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
2022-06-15 09:18:28	ga_ls8c_ard_3-2-1_090079_2022-06-14_final
2022-07-13 11:18:32	ga_ls8c_ard_3-2-1_110070_2022-07-13_final
2022-07-15 09:29:16	ga_ls8c_ard_3-2-1_092075_2022-07-14_final
2022-07-18 09:59:49	ga_ls8c_ard_3-2-1_097074_2022-07-18_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-07-27 09:52:09	ga_ls8c_ard_3-2-1_096070_2022-07-27_final
2022-07-28 10:40:13	ga_ls8c_ard_3-2-1_103082_2022-07-28_final
2022-08-05 11:29:20	ga_ls8c_ard_3-2-1_111081_2022-08-05_final
2022-08-07 11:12:12	ga_ls8c_ard_3-2-1_109069_2022-08-07_final
2022-08-08 10:20:11	ga_ls8c_ard_3-2-1_100078_2022-08-08_final
2022-08-09 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-08-09_final
2022-08-11 09:13:01	ga_ls8c_ard_3-2-1_089080_2022-08-10_final
2022-08-14 11:23:37	ga_ls8c_ard_3-2-1_110082_2022-08-14_final
2022-08-15 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-15_final
2022-08-16 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-08-16_final
2022-08-18 09:19:37	ga_ls8c_ard_3-2-1_090081_2022-08-17_final
2022-08-23 09:40:34	ga_ls8c_ard_3-2-1_093087_2022-08-23_final
2022-08-25 09:25:49	ga_ls8c_ard_3-2-1_091081_2022-08-24_final
2022-08-26 11:47:10	ga_ls8c_ard_3-2-1_114079_2022-08-26_final
2022-09-02 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-09-02_final
2022-09-03 09:22:25	ga_ls8c_ard_3-2-1_090088_2022-09-02_final
2022-09-06 09:52:57	ga_ls8c_ard_3-2-1_095087_2022-09-06_final
2022-09-12 09:15:07	ga_ls8c_ard_3-2-1_089085_2022-09-11_final
2022-09-17 11:08:35	ga_ls8c_ard_3-2-1_108075_2022-09-17_final
2022-09-23 10:29:07	ga_ls8c_ard_3-2-1_102069_2022-09-23_final
2022-09-26 09:25:55	ga_ls8c_ard_3-2-1_091081_2022-09-25_final
2022-09-29 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-09-29_final
2022-09-29 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-09-29_final
2022-09-30 10:34:53	ga_ls8c_ard_3-2-1_103068_2022-09-30_final
2022-10-01 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-10-01_final
2022-10-10 09:35:23	ga_ls8c_ard_3-2-1_093074_2022-10-10_final
2022-10-14 09:14:12	ga_ls8c_ard_3-2-1_089083_2022-10-13_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-10-14 10:49:06	ga_ls8c_ard_3-2-1_105073_2022-10-14_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-23 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-23_final
2022-10-28 09:23:55	ga_ls8c_ard_3-2-1_091076_2022-10-27_final
2022-10-30 09:13:09	ga_ls8c_ard_3-2-1_089080_2022-10-29_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-02 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-11-02_final
2022-11-05 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-11-05_final
2022-11-07 09:58:12	ga_ls8c_ard_3-2-1_097069_2022-11-07_final
2022-11-08 10:43:51	ga_ls8c_ard_3-2-1_104075_2022-11-08_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-10 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-11-10_final
2022-11-11 09:35:50	ga_ls8c_ard_3-2-1_093075_2022-11-11_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-21 10:13:39	ga_ls8c_ard_3-2-1_099077_2022-11-21_final
2022-11-21 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-11-21_final
2022-11-24 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-11-23_final
2022-11-25 11:26:38	ga_ls8c_ard_3-2-1_111074_2022-11-25_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-11-28 11:59:09	ga_ls8c_ard_3-2-1_116078_2022-11-28_final
2022-11-29 09:27:50	ga_ls8c_ard_3-2-1_091086_2022-11-28_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-06 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-12-06_final
2022-12-07 11:52:57	ga_ls8c_ard_3-2-1_115078_2022-12-07_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-14 11:59:05	ga_ls8c_ard_3-2-1_116078_2022-12-14_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2023-01-05 09:44:38	ga_ls8c_ard_3-2-1_094082_2023-01-05_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-07 11:08:45	ga_ls8c_ard_3-2-1_108076_2023-01-07_final
2023-01-19 11:36:09	ga_ls8c_ard_3-2-1_112083_2023-01-19_final
2023-01-20 10:36:09	ga_ls8c_ard_3-2-1_103072_2023-01-20_final
2023-01-20 10:40:09	ga_ls8c_ard_3-2-1_103082_2023-01-20_final
2023-01-30 09:35:37	ga_ls8c_ard_3-2-1_093075_2023-01-30_final
2023-01-31 10:17:41	ga_ls8c_ard_3-2-1_100072_2023-01-31_final
2023-01-31 10:20:53	ga_ls8c_ard_3-2-1_100080_2023-01-31_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-10 10:54:43	ga_ls8c_ard_3-2-1_106072_2023-02-10_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-19 10:48:24	ga_ls8c_ard_3-2-1_105072_2023-02-19_final
2023-02-20 09:57:33	ga_ls8c_ard_3-2-1_096084_2023-02-20_final
2023-02-26 10:55:14	ga_ls8c_ard_3-2-1_106074_2023-02-26_final
2023-03-01 09:50:27	ga_ls8c_ard_3-2-1_095082_2023-03-01_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_2023-03-08_final
2023-03-22 11:46:29	ga_ls8c_ard_3-2-1_114079_2023-03-22_final
2023-03-24 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-03-24_final
2023-04-01 10:40:12	ga_ls8c_ard_3-2-1_104068_2023-04-01_final
2023-04-08 09:11:45	ga_ls8c_ard_3-2-1_089079_2023-04-07_final
2023-04-08 09:14:09	ga_ls8c_ard_3-2-1_089085_2023-04-07_final
2023-04-13 09:33:24	ga_ls8c_ard_3-2-1_092087_2023-04-13_final
2023-04-13 09:34:12	ga_ls8c_ard_3-2-1_092089_2023-04-13_final
2023-04-14 10:12:17	ga_ls8c_ard_3-2-1_099076_2023-04-14_final
2023-04-17 09:06:16	ga_ls8c_ard_3-2-1_088081_2023-04-16_final
2023-04-18 09:51:55	ga_ls8c_ard_3-2-1_095087_2023-04-18_final
2023-04-29 09:28:33	ga_ls8c_ard_3-2-1_092075_2023-04-28_final
2023-04-29 09:34:08	ga_ls8c_ard_3-2-1_092089_2023-04-29_final
2023-04-30 10:15:00	ga_ls8c_ard_3-2-1_099083_2023-04-30_final
2023-04-30 11:50:41	ga_ls8c_ard_3-2-1_115075_2023-04-30_final
2023-05-01 09:17:22	ga_ls8c_ard_3-2-1_090078_2023-04-30_final
2023-05-19 09:06:00	ga_ls8c_ard_3-2-1_088081_2023-05-18_final
2023-05-26 10:48:19	ga_ls8c_ard_3-2-1_105074_2023-05-26_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