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
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-08-21 09:52:56	ga_ls8c_ard_3-2-1_095087_2022-08-21_final
2022-08-21 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-08-21_final
2022-09-04 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-09-04_final
2022-09-06 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-09-06_final
2022-09-10 09:22:41	ga_ls8c_ard_3-2-1_091073_2022-09-09_final
2022-09-12 10:53:12	ga_ls8c_ard_3-2-1_105083_2022-09-12_final
2022-09-27 10:04:48	ga_ls8c_ard_3-2-1_098070_2022-09-27_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-09-29 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-09-29_final
2022-10-04 10:10:33	ga_ls8c_ard_3-2-1_099069_2022-10-04_final
2022-10-05 10:56:11	ga_ls8c_ard_3-2-1_106075_2022-10-05_final
2022-10-05 10:56:35	ga_ls8c_ard_3-2-1_106076_2022-10-05_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-14 10:53:05	ga_ls8c_ard_3-2-1_105083_2022-10-14_final
2022-10-16 10:37:34	ga_ls8c_ard_3-2-1_103075_2022-10-16_final
2022-10-17 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-10-17_final
2022-10-19 09:33:37	ga_ls8c_ard_3-2-1_092085_2022-10-19_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-27 10:22:43	ga_ls8c_ard_3-2-1_100084_2022-10-27_final
2022-10-29 10:07:35	ga_ls8c_ard_3-2-1_098077_2022-10-29_final
2022-11-01 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-11-01_final
2022-11-06 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-11-05_final
2022-11-07 09:57:48	ga_ls8c_ard_3-2-1_097068_2022-11-07_final
2022-11-14 10:04:19	ga_ls8c_ard_3-2-1_098069_2022-11-14_final
2022-11-15 09:12:40	ga_ls8c_ard_3-2-1_089079_2022-11-14_final
2022-11-20 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-11-20_final
2022-11-20 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-11-20_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-12-01 09:15:04	ga_ls8c_ard_3-2-1_089085_2022-11-30_final
2022-12-11 11:30:36	ga_ls8c_ard_3-2-1_111084_2022-12-11_final
2022-12-13 09:34:57	ga_ls8c_ard_3-2-1_093073_2022-12-13_final
2022-12-13 11:13:02	ga_ls8c_ard_3-2-1_109071_2022-12-13_final
2022-12-15 11:00:15	ga_ls8c_ard_3-2-1_107070_2022-12-15_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-23 10:09:30	ga_ls8c_ard_3-2-1_099067_2022-12-23_final
2022-12-25 11:42:26	ga_ls8c_ard_3-2-1_113083_2022-12-25_final
2023-01-06 10:28:17	ga_ls8c_ard_3-2-1_101083_2023-01-06_final
2023-01-08 10:11:55	ga_ls8c_ard_3-2-1_099073_2023-01-08_final
2023-01-25 09:23:03	ga_ls8c_ard_3-2-1_090090_2023-01-24_final
2023-01-31 10:19:17	ga_ls8c_ard_3-2-1_100076_2023-01-31_final
2023-02-12 09:07:02	ga_ls8c_ard_3-2-1_088081_2023-02-11_final
2023-02-18 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-02-18_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-25 11:52:27	ga_ls8c_ard_3-2-1_115078_2023-02-25_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-09 10:35:49	ga_ls8c_ard_3-2-1_103072_2023-03-09_final
2023-03-19 09:35:09	ga_ls8c_ard_3-2-1_093075_2023-03-19_final
2023-03-20 10:19:36	ga_ls8c_ard_3-2-1_100078_2023-03-20_final
