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
2021-10-05 11:23:40	ga_ls8c_ard_3-2-0_111067_2021-10-05_final
2021-10-05 11:25:40	ga_ls8c_ard_3-2-0_111072_2021-10-05_final
2021-12-23 10:44:44	ga_ls8c_ard_3-2-1_104078_2021-12-23_final
2021-12-31 09:52:02	ga_ls8c_ard_3-2-1_096070_2021-12-31_final
2022-01-02 11:20:09	ga_ls8c_ard_3-2-1_110074_2022-01-02_final
2022-01-07 09:58:13	ga_ls8c_ard_3-2-1_097070_2022-01-07_final
2022-01-15 09:13:32	ga_ls8c_ard_3-2-1_089082_2022-01-14_final
2022-01-19 10:25:41	ga_ls8c_ard_3-2-1_101077_2022-01-19_final
2022-01-31 09:13:27	ga_ls8c_ard_3-2-1_089082_2022-01-30_final
2022-02-04 10:24:25	ga_ls8c_ard_3-2-1_101074_2022-02-04_final
2022-02-06 10:14:27	ga_ls8c_ard_3-2-1_099080_2022-02-06_final
2022-02-08 10:03:40	ga_ls8c_ard_3-2-1_097084_2022-02-08_final
2022-02-16 09:12:59	ga_ls8c_ard_3-2-1_089081_2022-02-15_final
2022-02-16 10:49:04	ga_ls8c_ard_3-2-1_105074_2022-02-16_final
2022-02-18 10:35:54	ga_ls8c_ard_3-2-1_103072_2022-02-18_final
2022-02-26 11:26:07	ga_ls8c_ard_3-2-1_111074_2022-02-26_final
2022-03-04 09:12:55	ga_ls8c_ard_3-2-1_089081_2022-03-03_final
2022-03-10 10:14:18	ga_ls8c_ard_3-2-1_099080_2022-03-10_final
2022-03-30 09:46:32	ga_ls8c_ard_3-2-1_095073_2022-03-30_final
2022-04-08 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-08_final
2022-04-11 11:53:01	ga_ls8c_ard_3-2-1_115080_2022-04-11_final
2022-04-12 09:20:31	ga_ls8c_ard_3-2-1_090085_2022-04-11_final
2022-04-12 10:58:36	ga_ls8c_ard_3-2-1_106083_2022-04-12_final
2022-04-13 09:57:00	ga_ls8c_ard_3-2-1_097068_2022-04-13_final
2022-04-20 10:03:10	ga_ls8c_ard_3-2-1_098068_2022-04-20_final
2022-04-27 11:52:34	ga_ls8c_ard_3-2-1_115079_2022-04-27_final
2022-04-29 09:56:31	ga_ls8c_ard_3-2-1_097067_2022-04-29_final
2022-05-13 10:13:50	ga_ls8c_ard_3-2-1_099079_2022-05-13_final
2022-05-22 10:07:17	ga_ls8c_ard_3-2-1_098078_2022-05-22_final
2022-05-24 09:57:19	ga_ls8c_ard_3-2-1_096084_2022-05-24_final
2022-05-28 11:08:16	ga_ls8c_ard_3-2-1_108076_2022-05-28_final
2022-05-29 10:10:40	ga_ls8c_ard_3-2-1_099071_2022-05-29_final
2022-06-02 11:24:54	ga_ls8c_ard_3-2-1_111071_2022-06-02_final
2022-06-04 09:40:04	ga_ls8c_ard_3-2-1_093087_2022-06-04_final
2022-06-07 10:07:49	ga_ls8c_ard_3-2-1_098079_2022-06-07_final
2022-06-09 09:57:53	ga_ls8c_ard_3-2-1_096085_2022-06-09_final
2022-06-30 10:14:34	ga_ls8c_ard_3-2-1_099080_2022-06-30_final
2022-07-05 10:28:43	ga_ls8c_ard_3-2-1_102069_2022-07-05_final
2022-07-12 10:39:40	ga_ls8c_ard_3-2-1_103081_2022-07-12_final
2022-07-15 09:33:40	ga_ls8c_ard_3-2-1_092086_2022-07-15_final
2022-07-15 11:11:21	ga_ls8c_ard_3-2-1_108083_2022-07-15_final
2022-07-20 09:52:40	ga_ls8c_ard_3-2-1_095087_2022-07-20_final
2022-08-07 09:34:55	ga_ls8c_ard_3-2-1_093073_2022-08-07_final
2022-08-21 11:25:25	ga_ls8c_ard_3-2-1_111071_2022-08-21_final
2022-08-26 10:05:05	ga_ls8c_ard_3-2-1_098071_2022-08-26_final
2022-08-26 10:07:29	ga_ls8c_ard_3-2-1_098077_2022-08-26_final
2022-09-04 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-09-04_final
2022-09-09 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-09-09_final
2022-09-11 10:04:45	ga_ls8c_ard_3-2-1_098070_2022-09-11_final
