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
2021-06-15 08:10:33	ga_ls8c_ard_3-2-1_079080_2021-06-14_final
2023-02-02 11:45:01	ga_ls8c_ard_3-2-1_114074_2023-02-02_final
2023-02-02 11:46:12	ga_ls8c_ard_3-2-1_114077_2023-02-02_final
2023-03-12 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-03-12_final
2023-03-14 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-03-14_final
2023-03-19 09:38:45	ga_ls8c_ard_3-2-1_093084_2023-03-19_final
2023-03-19 11:12:50	ga_ls8c_ard_3-2-1_109072_2023-03-19_final
2023-03-20 10:18:00	ga_ls8c_ard_3-2-1_100074_2023-03-20_final
2023-03-21 11:00:27	ga_ls8c_ard_3-2-1_107072_2023-03-21_final
2023-03-22 10:08:00	ga_ls8c_ard_3-2-1_098080_2023-03-22_final
2023-06-30 09:40:13	ga_ls8c_ard_3-2-1_094073_2023-06-30_final
2023-07-05 10:03:36	ga_ls8c_ard_3-2-1_097085_2023-07-05_final
2023-07-07 09:50:04	ga_ls8c_ard_3-2-1_095082_2023-07-07_final
2023-07-11 11:00:40	ga_ls8c_ard_3-2-1_107073_2023-07-11_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-19 11:51:18	ga_ls8c_ard_3-2-1_115076_2023-07-19_final
2023-07-23 11:28:37	ga_ls8c_ard_3-2-1_111081_2023-07-23_final
2023-07-30 09:56:00	ga_ls8c_ard_3-2-1_096081_2023-07-30_final
2023-08-10 09:37:53	ga_ls8c_ard_3-2-1_093082_2023-08-10_final
2023-08-10 09:38:41	ga_ls8c_ard_3-2-1_093084_2023-08-10_final
2023-08-28 09:25:17	ga_ls8c_ard_3-2-1_091081_2023-08-27_final
2023-08-31 09:56:58	ga_ls8c_ard_3-2-1_096083_2023-08-31_final
2023-08-31 11:35:51	ga_ls8c_ard_3-2-1_112083_2023-08-31_final
2023-09-02 09:46:12	ga_ls8c_ard_3-2-1_094087_2023-09-02_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-07 09:59:07	ga_ls8c_ard_3-2-1_097073_2023-09-07_final
2023-09-07 10:01:07	ga_ls8c_ard_3-2-1_097078_2023-09-07_final
2023-09-07 11:40:48	ga_ls8c_ard_3-2-1_113080_2023-09-07_final
2023-09-09 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-09-09_final
2023-09-13 09:25:19	ga_ls8c_ard_3-2-1_091081_2023-09-12_final
2023-09-19 10:23:09	ga_ls8c_ard_3-2-1_101071_2023-09-19_final
2023-09-22 09:18:22	ga_ls8c_ard_3-2-1_090079_2023-09-21_final
2023-09-30 11:45:57	ga_ls8c_ard_3-2-1_114077_2023-09-30_final
2023-10-01 09:13:50	ga_ls8c_ard_3-2-1_089083_2023-09-30_final
2023-10-02 09:53:30	ga_ls8c_ard_3-2-1_096074_2023-10-02_final
2023-10-05 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-10-05_final
2023-10-07 10:15:38	ga_ls8c_ard_3-2-1_099083_2023-10-07_final
2023-10-11 09:47:46	ga_ls8c_ard_3-2-1_095075_2023-10-11_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-16 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-10-16_final
2023-10-19 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-10-19_final
2023-10-23 10:11:42	ga_ls8c_ard_3-2-1_099073_2023-10-23_final
2023-10-23 11:52:11	ga_ls8c_ard_3-2-1_115077_2023-10-23_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-10-25 11:42:38	ga_ls8c_ard_3-2-1_113084_2023-10-25_final
2023-10-28 10:30:41	ga_ls8c_ard_3-2-1_102074_2023-10-28_final
2023-10-28 10:33:04	ga_ls8c_ard_3-2-1_102080_2023-10-28_final
2023-10-29 09:39:51	ga_ls8c_ard_3-2-1_093086_2023-10-29_final
2023-10-31 11:03:59	ga_ls8c_ard_3-2-1_107080_2023-10-31_final
2023-10-31 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-10-31_final
