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
2022-05-22 10:04:29	ga_ls8c_ard_3-2-1_098071_2022-05-22_final
2022-05-26 11:18:38	ga_ls8c_ard_3-2-1_110071_2022-05-26_final
2022-05-28 11:05:52	ga_ls8c_ard_3-2-1_108070_2022-05-28_final
2022-05-28 11:07:04	ga_ls8c_ard_3-2-1_108073_2022-05-28_final
2022-05-28 11:11:04	ga_ls8c_ard_3-2-1_108083_2022-05-28_final
2022-06-12 10:22:50	ga_ls8c_ard_3-2-1_101070_2022-06-12_final
2022-06-16 10:01:20	ga_ls8c_ard_3-2-1_097078_2022-06-16_final
2022-06-16 11:41:01	ga_ls8c_ard_3-2-1_113080_2022-06-16_final
2022-06-21 10:17:31	ga_ls8c_ard_3-2-1_100072_2022-06-21_final
2022-06-24 09:13:56	ga_ls8c_ard_3-2-1_089083_2022-06-23_final
2022-06-27 11:18:57	ga_ls8c_ard_3-2-1_110071_2022-06-27_final
2022-06-29 09:32:06	ga_ls8c_ard_3-2-1_092082_2022-06-29_final
2022-07-08 11:00:01	ga_ls8c_ard_3-2-1_107070_2022-07-08_final
2022-07-15 11:06:10	ga_ls8c_ard_3-2-1_108070_2022-07-15_final
2022-07-15 11:10:57	ga_ls8c_ard_3-2-1_108082_2022-07-15_final
2022-07-20 09:51:52	ga_ls8c_ard_3-2-1_095085_2022-07-20_final
2022-07-20 11:25:34	ga_ls8c_ard_3-2-1_111072_2022-07-20_final
2022-07-26 09:13:16	ga_ls8c_ard_3-2-1_089081_2022-07-25_final
2022-07-31 11:06:22	ga_ls8c_ard_3-2-1_108070_2022-07-31_final
2022-08-05 11:26:33	ga_ls8c_ard_3-2-1_111074_2022-08-05_final
2022-08-08 10:19:23	ga_ls8c_ard_3-2-1_100076_2022-08-08_final
2022-08-09 09:26:58	ga_ls8c_ard_3-2-1_091084_2022-08-08_final
2022-08-11 09:11:49	ga_ls8c_ard_3-2-1_089077_2022-08-10_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-19 11:42:10	ga_ls8c_ard_3-2-1_113082_2022-08-19_final
2022-08-27 09:15:27	ga_ls8c_ard_3-2-1_089086_2022-08-26_final
2022-09-06 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-09-06_final
2022-09-22 09:48:15	ga_ls8c_ard_3-2-1_095075_2022-09-22_final
2022-09-24 09:37:29	ga_ls8c_ard_3-2-1_093079_2022-09-24_final
2022-09-27 10:04:48	ga_ls8c_ard_3-2-1_098070_2022-09-27_final
2022-10-12 09:23:48	ga_ls8c_ard_3-2-1_091076_2022-10-11_final
2022-10-12 09:26:35	ga_ls8c_ard_3-2-1_091083_2022-10-11_final
2022-10-12 11:02:17	ga_ls8c_ard_3-2-1_107075_2022-10-12_final
2022-10-14 09:14:36	ga_ls8c_ard_3-2-1_089084_2022-10-13_final
2022-10-16 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-10-16_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-20 10:12:06	ga_ls8c_ard_3-2-1_099073_2022-10-20_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-11-08 10:41:03	ga_ls8c_ard_3-2-1_104068_2022-11-08_final
2022-11-12 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-11-12_final
2022-11-13 09:23:51	ga_ls8c_ard_3-2-1_091076_2022-11-12_final
2022-12-08 09:18:27	ga_ls8c_ard_3-2-1_090078_2022-12-07_final
2022-12-08 10:55:44	ga_ls8c_ard_3-2-1_106074_2022-12-08_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-11 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-12-11_final
2022-12-15 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-12-15_final
2023-01-17 11:47:18	ga_ls8c_ard_3-2-1_114080_2023-01-17_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-02-06 11:19:05	ga_ls8c_ard_3-2-1_110071_2023-02-06_final
