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
2022-08-31 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-31_final
2022-09-11 10:04:45	ga_ls8c_ard_3-2-1_098070_2022-09-11_final
2022-09-12 10:47:37	ga_ls8c_ard_3-2-1_105069_2022-09-12_final
2022-09-15 11:21:44	ga_ls8c_ard_3-2-1_110077_2022-09-15_final
2022-09-17 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-09-17_final
2022-09-18 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-09-18_final
2022-09-27 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-09-27_final
2022-10-06 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-06_final
2022-10-08 11:27:52	ga_ls8c_ard_3-2-1_111077_2022-10-08_final
2022-10-10 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-10-10_final
2022-10-16 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-10-16_final
2022-10-20 10:12:06	ga_ls8c_ard_3-2-1_099073_2022-10-20_final
2022-10-20 11:51:23	ga_ls8c_ard_3-2-1_115074_2022-10-20_final
2022-10-23 10:43:25	ga_ls8c_ard_3-2-1_104074_2022-10-23_final
2022-10-27 10:19:32	ga_ls8c_ard_3-2-1_100076_2022-10-27_final
2022-10-28 09:24:43	ga_ls8c_ard_3-2-1_091078_2022-10-27_final
2022-10-29 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-10-29_final
2022-10-30 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-10-29_final
2022-11-05 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-11-05_final
2022-11-09 11:27:30	ga_ls8c_ard_3-2-1_111076_2022-11-09_final
2022-11-16 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-11-16_final
2022-11-30 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-30_final
2022-12-04 09:42:47	ga_ls8c_ard_3-2-1_094077_2022-12-04_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-06 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-12-06_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-11 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-12-11_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-22 11:09:07	ga_ls8c_ard_3-2-1_108077_2022-12-22_final
2022-12-26 10:42:25	ga_ls8c_ard_3-2-1_104072_2022-12-26_final
2022-12-27 11:27:41	ga_ls8c_ard_3-2-1_111077_2022-12-27_final
2022-12-27 11:28:05	ga_ls8c_ard_3-2-1_111078_2022-12-27_final
2023-01-01 10:10:09	ga_ls8c_ard_3-2-1_098084_2023-01-01_final
2023-01-06 10:26:41	ga_ls8c_ard_3-2-1_101079_2023-01-06_final
2023-01-18 09:11:35	ga_ls8c_ard_3-2-1_089077_2023-01-17_final
2023-01-26 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-26_final
2023-01-26 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-26_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-02 11:45:01	ga_ls8c_ard_3-2-1_114074_2023-02-02_final
2023-02-02 11:47:00	ga_ls8c_ard_3-2-1_114079_2023-02-02_final
2023-02-08 09:34:12	ga_ls8c_ard_3-2-1_092087_2023-02-08_final
2023-02-17 09:22:19	ga_ls8c_ard_3-2-1_091073_2023-02-16_final
2023-02-17 11:05:11	ga_ls8c_ard_3-2-1_107083_2023-02-17_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-03-03 09:34:53	ga_ls8c_ard_3-2-1_093074_2023-03-03_final
2023-03-06 11:44:38	ga_ls8c_ard_3-2-1_114074_2023-03-06_final
2023-03-13 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-03-13_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-15 10:02:19	ga_ls8c_ard_3-2-1_097081_2023-03-15_final
2023-03-17 09:51:56	ga_ls8c_ard_3-2-1_095086_2023-03-17_final
