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
2023-08-28 09:24:29	ga_ls8c_ard_3-2-1_091079_2023-08-27_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-29 10:06:32	ga_ls8c_ard_3-2-1_098076_2023-08-29_final
2023-08-29 10:06:56	ga_ls8c_ard_3-2-1_098077_2023-08-29_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-08-30 10:52:12	ga_ls8c_ard_3-2-1_105082_2023-08-30_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-02 11:18:18	ga_ls8c_ard_3-2-1_110070_2023-09-02_final
2023-09-02 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-09-02_final
2023-09-03 10:26:16	ga_ls8c_ard_3-2-1_101079_2023-09-03_final
2023-09-04 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-09-04_final
2023-09-04 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-09-04_final
2023-09-04 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-09-04_final
2023-09-05 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-09-05_final
2023-09-06 09:19:27	ga_ls8c_ard_3-2-1_090082_2023-09-05_final
2023-09-06 10:53:09	ga_ls8c_ard_3-2-1_106069_2023-09-06_final
2023-09-06 10:55:33	ga_ls8c_ard_3-2-1_106075_2023-09-06_final
2023-09-07 09:57:08	ga_ls8c_ard_3-2-1_097068_2023-09-07_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-09-09 09:47:36	ga_ls8c_ard_3-2-1_095075_2023-09-09_final
2023-09-10 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-09-10_final
2023-09-11 11:11:45	ga_ls8c_ard_3-2-1_109069_2023-09-11_final
2023-09-12 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-09-12_final
2023-09-15 10:46:40	ga_ls8c_ard_3-2-1_105068_2023-09-15_final
2023-09-19 10:26:21	ga_ls8c_ard_3-2-1_101079_2023-09-19_final
2023-09-20 11:05:37	ga_ls8c_ard_3-2-1_108069_2023-09-20_final
2023-09-22 10:53:39	ga_ls8c_ard_3-2-1_106070_2023-09-22_final
2023-09-23 11:38:31	ga_ls8c_ard_3-2-1_113074_2023-09-23_final
2023-09-23 11:39:43	ga_ls8c_ard_3-2-1_113077_2023-09-23_final
2023-09-23 11:40:31	ga_ls8c_ard_3-2-1_113079_2023-09-23_final
2023-09-25 09:47:18	ga_ls8c_ard_3-2-1_095074_2023-09-25_final
2023-09-25 09:47:42	ga_ls8c_ard_3-2-1_095075_2023-09-25_final
2023-09-25 09:49:17	ga_ls8c_ard_3-2-1_095079_2023-09-25_final
2023-09-25 09:49:41	ga_ls8c_ard_3-2-1_095080_2023-09-25_final
2023-09-25 11:28:58	ga_ls8c_ard_3-2-1_111081_2023-09-25_final
2023-09-25 11:29:22	ga_ls8c_ard_3-2-1_111082_2023-09-25_final
2023-09-27 09:39:44	ga_ls8c_ard_3-2-1_093086_2023-09-27_final
2023-09-28 10:17:25	ga_ls8c_ard_3-2-1_100072_2023-09-28_final
2023-09-29 11:03:29	ga_ls8c_ard_3-2-1_107079_2023-09-29_final
2023-09-30 10:07:04	ga_ls8c_ard_3-2-1_098077_2023-09-30_final
2023-09-30 10:07:52	ga_ls8c_ard_3-2-1_098079_2023-09-30_final
2023-10-01 10:52:19	ga_ls8c_ard_3-2-1_105082_2023-10-01_final
2023-10-02 09:53:30	ga_ls8c_ard_3-2-1_096074_2023-10-02_final
2023-10-02 09:57:06	ga_ls8c_ard_3-2-1_096083_2023-10-02_final
2023-10-02 11:35:11	ga_ls8c_ard_3-2-1_112081_2023-10-02_final
2023-10-04 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-10-04_final
2023-10-05 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-10-05_final
2023-10-08 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-10-07_final
2023-10-08 09:19:38	ga_ls8c_ard_3-2-1_090082_2023-10-07_final
2023-10-08 10:52:56	ga_ls8c_ard_3-2-1_106068_2023-10-08_final
