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
2019-03-10 09:26:30	ga_ls8c_ard_3-1-0_091085_2019-03-09_final
2019-03-22 09:50:22	ga_ls8c_ard_3-1-0_095083_2019-03-22_final
2019-03-22 09:50:46	ga_ls8c_ard_3-1-0_095084_2019-03-22_final
2019-04-11 09:26:22	ga_ls8c_ard_3-1-0_091085_2019-04-10_final
2019-06-14 09:25:05	ga_ls8c_ard_3-1-0_091081_2019-06-13_final
2019-06-14 09:26:41	ga_ls8c_ard_3-1-0_091085_2019-06-13_final
2019-06-14 09:27:53	ga_ls8c_ard_3-1-0_091088_2019-06-13_final
2019-06-17 09:56:25	ga_ls8c_ard_3-1-0_096082_2019-06-17_final
2019-06-21 11:06:36	ga_ls8c_ard_3-1-0_108072_2019-06-21_final
2019-06-26 09:49:29	ga_ls8c_ard_3-1-0_095080_2019-06-26_final
2019-07-12 09:46:20	ga_ls8c_ard_3-1-0_095072_2019-07-12_final
2019-07-28 09:49:37	ga_ls8c_ard_3-1-0_095080_2019-07-28_final
2019-08-04 09:57:51	ga_ls8c_ard_3-1-0_096085_2019-08-04_final
2019-08-13 09:49:43	ga_ls8c_ard_3-1-0_095080_2019-08-13_final
2019-08-17 09:26:37	ga_ls8c_ard_3-1-0_091084_2019-08-16_final
2019-08-20 09:56:20	ga_ls8c_ard_3-1-0_096081_2019-08-20_final
2019-09-02 09:26:16	ga_ls8c_ard_3-1-0_091083_2019-09-01_final
2019-09-05 09:56:23	ga_ls8c_ard_3-1-0_096081_2019-09-05_final
2019-09-05 09:57:35	ga_ls8c_ard_3-1-0_096084_2019-09-05_final
2019-09-14 09:51:04	ga_ls8c_ard_3-1-0_095083_2019-09-14_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-21 09:55:41	ga_ls8c_ard_3-1-0_096079_2019-09-21_final
2019-09-21 09:56:53	ga_ls8c_ard_3-1-0_096082_2019-09-21_final
2019-10-04 09:27:14	ga_ls8c_ard_3-1-0_091085_2019-10-03_final
2019-10-20 09:23:40	ga_ls8c_ard_3-1-0_091076_2019-10-19_final
2019-10-27 11:11:08	ga_ls8c_ard_3-1-0_108082_2019-10-27_final
2019-11-05 09:24:27	ga_ls8c_ard_3-1-0_091078_2019-11-04_final
2019-11-05 09:27:15	ga_ls8c_ard_3-1-0_091085_2019-11-04_final
2019-11-17 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-11-17_final
2019-11-24 09:52:06	ga_ls8c_ard_3-1-0_096070_2019-11-24_final
2019-12-03 09:47:55	ga_ls8c_ard_3-1-0_095075_2019-12-03_final
2019-12-07 09:24:47	ga_ls8c_ard_3-1-0_091079_2019-12-06_final
2019-12-09 10:49:19	ga_ls8c_ard_3-1-0_105074_2019-12-09_final
2019-12-10 09:54:05	ga_ls8c_ard_3-1-0_096075_2019-12-10_final
2019-12-23 09:25:32	ga_ls8c_ard_3-1-0_091081_2019-12-22_final
2019-12-26 09:56:02	ga_ls8c_ard_3-1-0_096080_2019-12-26_final
2019-12-26 09:58:25	ga_ls8c_ard_3-1-0_096086_2019-12-26_final
2020-01-04 09:51:00	ga_ls8c_ard_3-1-0_095083_2020-01-04_final
2020-01-08 09:24:40	ga_ls8c_ard_3-1-0_091079_2020-01-07_final
2020-01-08 09:25:52	ga_ls8c_ard_3-1-0_091082_2020-01-07_final
2020-01-20 09:46:33	ga_ls8c_ard_3-1-0_095072_2020-01-20_final
2020-01-27 09:57:53	ga_ls8c_ard_3-1-0_096085_2020-01-27_final
2020-02-12 09:55:49	ga_ls8c_ard_3-1-0_096080_2020-02-12_final
2020-02-28 09:55:45	ga_ls8c_ard_3-1-0_096080_2020-02-28_final
2020-03-08 09:51:30	ga_ls8c_ard_3-1-0_095085_2020-03-08_final
2020-03-14 10:48:52	ga_ls8c_ard_3-1-0_105074_2020-03-14_final
2020-03-28 09:19:49	ga_ls8c_ard_3-1-0_091068_2020-03-27_final
2020-03-28 09:26:36	ga_ls8c_ard_3-1-0_091085_2020-03-27_final
2020-03-28 09:28:36	ga_ls8c_ard_3-1-0_091090_2020-03-27_final
