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
2022-03-15 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-03-15_final
2022-03-21 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-03-21_final
2022-03-28 09:58:56	ga_ls8c_ard_3-2-1_097073_2022-03-28_final
2022-04-01 09:35:22	ga_ls8c_ard_3-2-1_093076_2022-04-01_final
2022-04-20 11:45:39	ga_ls8c_ard_3-2-1_114077_2022-04-20_final
2022-04-24 09:43:13	ga_ls8c_ard_3-2-1_094080_2022-04-24_final
2022-04-24 11:18:30	ga_ls8c_ard_3-2-1_110071_2022-04-24_final
2022-04-26 09:34:26	ga_ls8c_ard_3-2-1_092089_2022-04-26_final
2022-04-29 11:41:48	ga_ls8c_ard_3-2-1_113083_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-05-02 10:29:04	ga_ls8c_ard_3-2-1_102071_2022-05-02_final
2022-05-08 11:33:20	ga_ls8c_ard_3-2-1_112077_2022-05-08_final
2022-05-17 11:29:37	ga_ls8c_ard_3-2-1_111083_2022-05-17_final
2022-05-19 11:15:16	ga_ls8c_ard_3-2-1_109078_2022-05-19_final
2022-05-20 10:21:14	ga_ls8c_ard_3-2-1_100082_2022-05-20_final
2022-05-25 10:36:11	ga_ls8c_ard_3-2-1_103073_2022-05-25_final
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-09 11:32:46	ga_ls8c_ard_3-2-1_112075_2022-06-09_final
2022-06-16 10:01:44	ga_ls8c_ard_3-2-1_097079_2022-06-16_final
2022-06-17 10:41:25	ga_ls8c_ard_3-2-1_104070_2022-06-17_final
2022-06-22 09:23:54	ga_ls8c_ard_3-2-1_091077_2022-06-21_final
2022-06-23 10:03:10	ga_ls8c_ard_3-2-1_098067_2022-06-23_final
2022-06-29 09:31:42	ga_ls8c_ard_3-2-1_092081_2022-06-29_final
2022-07-02 10:01:24	ga_ls8c_ard_3-2-1_097078_2022-07-02_final
2022-07-06 09:35:53	ga_ls8c_ard_3-2-1_093076_2022-07-06_final
2022-07-13 09:40:51	ga_ls8c_ard_3-2-1_094073_2022-07-13_final
2022-07-14 10:24:06	ga_ls8c_ard_3-2-1_101073_2022-07-14_final
2022-07-22 09:37:57	ga_ls8c_ard_3-2-1_093081_2022-07-22_final
2022-07-26 10:46:34	ga_ls8c_ard_3-2-1_105067_2022-07-26_final
2022-07-28 10:34:38	ga_ls8c_ard_3-2-1_103068_2022-07-28_final
2022-07-29 09:41:01	ga_ls8c_ard_3-2-1_094073_2022-07-29_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-08-05 09:50:03	ga_ls8c_ard_3-2-1_095080_2022-08-05_final
2022-08-12 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-08-12_final
2022-08-13 10:34:46	ga_ls8c_ard_3-2-1_103068_2022-08-13_final
2022-08-14 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-08-14_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-08-26 10:04:17	ga_ls8c_ard_3-2-1_098069_2022-08-26_final
2022-08-29 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-08-29_final
2022-09-01 09:32:23	ga_ls8c_ard_3-2-1_092082_2022-09-01_final
2022-09-02 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-09-02_final
2022-09-09 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-09-09_final
2022-09-12 09:17:07	ga_ls8c_ard_3-2-1_089090_2022-09-11_final
2022-09-16 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-09-16_final
2022-09-17 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-09-17_final
2022-09-18 11:53:27	ga_ls8c_ard_3-2-1_115079_2022-09-18_final
2022-09-22 09:48:39	ga_ls8c_ard_3-2-1_095076_2022-09-22_final
