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
2022-11-26 10:28:37	ga_ls8c_ard_3-2-1_102068_2022-11-26_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-12-04 09:41:35	ga_ls8c_ard_3-2-1_094074_2022-12-04_final
2022-12-07 10:10:29	ga_ls8c_ard_3-2-1_099069_2022-12-07_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-07 11:52:09	ga_ls8c_ard_3-2-1_115076_2022-12-07_final
2022-12-16 11:45:54	ga_ls8c_ard_3-2-1_114076_2022-12-16_final
2022-12-19 10:34:41	ga_ls8c_ard_3-2-1_103068_2022-12-19_final
2022-12-20 11:19:55	ga_ls8c_ard_3-2-1_110073_2022-12-20_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-22 11:06:44	ga_ls8c_ard_3-2-1_108071_2022-12-22_final
2022-12-26 10:42:49	ga_ls8c_ard_3-2-1_104073_2022-12-26_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2023-01-02 09:12:32	ga_ls8c_ard_3-2-1_089079_2023-01-01_final
2023-01-05 09:41:50	ga_ls8c_ard_3-2-1_094075_2023-01-05_final
2023-01-07 09:34:39	ga_ls8c_ard_3-2-1_092088_2023-01-07_final
2023-01-12 09:46:22	ga_ls8c_ard_3-2-1_095071_2023-01-12_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-19 09:52:52	ga_ls8c_ard_3-2-1_096072_2023-01-19_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-30 09:35:13	ga_ls8c_ard_3-2-1_093074_2023-01-30_final
2023-01-30 11:13:19	ga_ls8c_ard_3-2-1_109072_2023-01-30_final
2023-01-31 10:18:29	ga_ls8c_ard_3-2-1_100074_2023-01-31_final
2023-02-03 09:12:54	ga_ls8c_ard_3-2-1_089080_2023-02-02_final
2023-02-05 10:35:01	ga_ls8c_ard_3-2-1_103069_2023-02-05_final
2023-02-08 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-02-08_final
2023-02-09 10:10:16	ga_ls8c_ard_3-2-1_099069_2023-02-09_final
2023-02-17 09:26:42	ga_ls8c_ard_3-2-1_091084_2023-02-16_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-19 09:13:31	ga_ls8c_ard_3-2-1_089082_2023-02-18_final
2023-02-23 10:24:23	ga_ls8c_ard_3-2-1_101074_2023-02-23_final
2023-02-24 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-02-24_final
2023-02-27 10:00:25	ga_ls8c_ard_3-2-1_097076_2023-02-27_final
2023-02-27 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-02-27_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-11 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-03-11_final
2023-03-16 09:07:29	ga_ls8c_ard_3-2-1_088083_2023-03-15_final
2023-03-22 10:04:48	ga_ls8c_ard_3-2-1_098072_2023-03-22_final
2023-03-30 09:18:06	ga_ls8c_ard_3-2-1_090079_2023-03-29_final
2023-04-02 09:51:45	ga_ls8c_ard_3-2-1_095086_2023-04-02_final
2023-04-07 10:07:48	ga_ls8c_ard_3-2-1_098080_2023-04-07_final
2023-04-11 09:40:11	ga_ls8c_ard_3-2-1_094073_2023-04-11_final
2023-04-13 11:05:54	ga_ls8c_ard_3-2-1_108071_2023-04-13_final
2023-04-14 10:11:05	ga_ls8c_ard_3-2-1_099073_2023-04-14_final
2023-04-16 09:59:06	ga_ls8c_ard_3-2-1_097074_2023-04-16_final
2023-04-24 09:10:50	ga_ls8c_ard_3-2-1_089077_2023-04-23_final
2023-04-28 10:22:35	ga_ls8c_ard_3-2-1_101071_2023-04-28_final
2023-04-28 10:27:22	ga_ls8c_ard_3-2-1_101083_2023-04-28_final
2023-05-01 09:18:34	ga_ls8c_ard_3-2-1_090081_2023-04-30_final
2023-05-02 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-05-02_final
2023-05-07 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-05-07_final
