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
2022-09-11 10:03:57	ga_ls8c_ard_3-2-1_098068_2022-09-11_final
2022-09-11 10:05:57	ga_ls8c_ard_3-2-1_098073_2022-09-11_final
2022-09-17 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-09-17_final
2022-09-18 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-09-18_final
2022-09-20 09:59:49	ga_ls8c_ard_3-2-1_097073_2022-09-20_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-22 09:48:15	ga_ls8c_ard_3-2-1_095075_2022-09-22_final
2022-09-27 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-09-27_final
2022-10-07 09:06:55	ga_ls8c_ard_3-2-1_088080_2022-10-06_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-10 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-10-10_final
2022-10-10 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-10-10_final
2022-10-12 09:26:35	ga_ls8c_ard_3-2-1_091083_2022-10-11_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-13 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-10-13_final
2022-10-17 09:46:45	ga_ls8c_ard_3-2-1_094087_2022-10-17_final
2022-10-19 11:06:07	ga_ls8c_ard_3-2-1_108069_2022-10-19_final
2022-10-20 10:11:42	ga_ls8c_ard_3-2-1_099072_2022-10-20_final
2022-10-24 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-10-24_final
2022-10-24 09:50:36	ga_ls8c_ard_3-2-1_095081_2022-10-24_final
2022-10-26 11:13:33	ga_ls8c_ard_3-2-1_109072_2022-10-26_final
2022-10-29 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-10-29_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-04 09:34:54	ga_ls8c_ard_3-2-1_092088_2022-11-04_final
2022-11-05 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-11-05_final
2022-11-07 09:59:00	ga_ls8c_ard_3-2-1_097071_2022-11-07_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-11 09:37:50	ga_ls8c_ard_3-2-1_093080_2022-11-11_final
2022-11-13 09:25:27	ga_ls8c_ard_3-2-1_091080_2022-11-12_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-14 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-14_final
2022-11-14 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-14_final
2022-11-18 09:46:19	ga_ls8c_ard_3-2-1_094086_2022-11-18_final
2022-11-18 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-11-18_final
2022-11-20 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-11-19_final
2022-11-20 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-11-20_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-23 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-11-23_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-25 11:27:02	ga_ls8c_ard_3-2-1_111075_2022-11-25_final
2022-11-25 11:29:50	ga_ls8c_ard_3-2-1_111082_2022-11-25_final
2022-11-27 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-11-27_final
2022-11-27 11:13:53	ga_ls8c_ard_3-2-1_109073_2022-11-27_final
2022-11-29 11:00:20	ga_ls8c_ard_3-2-1_107070_2022-11-29_final
2022-11-30 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-30_final
2022-12-04 11:19:40	ga_ls8c_ard_3-2-1_110072_2022-12-04_final
2022-12-06 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-12-06_final
2022-12-09 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-12-09_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2022-12-11 11:29:24	ga_ls8c_ard_3-2-1_111081_2022-12-11_final
2022-12-13 11:14:38	ga_ls8c_ard_3-2-1_109075_2022-12-13_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-16 10:05:25	ga_ls8c_ard_3-2-1_098072_2022-12-16_final
2022-12-16 10:08:13	ga_ls8c_ard_3-2-1_098079_2022-12-16_final
2022-12-21 10:27:52	ga_ls8c_ard_3-2-1_101082_2022-12-21_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-24 10:57:10	ga_ls8c_ard_3-2-1_106078_2022-12-24_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-28 10:32:28	ga_ls8c_ard_3-2-1_102078_2022-12-28_final
2022-12-30 11:58:36	ga_ls8c_ard_3-2-1_116077_2022-12-30_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-02 10:52:13	ga_ls8c_ard_3-2-1_105081_2023-01-02_final
2023-01-03 09:57:23	ga_ls8c_ard_3-2-1_096083_2023-01-03_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-05 09:41:26	ga_ls8c_ard_3-2-1_094074_2023-01-05_final
2023-01-06 10:27:53	ga_ls8c_ard_3-2-1_101082_2023-01-06_final
2023-01-08 10:12:19	ga_ls8c_ard_3-2-1_099074_2023-01-08_final
2023-01-08 10:13:31	ga_ls8c_ard_3-2-1_099077_2023-01-08_final
2023-01-09 10:57:10	ga_ls8c_ard_3-2-1_106078_2023-01-09_final
2023-01-10 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-10_final
2023-01-13 10:32:24	ga_ls8c_ard_3-2-1_102078_2023-01-13_final
2023-01-13 10:33:36	ga_ls8c_ard_3-2-1_102081_2023-01-13_final
2023-01-15 11:58:06	ga_ls8c_ard_3-2-1_116076_2023-01-15_final
2023-01-16 09:25:34	ga_ls8c_ard_3-2-1_091081_2023-01-15_final
2023-01-16 09:26:46	ga_ls8c_ard_3-2-1_091084_2023-01-15_final
2023-01-19 09:56:28	ga_ls8c_ard_3-2-1_096081_2023-01-19_final
2023-01-20 10:34:33	ga_ls8c_ard_3-2-1_103068_2023-01-20_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-23 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-01-23_final
2023-01-25 10:57:09	ga_ls8c_ard_3-2-1_106078_2023-01-25_final
2023-01-26 11:40:49	ga_ls8c_ard_3-2-1_113079_2023-01-26_final
2023-01-29 10:30:03	ga_ls8c_ard_3-2-1_102072_2023-01-29_final
2023-02-05 10:34:37	ga_ls8c_ard_3-2-1_103068_2023-02-05_final
2023-02-08 11:08:42	ga_ls8c_ard_3-2-1_108076_2023-02-08_final
2023-02-10 09:21:25	ga_ls8c_ard_3-2-1_090086_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-11 11:41:57	ga_ls8c_ard_3-2-1_113082_2023-02-11_final
2023-02-13 11:29:34	ga_ls8c_ard_3-2-1_111082_2023-02-13_final
2023-02-15 09:40:18	ga_ls8c_ard_3-2-1_093087_2023-02-15_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-02-17 09:28:42	ga_ls8c_ard_3-2-1_091089_2023-02-16_final
2023-02-24 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-02-24_final
2023-03-01 11:29:20	ga_ls8c_ard_3-2-1_111082_2023-03-01_final
2023-03-03 11:14:34	ga_ls8c_ard_3-2-1_109076_2023-03-03_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-07 09:13:43	ga_ls8c_ard_3-2-1_089083_2023-03-06_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_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