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
2023-07-20 09:19:11	ga_ls8c_ard_3-2-1_090082_2023-07-19_final
2023-07-21 09:58:28	ga_ls8c_ard_3-2-1_097072_2023-07-21_final
2023-07-21 11:39:21	ga_ls8c_ard_3-2-1_113077_2023-07-21_final
2023-07-30 09:52:48	ga_ls8c_ard_3-2-1_096073_2023-07-30_final
2023-07-31 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-07-31_final
2023-08-03 11:06:12	ga_ls8c_ard_3-2-1_108071_2023-08-03_final
2023-08-05 10:54:39	ga_ls8c_ard_3-2-1_106073_2023-08-05_final
2023-08-06 09:58:37	ga_ls8c_ard_3-2-1_097072_2023-08-06_final
2023-08-06 10:01:01	ga_ls8c_ard_3-2-1_097078_2023-08-06_final
2023-08-09 10:29:07	ga_ls8c_ard_3-2-1_102071_2023-08-09_final
2023-08-10 11:13:11	ga_ls8c_ard_3-2-1_109073_2023-08-10_final
2023-08-11 10:17:57	ga_ls8c_ard_3-2-1_100074_2023-08-11_final
2023-08-12 09:25:56	ga_ls8c_ard_3-2-1_091083_2023-08-11_final
2023-08-12 09:26:44	ga_ls8c_ard_3-2-1_091085_2023-08-11_final
2023-08-13 10:04:50	ga_ls8c_ard_3-2-1_098072_2023-08-13_final
2023-08-13 11:46:07	ga_ls8c_ard_3-2-1_114078_2023-08-13_final
2023-08-14 09:12:49	ga_ls8c_ard_3-2-1_089081_2023-08-13_final
2023-08-14 09:16:00	ga_ls8c_ard_3-2-1_089089_2023-08-13_final
2023-08-14 10:47:18	ga_ls8c_ard_3-2-1_105070_2023-08-14_final
2023-08-14 10:47:42	ga_ls8c_ard_3-2-1_105071_2023-08-14_final
2023-08-15 09:53:18	ga_ls8c_ard_3-2-1_096074_2023-08-15_final
2023-08-16 10:39:46	ga_ls8c_ard_3-2-1_103082_2023-08-16_final
2023-08-18 10:27:02	ga_ls8c_ard_3-2-1_101081_2023-08-18_final
2023-08-19 11:11:06	ga_ls8c_ard_3-2-1_108083_2023-08-19_final
2023-08-21 10:54:22	ga_ls8c_ard_3-2-1_106072_2023-08-21_final
2023-08-21 10:55:10	ga_ls8c_ard_3-2-1_106074_2023-08-21_final
2023-08-21 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-08-21_final
2023-08-22 11:38:26	ga_ls8c_ard_3-2-1_113074_2023-08-22_final
2023-08-22 11:39:38	ga_ls8c_ard_3-2-1_113077_2023-08-22_final
2023-08-25 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-08-25_final
2023-08-25 10:30:04	ga_ls8c_ard_3-2-1_102073_2023-08-25_final
2023-08-28 09:28:28	ga_ls8c_ard_3-2-1_091089_2023-08-27_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-09-05 10:12:41	ga_ls8c_ard_3-2-1_099076_2023-09-05_final
2023-09-07 09:58:44	ga_ls8c_ard_3-2-1_097072_2023-09-07_final
2023-09-09 09:47:59	ga_ls8c_ard_3-2-1_095076_2023-09-09_final
2023-09-09 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-09-09_final
2023-09-10 10:31:40	ga_ls8c_ard_3-2-1_102077_2023-09-10_final
2023-09-11 11:11:45	ga_ls8c_ard_3-2-1_109069_2023-09-11_final
2023-09-11 11:12:57	ga_ls8c_ard_3-2-1_109072_2023-09-11_final
2023-09-12 10:16:56	ga_ls8c_ard_3-2-1_100071_2023-09-12_final
2023-09-15 10:47:52	ga_ls8c_ard_3-2-1_105071_2023-09-15_final
2023-09-18 09:45:29	ga_ls8c_ard_3-2-1_094085_2023-09-18_final
2023-09-18 11:23:58	ga_ls8c_ard_3-2-1_110084_2023-09-18_final
2023-09-22 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-09-21_final
2023-09-22 10:54:51	ga_ls8c_ard_3-2-1_106073_2023-09-22_final
2023-09-22 10:56:03	ga_ls8c_ard_3-2-1_106076_2023-09-22_final
2023-09-23 09:59:14	ga_ls8c_ard_3-2-1_097073_2023-09-23_final
2023-09-23 10:01:14	ga_ls8c_ard_3-2-1_097078_2023-09-23_final
2023-09-27 09:34:57	ga_ls8c_ard_3-2-1_093074_2023-09-27_final