2023-05-11 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-11_final
2023-05-16 10:15:11	ga_ls8c_ard_3-2-1_099084_2023-05-16_final
2023-05-19 09:05:36	ga_ls8c_ard_3-2-1_088080_2023-05-18_final
2023-05-25 10:08:14	ga_ls8c_ard_3-2-1_098082_2023-05-25_final
2023-05-26 09:11:49	ga_ls8c_ard_3-2-1_089080_2023-05-25_final
2023-05-26 10:51:54	ga_ls8c_ard_3-2-1_105083_2023-05-26_final
2023-06-06 10:27:50	ga_ls8c_ard_3-2-1_102069_2023-06-06_final
2023-06-14 11:17:46	ga_ls8c_ard_3-2-1_110070_2023-06-14_final
2023-06-17 11:51:28	ga_ls8c_ard_3-2-1_115077_2023-06-17_final
2023-06-20 10:44:41	ga_ls8c_ard_3-2-1_104080_2023-06-20_final
2023-06-23 11:12:48	ga_ls8c_ard_3-2-1_109073_2023-06-23_final
2023-06-23 11:13:12	ga_ls8c_ard_3-2-1_109074_2023-06-23_final
2023-06-25 09:25:59	ga_ls8c_ard_3-2-1_091084_2023-06-24_final
2023-07-02 09:32:40	ga_ls8c_ard_3-2-1_092085_2023-07-02_final
2023-07-02 11:07:34	ga_ls8c_ard_3-2-1_108075_2023-07-02_final
2023-07-05 10:01:36	ga_ls8c_ard_3-2-1_097080_2023-07-05_final
2023-07-13 09:12:13	ga_ls8c_ard_3-2-1_089080_2023-07-12_final
2023-07-18 11:05:15	ga_ls8c_ard_3-2-1_108069_2023-07-18_final
2023-07-25 11:11:30	ga_ls8c_ard_3-2-1_109069_2023-07-25_final
2023-07-26 10:17:05	ga_ls8c_ard_3-2-1_100072_2023-07-26_final
2023-07-31 10:34:05	ga_ls8c_ard_3-2-1_103068_2023-07-31_final
2023-08-03 11:05:24	ga_ls8c_ard_3-2-1_108069_2023-08-03_final
2023-08-10 11:11:35	ga_ls8c_ard_3-2-1_109069_2023-08-10_final
2023-08-10 11:14:23	ga_ls8c_ard_3-2-1_109076_2023-08-10_final
2023-08-13 10:04:26	ga_ls8c_ard_3-2-1_098071_2023-08-13_final
2023-08-13 10:07:13	ga_ls8c_ard_3-2-1_098078_2023-08-13_final
2023-08-17 09:40:58	ga_ls8c_ard_3-2-1_094074_2023-08-17_final
2023-08-17 09:45:45	ga_ls8c_ard_3-2-1_094086_2023-08-17_final
2023-09-01 10:35:50	ga_ls8c_ard_3-2-1_103072_2023-09-01_final
2023-09-02 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-09-02_final
2023-09-06 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-09-05_final
2023-09-18 09:40:41	ga_ls8c_ard_3-2-1_094073_2023-09-18_final
2023-09-19 10:27:33	ga_ls8c_ard_3-2-1_101082_2023-09-19_final
2023-09-23 11:41:19	ga_ls8c_ard_3-2-1_113081_2023-09-23_final
2023-09-25 09:50:53	ga_ls8c_ard_3-2-1_095083_2023-09-25_final
2023-09-27 11:11:50	ga_ls8c_ard_3-2-1_109069_2023-09-27_final
2023-10-04 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-04_final
2023-10-11 09:46:10	ga_ls8c_ard_3-2-1_095071_2023-10-11_final
2023-10-15 09:28:38	ga_ls8c_ard_3-2-1_091089_2023-10-14_final
2023-10-15 10:59:56	ga_ls8c_ard_3-2-1_107070_2023-10-15_final
2023-10-24 10:54:10	ga_ls8c_ard_3-2-1_106071_2023-10-24_final
2023-10-25 09:58:33	ga_ls8c_ard_3-2-1_097071_2023-10-25_final
2023-10-29 09:40:15	ga_ls8c_ard_3-2-1_093087_2023-10-29_final
2023-11-03 09:52:24	ga_ls8c_ard_3-2-1_096071_2023-11-03_final
2023-11-07 09:34:25	ga_ls8c_ard_3-2-1_092088_2023-11-07_final
2023-11-08 11:52:09	ga_ls8c_ard_3-2-1_115077_2023-11-08_final
2023-11-11 09:07:16	ga_ls8c_ard_3-2-1_088082_2023-11-10_final
2023-11-15 11:58:23	ga_ls8c_ard_3-2-1_116077_2023-11-15_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