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
2022-07-01 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-07-01_final
2022-07-24 09:27:12	ga_ls8c_ard_3-2-1_091085_2022-07-23_final
2022-07-29 11:19:30	ga_ls8c_ard_3-2-1_110072_2022-07-29_final
2022-07-31 11:06:22	ga_ls8c_ard_3-2-1_108070_2022-07-31_final
2022-08-03 09:58:48	ga_ls8c_ard_3-2-1_097071_2022-08-03_final
2022-08-05 11:30:08	ga_ls8c_ard_3-2-1_111083_2022-08-05_final
2022-08-09 09:22:58	ga_ls8c_ard_3-2-1_091074_2022-08-08_final
2022-08-10 10:08:14	ga_ls8c_ard_3-2-1_098079_2022-08-10_final
2022-08-11 09:14:37	ga_ls8c_ard_3-2-1_089084_2022-08-10_final
2022-08-14 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-14_final
2022-08-19 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-08-19_final
2022-08-25 09:27:48	ga_ls8c_ard_3-2-1_091086_2022-08-24_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
2022-09-01 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-08-31_final
2022-09-01 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-09-01_final
2022-09-01 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-09-01_final
2022-09-04 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-09-04_final
2022-09-05 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-09-04_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-11 10:05:09	ga_ls8c_ard_3-2-1_098071_2022-09-11_final
2022-09-13 09:52:24	ga_ls8c_ard_3-2-1_096070_2022-09-13_final
2022-09-15 09:46:02	ga_ls8c_ard_3-2-1_094085_2022-09-15_final
2022-09-18 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-09-18_final
2022-09-26 09:23:56	ga_ls8c_ard_3-2-1_091076_2022-09-25_final
2022-09-26 09:27:31	ga_ls8c_ard_3-2-1_091085_2022-09-25_final
2022-09-27 10:09:59	ga_ls8c_ard_3-2-1_098083_2022-09-27_final
2022-09-28 09:13:10	ga_ls8c_ard_3-2-1_089080_2022-09-27_final
2022-10-01 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-10-01_final
2022-10-01 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-10-01_final
2022-10-03 09:35:16	ga_ls8c_ard_3-2-1_092089_2022-10-03_final
2022-10-03 11:07:46	ga_ls8c_ard_3-2-1_108073_2022-10-03_final
2022-10-03 11:08:10	ga_ls8c_ard_3-2-1_108074_2022-10-03_final
2022-10-04 10:15:20	ga_ls8c_ard_3-2-1_099081_2022-10-04_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-09 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-10-09_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-19 11:06:54	ga_ls8c_ard_3-2-1_108071_2022-10-19_final
2022-10-22 09:58:33	ga_ls8c_ard_3-2-1_097070_2022-10-22_final
2022-10-24 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-10-24_final
2022-10-28 09:27:54	ga_ls8c_ard_3-2-1_091086_2022-10-27_final
2022-10-29 10:08:22	ga_ls8c_ard_3-2-1_098079_2022-10-29_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-10-30 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-10-29_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-04 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-11-04_final
2022-11-05 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-11-05_final
2022-11-06 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-11-05_final
2022-11-06 09:22:55	ga_ls8c_ard_3-2-1_090089_2022-11-05_final
2022-11-06 10:53:49	ga_ls8c_ard_3-2-1_106069_2022-11-06_final
2022-11-06 10:54:13	ga_ls8c_ard_3-2-1_106070_2022-11-06_final
2022-11-07 11:41:52	ga_ls8c_ard_3-2-1_113081_2022-11-07_final
2022-11-08 10:43:03	ga_ls8c_ard_3-2-1_104073_2022-11-08_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-10 10:30:40	ga_ls8c_ard_3-2-1_102073_2022-11-10_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-14 10:05:06	ga_ls8c_ard_3-2-1_098071_2022-11-14_final
2022-11-15 09:13:28	ga_ls8c_ard_3-2-1_089081_2022-11-14_final
2022-11-15 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-14_final
2022-11-16 09:52:43	ga_ls8c_ard_3-2-1_096071_2022-11-16_final
2022-11-19 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-11-19_final
2022-11-21 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-11-21_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-11-28 10:20:16	ga_ls8c_ard_3-2-1_100078_2022-11-28_final
2022-11-29 09:29:02	ga_ls8c_ard_3-2-1_091089_2022-11-28_final
2022-12-05 10:23:39	ga_ls8c_ard_3-2-1_101071_2022-12-05_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-15 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-12-14_final
2022-12-15 09:26:57	ga_ls8c_ard_3-2-1_091084_2022-12-14_final
2022-12-18 09:52:38	ga_ls8c_ard_3-2-1_096071_2022-12-18_final
2022-12-24 10:56:22	ga_ls8c_ard_3-2-1_106076_2022-12-24_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-26 10:42:49	ga_ls8c_ard_3-2-1_104073_2022-12-26_final
2022-12-27 11:25:41	ga_ls8c_ard_3-2-1_111072_2022-12-27_final
2022-12-28 10:31:40	ga_ls8c_ard_3-2-1_102076_2022-12-28_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-14 09:36:22	ga_ls8c_ard_3-2-1_093077_2023-01-14_final
2023-01-21 09:44:32	ga_ls8c_ard_3-2-1_094082_2023-01-21_final
2023-01-22 10:23:49	ga_ls8c_ard_3-2-1_101072_2023-01-22_final
2023-01-22 10:25:49	ga_ls8c_ard_3-2-1_101077_2023-01-22_final
2023-01-23 11:07:29	ga_ls8c_ard_3-2-1_108073_2023-01-23_final
2023-01-25 10:58:44	ga_ls8c_ard_3-2-1_106082_2023-01-25_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-01-29 10:30:27	ga_ls8c_ard_3-2-1_102073_2023-01-29_final
2023-01-30 09:35:37	ga_ls8c_ard_3-2-1_093075_2023-01-30_final
2023-01-30 11:14:54	ga_ls8c_ard_3-2-1_109076_2023-01-30_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-09 11:53:09	ga_ls8c_ard_3-2-1_115079_2023-02-09_final
2023-02-10 10:55:31	ga_ls8c_ard_3-2-1_106074_2023-02-10_final
2023-02-14 10:30:21	ga_ls8c_ard_3-2-1_102073_2023-02-14_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-02-18 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-02-18_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-26 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-02-25_final
2023-03-03 11:13:22	ga_ls8c_ard_3-2-1_109073_2023-03-03_final
2023-03-05 09:28:06	ga_ls8c_ard_3-2-1_091088_2023-03-04_final
2023-03-05 09:28:54	ga_ls8c_ard_3-2-1_091090_2023-03-04_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_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