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
2022-01-14 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-01-14_final
2022-01-23 11:42:37	ga_ls8c_ard_3-2-1_113084_2022-01-23_final
2022-04-21 09:11:56	ga_ls8c_ard_3-2-1_089079_2022-04-20_final
2022-05-01 09:48:59	ga_ls8c_ard_3-2-1_095079_2022-05-01_final
2022-05-01 11:26:16	ga_ls8c_ard_3-2-1_111075_2022-05-01_final
2022-05-14 09:20:37	ga_ls8c_ard_3-2-1_090085_2022-05-13_final
2022-05-15 10:02:17	ga_ls8c_ard_3-2-1_097081_2022-05-15_final
2022-05-16 10:43:33	ga_ls8c_ard_3-2-1_104076_2022-05-16_final
2022-05-17 09:47:08	ga_ls8c_ard_3-2-1_095074_2022-05-17_final
2022-05-19 11:16:52	ga_ls8c_ard_3-2-1_109082_2022-05-19_final
2022-05-21 09:28:25	ga_ls8c_ard_3-2-1_091089_2022-05-20_final
2022-06-10 10:38:21	ga_ls8c_ard_3-2-1_103078_2022-06-10_final
2022-06-11 11:20:50	ga_ls8c_ard_3-2-1_110076_2022-06-11_final
2022-06-17 09:07:19	ga_ls8c_ard_3-2-1_088082_2022-06-16_final
2022-06-22 09:25:30	ga_ls8c_ard_3-2-1_091081_2022-06-21_final
2022-07-03 09:06:35	ga_ls8c_ard_3-2-1_088080_2022-07-02_final
2022-07-04 11:27:08	ga_ls8c_ard_3-2-1_111076_2022-07-04_final
2022-07-08 11:00:24	ga_ls8c_ard_3-2-1_107071_2022-07-08_final
2022-07-12 10:38:28	ga_ls8c_ard_3-2-1_103078_2022-07-12_final
2022-08-07 09:37:19	ga_ls8c_ard_3-2-1_093079_2022-08-07_final
2022-08-14 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-08-14_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-25 09:22:13	ga_ls8c_ard_3-2-1_091072_2022-08-24_final
2022-08-27 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-08-27_final
2022-09-06 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-09-06_final
2022-09-15 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-09-15_final
2022-10-01 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-10-01_final
2022-10-01 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-10-01_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-29 11:47:39	ga_ls8c_ard_3-2-1_114080_2022-10-29_final
2022-10-31 09:57:13	ga_ls8c_ard_3-2-1_096082_2022-10-31_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-07 11:41:52	ga_ls8c_ard_3-2-1_113081_2022-11-07_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-18 11:19:37	ga_ls8c_ard_3-2-1_110072_2022-11-18_final
2022-11-20 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-11-20_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-25 10:02:45	ga_ls8c_ard_3-2-1_097081_2022-12-25_final
2023-01-08 10:16:19	ga_ls8c_ard_3-2-1_099084_2023-01-08_final
2023-01-17 10:10:01	ga_ls8c_ard_3-2-1_098084_2023-01-17_final
2023-01-29 10:31:15	ga_ls8c_ard_3-2-1_102075_2023-01-29_final
2023-02-05 10:35:01	ga_ls8c_ard_3-2-1_103069_2023-02-05_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-03-05 09:28:54	ga_ls8c_ard_3-2-1_091090_2023-03-04_final
2023-03-08 09:56:57	ga_ls8c_ard_3-2-1_096083_2023-03-08_final
2023-03-17 09:50:44	ga_ls8c_ard_3-2-1_095083_2023-03-17_final
2023-03-30 09:20:29	ga_ls8c_ard_3-2-1_090085_2023-03-29_final
2023-04-02 09:46:10	ga_ls8c_ard_3-2-1_095072_2023-04-02_final
