ls8c_ard_3-2-1_096072_2023-04-25_final
2023-05-03 09:06:59	ga_ls8c_ard_3-2-1_088083_2023-05-02_final
2023-05-04 11:29:07	ga_ls8c_ard_3-2-1_111083_2023-05-04_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-10 10:51:56	ga_ls8c_ard_3-2-1_105083_2023-05-10_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years