2020-04-09 09:52:02	ga_ls8c_ard_3-1-0_095087_2020-04-09_final
2020-04-13 09:19:42	ga_ls8c_ard_3-1-0_091068_2020-04-12_final
2020-04-13 09:26:29	ga_ls8c_ard_3-1-0_091085_2020-04-12_final
2020-04-15 10:46:37	ga_ls8c_ard_3-1-0_105069_2020-04-15_final
2020-04-16 09:51:23	ga_ls8c_ard_3-1-0_096070_2020-04-16_final
2020-05-01 10:50:28	ga_ls8c_ard_3-1-0_105079_2020-05-01_final
2022-03-29 10:40:58	ga_ls8c_ard_3-2-1_104070_2022-03-29_final
2022-03-30 09:50:08	ga_ls8c_ard_3-2-1_095082_2022-03-30_final
2022-04-01 09:38:34	ga_ls8c_ard_3-2-1_093084_2022-04-01_final
2022-04-03 11:03:54	ga_ls8c_ard_3-2-1_107081_2022-04-03_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-08 09:40:25	ga_ls8c_ard_3-2-1_094073_2022-04-08_final
2022-04-08 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-08_final
2022-04-08 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-08_final
2022-04-09 10:27:17	ga_ls8c_ard_3-2-1_101082_2022-04-09_final
2022-04-10 09:34:51	ga_ls8c_ard_3-2-1_092090_2022-04-10_final
2022-04-10 11:08:57	ga_ls8c_ard_3-2-1_108078_2022-04-10_final
2022-04-11 11:50:38	ga_ls8c_ard_3-2-1_115074_2022-04-11_final
2022-04-14 10:44:39	ga_ls8c_ard_3-2-1_104079_2022-04-14_final
2022-04-15 09:48:38	ga_ls8c_ard_3-2-1_095078_2022-04-15_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-17 11:15:09	ga_ls8c_ard_3-2-1_109078_2022-04-17_final
2022-04-17 11:15:33	ga_ls8c_ard_3-2-1_109079_2022-04-17_final
2022-04-24 11:21:18	ga_ls8c_ard_3-2-1_110078_2022-04-24_final
2022-04-24 11:21:42	ga_ls8c_ard_3-2-1_110079_2022-04-24_final
2022-04-26 11:08:55	ga_ls8c_ard_3-2-1_108078_2022-04-26_final
2022-04-28 10:56:56	ga_ls8c_ard_3-2-1_106079_2022-04-28_final
2022-04-28 10:57:44	ga_ls8c_ard_3-2-1_106081_2022-04-28_final
2022-05-03 11:14:44	ga_ls8c_ard_3-2-1_109077_2022-05-03_final
2022-05-03 11:15:08	ga_ls8c_ard_3-2-1_109078_2022-05-03_final
2022-05-03 11:15:56	ga_ls8c_ard_3-2-1_109080_2022-05-03_final
2022-05-04 10:19:55	ga_ls8c_ard_3-2-1_100079_2022-05-04_final
2022-05-07 10:49:40	ga_ls8c_ard_3-2-1_105076_2022-05-07_final
2022-05-09 10:39:19	ga_ls8c_ard_3-2-1_103081_2022-05-09_final
2022-05-10 11:21:00	ga_ls8c_ard_3-2-1_110077_2022-05-10_final
2022-05-18 10:28:25	ga_ls8c_ard_3-2-1_102069_2022-05-18_final
2022-05-19 11:14:52	ga_ls8c_ard_3-2-1_109077_2022-05-19_final
2022-05-19 11:16:04	ga_ls8c_ard_3-2-1_109080_2022-05-19_final
2022-05-20 10:20:02	ga_ls8c_ard_3-2-1_100079_2022-05-20_final
2022-05-26 09:42:57	ga_ls8c_ard_3-2-1_094079_2022-05-26_final
2022-05-26 11:20:14	ga_ls8c_ard_3-2-1_110075_2022-05-26_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-03 10:30:53	ga_ls8c_ard_3-2-1_102075_2022-06-03_final
2022-06-04 11:16:09	ga_ls8c_ard_3-2-1_109080_2022-06-04_final
2022-06-13 11:09:17	ga_ls8c_ard_3-2-1_108078_2022-06-13_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-17 10:45:48	ga_ls8c_ard_3-2-1_104081_2022-06-17_final
2022-06-18 11:26:17	ga_ls8c_ard_3-2-1_111074_2022-06-18_final
2022-06-18 11:29:52	ga_ls8c_ard_3-2-1_111083_2022-06-18_final
2022-06-22 09:26:41	ga_ls8c_ard_3-2-1_091084_2022-06-21_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