2023-03-26 11:21:20	ga_ls8c_ard_3-2-1_110078_2023-03-26_final
2023-03-28 09:33:40	ga_ls8c_ard_3-2-1_092087_2023-03-28_final
2023-04-02 11:27:02	ga_ls8c_ard_3-2-1_111077_2023-04-02_final
2023-04-04 09:39:45	ga_ls8c_ard_3-2-1_093087_2023-04-04_final
2023-04-13 09:32:37	ga_ls8c_ard_3-2-1_092085_2023-04-13_final
2023-04-13 09:33:48	ga_ls8c_ard_3-2-1_092088_2023-04-13_final
2023-04-13 11:06:42	ga_ls8c_ard_3-2-1_108073_2023-04-13_final
2023-04-15 10:58:20	ga_ls8c_ard_3-2-1_106083_2023-04-15_final
2023-04-16 10:01:54	ga_ls8c_ard_3-2-1_097081_2023-04-16_final
2023-05-02 09:57:26	ga_ls8c_ard_3-2-1_097070_2023-05-02_final
2023-05-02 10:00:37	ga_ls8c_ard_3-2-1_097078_2023-05-02_final
2023-05-02 10:01:49	ga_ls8c_ard_3-2-1_097081_2023-05-02_final
2023-05-04 09:50:38	ga_ls8c_ard_3-2-1_095084_2023-05-04_final
2023-05-19 09:06:24	ga_ls8c_ard_3-2-1_088082_2023-05-18_final
2023-05-20 11:24:34	ga_ls8c_ard_3-2-1_111072_2023-05-20_final
2023-05-24 09:26:34	ga_ls8c_ard_3-2-1_091086_2023-05-23_final
2023-05-29 11:22:01	ga_ls8c_ard_3-2-1_110081_2023-05-29_final
2023-06-01 11:51:19	ga_ls8c_ard_3-2-1_115077_2023-06-01_final
2023-06-03 10:01:17	ga_ls8c_ard_3-2-1_097080_2023-06-03_final
2023-06-05 11:27:50	ga_ls8c_ard_3-2-1_111080_2023-06-05_final
2023-06-11 09:13:08	ga_ls8c_ard_3-2-1_089083_2023-06-10_final
2023-06-15 10:24:56	ga_ls8c_ard_3-2-1_101077_2023-06-15_final
2023-07-03 10:09:33	ga_ls8c_ard_3-2-1_099069_2023-07-03_final
2023-07-03 11:51:38	ga_ls8c_ard_3-2-1_115077_2023-07-03_final
2023-07-07 11:26:09	ga_ls8c_ard_3-2-1_111075_2023-07-07_final
2023-07-10 10:19:47	ga_ls8c_ard_3-2-1_100079_2023-07-10_final
2023-07-24 10:29:49	ga_ls8c_ard_3-2-1_102073_2023-07-24_final
2023-07-27 09:23:04	ga_ls8c_ard_3-2-1_091076_2023-07-26_final
2023-07-28 10:04:21	ga_ls8c_ard_3-2-1_098071_2023-07-28_final
2023-07-28 10:09:56	ga_ls8c_ard_3-2-1_098085_2023-07-28_final
2023-08-02 10:27:43	ga_ls8c_ard_3-2-1_101083_2023-08-02_final
2023-08-03 09:32:54	ga_ls8c_ard_3-2-1_092085_2023-08-03_final
2023-08-04 11:52:16	ga_ls8c_ard_3-2-1_115078_2023-08-04_final
2023-08-08 11:28:20	ga_ls8c_ard_3-2-1_111080_2023-08-08_final
2023-08-21 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-08-20_final
2023-08-22 10:02:20	ga_ls8c_ard_3-2-1_097081_2023-08-22_final
2023-08-27 10:19:42	ga_ls8c_ard_3-2-1_100078_2023-08-27_final
2023-08-28 09:22:53	ga_ls8c_ard_3-2-1_091075_2023-08-27_final
2023-08-30 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-08-29_final
2023-08-30 10:46:37	ga_ls8c_ard_3-2-1_105068_2023-08-30_final
2023-09-06 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-09-05_final
2023-09-06 09:21:27	ga_ls8c_ard_3-2-1_090087_2023-09-05_final
2023-09-18 11:21:10	ga_ls8c_ard_3-2-1_110077_2023-09-18_final
2023-10-02 11:32:23	ga_ls8c_ard_3-2-1_112074_2023-10-02_final
2023-10-07 10:09:39	ga_ls8c_ard_3-2-1_099068_2023-10-07_final
2023-10-10 10:46:10	ga_ls8c_ard_3-2-1_104082_2023-10-10_final
2023-10-19 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-10-19_final
2023-10-25 09:58:10	ga_ls8c_ard_3-2-1_097070_2023-10-25_final
2023-11-02 10:47:13	ga_ls8c_ard_3-2-1_105069_2023-11-02_final
2023-11-05 11:19:42	ga_ls8c_ard_3-2-1_110073_2023-11-05_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