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
2022-04-26 09:32:26	ga_ls8c_ard_3-2-1_092084_2022-04-26_final
2022-04-27 10:14:53	ga_ls8c_ard_3-2-1_099082_2022-04-27_final
2022-05-01 11:24:40	ga_ls8c_ard_3-2-1_111071_2022-05-01_final
2022-05-05 09:23:31	ga_ls8c_ard_3-2-1_091077_2022-05-04_final
2022-05-05 11:02:00	ga_ls8c_ard_3-2-1_107076_2022-05-05_final
2022-05-06 10:07:35	ga_ls8c_ard_3-2-1_098079_2022-05-06_final
2022-05-06 11:44:29	ga_ls8c_ard_3-2-1_114074_2022-05-06_final
2022-05-10 09:44:54	ga_ls8c_ard_3-2-1_094084_2022-05-10_final
2022-05-10 11:22:59	ga_ls8c_ard_3-2-1_110082_2022-05-10_final
2022-05-19 09:35:35	ga_ls8c_ard_3-2-1_093076_2022-05-19_final
2022-05-19 09:37:59	ga_ls8c_ard_3-2-1_093082_2022-05-19_final
2022-05-20 10:21:38	ga_ls8c_ard_3-2-1_100083_2022-05-20_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-05-21 11:00:07	ga_ls8c_ard_3-2-1_107071_2022-05-21_final
2022-05-22 10:04:53	ga_ls8c_ard_3-2-1_098072_2022-05-22_final
2022-05-23 09:14:27	ga_ls8c_ard_3-2-1_089085_2022-05-22_final
2022-05-26 09:41:45	ga_ls8c_ard_3-2-1_094076_2022-05-26_final
2022-05-28 09:30:35	ga_ls8c_ard_3-2-1_092079_2022-05-28_final
2022-05-31 10:01:08	ga_ls8c_ard_3-2-1_097078_2022-05-31_final
2022-05-31 10:03:32	ga_ls8c_ard_3-2-1_097084_2022-05-31_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-11 11:22:50	ga_ls8c_ard_3-2-1_110081_2022-06-11_final
2022-06-15 09:18:28	ga_ls8c_ard_3-2-1_090079_2022-06-14_final
2022-06-21 10:20:19	ga_ls8c_ard_3-2-1_100079_2022-06-21_final
2022-06-23 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-06-23_final
2022-06-29 09:32:54	ga_ls8c_ard_3-2-1_092084_2022-06-29_final
2022-07-08 09:25:31	ga_ls8c_ard_3-2-1_091081_2022-07-07_final
2022-07-15 11:06:34	ga_ls8c_ard_3-2-1_108071_2022-07-15_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
2022-07-17 10:59:01	ga_ls8c_ard_3-2-1_106083_2022-07-17_final
2022-07-26 09:12:05	ga_ls8c_ard_3-2-1_089078_2022-07-25_final
2022-07-26 09:14:52	ga_ls8c_ard_3-2-1_089085_2022-07-25_final
2022-07-31 09:31:28	ga_ls8c_ard_3-2-1_092080_2022-07-31_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-08-06 10:30:56	ga_ls8c_ard_3-2-1_102074_2022-08-06_final
2022-08-11 09:11:49	ga_ls8c_ard_3-2-1_089077_2022-08-10_final
2022-08-11 09:12:13	ga_ls8c_ard_3-2-1_089078_2022-08-10_final
2022-08-11 09:14:13	ga_ls8c_ard_3-2-1_089083_2022-08-10_final
2022-08-12 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-08-12_final
2022-08-14 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-08-14_final
2022-08-19 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-08-19_final
2022-08-22 10:29:48	ga_ls8c_ard_3-2-1_102071_2022-08-22_final
2022-08-31 10:23:37	ga_ls8c_ard_3-2-1_101071_2022-08-31_final
2022-08-31 10:24:25	ga_ls8c_ard_3-2-1_101073_2022-08-31_final
2022-09-01 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-09-01_final
2022-09-07 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-09-07_final
2022-09-10 09:25:28	ga_ls8c_ard_3-2-1_091080_2022-09-09_final
2022-09-12 10:46:49	ga_ls8c_ard_3-2-1_105067_2022-09-12_final
2022-09-13 09:52:48	ga_ls8c_ard_3-2-1_096071_2022-09-13_final
2022-09-17 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-09-17_final
2022-09-22 09:47:51	ga_ls8c_ard_3-2-1_095074_2022-09-22_final
2022-10-06 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-06_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-16 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-10-16_final
2022-10-16 10:37:10	ga_ls8c_ard_3-2-1_103074_2022-10-16_final
2022-10-17 09:46:45	ga_ls8c_ard_3-2-1_094087_2022-10-17_final
2022-10-19 09:33:37	ga_ls8c_ard_3-2-1_092085_2022-10-19_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-10-27 10:18:44	ga_ls8c_ard_3-2-1_100074_2022-10-27_final
2022-10-30 09:14:45	ga_ls8c_ard_3-2-1_089084_2022-10-29_final
2022-10-31 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-10-31_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-03 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-11-03_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-05 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-11-05_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-18 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-11-18_final
2022-11-20 11:07:16	ga_ls8c_ard_3-2-1_108072_2022-11-20_final
2022-12-06 11:06:06	ga_ls8c_ard_3-2-1_108069_2022-12-06_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-31 09:29:17	ga_ls8c_ard_3-2-1_091090_2022-12-30_final
2023-01-01 11:45:27	ga_ls8c_ard_3-2-1_114075_2023-01-01_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-01 11:47:50	ga_ls8c_ard_3-2-1_114081_2023-01-01_final
2023-01-04 10:35:04	ga_ls8c_ard_3-2-1_103069_2023-01-04_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-07 09:31:28	ga_ls8c_ard_3-2-1_092080_2023-01-07_final
2023-01-13 10:31:37	ga_ls8c_ard_3-2-1_102076_2023-01-13_final
2023-01-14 11:17:15	ga_ls8c_ard_3-2-1_109082_2023-01-14_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-24 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-01-24_final
2023-01-25 09:19:51	ga_ls8c_ard_3-2-1_090082_2023-01-24_final
2023-02-01 09:27:39	ga_ls8c_ard_3-2-1_091086_2023-01-31_final
2023-02-06 11:23:28	ga_ls8c_ard_3-2-1_110082_2023-02-06_final
2023-02-08 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-02-08_final
2023-02-10 09:19:26	ga_ls8c_ard_3-2-1_090081_2023-02-09_final
2023-02-13 11:29:34	ga_ls8c_ard_3-2-1_111082_2023-02-13_final
2023-02-22 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-02-22_final
2023-02-27 11:40:54	ga_ls8c_ard_3-2-1_113080_2023-02-27_final
2023-02-28 10:43:17	ga_ls8c_ard_3-2-1_104075_2023-02-28_final
2023-03-02 10:33:42	ga_ls8c_ard_3-2-1_102082_2023-03-02_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_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