2023-02-06 11:20:40	ga_ls8c_ard_3-2-1_110075_2023-02-06_final
2023-02-16 10:21:57	ga_ls8c_ard_3-2-1_100083_2023-02-16_final
2023-02-17 09:26:42	ga_ls8c_ard_3-2-1_091084_2023-02-16_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-03-05 09:23:18	ga_ls8c_ard_3-2-1_091076_2023-03-04_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_final
2023-03-13 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-03-13_final
2023-03-20 11:58:05	ga_ls8c_ard_3-2-1_116077_2023-03-20_final
2023-03-29 11:52:37	ga_ls8c_ard_3-2-1_115079_2023-03-29_final
2023-04-06 09:24:57	ga_ls8c_ard_3-2-1_091081_2023-04-05_final
2023-04-24 10:48:07	ga_ls8c_ard_3-2-1_105073_2023-04-24_final
2023-04-25 09:51:42	ga_ls8c_ard_3-2-1_096071_2023-04-25_final
2023-04-27 11:19:01	ga_ls8c_ard_3-2-1_110073_2023-04-27_final
2023-05-05 10:27:54	ga_ls8c_ard_3-2-1_102069_2023-05-05_final
2023-05-08 11:00:44	ga_ls8c_ard_3-2-1_107074_2023-05-08_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_final
2023-05-20 11:24:10	ga_ls8c_ard_3-2-1_111071_2023-05-20_final
2023-06-06 10:28:38	ga_ls8c_ard_3-2-1_102071_2023-06-06_final
2023-06-08 10:21:06	ga_ls8c_ard_3-2-1_100083_2023-06-08_final
2023-06-11 09:15:56	ga_ls8c_ard_3-2-1_089090_2023-06-10_final
2023-06-12 09:56:49	ga_ls8c_ard_3-2-1_096084_2023-06-12_final
2023-06-13 10:34:30	ga_ls8c_ard_3-2-1_103070_2023-06-13_final
2023-06-30 09:43:48	ga_ls8c_ard_3-2-1_094082_2023-06-30_final
2023-07-07 11:28:57	ga_ls8c_ard_3-2-1_111082_2023-07-07_final
2023-07-16 09:40:44	ga_ls8c_ard_3-2-1_094074_2023-07-16_final
2023-07-20 09:17:12	ga_ls8c_ard_3-2-1_090077_2023-07-19_final
2023-07-21 11:41:44	ga_ls8c_ard_3-2-1_113083_2023-07-21_final
2023-07-27 10:59:34	ga_ls8c_ard_3-2-1_107070_2023-07-27_final
2023-07-29 09:13:32	ga_ls8c_ard_3-2-1_089083_2023-07-28_final
2023-08-03 11:05:48	ga_ls8c_ard_3-2-1_108070_2023-08-03_final
2023-08-10 09:34:42	ga_ls8c_ard_3-2-1_093074_2023-08-10_final
2023-08-14 09:16:24	ga_ls8c_ard_3-2-1_089090_2023-08-13_final
2023-08-17 09:46:09	ga_ls8c_ard_3-2-1_094087_2023-08-17_final
2023-09-04 09:34:38	ga_ls8c_ard_3-2-1_092089_2023-09-04_final
2023-09-13 09:23:19	ga_ls8c_ard_3-2-1_091076_2023-09-12_final
2023-09-14 10:05:00	ga_ls8c_ard_3-2-1_098072_2023-09-14_final
2023-09-14 10:06:59	ga_ls8c_ard_3-2-1_098077_2023-09-14_final
2023-09-15 09:13:22	ga_ls8c_ard_3-2-1_089082_2023-09-14_final
2023-09-18 09:41:05	ga_ls8c_ard_3-2-1_094074_2023-09-18_final
2023-09-20 11:06:01	ga_ls8c_ard_3-2-1_108070_2023-09-20_final
2023-10-01 10:51:55	ga_ls8c_ard_3-2-1_105081_2023-10-01_final
2023-10-07 11:51:20	ga_ls8c_ard_3-2-1_115075_2023-10-07_final
2023-10-08 10:53:20	ga_ls8c_ard_3-2-1_106069_2023-10-08_final
2023-10-23 10:15:41	ga_ls8c_ard_3-2-1_099083_2023-10-23_final
2023-10-30 10:18:19	ga_ls8c_ard_3-2-1_100074_2023-10-30_final
2023-10-31 09:27:29	ga_ls8c_ard_3-2-1_091086_2023-10-30_final
2023-11-08 11:53:21	ga_ls8c_ard_3-2-1_115080_2023-11-08_final
2023-11-09 10:54:31	ga_ls8c_ard_3-2-1_106072_2023-11-09_final
2023-11-12 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-11-12_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