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
2022-03-07 09:45:24	ga_ls8c_ard_3-2-1_094085_2022-03-07_final
2022-03-22 10:38:53	ga_ls8c_ard_3-2-1_103080_2022-03-22_final
2022-04-14 10:41:28	ga_ls8c_ard_3-2-1_104071_2022-04-14_final
2022-04-26 11:05:20	ga_ls8c_ard_3-2-1_108069_2022-04-26_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-10 09:44:30	ga_ls8c_ard_3-2-1_094083_2022-05-10_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-12 11:08:39	ga_ls8c_ard_3-2-1_108077_2022-05-12_final
2022-05-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2022-05-17_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-21 11:00:31	ga_ls8c_ard_3-2-1_107072_2022-05-21_final
2022-05-21 11:04:30	ga_ls8c_ard_3-2-1_107082_2022-05-21_final
2022-05-22 11:46:58	ga_ls8c_ard_3-2-1_114080_2022-05-22_final
2022-05-26 11:18:14	ga_ls8c_ard_3-2-1_110070_2022-05-26_final
2022-05-28 09:29:47	ga_ls8c_ard_3-2-1_092077_2022-05-27_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-08 10:51:29	ga_ls8c_ard_3-2-1_105080_2022-06-08_final
2022-06-10 10:38:45	ga_ls8c_ard_3-2-1_103079_2022-06-10_final
2022-06-11 11:18:26	ga_ls8c_ard_3-2-1_110070_2022-06-11_final
2022-06-11 11:22:26	ga_ls8c_ard_3-2-1_110080_2022-06-11_final
2022-06-13 11:10:29	ga_ls8c_ard_3-2-1_108081_2022-06-13_final
2022-06-17 10:45:48	ga_ls8c_ard_3-2-1_104081_2022-06-17_final
2022-06-20 11:16:20	ga_ls8c_ard_3-2-1_109080_2022-06-20_final
2022-06-22 11:00:47	ga_ls8c_ard_3-2-1_107072_2022-06-22_final
2022-06-25 11:35:41	ga_ls8c_ard_3-2-1_112082_2022-06-25_final
2022-06-26 10:35:41	ga_ls8c_ard_3-2-1_103071_2022-06-26_final
2022-06-26 10:39:16	ga_ls8c_ard_3-2-1_103080_2022-06-26_final
2022-07-04 09:50:14	ga_ls8c_ard_3-2-1_095081_2022-07-04_final
2022-07-10 09:14:21	ga_ls8c_ard_3-2-1_089084_2022-07-09_final
2022-07-10 10:51:38	ga_ls8c_ard_3-2-1_105080_2022-07-10_final
2022-07-16 10:12:08	ga_ls8c_ard_3-2-1_099074_2022-07-16_final
2022-07-18 10:01:48	ga_ls8c_ard_3-2-1_097079_2022-07-18_final
2022-07-19 10:41:06	ga_ls8c_ard_3-2-1_104069_2022-07-19_final
2022-07-22 09:35:09	ga_ls8c_ard_3-2-1_093074_2022-07-22_final
2022-07-23 10:20:49	ga_ls8c_ard_3-2-1_100080_2022-07-23_final
2022-07-24 09:26:01	ga_ls8c_ard_3-2-1_091082_2022-07-23_final
2022-07-25 11:45:46	ga_ls8c_ard_3-2-1_114076_2022-07-25_final
2022-07-29 11:18:42	ga_ls8c_ard_3-2-1_110070_2022-07-29_final
2022-07-31 09:29:52	ga_ls8c_ard_3-2-1_092076_2022-07-30_final
2022-08-01 10:12:21	ga_ls8c_ard_3-2-1_099074_2022-08-01_final
2022-08-09 09:27:22	ga_ls8c_ard_3-2-1_091085_2022-08-08_final
2022-08-21 09:50:56	ga_ls8c_ard_3-2-1_095082_2022-08-21_final
2022-08-25 11:03:06	ga_ls8c_ard_3-2-1_107077_2022-08-25_final
2022-08-25 11:04:42	ga_ls8c_ard_3-2-1_107081_2022-08-25_final
2022-08-30 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-08-30_final
2022-09-03 10:57:42	ga_ls8c_ard_3-2-1_106079_2022-09-03_final
2022-09-05 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-09-05_final
2022-09-07 10:31:02	ga_ls8c_ard_3-2-1_102074_2022-09-07_final
2022-09-13 09:57:36	ga_ls8c_ard_3-2-1_096083_2022-09-13_final
2022-09-27 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-09-27_final
2022-10-03 09:30:53	ga_ls8c_ard_3-2-1_092078_2022-10-03_final
2022-10-07 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-07_final
2022-10-09 10:30:14	ga_ls8c_ard_3-2-1_102072_2022-10-09_final
2022-10-13 10:06:38	ga_ls8c_ard_3-2-1_098075_2022-10-13_final
2022-10-13 11:47:31	ga_ls8c_ard_3-2-1_114080_2022-10-13_final
2022-10-17 09:42:21	ga_ls8c_ard_3-2-1_094076_2022-10-17_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-25 10:31:05	ga_ls8c_ard_3-2-1_102074_2022-10-25_final
2022-11-04 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-11-04_final
2022-11-04 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-11-04_final
2022-11-16 09:55:31	ga_ls8c_ard_3-2-1_096078_2022-11-16_final
2022-11-20 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-11-20_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-25 09:50:33	ga_ls8c_ard_3-2-1_095081_2022-11-25_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-12-02 09:57:08	ga_ls8c_ard_3-2-1_096082_2022-12-02_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-03 10:39:36	ga_ls8c_ard_3-2-1_103080_2022-12-03_final
2022-12-06 09:30:49	ga_ls8c_ard_3-2-1_092078_2022-12-06_final
2022-12-06 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-12-06_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-15 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-12-14_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-18 09:56:13	ga_ls8c_ard_3-2-1_096080_2022-12-18_final
2022-12-24 10:57:10	ga_ls8c_ard_3-2-1_106078_2022-12-24_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2022-12-27 09:50:00	ga_ls8c_ard_3-2-1_095080_2022-12-27_final
2023-01-04 10:39:27	ga_ls8c_ard_3-2-1_103080_2023-01-04_final
2023-01-05 09:41:50	ga_ls8c_ard_3-2-1_094075_2023-01-05_final
2023-01-05 11:21:31	ga_ls8c_ard_3-2-1_110077_2023-01-05_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-14 09:37:34	ga_ls8c_ard_3-2-1_093080_2023-01-14_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-23 09:33:00	ga_ls8c_ard_3-2-1_092084_2023-01-23_final
2023-02-09 10:12:16	ga_ls8c_ard_3-2-1_099074_2023-02-09_final
2023-02-12 10:43:31	ga_ls8c_ard_3-2-1_104075_2023-02-12_final
2023-02-13 09:49:53	ga_ls8c_ard_3-2-1_095080_2023-02-13_final
2023-02-13 11:26:46	ga_ls8c_ard_3-2-1_111075_2023-02-13_final
2023-02-22 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-02-22_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-23 10:23:35	ga_ls8c_ard_3-2-1_101072_2023-02-23_final
2023-02-24 09:32:20	ga_ls8c_ard_3-2-1_092083_2023-02-24_final
2023-02-25 10:12:46	ga_ls8c_ard_3-2-1_099076_2023-02-25_final
2023-02-26 10:56:50	ga_ls8c_ard_3-2-1_106078_2023-02-26_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-03-07 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-03-06_final
2023-03-09 10:38:13	ga_ls8c_ard_3-2-1_103078_2023-03-09_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