2022-09-13 11:36:05	ga_ls8c_ard_3-2-1_112082_2022-09-13_final
2022-09-18 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-09-18_final
2022-09-23 10:30:43	ga_ls8c_ard_3-2-1_102073_2022-09-23_final
2022-09-27 10:07:59	ga_ls8c_ard_3-2-1_098078_2022-09-27_final
2022-09-28 09:12:46	ga_ls8c_ard_3-2-1_089079_2022-09-27_final
2022-09-28 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-09-28_final
2022-10-03 09:28:29	ga_ls8c_ard_3-2-1_092072_2022-10-02_final
2022-10-03 09:34:04	ga_ls8c_ard_3-2-1_092086_2022-10-03_final
2022-10-06 10:01:21	ga_ls8c_ard_3-2-1_097077_2022-10-06_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-11 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-10-11_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-28 09:23:55	ga_ls8c_ard_3-2-1_091076_2022-10-27_final
2022-10-30 09:17:09	ga_ls8c_ard_3-2-1_089090_2022-10-29_final
2022-11-01 10:34:54	ga_ls8c_ard_3-2-1_103068_2022-11-01_final
2022-11-12 10:20:17	ga_ls8c_ard_3-2-1_100078_2022-11-12_final
2022-11-13 09:23:03	ga_ls8c_ard_3-2-1_091074_2022-11-12_final
2022-11-13 09:23:27	ga_ls8c_ard_3-2-1_091075_2022-11-12_final
2022-11-14 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-14_final
2022-11-18 11:18:25	ga_ls8c_ard_3-2-1_110069_2022-11-18_final
2022-11-25 11:24:15	ga_ls8c_ard_3-2-1_111068_2022-11-25_final
2022-11-28 10:20:16	ga_ls8c_ard_3-2-1_100078_2022-11-28_final
2022-12-01 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-12-01_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-13 09:35:45	ga_ls8c_ard_3-2-1_093075_2022-12-13_final
2022-12-23 10:14:41	ga_ls8c_ard_3-2-1_099080_2022-12-23_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-29 09:39:38	ga_ls8c_ard_3-2-1_093085_2022-12-29_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2023-01-02 09:12:32	ga_ls8c_ard_3-2-1_089079_2023-01-01_final
2023-01-08 10:13:31	ga_ls8c_ard_3-2-1_099077_2023-01-08_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-25 09:17:28	ga_ls8c_ard_3-2-1_090076_2023-01-24_final
2023-01-26 09:59:08	ga_ls8c_ard_3-2-1_097072_2023-01-26_final
2023-01-30 11:14:06	ga_ls8c_ard_3-2-1_109074_2023-01-30_final
2023-02-10 10:55:31	ga_ls8c_ard_3-2-1_106074_2023-02-10_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_final
2023-03-12 09:27:50	ga_ls8c_ard_3-2-1_092072_2023-03-11_final
2023-03-13 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-03-13_final
2023-03-21 09:23:34	ga_ls8c_ard_3-2-1_091077_2023-03-20_final
2023-03-21 10:59:39	ga_ls8c_ard_3-2-1_107070_2023-03-21_final
2023-03-26 11:18:56	ga_ls8c_ard_3-2-1_110072_2023-03-26_final
2023-04-04 11:11:27	ga_ls8c_ard_3-2-1_109069_2023-04-04_final
2023-04-04 11:16:38	ga_ls8c_ard_3-2-1_109082_2023-04-04_final
2023-04-06 11:05:02	ga_ls8c_ard_3-2-1_107084_2023-04-06_final
2023-04-12 10:25:02	ga_ls8c_ard_3-2-1_101077_2023-04-12_final
2023-04-13 09:28:13	ga_ls8c_ard_3-2-1_092074_2023-04-12_final
2023-04-17 09:07:04	ga_ls8c_ard_3-2-1_088083_2023-04-16_final
2023-04-26 10:34:10	ga_ls8c_ard_3-2-1_103069_2023-04-26_final
2023-05-17 09:21:33	ga_ls8c_ard_3-2-1_090089_2023-05-16_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