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
2021-10-03 11:41:37	ga_ls8c_ard_3-2-0_113081_2021-10-03_final
2021-10-30 09:38:39	ga_ls8c_ard_3-2-0_094067_2021-10-30_final
2021-11-24 11:14:52	ga_ls8c_ard_3-2-0_109076_2021-11-24_final
2021-12-01 11:19:28	ga_ls8c_ard_3-2-0_110072_2021-12-01_final
2021-12-02 10:23:27	ga_ls8c_ard_3-2-0_101071_2021-12-02_final
2021-12-04 10:15:29	ga_ls8c_ard_3-2-0_099082_2021-12-04_final
2021-12-05 10:53:33	ga_ls8c_ard_3-2-1_106069_2021-12-05_final
2021-12-09 10:34:01	ga_ls8c_ard_3-2-1_102082_2021-12-09_final
2021-12-12 11:00:07	ga_ls8c_ard_3-2-1_107070_2021-12-12_final
2021-12-20 11:51:32	ga_ls8c_ard_3-2-1_115075_2021-12-20_final
2021-12-22 09:57:05	ga_ls8c_ard_3-2-1_097067_2021-12-22_final
2021-12-23 10:43:08	ga_ls8c_ard_3-2-1_104074_2021-12-23_final
2021-12-28 09:24:45	ga_ls8c_ard_3-2-1_091079_2021-12-27_final
2021-12-30 09:16:22	ga_ls8c_ard_3-2-1_089089_2021-12-29_final
2022-01-12 10:21:56	ga_ls8c_ard_3-2-1_100083_2022-01-12_final
2022-01-13 09:27:30	ga_ls8c_ard_3-2-1_091086_2022-01-12_final
2022-01-13 11:05:35	ga_ls8c_ard_3-2-1_107084_2022-01-13_final
2022-01-16 09:58:23	ga_ls8c_ard_3-2-1_096086_2022-01-16_final
2022-01-21 11:52:59	ga_ls8c_ard_3-2-1_115079_2022-01-21_final
2022-01-26 10:29:01	ga_ls8c_ard_3-2-1_102070_2022-01-26_final
2022-01-28 11:57:55	ga_ls8c_ard_3-2-1_116076_2022-01-28_final
2022-01-29 09:28:12	ga_ls8c_ard_3-2-1_091088_2022-01-28_final
2022-02-01 09:57:55	ga_ls8c_ard_3-2-1_096085_2022-02-01_final
2022-02-02 10:37:11	ga_ls8c_ard_3-2-1_103075_2022-02-02_final
2022-02-26 11:24:55	ga_ls8c_ard_3-2-1_111071_2022-02-26_final
2022-03-02 09:25:17	ga_ls8c_ard_3-2-1_091081_2022-03-01_final
2022-03-07 11:19:30	ga_ls8c_ard_3-2-1_110073_2022-03-07_final
2022-03-10 10:11:06	ga_ls8c_ard_3-2-1_099072_2022-03-10_final
2022-03-23 11:20:09	ga_ls8c_ard_3-2-1_110075_2022-03-23_final
2022-03-30 09:46:32	ga_ls8c_ard_3-2-1_095073_2022-03-30_final
2022-04-05 10:46:22	ga_ls8c_ard_3-2-1_105068_2022-04-05_final
2022-04-11 10:14:08	ga_ls8c_ard_3-2-1_099080_2022-04-11_final
2022-04-12 09:21:43	ga_ls8c_ard_3-2-1_090088_2022-04-11_final
2022-04-17 11:16:45	ga_ls8c_ard_3-2-1_109082_2022-04-17_final
2022-04-20 10:09:57	ga_ls8c_ard_3-2-1_098085_2022-04-20_final
2022-04-26 09:31:38	ga_ls8c_ard_3-2-1_092082_2022-04-26_final
2022-05-05 09:28:18	ga_ls8c_ard_3-2-1_091089_2022-05-04_final
2022-05-14 09:21:01	ga_ls8c_ard_3-2-1_090086_2022-05-13_final
2022-05-20 11:58:32	ga_ls8c_ard_3-2-1_116078_2022-05-20_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-25 09:57:36	ga_ls8c_ard_3-2-1_096084_2022-06-25_final
2022-07-08 11:02:00	ga_ls8c_ard_3-2-1_107075_2022-07-08_final
2022-07-10 10:52:26	ga_ls8c_ard_3-2-1_105082_2022-07-10_final
2022-07-16 10:14:08	ga_ls8c_ard_3-2-1_099079_2022-07-16_final
2022-07-20 11:26:22	ga_ls8c_ard_3-2-1_111074_2022-07-20_final
2022-07-24 09:27:12	ga_ls8c_ard_3-2-1_091085_2022-07-23_final
2022-07-24 11:02:30	ga_ls8c_ard_3-2-1_107076_2022-07-24_final
2022-08-09 09:22:34	ga_ls8c_ard_3-2-1_091073_2022-08-08_final