2023-11-01 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-01_final
2023-11-04 10:35:15	ga_ls8c_ard_3-2-1_103070_2023-11-04_final
2023-11-06 10:25:16	ga_ls8c_ard_3-2-1_101076_2023-11-06_final
2023-11-08 10:12:52	ga_ls8c_ard_3-2-1_099076_2023-11-08_final
2023-11-08 10:16:28	ga_ls8c_ard_3-2-1_099085_2023-11-08_final
2023-11-10 10:01:17	ga_ls8c_ard_3-2-1_097078_2023-11-10_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-11 10:40:34	ga_ls8c_ard_3-2-1_104068_2023-11-11_final
2023-11-12 11:26:38	ga_ls8c_ard_3-2-1_111075_2023-11-12_final
2023-11-15 10:17:54	ga_ls8c_ard_3-2-1_100073_2023-11-15_final
2023-11-16 11:02:46	ga_ls8c_ard_3-2-1_107077_2023-11-16_final
2023-11-19 11:32:54	ga_ls8c_ard_3-2-1_112075_2023-11-19_final
2023-11-19 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-11-19_final
2023-11-22 10:24:56	ga_ls8c_ard_3-2-1_101075_2023-11-22_final
2023-11-26 10:02:12	ga_ls8c_ard_3-2-1_097080_2023-11-26_final
2023-11-30 11:17:32	ga_ls8c_ard_3-2-1_109083_2023-11-30_final
2023-12-05 11:35:35	ga_ls8c_ard_3-2-1_112082_2023-12-05_final
2023-12-07 09:45:30	ga_ls8c_ard_3-2-1_094085_2023-12-07_final
2023-12-09 09:31:58	ga_ls8c_ard_3-2-1_092082_2023-12-09_final
2023-12-12 09:59:19	ga_ls8c_ard_3-2-1_097073_2023-12-12_final
2023-12-12 11:40:12	ga_ls8c_ard_3-2-1_113078_2023-12-12_final
2023-12-13 10:44:35	ga_ls8c_ard_3-2-1_104078_2023-12-13_final
2023-12-16 11:12:43	ga_ls8c_ard_3-2-1_109071_2023-12-16_final
2023-12-24 10:22:54	ga_ls8c_ard_3-2-1_101070_2023-12-24_final
2023-12-24 10:27:17	ga_ls8c_ard_3-2-1_101081_2023-12-24_final
2023-12-25 11:05:45	ga_ls8c_ard_3-2-1_108069_2023-12-25_final
2023-12-26 10:14:55	ga_ls8c_ard_3-2-1_099081_2023-12-26_final
2023-12-30 09:50:33	ga_ls8c_ard_3-2-1_095082_2023-12-30_final
2024-01-04 10:05:25	ga_ls8c_ard_3-2-1_098073_2024-01-04_final
2024-01-06 09:53:27	ga_ls8c_ard_3-2-1_096074_2024-01-06_final
2024-01-06 09:55:51	ga_ls8c_ard_3-2-1_096080_2024-01-06_final
2024-01-07 10:37:32	ga_ls8c_ard_3-2-1_103076_2024-01-07_final
2024-01-13 09:59:17	ga_ls8c_ard_3-2-1_097073_2024-01-13_final
2024-01-13 10:01:41	ga_ls8c_ard_3-2-1_097079_2024-01-13_final
2024-01-13 10:02:05	ga_ls8c_ard_3-2-1_097080_2024-01-13_final
2024-01-15 09:48:08	ga_ls8c_ard_3-2-1_095076_2024-01-15_final
2024-01-17 11:15:02	ga_ls8c_ard_3-2-1_109077_2024-01-17_final
2024-01-25 10:27:30	ga_ls8c_ard_3-2-1_101082_2024-01-25_final
2024-01-25 10:27:30	ga_ls8c_ard_3-2-1_101082_2024-01-25_nrt
2024-01-26 11:07:09	ga_ls8c_ard_3-2-1_108073_2024-01-26_final
2024-01-28 09:18:42	ga_ls8c_ard_3-2-1_090080_2024-01-27_final
2024-02-01 10:29:44	ga_ls8c_ard_3-2-1_102072_2024-02-01_final
2024-02-05 10:06:14	ga_ls8c_ard_3-2-1_098075_2024-02-05_final
2024-02-06 10:48:18	ga_ls8c_ard_3-2-1_105072_2024-02-06_final
2024-02-09 09:41:55	ga_ls8c_ard_3-2-1_094076_2024-02-09_final
2024-02-12 10:16:24	ga_ls8c_ard_3-2-1_099085_2024-02-12_final
2024-02-16 09:51:15	ga_ls8c_ard_3-2-1_095084_2024-02-16_final
2024-02-24 10:37:53	ga_ls8c_ard_3-2-1_103077_2024-02-24_final
2024-02-29 09:19:29	ga_ls8c_ard_3-2-1_090082_2024-02-28_final
2024-03-01 11:38:49	ga_ls8c_ard_3-2-1_113075_2024-03-01_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years