2023-09-29 09:23:24	ga_ls8c_ard_3-2-1_091076_2023-09-28_final
2023-09-29 11:00:41	ga_ls8c_ard_3-2-1_107072_2023-09-29_final
2023-09-30 10:08:40	ga_ls8c_ard_3-2-1_098081_2023-09-30_final
2023-09-30 11:45:09	ga_ls8c_ard_3-2-1_114075_2023-09-30_final
2023-10-01 09:13:50	ga_ls8c_ard_3-2-1_089083_2023-09-30_final
2023-10-01 10:47:32	ga_ls8c_ard_3-2-1_105070_2023-10-01_final
2023-10-02 09:53:06	ga_ls8c_ard_3-2-1_096073_2023-10-02_final
2023-10-04 09:42:44	ga_ls8c_ard_3-2-1_094078_2023-10-04_final
2023-10-05 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-10-05_final
2023-10-06 09:31:58	ga_ls8c_ard_3-2-1_092082_2023-10-06_final
2023-10-06 09:35:09	ga_ls8c_ard_3-2-1_092090_2023-10-06_final
2023-10-07 10:15:38	ga_ls8c_ard_3-2-1_099083_2023-10-07_final
2023-10-08 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-10-07_final
2023-10-08 10:53:20	ga_ls8c_ard_3-2-1_106069_2023-10-08_final
2023-10-08 10:56:55	ga_ls8c_ard_3-2-1_106078_2023-10-08_final
2023-10-09 09:58:31	ga_ls8c_ard_3-2-1_097071_2023-10-09_final
2023-10-09 09:59:19	ga_ls8c_ard_3-2-1_097073_2023-10-09_final
2023-10-09 09:59:43	ga_ls8c_ard_3-2-1_097074_2023-10-09_final
2023-10-10 09:06:53	ga_ls8c_ard_3-2-1_088081_2023-10-09_final
2023-10-10 10:42:11	ga_ls8c_ard_3-2-1_104072_2023-10-10_final
2023-10-13 09:33:49	ga_ls8c_ard_3-2-1_093071_2023-10-13_final
2023-10-16 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-10-16_final
2023-10-16 10:06:18	ga_ls8c_ard_3-2-1_098075_2023-10-16_final
2023-10-20 09:41:09	ga_ls8c_ard_3-2-1_094074_2023-10-20_final
2023-10-21 10:26:02	ga_ls8c_ard_3-2-1_101078_2023-10-21_final
2023-10-21 10:26:26	ga_ls8c_ard_3-2-1_101079_2023-10-21_final
2023-10-23 10:12:30	ga_ls8c_ard_3-2-1_099075_2023-10-23_final
2023-10-24 09:19:17	ga_ls8c_ard_3-2-1_090081_2023-10-23_final
2023-10-25 11:40:38	ga_ls8c_ard_3-2-1_113079_2023-10-25_final
2023-10-26 10:43:25	ga_ls8c_ard_3-2-1_104075_2023-10-26_final
2023-10-29 09:38:39	ga_ls8c_ard_3-2-1_093083_2023-10-29_final
2023-10-30 10:21:31	ga_ls8c_ard_3-2-1_100082_2023-10-30_final
2023-11-01 11:44:51	ga_ls8c_ard_3-2-1_114074_2023-11-01_final
2023-11-02 10:48:25	ga_ls8c_ard_3-2-1_105072_2023-11-02_final
2023-11-02 10:50:01	ga_ls8c_ard_3-2-1_105076_2023-11-02_final
2023-11-03 09:53:35	ga_ls8c_ard_3-2-1_096074_2023-11-03_final
2023-11-03 11:35:16	ga_ls8c_ard_3-2-1_112081_2023-11-03_final
2023-11-03 11:35:40	ga_ls8c_ard_3-2-1_112082_2023-11-03_final
2023-11-05 11:22:54	ga_ls8c_ard_3-2-1_110081_2023-11-05_final
2023-11-06 10:22:52	ga_ls8c_ard_3-2-1_101070_2023-11-06_final
2023-11-09 10:54:55	ga_ls8c_ard_3-2-1_106073_2023-11-09_final
2023-11-09 10:57:19	ga_ls8c_ard_3-2-1_106079_2023-11-09_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-10 11:40:34	ga_ls8c_ard_3-2-1_113079_2023-11-10_final
2023-11-10 11:40:58	ga_ls8c_ard_3-2-1_113080_2023-11-10_final
2023-11-11 09:07:16	ga_ls8c_ard_3-2-1_088082_2023-11-10_final
2023-11-13 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-11-13_final
2023-11-15 10:18:18	ga_ls8c_ard_3-2-1_100074_2023-11-15_final
2023-11-17 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-11-17_final
2023-11-18 09:14:20	ga_ls8c_ard_3-2-1_089084_2023-11-17_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