2022-09-24 11:15:34	ga_ls8c_ard_3-2-1_109077_2022-09-24_final
2022-09-24 11:15:58	ga_ls8c_ard_3-2-1_109078_2022-09-24_final
2022-09-29 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-09-29_final
2022-10-01 09:40:28	ga_ls8c_ard_3-2-1_094071_2022-10-01_final
2022-10-06 09:59:22	ga_ls8c_ard_3-2-1_097072_2022-10-06_final
2022-10-23 10:41:26	ga_ls8c_ard_3-2-1_104069_2022-10-23_final
2022-10-24 09:50:12	ga_ls8c_ard_3-2-1_095080_2022-10-24_final
2022-11-04 09:30:06	ga_ls8c_ard_3-2-1_092076_2022-11-04_final
2022-11-07 10:00:59	ga_ls8c_ard_3-2-1_097076_2022-11-07_final
2022-11-14 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-14_final
2022-11-14 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-14_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-22 09:31:26	ga_ls8c_ard_3-2-1_092080_2022-12-22_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-12 09:46:22	ga_ls8c_ard_3-2-1_095071_2023-01-12_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-21 11:20:38	ga_ls8c_ard_3-2-1_110075_2023-01-21_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-20 11:32:02	ga_ls8c_ard_3-2-1_112073_2023-02-20_final
2023-03-06 10:07:45	ga_ls8c_ard_3-2-1_098079_2023-03-06_final
2023-03-21 11:03:38	ga_ls8c_ard_3-2-1_107080_2023-03-21_final
2023-03-29 10:14:55	ga_ls8c_ard_3-2-1_099082_2023-03-29_final
2023-03-30 10:57:47	ga_ls8c_ard_3-2-1_106081_2023-03-30_final
2023-04-05 10:17:48	ga_ls8c_ard_3-2-1_100074_2023-04-05_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-04-13 09:34:12	ga_ls8c_ard_3-2-1_092089_2023-04-13_final
2023-04-20 09:35:33	ga_ls8c_ard_3-2-1_093077_2023-04-20_final
2023-04-20 11:16:01	ga_ls8c_ard_3-2-1_109081_2023-04-20_final
2023-04-27 09:43:19	ga_ls8c_ard_3-2-1_094081_2023-04-27_final
2023-04-27 11:18:13	ga_ls8c_ard_3-2-1_110071_2023-04-27_final
2023-05-09 10:09:29	ga_ls8c_ard_3-2-1_098085_2023-05-09_final
2023-05-11 09:56:17	ga_ls8c_ard_3-2-1_096083_2023-05-11_final
2023-05-22 09:34:08	ga_ls8c_ard_3-2-1_093074_2023-05-22_final
2023-05-23 10:20:36	ga_ls8c_ard_3-2-1_100082_2023-05-23_final
2023-05-24 09:27:22	ga_ls8c_ard_3-2-1_091088_2023-05-23_final
2023-06-03 09:57:41	ga_ls8c_ard_3-2-1_097071_2023-06-03_final
2023-06-05 09:51:45	ga_ls8c_ard_3-2-1_095087_2023-06-05_final
2023-06-08 10:19:54	ga_ls8c_ard_3-2-1_100080_2023-06-08_final
2023-06-25 11:00:29	ga_ls8c_ard_3-2-1_107073_2023-06-25_final
2023-06-30 11:20:42	ga_ls8c_ard_3-2-1_110077_2023-06-30_final
2023-07-14 09:51:53	ga_ls8c_ard_3-2-1_096071_2023-07-14_final
2023-07-16 09:45:07	ga_ls8c_ard_3-2-1_094085_2023-07-16_final
2023-07-21 10:00:27	ga_ls8c_ard_3-2-1_097077_2023-07-21_final
2023-08-08 09:51:03	ga_ls8c_ard_3-2-1_095084_2023-08-08_final
2023-08-10 11:16:46	ga_ls8c_ard_3-2-1_109082_2023-08-10_final
2023-08-19 11:05:55	ga_ls8c_ard_3-2-1_108070_2023-08-19_final
2023-09-04 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-09-04_final
2023-09-05 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-09-05_final
2023-09-06 10:57:32	ga_ls8c_ard_3-2-1_106080_2023-09-06_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