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
2022-06-15 09:20:28	ga_ls8c_ard_3-2-1_090084_2022-06-14_final
2022-07-15 11:08:33	ga_ls8c_ard_3-2-1_108076_2022-07-15_final
2022-07-15 11:08:57	ga_ls8c_ard_3-2-1_108077_2022-07-15_final
2022-07-18 11:37:54	ga_ls8c_ard_3-2-1_113072_2022-07-18_final
2022-07-19 10:43:29	ga_ls8c_ard_3-2-1_104075_2022-07-19_final
2022-07-27 09:52:33	ga_ls8c_ard_3-2-1_096071_2022-07-27_final
2022-07-27 11:35:26	ga_ls8c_ard_3-2-1_112081_2022-07-27_final
2022-08-05 09:51:39	ga_ls8c_ard_3-2-1_095084_2022-08-05_final
2022-08-08 10:21:47	ga_ls8c_ard_3-2-1_100082_2022-08-08_final
2022-08-15 10:24:00	ga_ls8c_ard_3-2-1_101072_2022-08-15_final
2022-08-23 11:15:51	ga_ls8c_ard_3-2-1_109078_2022-08-23_final
2022-08-24 10:19:02	ga_ls8c_ard_3-2-1_100075_2022-08-24_final
2022-08-26 10:08:40	ga_ls8c_ard_3-2-1_098080_2022-08-26_final
2022-08-28 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-08-28_final
2022-08-30 09:43:57	ga_ls8c_ard_3-2-1_094080_2022-08-30_final
2022-09-05 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-09-05_final
2022-09-13 11:35:17	ga_ls8c_ard_3-2-1_112080_2022-09-13_final
2022-09-17 11:06:11	ga_ls8c_ard_3-2-1_108069_2022-09-17_final
2022-09-28 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-09-28_final
2022-10-01 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-10-01_final
2022-10-07 10:41:49	ga_ls8c_ard_3-2-1_104070_2022-10-07_final
2022-10-10 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-10-10_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-10-23 10:44:13	ga_ls8c_ard_3-2-1_104076_2022-10-23_final
2022-10-24 09:48:12	ga_ls8c_ard_3-2-1_095075_2022-10-24_final
2022-10-28 11:01:36	ga_ls8c_ard_3-2-1_107073_2022-10-28_final
2022-10-29 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-10-29_final
2022-10-31 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-10-31_final
2022-11-11 11:13:08	ga_ls8c_ard_3-2-1_109071_2022-11-11_final
2022-11-11 11:15:55	ga_ls8c_ard_3-2-1_109078_2022-11-11_final
2022-11-18 09:43:55	ga_ls8c_ard_3-2-1_094080_2022-11-18_final
2022-11-19 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-11-19_final
2022-11-27 11:16:17	ga_ls8c_ard_3-2-1_109079_2022-11-27_final
2022-12-01 10:48:46	ga_ls8c_ard_3-2-1_105072_2022-12-01_final
2022-12-02 09:56:44	ga_ls8c_ard_3-2-1_096081_2022-12-02_final
2022-12-06 11:06:06	ga_ls8c_ard_3-2-1_108069_2022-12-06_final
2022-12-10 10:42:57	ga_ls8c_ard_3-2-1_104073_2022-12-10_final
2022-12-23 11:53:35	ga_ls8c_ard_3-2-1_115080_2022-12-23_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2023-01-12 11:30:02	ga_ls8c_ard_3-2-1_111083_2023-01-12_final
2023-01-17 11:44:54	ga_ls8c_ard_3-2-1_114074_2023-01-17_final
2023-01-30 11:16:06	ga_ls8c_ard_3-2-1_109079_2023-01-30_final
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-03 10:50:35	ga_ls8c_ard_3-2-1_105077_2023-02-03_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-09 10:16:39	ga_ls8c_ard_3-2-1_099085_2023-02-09_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-18 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-02-18_final
2023-02-26 09:18:21	ga_ls8c_ard_3-2-1_090079_2023-02-25_final
