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
2022-03-27 09:20:52	ga_ls8c_ard_3-2-1_090086_2022-03-26_final
2022-04-12 09:20:55	ga_ls8c_ard_3-2-1_090086_2022-04-11_final
2022-04-16 10:32:42	ga_ls8c_ard_3-2-1_102080_2022-04-16_final
2022-05-12 11:07:03	ga_ls8c_ard_3-2-1_108073_2022-05-12_final
2022-05-23 09:10:04	ga_ls8c_ard_3-2-1_089074_2022-05-22_final
2022-05-28 11:06:16	ga_ls8c_ard_3-2-1_108071_2022-05-28_final
2022-05-30 10:57:32	ga_ls8c_ard_3-2-1_106080_2022-05-30_final
2022-06-13 09:29:13	ga_ls8c_ard_3-2-1_092075_2022-06-12_final
2022-06-16 09:58:09	ga_ls8c_ard_3-2-1_097070_2022-06-16_final
2022-06-17 09:06:55	ga_ls8c_ard_3-2-1_088081_2022-06-16_final
2022-06-18 11:25:53	ga_ls8c_ard_3-2-1_111073_2022-06-18_final
2022-06-30 10:15:45	ga_ls8c_ard_3-2-1_099083_2022-06-30_final
2022-06-30 11:53:27	ga_ls8c_ard_3-2-1_115080_2022-06-30_final
2022-07-05 10:29:07	ga_ls8c_ard_3-2-1_102070_2022-07-05_final
2022-07-08 11:01:36	ga_ls8c_ard_3-2-1_107074_2022-07-08_final
2022-07-13 11:19:20	ga_ls8c_ard_3-2-1_110072_2022-07-13_final
2022-07-13 11:19:44	ga_ls8c_ard_3-2-1_110073_2022-07-13_final
2022-07-18 09:57:49	ga_ls8c_ard_3-2-1_097069_2022-07-18_final
2022-07-19 10:41:30	ga_ls8c_ard_3-2-1_104070_2022-07-19_final
2022-08-04 09:06:47	ga_ls8c_ard_3-2-1_088080_2022-08-03_final
2022-08-17 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-08-17_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-16 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-09-16_final
2022-09-24 09:34:18	ga_ls8c_ard_3-2-1_093071_2022-09-24_final
2022-10-04 10:15:44	ga_ls8c_ard_3-2-1_099082_2022-10-04_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-14 09:17:00	ga_ls8c_ard_3-2-1_089090_2022-10-13_final
2022-10-15 09:56:41	ga_ls8c_ard_3-2-1_096081_2022-10-15_final
2022-10-20 11:53:22	ga_ls8c_ard_3-2-1_115079_2022-10-20_final
2022-10-22 09:58:57	ga_ls8c_ard_3-2-1_097071_2022-10-22_final
2022-10-24 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-10-24_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-02 09:41:40	ga_ls8c_ard_3-2-1_094074_2022-11-02_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-27 09:38:12	ga_ls8c_ard_3-2-1_093081_2022-11-27_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-12 10:34:10	ga_ls8c_ard_3-2-1_102082_2022-12-12_final
2022-12-13 11:13:02	ga_ls8c_ard_3-2-1_109071_2022-12-13_final
2022-12-15 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-12-14_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-20 09:46:14	ga_ls8c_ard_3-2-1_094086_2022-12-20_final
2022-12-24 10:59:09	ga_ls8c_ard_3-2-1_106083_2022-12-24_final
2023-01-02 10:48:37	ga_ls8c_ard_3-2-1_105072_2023-01-02_final
2023-01-11 10:43:12	ga_ls8c_ard_3-2-1_104074_2023-01-11_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-24 10:14:40	ga_ls8c_ard_3-2-1_099080_2023-01-24_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-09 11:53:33	ga_ls8c_ard_3-2-1_115080_2023-02-09_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-20 09:57:33	ga_ls8c_ard_3-2-1_096084_2023-02-20_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-02-25 11:53:15	ga_ls8c_ard_3-2-1_115080_2023-02-25_final
