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
2022-10-10 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-10-10_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-10 11:17:04	ga_ls8c_ard_3-2-1_109081_2022-10-10_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-17 11:22:50	ga_ls8c_ard_3-2-1_110080_2022-10-17_final
2022-10-19 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-10-19_final
2022-10-22 09:58:57	ga_ls8c_ard_3-2-1_097071_2022-10-22_final
2022-10-22 11:41:50	ga_ls8c_ard_3-2-1_113081_2022-10-22_final
2022-10-28 09:27:54	ga_ls8c_ard_3-2-1_091086_2022-10-27_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-10-30 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-11-02 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-11-02_final
2022-11-04 11:11:47	ga_ls8c_ard_3-2-1_108083_2022-11-04_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-21 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-11-21_final
2022-11-27 11:17:52	ga_ls8c_ard_3-2-1_109083_2022-11-27_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-02 09:53:09	ga_ls8c_ard_3-2-1_096072_2022-12-02_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-09 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-12-09_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-16 10:09:48	ga_ls8c_ard_3-2-1_098083_2022-12-16_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-08 11:52:00	ga_ls8c_ard_3-2-1_115076_2023-01-08_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-22 10:23:49	ga_ls8c_ard_3-2-1_101072_2023-01-22_final
2023-02-06 11:19:29	ga_ls8c_ard_3-2-1_110072_2023-02-06_final
2023-02-06 11:19:53	ga_ls8c_ard_3-2-1_110073_2023-02-06_final
2023-02-07 10:23:51	ga_ls8c_ard_3-2-1_101072_2023-02-07_final
2023-02-09 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-02-09_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-24 11:07:13	ga_ls8c_ard_3-2-1_108073_2023-02-24_final
2023-03-08 09:53:22	ga_ls8c_ard_3-2-1_096074_2023-03-08_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-10 11:19:05	ga_ls8c_ard_3-2-1_110072_2023-03-10_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-18 10:28:24	ga_ls8c_ard_3-2-1_102069_2023-03-18_final
2023-03-19 09:35:09	ga_ls8c_ard_3-2-1_093075_2023-03-19_final
2023-03-22 10:07:36	ga_ls8c_ard_3-2-1_098079_2023-03-22_final
2023-03-28 09:28:53	ga_ls8c_ard_3-2-1_092075_2023-03-27_final
2023-03-30 10:53:23	ga_ls8c_ard_3-2-1_106070_2023-03-30_final
2023-04-01 10:42:12	ga_ls8c_ard_3-2-1_104073_2023-04-01_final
2023-04-02 11:25:51	ga_ls8c_ard_3-2-1_111074_2023-04-02_final
2023-04-16 09:58:19	ga_ls8c_ard_3-2-1_097072_2023-04-16_final
2023-04-16 10:01:06	ga_ls8c_ard_3-2-1_097079_2023-04-16_final
2023-04-27 11:19:01	ga_ls8c_ard_3-2-1_110073_2023-04-27_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-19 09:05:36	ga_ls8c_ard_3-2-1_088080_2023-05-18_final
2023-05-19 10:41:41	ga_ls8c_ard_3-2-1_104073_2023-05-19_final
2023-05-20 11:24:34	ga_ls8c_ard_3-2-1_111072_2023-05-20_final
2023-05-21 10:27:21	ga_ls8c_ard_3-2-1_102068_2023-05-21_final
2023-05-22 11:16:36	ga_ls8c_ard_3-2-1_109083_2023-05-22_final
2023-06-14 09:44:52	ga_ls8c_ard_3-2-1_094085_2023-06-14_final
2023-06-18 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-06-18_final
2023-06-19 10:01:25	ga_ls8c_ard_3-2-1_097080_2023-06-19_final
2023-07-05 09:58:01	ga_ls8c_ard_3-2-1_097071_2023-07-05_final
2023-07-11 09:26:34	ga_ls8c_ard_3-2-1_091085_2023-07-10_final
2023-07-17 10:27:35	ga_ls8c_ard_3-2-1_101083_2023-07-17_final
2023-07-19 10:10:49	ga_ls8c_ard_3-2-1_099072_2023-07-19_final
2023-07-27 11:03:33	ga_ls8c_ard_3-2-1_107080_2023-07-27_final
2023-07-28 10:03:57	ga_ls8c_ard_3-2-1_098070_2023-07-28_final
2023-07-29 10:46:02	ga_ls8c_ard_3-2-1_105067_2023-07-29_final
2023-07-31 10:34:05	ga_ls8c_ard_3-2-1_103068_2023-07-31_final
2023-08-06 10:03:49	ga_ls8c_ard_3-2-1_097085_2023-08-06_final
2023-08-08 09:46:40	ga_ls8c_ard_3-2-1_095073_2023-08-08_final
2023-08-10 11:17:34	ga_ls8c_ard_3-2-1_109084_2023-08-10_final
2023-08-14 09:13:13	ga_ls8c_ard_3-2-1_089082_2023-08-13_final
2023-08-30 09:14:55	ga_ls8c_ard_3-2-1_089086_2023-08-29_final
2023-09-02 11:20:18	ga_ls8c_ard_3-2-1_110075_2023-09-02_final
2023-09-05 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-09-05_final
2023-09-15 10:46:40	ga_ls8c_ard_3-2-1_105068_2023-09-15_final
2023-09-20 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-09-20_final
2023-09-23 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-09-23_final
2023-09-28 10:19:01	ga_ls8c_ard_3-2-1_100076_2023-09-28_final
2023-10-01 10:47:08	ga_ls8c_ard_3-2-1_105069_2023-10-01_final
2023-10-04 09:41:08	ga_ls8c_ard_3-2-1_094074_2023-10-04_final
2023-10-06 09:33:10	ga_ls8c_ard_3-2-1_092085_2023-10-06_final
2023-10-08 09:20:26	ga_ls8c_ard_3-2-1_090084_2023-10-07_final
2023-10-11 09:52:33	ga_ls8c_ard_3-2-1_095087_2023-10-11_final
2023-10-12 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-10-12_final
2023-10-21 10:23:14	ga_ls8c_ard_3-2-1_101071_2023-10-21_final
2023-10-22 09:29:37	ga_ls8c_ard_3-2-1_092076_2023-10-21_final
2023-10-23 10:09:42	ga_ls8c_ard_3-2-1_099068_2023-10-23_final
2023-10-24 09:17:41	ga_ls8c_ard_3-2-1_090077_2023-10-23_final
2023-10-27 11:30:17	ga_ls8c_ard_3-2-1_111084_2023-10-27_final
2023-10-29 09:35:27	ga_ls8c_ard_3-2-1_093075_2023-10-29_final
2023-10-30 10:21:31	ga_ls8c_ard_3-2-1_100082_2023-10-30_final
2023-11-02 10:48:49	ga_ls8c_ard_3-2-1_105073_2023-11-02_final
2023-11-02 10:52:01	ga_ls8c_ard_3-2-1_105081_2023-11-02_final
2023-11-03 09:52:24	ga_ls8c_ard_3-2-1_096071_2023-11-03_final
2023-11-06 10:23:16	ga_ls8c_ard_3-2-1_101071_2023-11-06_final
2023-11-07 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-11-07_final
2023-11-13 10:29:26	ga_ls8c_ard_3-2-1_102071_2023-11-13_final
2023-11-17 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-11-17_final
2023-11-22 10:28:07	ga_ls8c_ard_3-2-1_101083_2023-11-22_final
2023-11-28 11:30:19	ga_ls8c_ard_3-2-1_111084_2023-11-28_nrt

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