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
2022-01-28 11:58:43	ga_ls8c_ard_3-2-1_116078_2022-01-28_final
2022-01-30 10:07:29	ga_ls8c_ard_3-2-1_098078_2022-01-30_final
2022-02-11 10:28:34	ga_ls8c_ard_3-2-1_102069_2022-02-11_final
2022-02-13 11:58:40	ga_ls8c_ard_3-2-1_116078_2022-02-13_final
2022-02-15 10:07:25	ga_ls8c_ard_3-2-1_098078_2022-02-15_final
2022-02-21 09:31:05	ga_ls8c_ard_3-2-1_092080_2022-02-21_final
2022-02-24 11:37:41	ga_ls8c_ard_3-2-1_113072_2022-02-24_final
2022-02-28 09:35:40	ga_ls8c_ard_3-2-1_093076_2022-02-28_final
2022-03-16 11:13:15	ga_ls8c_ard_3-2-1_109073_2022-03-16_final
2022-03-17 11:58:30	ga_ls8c_ard_3-2-1_116078_2022-03-17_final
2022-03-24 10:23:42	ga_ls8c_ard_3-2-1_101073_2022-03-24_final
2022-03-25 11:06:33	ga_ls8c_ard_3-2-1_108072_2022-03-25_final
2022-03-28 09:58:08	ga_ls8c_ard_3-2-1_097071_2022-03-28_final
2022-04-06 09:51:57	ga_ls8c_ard_3-2-1_096071_2022-04-06_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-14 10:40:40	ga_ls8c_ard_3-2-1_104069_2022-04-14_final
2022-04-25 10:26:04	ga_ls8c_ard_3-2-1_101079_2022-04-25_final
2022-04-29 10:01:19	ga_ls8c_ard_3-2-1_097079_2022-04-29_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-04-30 10:44:59	ga_ls8c_ard_3-2-1_104080_2022-04-30_final
2022-05-05 11:02:24	ga_ls8c_ard_3-2-1_107077_2022-05-05_final
2022-05-17 11:29:13	ga_ls8c_ard_3-2-1_111082_2022-05-17_final
2022-05-23 10:46:09	ga_ls8c_ard_3-2-1_105067_2022-05-23_final
2022-05-26 11:18:38	ga_ls8c_ard_3-2-1_110071_2022-05-26_final
2022-06-02 11:25:42	ga_ls8c_ard_3-2-1_111073_2022-06-02_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-11 11:22:50	ga_ls8c_ard_3-2-1_110081_2022-06-11_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-06-20 11:12:44	ga_ls8c_ard_3-2-1_109071_2022-06-20_final
2022-06-23 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-06-23_final
2022-06-24 09:13:56	ga_ls8c_ard_3-2-1_089083_2022-06-23_final
2022-06-25 09:57:12	ga_ls8c_ard_3-2-1_096083_2022-06-25_final
2022-06-27 09:40:52	ga_ls8c_ard_3-2-1_094073_2022-06-27_final
2022-07-03 10:40:40	ga_ls8c_ard_3-2-1_104068_2022-07-03_final
2022-07-13 09:45:14	ga_ls8c_ard_3-2-1_094084_2022-07-13_final
2022-07-13 11:24:07	ga_ls8c_ard_3-2-1_110084_2022-07-13_final
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-07-30 10:23:05	ga_ls8c_ard_3-2-1_101070_2022-07-30_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-08-08 10:20:35	ga_ls8c_ard_3-2-1_100079_2022-08-08_final
2022-08-09 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-08-08_final
2022-08-29 10:36:47	ga_ls8c_ard_3-2-1_103073_2022-08-29_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-17 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-09-17_final
2022-09-22 11:29:32	ga_ls8c_ard_3-2-1_111081_2022-09-22_final
2022-09-28 10:48:51	ga_ls8c_ard_3-2-1_105072_2022-09-28_final
2022-09-30 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-09-30_final
2022-10-14 09:16:36	ga_ls8c_ard_3-2-1_089089_2022-10-13_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-23 10:41:02	ga_ls8c_ard_3-2-1_104068_2022-10-23_final
