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
2022-03-20 10:48:29	ga_ls8c_ard_3-2-1_105073_2022-03-20_final
2022-03-22 10:34:54	ga_ls8c_ard_3-2-1_103070_2022-03-22_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-04-03 09:26:12	ga_ls8c_ard_3-2-1_091084_2022-04-02_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-24 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-24_final
2022-04-24 11:20:30	ga_ls8c_ard_3-2-1_110076_2022-04-24_final
2022-04-26 09:32:02	ga_ls8c_ard_3-2-1_092083_2022-04-26_final
2022-04-29 09:58:07	ga_ls8c_ard_3-2-1_097071_2022-04-29_final
2022-05-02 10:28:40	ga_ls8c_ard_3-2-1_102070_2022-05-02_final
2022-05-05 09:23:31	ga_ls8c_ard_3-2-1_091077_2022-05-04_final
2022-05-06 10:04:24	ga_ls8c_ard_3-2-1_098071_2022-05-06_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-19 09:35:35	ga_ls8c_ard_3-2-1_093076_2022-05-19_final
2022-05-20 11:57:44	ga_ls8c_ard_3-2-1_116076_2022-05-20_final
2022-05-22 10:04:05	ga_ls8c_ard_3-2-1_098070_2022-05-22_final
2022-05-22 10:04:29	ga_ls8c_ard_3-2-1_098071_2022-05-22_final
2022-05-23 10:46:33	ga_ls8c_ard_3-2-1_105068_2022-05-23_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_2022-05-24_final
2022-05-26 09:40:33	ga_ls8c_ard_3-2-1_094073_2022-05-26_final
2022-05-26 11:18:14	ga_ls8c_ard_3-2-1_110070_2022-05-26_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-05-28 11:05:52	ga_ls8c_ard_3-2-1_108070_2022-05-28_final
2022-05-30 10:53:57	ga_ls8c_ard_3-2-1_106071_2022-05-30_final
2022-06-04 09:39:40	ga_ls8c_ard_3-2-1_093086_2022-06-04_final
2022-06-06 11:00:14	ga_ls8c_ard_3-2-1_107071_2022-06-06_final
2022-06-07 10:04:13	ga_ls8c_ard_3-2-1_098070_2022-06-07_final
2022-06-13 11:05:42	ga_ls8c_ard_3-2-1_108069_2022-06-13_final
2022-06-15 10:54:57	ga_ls8c_ard_3-2-1_106073_2022-06-15_final
2022-06-16 11:41:01	ga_ls8c_ard_3-2-1_113080_2022-06-16_final
2022-06-21 11:58:00	ga_ls8c_ard_3-2-1_116076_2022-06-21_final
2022-06-23 10:03:58	ga_ls8c_ard_3-2-1_098069_2022-06-23_final
2022-06-23 11:44:51	ga_ls8c_ard_3-2-1_114074_2022-06-23_final
2022-06-26 10:34:29	ga_ls8c_ard_3-2-1_103068_2022-06-26_final
2022-06-27 09:45:39	ga_ls8c_ard_3-2-1_094085_2022-06-27_final
2022-07-08 09:25:55	ga_ls8c_ard_3-2-1_091082_2022-07-07_final
2022-07-09 11:47:40	ga_ls8c_ard_3-2-1_114081_2022-07-09_final
2022-07-10 09:13:33	ga_ls8c_ard_3-2-1_089082_2022-07-09_final
2022-07-15 11:10:57	ga_ls8c_ard_3-2-1_108082_2022-07-15_final
2022-07-17 10:55:01	ga_ls8c_ard_3-2-1_106073_2022-07-17_final
2022-07-18 10:03:48	ga_ls8c_ard_3-2-1_097084_2022-07-18_final
2022-07-22 09:37:33	ga_ls8c_ard_3-2-1_093080_2022-07-22_final
2022-07-29 11:18:42	ga_ls8c_ard_3-2-1_110070_2022-07-29_final
2022-08-02 09:18:20	ga_ls8c_ard_3-2-1_090078_2022-08-01_final
2022-08-07 09:38:54	ga_ls8c_ard_3-2-1_093083_2022-08-07_final
2022-08-09 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-08-09_final
2022-08-10 10:05:26	ga_ls8c_ard_3-2-1_098072_2022-08-10_final
2022-08-10 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-08-10_final
2022-08-14 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-08-14_final
2022-08-16 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-08-15_final
2022-08-17 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-08-17_final
2022-08-23 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-08-23_final
2022-08-28 11:36:48	ga_ls8c_ard_3-2-1_112084_2022-08-28_final
2022-08-30 11:21:14	ga_ls8c_ard_3-2-1_110076_2022-08-30_final
2022-09-03 10:55:19	ga_ls8c_ard_3-2-1_106073_2022-09-03_final
2022-09-08 09:35:25	ga_ls8c_ard_3-2-1_093074_2022-09-08_final
2022-09-10 09:25:28	ga_ls8c_ard_3-2-1_091080_2022-09-09_final
2022-09-11 10:10:44	ga_ls8c_ard_3-2-1_098085_2022-09-11_final
2022-09-14 10:35:16	ga_ls8c_ard_3-2-1_103069_2022-09-14_final
2022-09-14 10:38:28	ga_ls8c_ard_3-2-1_103077_2022-09-14_final
2022-09-17 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-09-17_final
2022-09-18 11:51:27	ga_ls8c_ard_3-2-1_115074_2022-09-18_final
2022-09-23 10:31:07	ga_ls8c_ard_3-2-1_102074_2022-09-23_final
2022-10-03 11:11:22	ga_ls8c_ard_3-2-1_108082_2022-10-03_final
2022-10-13 11:45:07	ga_ls8c_ard_3-2-1_114074_2022-10-13_final
2022-10-28 11:03:36	ga_ls8c_ard_3-2-1_107078_2022-10-28_final
2022-11-14 11:45:11	ga_ls8c_ard_3-2-1_114074_2022-11-14_final
2022-11-17 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-11-17_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-25 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-11-25_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-07 10:14:04	ga_ls8c_ard_3-2-1_099078_2022-12-07_final
2022-12-10 10:43:21	ga_ls8c_ard_3-2-1_104074_2022-12-10_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-20 09:46:38	ga_ls8c_ard_3-2-1_094087_2022-12-20_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2022-12-28 10:33:40	ga_ls8c_ard_3-2-1_102081_2022-12-28_final
2022-12-29 09:35:39	ga_ls8c_ard_3-2-1_093075_2022-12-29_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-09 09:18:41	ga_ls8c_ard_3-2-1_090079_2023-01-08_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-14 11:13:16	ga_ls8c_ard_3-2-1_109072_2023-01-14_final
2023-01-18 09:14:23	ga_ls8c_ard_3-2-1_089084_2023-01-17_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-01-25 10:59:08	ga_ls8c_ard_3-2-1_106083_2023-01-25_final
2023-02-01 09:26:27	ga_ls8c_ard_3-2-1_091083_2023-01-31_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-12 10:43:07	ga_ls8c_ard_3-2-1_104074_2023-02-12_final
2023-02-15 09:40:42	ga_ls8c_ard_3-2-1_093088_2023-02-15_final
2023-02-17 11:00:24	ga_ls8c_ard_3-2-1_107071_2023-02-17_final
2023-02-18 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-02-18_final
2023-02-22 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-02-22_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-03-05 11:01:47	ga_ls8c_ard_3-2-1_107075_2023-03-05_final
2023-03-05 11:05:23	ga_ls8c_ard_3-2-1_107084_2023-03-05_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