2023-10-09 09:58:55	ga_ls8c_ard_3-2-1_097072_2023-10-09_final
2023-10-09 10:00:30	ga_ls8c_ard_3-2-1_097076_2023-10-09_final
2023-10-10 10:43:23	ga_ls8c_ard_3-2-1_104075_2023-10-10_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-12 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-10-12_final
2023-10-13 11:11:54	ga_ls8c_ard_3-2-1_109069_2023-10-13_final
2023-10-14 11:58:45	ga_ls8c_ard_3-2-1_116078_2023-10-14_final
2023-10-15 11:00:20	ga_ls8c_ard_3-2-1_107071_2023-10-15_final
2023-10-16 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-10-16_final
2023-10-17 09:14:40	ga_ls8c_ard_3-2-1_089085_2023-10-16_final
2023-10-17 10:47:58	ga_ls8c_ard_3-2-1_105071_2023-10-17_final
2023-10-19 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-10-19_final
2023-10-20 09:44:45	ga_ls8c_ard_3-2-1_094083_2023-10-20_final
2023-10-20 11:22:26	ga_ls8c_ard_3-2-1_110080_2023-10-20_final
2023-10-21 10:27:37	ga_ls8c_ard_3-2-1_101082_2023-10-21_final
2023-10-22 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-10-22_final
2023-10-23 11:53:23	ga_ls8c_ard_3-2-1_115080_2023-10-23_final
2023-10-24 09:19:41	ga_ls8c_ard_3-2-1_090082_2023-10-23_final
2023-10-24 10:56:58	ga_ls8c_ard_3-2-1_106078_2023-10-24_final
2023-10-25 09:58:57	ga_ls8c_ard_3-2-1_097072_2023-10-25_final
2023-10-25 11:40:38	ga_ls8c_ard_3-2-1_113079_2023-10-25_final
2023-10-27 11:29:29	ga_ls8c_ard_3-2-1_111082_2023-10-27_final
2023-10-29 09:38:39	ga_ls8c_ard_3-2-1_093083_2023-10-29_final
2023-10-29 11:11:57	ga_ls8c_ard_3-2-1_109069_2023-10-29_final
2023-10-30 10:17:31	ga_ls8c_ard_3-2-1_100072_2023-10-30_final
2023-11-01 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-11-01_final
2023-11-02 09:13:56	ga_ls8c_ard_3-2-1_089083_2023-11-01_final
2023-11-02 10:46:49	ga_ls8c_ard_3-2-1_105068_2023-11-02_final
2023-11-02 10:48:01	ga_ls8c_ard_3-2-1_105071_2023-11-02_final
2023-11-03 09:57:11	ga_ls8c_ard_3-2-1_096083_2023-11-03_final
2023-11-04 10:35:39	ga_ls8c_ard_3-2-1_103071_2023-11-04_final
2023-11-05 11:22:30	ga_ls8c_ard_3-2-1_110080_2023-11-05_final
2023-11-06 10:23:16	ga_ls8c_ard_3-2-1_101071_2023-11-06_final
2023-11-06 10:26:04	ga_ls8c_ard_3-2-1_101078_2023-11-06_final
2023-11-06 10:26:28	ga_ls8c_ard_3-2-1_101079_2023-11-06_final
2023-11-07 09:29:14	ga_ls8c_ard_3-2-1_092075_2023-11-06_final
2023-11-08 10:12:28	ga_ls8c_ard_3-2-1_099075_2023-11-08_final
2023-11-09 10:54:07	ga_ls8c_ard_3-2-1_106071_2023-11-09_final
2023-11-10 10:00:53	ga_ls8c_ard_3-2-1_097077_2023-11-10_final
2023-11-10 11:40:34	ga_ls8c_ard_3-2-1_113079_2023-11-10_final
2023-11-10 11:41:46	ga_ls8c_ard_3-2-1_113082_2023-11-10_final
2023-11-10 11:42:09	ga_ls8c_ard_3-2-1_113083_2023-11-10_final
2023-11-12 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-11-12_final
2023-11-16 11:00:46	ga_ls8c_ard_3-2-1_107072_2023-11-16_final
2023-11-17 10:06:21	ga_ls8c_ard_3-2-1_098075_2023-11-17_final
2023-11-17 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-11-17_final
2023-11-18 09:14:44	ga_ls8c_ard_3-2-1_089085_2023-11-17_final
2023-11-18 09:16:20	ga_ls8c_ard_3-2-1_089089_2023-11-17_final
2023-11-20 10:37:41	ga_ls8c_ard_3-2-1_103076_2023-11-20_final
2023-11-21 09:46:03	ga_ls8c_ard_3-2-1_094086_2023-11-21_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