2022-11-07 11:40:16	ga_ls8c_ard_3-2-1_113077_2022-11-07_final
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-18 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-11-18_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-12-10 10:44:57	ga_ls8c_ard_3-2-1_104078_2022-12-10_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-29 11:16:56	ga_ls8c_ard_3-2-1_109081_2022-12-29_final
2022-12-29 11:17:20	ga_ls8c_ard_3-2-1_109082_2022-12-29_final
2022-12-30 11:59:00	ga_ls8c_ard_3-2-1_116078_2022-12-30_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-08 11:51:12	ga_ls8c_ard_3-2-1_115074_2023-01-08_final
2023-01-10 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-10_final
2023-01-23 09:29:48	ga_ls8c_ard_3-2-1_092076_2023-01-22_final
2023-02-03 09:16:29	ga_ls8c_ard_3-2-1_089089_2023-02-02_final
2023-02-06 11:18:41	ga_ls8c_ard_3-2-1_110070_2023-02-06_final
2023-02-09 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-02-09_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-20 11:34:50	ga_ls8c_ard_3-2-1_112080_2023-02-20_final
2023-02-23 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-02-23_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-12 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-03-12_final
2023-04-03 10:33:24	ga_ls8c_ard_3-2-1_102082_2023-04-03_final
2023-04-06 09:22:10	ga_ls8c_ard_3-2-1_091074_2023-04-05_final
2023-04-17 09:06:16	ga_ls8c_ard_3-2-1_088081_2023-04-16_final
2023-04-25 09:51:18	ga_ls8c_ard_3-2-1_096070_2023-04-25_final
2023-04-26 10:36:09	ga_ls8c_ard_3-2-1_103074_2023-04-26_final
2023-04-30 10:13:48	ga_ls8c_ard_3-2-1_099080_2023-04-30_final
2023-05-02 11:40:18	ga_ls8c_ard_3-2-1_113080_2023-05-02_final
2023-05-07 10:18:18	ga_ls8c_ard_3-2-1_100076_2023-05-07_final
2023-05-08 11:01:56	ga_ls8c_ard_3-2-1_107077_2023-05-08_final
2023-05-15 09:29:56	ga_ls8c_ard_3-2-1_092079_2023-05-14_final
2023-05-22 11:14:13	ga_ls8c_ard_3-2-1_109077_2023-05-22_final
2023-05-25 10:04:39	ga_ls8c_ard_3-2-1_098073_2023-05-25_final
2023-05-27 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-27_final
2023-05-30 10:27:11	ga_ls8c_ard_3-2-1_101083_2023-05-30_final
2023-06-09 11:01:58	ga_ls8c_ard_3-2-1_107077_2023-06-09_final
2023-06-09 11:03:10	ga_ls8c_ard_3-2-1_107080_2023-06-09_final
2023-06-15 10:22:09	ga_ls8c_ard_3-2-1_101070_2023-06-15_final
2023-06-19 10:00:38	ga_ls8c_ard_3-2-1_097078_2023-06-19_final
2023-07-04 10:54:02	ga_ls8c_ard_3-2-1_106072_2023-07-04_final
2023-07-12 10:03:27	ga_ls8c_ard_3-2-1_098069_2023-07-12_final
2023-07-12 10:03:51	ga_ls8c_ard_3-2-1_098070_2023-07-12_final
2023-07-15 10:35:57	ga_ls8c_ard_3-2-1_103073_2023-07-15_final
2023-07-23 09:48:56	ga_ls8c_ard_3-2-1_095079_2023-07-23_final
2023-07-23 09:51:20	ga_ls8c_ard_3-2-1_095085_2023-07-23_final
2023-07-26 10:18:17	ga_ls8c_ard_3-2-1_100075_2023-07-26_final
2023-07-29 09:13:08	ga_ls8c_ard_3-2-1_089082_2023-07-28_final
2023-08-24 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-08-24_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