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
2022-09-21 10:41:53	ga_ls8c_ard_3-2-1_104070_2022-09-21_final
2022-09-22 09:47:51	ga_ls8c_ard_3-2-1_095074_2022-09-22_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-10 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-10-10_final
2022-10-12 09:26:35	ga_ls8c_ard_3-2-1_091083_2022-10-11_final
2022-10-13 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-10-13_final
2022-10-16 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-10-16_final
2022-10-17 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-10-17_final
2022-10-20 11:51:23	ga_ls8c_ard_3-2-1_115074_2022-10-20_final
2022-10-22 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-22_final
2022-10-24 09:47:48	ga_ls8c_ard_3-2-1_095074_2022-10-24_final
2022-10-27 10:21:31	ga_ls8c_ard_3-2-1_100081_2022-10-27_final
2022-10-29 10:08:46	ga_ls8c_ard_3-2-1_098080_2022-10-29_final
2022-11-02 09:44:04	ga_ls8c_ard_3-2-1_094080_2022-11-02_final
2022-11-02 11:23:45	ga_ls8c_ard_3-2-1_110082_2022-11-02_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-11-06 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-11-05_final
2022-11-06 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-11-06_final
2022-11-09 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-11-09_final
2022-11-14 10:04:19	ga_ls8c_ard_3-2-1_098069_2022-11-14_final
2022-11-17 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-11-17_final
2022-11-19 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-11-19_final
2022-11-22 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-11-21_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-23 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-11-23_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-11-28 11:58:21	ga_ls8c_ard_3-2-1_116076_2022-11-28_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-10 10:41:46	ga_ls8c_ard_3-2-1_104070_2022-12-10_final
2022-12-14 10:21:48	ga_ls8c_ard_3-2-1_100082_2022-12-14_final
2022-12-15 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-12-14_final
2022-12-16 10:04:37	ga_ls8c_ard_3-2-1_098070_2022-12-16_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2022-12-29 09:39:15	ga_ls8c_ard_3-2-1_093084_2022-12-29_final
2022-12-29 11:17:20	ga_ls8c_ard_3-2-1_109082_2022-12-29_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-01 11:45:27	ga_ls8c_ard_3-2-1_114075_2023-01-01_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-15 10:21:13	ga_ls8c_ard_3-2-1_100081_2023-01-15_final
2023-01-15 11:58:06	ga_ls8c_ard_3-2-1_116076_2023-01-15_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-21 09:44:56	ga_ls8c_ard_3-2-1_094083_2023-01-21_final
2023-01-22 10:23:49	ga_ls8c_ard_3-2-1_101072_2023-01-22_final
2023-01-22 10:27:25	ga_ls8c_ard_3-2-1_101081_2023-01-22_final
2023-01-24 10:11:53	ga_ls8c_ard_3-2-1_099073_2023-01-24_final
2023-01-24 11:51:10	ga_ls8c_ard_3-2-1_115074_2023-01-24_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-02-05 10:37:01	ga_ls8c_ard_3-2-1_103074_2023-02-05_final
2023-02-08 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-02-08_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-13 11:30:22	ga_ls8c_ard_3-2-1_111084_2023-02-13_final
2023-02-15 11:13:12	ga_ls8c_ard_3-2-1_109072_2023-02-15_final
2023-02-21 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-02-21_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-02-24 09:29:32	ga_ls8c_ard_3-2-1_092076_2023-02-23_final
2023-02-24 11:10:49	ga_ls8c_ard_3-2-1_108082_2023-02-24_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-03-03 09:35:17	ga_ls8c_ard_3-2-1_093075_2023-03-03_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-07 09:14:55	ga_ls8c_ard_3-2-1_089086_2023-03-06_final
2023-03-09 10:36:37	ga_ls8c_ard_3-2-1_103074_2023-03-09_final
2023-03-10 11:23:28	ga_ls8c_ard_3-2-1_110083_2023-03-10_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-12 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-03-12_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
2023-03-15 11:41:12	ga_ls8c_ard_3-2-1_113081_2023-03-15_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-03-15_final
2023-03-22 10:06:48	ga_ls8c_ard_3-2-1_098077_2023-03-22_final
2023-03-23 09:13:33	ga_ls8c_ard_3-2-1_089083_2023-03-22_final
2023-03-28 11:10:33	ga_ls8c_ard_3-2-1_108082_2023-03-28_final
2023-03-31 09:57:21	ga_ls8c_ard_3-2-1_097069_2023-03-31_final
2023-04-04 11:13:03	ga_ls8c_ard_3-2-1_109073_2023-04-04_final
2023-04-06 10:59:51	ga_ls8c_ard_3-2-1_107071_2023-04-06_final
2023-04-07 10:07:48	ga_ls8c_ard_3-2-1_098080_2023-04-07_final
2023-04-11 09:43:46	ga_ls8c_ard_3-2-1_094082_2023-04-11_final
2023-04-12 10:26:38	ga_ls8c_ard_3-2-1_101081_2023-04-12_final
2023-04-13 09:33:01	ga_ls8c_ard_3-2-1_092086_2023-04-13_final
2023-04-15 09:20:38	ga_ls8c_ard_3-2-1_090086_2023-04-14_final
2023-04-16 11:40:23	ga_ls8c_ard_3-2-1_113080_2023-04-16_final
2023-04-19 10:30:23	ga_ls8c_ard_3-2-1_102075_2023-04-19_final
2023-05-01 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-04-30_final
2023-05-08 09:25:27	ga_ls8c_ard_3-2-1_091083_2023-05-07_final
2023-05-14 10:23:34	ga_ls8c_ard_3-2-1_101074_2023-05-14_final
2023-05-15 09:31:08	ga_ls8c_ard_3-2-1_092082_2023-05-15_final
2023-05-17 09:18:21	ga_ls8c_ard_3-2-1_090081_2023-05-16_final
2023-05-18 11:40:06	ga_ls8c_ard_3-2-1_113080_2023-05-18_final
2023-05-20 09:46:53	ga_ls8c_ard_3-2-1_095075_2023-05-20_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