2023-03-01 11:28:32	ga_ls8c_ard_3-2-1_111080_2023-03-01_final
2023-03-10 09:43:00	ga_ls8c_ard_3-2-1_094079_2023-03-10_final
2023-03-10 11:23:52	ga_ls8c_ard_3-2-1_110084_2023-03-10_final
2023-03-12 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-03-12_final
2023-03-16 09:07:29	ga_ls8c_ard_3-2-1_088083_2023-03-15_final
2023-03-19 11:12:27	ga_ls8c_ard_3-2-1_109071_2023-03-19_final
2023-03-27 10:23:19	ga_ls8c_ard_3-2-1_101072_2023-03-27_final
2023-03-28 11:08:10	ga_ls8c_ard_3-2-1_108076_2023-03-28_final
2023-03-31 11:39:50	ga_ls8c_ard_3-2-1_113078_2023-03-31_final
2023-04-04 11:17:26	ga_ls8c_ard_3-2-1_109084_2023-04-04_final
2023-04-18 09:51:07	ga_ls8c_ard_3-2-1_095085_2023-04-18_final
2023-05-06 11:12:20	ga_ls8c_ard_3-2-1_109072_2023-05-06_final
2023-05-13 11:20:00	ga_ls8c_ard_3-2-1_110076_2023-05-13_final
2023-05-15 09:31:08	ga_ls8c_ard_3-2-1_092082_2023-05-15_final
2023-05-18 09:58:25	ga_ls8c_ard_3-2-1_097073_2023-05-18_final
2023-05-24 11:03:28	ga_ls8c_ard_3-2-1_107081_2023-05-24_final
2023-05-25 11:45:56	ga_ls8c_ard_3-2-1_114079_2023-05-25_final
2023-05-30 10:26:23	ga_ls8c_ard_3-2-1_101081_2023-05-30_final
2023-06-05 09:51:45	ga_ls8c_ard_3-2-1_095087_2023-06-05_final
2023-06-09 09:21:05	ga_ls8c_ard_3-2-1_091072_2023-06-08_final
2023-06-09 10:59:59	ga_ls8c_ard_3-2-1_107072_2023-06-09_final
2023-06-14 11:17:46	ga_ls8c_ard_3-2-1_110070_2023-06-14_final
2023-06-24 10:19:59	ga_ls8c_ard_3-2-1_100080_2023-06-24_final
2023-07-12 10:09:50	ga_ls8c_ard_3-2-1_098085_2023-07-12_final
2023-07-12 11:44:20	ga_ls8c_ard_3-2-1_114074_2023-07-12_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-21 11:41:20	ga_ls8c_ard_3-2-1_113082_2023-07-21_final
2023-07-25 11:17:05	ga_ls8c_ard_3-2-1_109083_2023-07-25_final
2023-08-09 10:29:07	ga_ls8c_ard_3-2-1_102071_2023-08-09_final
2023-08-18 10:24:14	ga_ls8c_ard_3-2-1_101074_2023-08-18_final
2023-08-20 11:51:34	ga_ls8c_ard_3-2-1_115076_2023-08-20_final
2023-08-23 10:41:13	ga_ls8c_ard_3-2-1_104070_2023-08-23_final
2023-08-31 09:56:10	ga_ls8c_ard_3-2-1_096081_2023-08-31_final
2023-09-11 09:33:40	ga_ls8c_ard_3-2-1_093071_2023-09-11_final
2023-09-23 09:59:14	ga_ls8c_ard_3-2-1_097073_2023-09-23_final
2023-09-27 11:13:02	ga_ls8c_ard_3-2-1_109072_2023-09-27_final
2023-09-30 10:08:16	ga_ls8c_ard_3-2-1_098080_2023-09-30_final
2023-10-01 10:48:20	ga_ls8c_ard_3-2-1_105072_2023-10-01_final
2023-10-25 10:02:57	ga_ls8c_ard_3-2-1_097082_2023-10-25_final
2023-10-27 09:51:00	ga_ls8c_ard_3-2-1_095083_2023-10-27_final
2023-10-27 11:29:29	ga_ls8c_ard_3-2-1_111082_2023-10-27_final
2023-10-31 09:25:30	ga_ls8c_ard_3-2-1_091081_2023-10-30_final
2023-10-31 11:01:11	ga_ls8c_ard_3-2-1_107073_2023-10-31_final
2023-11-01 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-01_final
2023-11-04 10:37:39	ga_ls8c_ard_3-2-1_103076_2023-11-04_final
2023-11-07 11:08:55	ga_ls8c_ard_3-2-1_108077_2023-11-07_final
2023-11-09 10:56:07	ga_ls8c_ard_3-2-1_106076_2023-11-09_final
2023-11-11 10:43:22	ga_ls8c_ard_3-2-1_104075_2023-11-11_final
2023-11-18 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-18_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