2023-03-03 09:39:17	ga_ls8c_ard_3-2-1_093085_2023-03-03_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-03-10 09:40:36	ga_ls8c_ard_3-2-1_094073_2023-03-10_final
2023-03-12 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-03-12_final
2023-03-27 10:22:55	ga_ls8c_ard_3-2-1_101071_2023-03-27_final
2023-04-07 10:03:00	ga_ls8c_ard_3-2-1_098068_2023-04-07_final
2023-04-16 10:03:06	ga_ls8c_ard_3-2-1_097084_2023-04-16_final
2023-04-20 09:39:32	ga_ls8c_ard_3-2-1_093087_2023-04-20_final
2023-04-27 09:45:19	ga_ls8c_ard_3-2-1_094086_2023-04-27_final
2023-04-30 10:10:37	ga_ls8c_ard_3-2-1_099072_2023-04-30_final
2023-05-09 10:09:29	ga_ls8c_ard_3-2-1_098085_2023-05-09_final
2023-05-13 11:18:24	ga_ls8c_ard_3-2-1_110072_2023-05-13_final
2023-05-16 11:52:04	ga_ls8c_ard_3-2-1_115079_2023-05-16_final
2023-05-18 11:40:30	ga_ls8c_ard_3-2-1_113081_2023-05-18_final
2023-05-19 09:06:00	ga_ls8c_ard_3-2-1_088081_2023-05-18_final
2023-05-24 09:21:23	ga_ls8c_ard_3-2-1_091073_2023-05-23_final
2023-06-05 11:24:39	ga_ls8c_ard_3-2-1_111072_2023-06-05_final
2023-06-08 11:57:11	ga_ls8c_ard_3-2-1_116076_2023-06-08_final
2023-06-09 11:01:34	ga_ls8c_ard_3-2-1_107076_2023-06-09_final
2023-06-12 11:34:54	ga_ls8c_ard_3-2-1_112082_2023-06-12_final
2023-06-25 10:59:41	ga_ls8c_ard_3-2-1_107071_2023-06-25_final
2023-06-26 10:08:04	ga_ls8c_ard_3-2-1_098081_2023-06-26_final
2023-07-24 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-07-24_final
2023-07-25 09:39:24	ga_ls8c_ard_3-2-1_093086_2023-07-25_final
2023-08-03 09:33:18	ga_ls8c_ard_3-2-1_092086_2023-08-03_final
2023-08-03 11:07:00	ga_ls8c_ard_3-2-1_108073_2023-08-03_final
2023-08-11 10:21:33	ga_ls8c_ard_3-2-1_100083_2023-08-11_final
2023-08-19 11:07:06	ga_ls8c_ard_3-2-1_108073_2023-08-19_final
2023-08-29 10:03:45	ga_ls8c_ard_3-2-1_098069_2023-08-29_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_final
2023-09-07 10:01:07	ga_ls8c_ard_3-2-1_097078_2023-09-07_final
2023-09-14 10:03:48	ga_ls8c_ard_3-2-1_098069_2023-09-14_final
2023-09-20 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-09-19_final
2023-10-07 10:16:02	ga_ls8c_ard_3-2-1_099084_2023-10-07_final
2023-10-16 10:03:54	ga_ls8c_ard_3-2-1_098069_2023-10-16_final
2023-10-17 10:48:46	ga_ls8c_ard_3-2-1_105073_2023-10-17_final
2023-10-20 09:45:33	ga_ls8c_ard_3-2-1_094085_2023-10-20_final
2023-10-20 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-10-20_final
2023-10-22 09:34:25	ga_ls8c_ard_3-2-1_092088_2023-10-22_final
2023-10-24 10:54:58	ga_ls8c_ard_3-2-1_106073_2023-10-24_final
2023-10-27 09:52:12	ga_ls8c_ard_3-2-1_095086_2023-10-27_final
2023-11-13 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-11-13_final
2023-11-23 09:32:54	ga_ls8c_ard_3-2-1_092084_2023-11-23_final
2023-11-23 11:06:12	ga_ls8c_ard_3-2-1_108070_2023-11-23_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