2023-04-07 10:02:36	ga_ls8c_ard_3-2-1_098067_2023-04-07_final
2023-04-12 10:23:03	ga_ls8c_ard_3-2-1_101072_2023-04-12_final
2023-04-13 11:10:42	ga_ls8c_ard_3-2-1_108083_2023-04-13_final
2023-04-15 09:18:39	ga_ls8c_ard_3-2-1_090081_2023-04-14_final
2023-04-16 09:56:19	ga_ls8c_ard_3-2-1_097067_2023-04-16_final
2023-04-16 09:58:19	ga_ls8c_ard_3-2-1_097072_2023-04-16_final
2023-05-04 09:49:50	ga_ls8c_ard_3-2-1_095082_2023-05-04_final
2023-05-12 10:36:44	ga_ls8c_ard_3-2-1_103076_2023-05-12_final
2023-06-03 10:03:17	ga_ls8c_ard_3-2-1_097085_2023-06-03_final
2023-06-03 11:41:22	ga_ls8c_ard_3-2-1_113083_2023-06-03_final
2023-06-09 11:00:22	ga_ls8c_ard_3-2-1_107073_2023-06-09_final
2023-06-11 09:12:45	ga_ls8c_ard_3-2-1_089082_2023-06-10_final
2023-06-11 10:51:38	ga_ls8c_ard_3-2-1_105082_2023-06-11_final
2023-06-27 10:47:21	ga_ls8c_ard_3-2-1_105071_2023-06-27_final
2023-07-05 09:57:13	ga_ls8c_ard_3-2-1_097069_2023-07-05_final
2023-07-10 10:19:47	ga_ls8c_ard_3-2-1_100079_2023-07-10_final
2023-07-11 09:28:10	ga_ls8c_ard_3-2-1_091089_2023-07-10_final
2023-07-18 11:10:02	ga_ls8c_ard_3-2-1_108081_2023-07-18_final
2023-08-12 10:59:38	ga_ls8c_ard_3-2-1_107070_2023-08-12_final
2023-08-14 09:11:37	ga_ls8c_ard_3-2-1_089078_2023-08-13_final
2023-08-17 11:20:39	ga_ls8c_ard_3-2-1_110076_2023-08-17_final
2023-08-20 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-08-20_final
2023-08-23 09:06:43	ga_ls8c_ard_3-2-1_088081_2023-08-22_final
2023-08-29 10:03:45	ga_ls8c_ard_3-2-1_098069_2023-08-29_final
2023-09-11 11:13:21	ga_ls8c_ard_3-2-1_109073_2023-09-11_final
2023-09-26 10:30:58	ga_ls8c_ard_3-2-1_102075_2023-09-26_final
2023-09-30 10:09:27	ga_ls8c_ard_3-2-1_098083_2023-09-30_final
2023-10-12 10:33:01	ga_ls8c_ard_3-2-1_102080_2023-10-12_final
2023-10-25 10:01:45	ga_ls8c_ard_3-2-1_097079_2023-10-25_final
2023-10-25 11:41:02	ga_ls8c_ard_3-2-1_113080_2023-10-25_final
2023-10-31 11:03:59	ga_ls8c_ard_3-2-1_107080_2023-10-31_final
2023-11-01 10:03:10	ga_ls8c_ard_3-2-1_098067_2023-11-01_final
2023-11-07 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-11-07_final
2023-11-18 09:16:44	ga_ls8c_ard_3-2-1_089090_2023-11-17_final
2023-11-28 11:24:19	ga_ls8c_ard_3-2-1_111069_2023-11-28_final
2023-12-14 09:50:34	ga_ls8c_ard_3-2-1_095082_2023-12-14_final
2023-12-20 09:15:56	ga_ls8c_ard_3-2-1_089088_2023-12-19_final
2023-12-25 09:34:27	ga_ls8c_ard_3-2-1_092088_2023-12-25_final
2024-01-01 09:39:22	ga_ls8c_ard_3-2-1_093085_2024-01-01_final
2024-01-10 09:31:10	ga_ls8c_ard_3-2-1_092080_2024-01-10_final
2024-01-13 11:38:58	ga_ls8c_ard_3-2-1_113075_2024-01-13_final
2024-01-29 11:42:28	ga_ls8c_ard_3-2-1_113084_2024-01-29_final
2024-01-31 11:26:08	ga_ls8c_ard_3-2-1_111074_2024-01-31_final
2024-02-06 09:11:49	ga_ls8c_ard_3-2-1_089078_2024-02-05_final
2024-02-06 10:46:43	ga_ls8c_ard_3-2-1_105068_2024-02-06_final
2024-02-13 09:20:47	ga_ls8c_ard_3-2-1_090085_2024-02-12_final
2024-02-23 09:55:02	ga_ls8c_ard_3-2-1_096078_2024-02-23_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