2023-03-23 10:46:27	ga_ls8c_ard_3-2-1_105068_2023-03-23_final
2023-03-24 11:32:06	ga_ls8c_ard_3-2-1_112074_2023-03-24_final
2023-03-24 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-03-24_final
2023-04-04 11:15:50	ga_ls8c_ard_3-2-1_109080_2023-04-04_final
2023-04-06 09:21:46	ga_ls8c_ard_3-2-1_091073_2023-04-05_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-10 09:15:27	ga_ls8c_ard_3-2-1_089089_2023-05-09_final
2023-05-17 10:57:38	ga_ls8c_ard_3-2-1_106082_2023-05-17_final
2023-05-19 10:41:41	ga_ls8c_ard_3-2-1_104073_2023-05-19_final
2023-05-24 09:25:46	ga_ls8c_ard_3-2-1_091084_2023-05-23_final
2023-06-03 11:40:10	ga_ls8c_ard_3-2-1_113080_2023-06-03_final
2023-06-07 09:34:14	ga_ls8c_ard_3-2-1_093074_2023-06-07_final
2023-06-09 09:23:53	ga_ls8c_ard_3-2-1_091079_2023-06-08_final
2023-06-10 10:09:09	ga_ls8c_ard_3-2-1_098084_2023-06-10_final
2023-06-12 11:35:42	ga_ls8c_ard_3-2-1_112084_2023-06-12_final
2023-06-17 10:09:48	ga_ls8c_ard_3-2-1_099070_2023-06-17_final
2023-06-18 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-06-18_final
2023-06-24 10:21:11	ga_ls8c_ard_3-2-1_100083_2023-06-24_final
2023-07-10 10:16:36	ga_ls8c_ard_3-2-1_100071_2023-07-10_final
2023-07-13 09:16:13	ga_ls8c_ard_3-2-1_089090_2023-07-12_final
2023-07-19 10:12:49	ga_ls8c_ard_3-2-1_099077_2023-07-19_final
2023-07-21 09:59:16	ga_ls8c_ard_3-2-1_097074_2023-07-21_final
2023-07-21 11:37:21	ga_ls8c_ard_3-2-1_113072_2023-07-21_final
2023-07-27 09:22:40	ga_ls8c_ard_3-2-1_091075_2023-07-26_final
2023-08-06 11:41:30	ga_ls8c_ard_3-2-1_113082_2023-08-06_final
2023-08-06 11:41:54	ga_ls8c_ard_3-2-1_113083_2023-08-06_final
2023-08-14 10:49:42	ga_ls8c_ard_3-2-1_105076_2023-08-14_final
2023-08-21 09:22:40	ga_ls8c_ard_3-2-1_090090_2023-08-20_final
2023-08-22 09:57:09	ga_ls8c_ard_3-2-1_097068_2023-08-22_final
2023-08-31 09:52:11	ga_ls8c_ard_3-2-1_096071_2023-08-31_final
2023-08-31 11:36:15	ga_ls8c_ard_3-2-1_112084_2023-08-31_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-05 10:13:53	ga_ls8c_ard_3-2-1_099079_2023-09-05_final
2023-09-09 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-09-09_final
2023-09-13 09:22:31	ga_ls8c_ard_3-2-1_091074_2023-09-12_final
2023-09-16 11:35:31	ga_ls8c_ard_3-2-1_112082_2023-09-16_final
2023-09-21 10:15:35	ga_ls8c_ard_3-2-1_099083_2023-09-21_final
2023-09-22 09:22:45	ga_ls8c_ard_3-2-1_090090_2023-09-21_final
2023-10-01 10:52:43	ga_ls8c_ard_3-2-1_105083_2023-10-01_final
2023-10-08 09:22:02	ga_ls8c_ard_3-2-1_090088_2023-10-07_final
2023-10-08 09:22:49	ga_ls8c_ard_3-2-1_090090_2023-10-07_final
2023-10-13 11:13:54	ga_ls8c_ard_3-2-1_109074_2023-10-13_final
2023-10-16 10:04:42	ga_ls8c_ard_3-2-1_098071_2023-10-16_final
2023-10-16 10:07:30	ga_ls8c_ard_3-2-1_098078_2023-10-16_final
2023-10-22 11:10:30	ga_ls8c_ard_3-2-1_108081_2023-10-22_final
2023-10-24 10:55:22	ga_ls8c_ard_3-2-1_106074_2023-10-24_final
2023-10-27 09:47:01	ga_ls8c_ard_3-2-1_095073_2023-10-27_final
2023-11-10 09:58:05	ga_ls8c_ard_3-2-1_097070_2023-11-10_final
2023-11-22 10:25:20	ga_ls8c_ard_3-2-1_101076_2023-11-22_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