2022-08-11 09:16:37	ga_ls8c_ard_3-2-1_089089_2022-08-10_final
2022-08-11 10:47:07	ga_ls8c_ard_3-2-1_105068_2022-08-11_final
2022-08-14 09:44:44	ga_ls8c_ard_3-2-1_094082_2022-08-14_final
2022-08-17 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-08-17_final
2022-08-17 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-08-17_final
2022-08-18 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-08-17_final
2022-08-18 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-08-18_final
2022-08-25 11:01:54	ga_ls8c_ard_3-2-1_107074_2022-08-25_final
2022-08-26 10:05:05	ga_ls8c_ard_3-2-1_098071_2022-08-26_final
2022-09-03 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-09-02_final
2022-09-09 10:20:17	ga_ls8c_ard_3-2-1_100078_2022-09-09_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-11 10:05:09	ga_ls8c_ard_3-2-1_098071_2022-09-11_final
2022-09-12 09:16:43	ga_ls8c_ard_3-2-1_089089_2022-09-11_final
2022-10-01 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-10-01_final
2022-10-04 10:09:45	ga_ls8c_ard_3-2-1_099067_2022-10-04_final
2022-10-04 10:15:44	ga_ls8c_ard_3-2-1_099082_2022-10-04_final
2022-10-09 10:30:38	ga_ls8c_ard_3-2-1_102073_2022-10-09_final
2022-10-12 11:02:17	ga_ls8c_ard_3-2-1_107075_2022-10-12_final
2022-10-13 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-10-13_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2022-10-14 10:47:06	ga_ls8c_ard_3-2-1_105068_2022-10-14_final
2022-10-15 09:56:41	ga_ls8c_ard_3-2-1_096081_2022-10-15_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-20 10:14:29	ga_ls8c_ard_3-2-1_099079_2022-10-20_final
2022-10-20 11:52:58	ga_ls8c_ard_3-2-1_115078_2022-10-20_final
2022-10-21 09:23:16	ga_ls8c_ard_3-2-1_090090_2022-10-20_final
2022-11-02 09:44:28	ga_ls8c_ard_3-2-1_094081_2022-11-02_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-29 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-28_final
2022-12-15 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-12-15_final
2022-12-17 09:13:46	ga_ls8c_ard_3-2-1_089082_2022-12-16_final
2023-01-03 09:53:48	ga_ls8c_ard_3-2-1_096074_2023-01-03_final
2023-01-03 09:58:11	ga_ls8c_ard_3-2-1_096085_2023-01-03_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-20 10:40:09	ga_ls8c_ard_3-2-1_103082_2023-01-20_final
2023-01-23 09:29:24	ga_ls8c_ard_3-2-1_092075_2023-01-22_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-03-13 11:51:11	ga_ls8c_ard_3-2-1_115075_2023-03-13_final
2023-03-23 09:11:10	ga_ls8c_ard_3-2-1_089077_2023-03-22_final
2023-03-28 09:27:41	ga_ls8c_ard_3-2-1_092072_2023-03-27_final
2023-04-01 10:45:00	ga_ls8c_ard_3-2-1_104080_2023-04-01_final
2023-04-07 10:03:48	ga_ls8c_ard_3-2-1_098070_2023-04-07_final
2023-04-08 09:14:09	ga_ls8c_ard_3-2-1_089085_2023-04-07_final
2023-04-11 09:39:47	ga_ls8c_ard_3-2-1_094072_2023-04-11_final
2023-04-27 11:18:37	ga_ls8c_ard_3-2-1_110072_2023-04-27_final
2023-05-02 11:37:55	ga_ls8c_ard_3-2-1_113074_2023-05-02_final
2023-05-17 09:20:45	ga_ls8c_ard_3-2-1_090087_2023-05-16_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