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
2021-10-01 11:52:22	ga_ls8c_ard_3-2-0_115077_2021-10-01_final
2021-10-11 09:15:19	ga_ls8c_ard_3-2-0_089086_2021-10-10_final
2021-10-11 10:47:49	ga_ls8c_ard_3-2-0_105070_2021-10-11_final
2021-10-18 09:19:31	ga_ls8c_ard_3-2-0_090081_2021-10-17_final
2021-10-20 10:42:51	ga_ls8c_ard_3-2-0_104073_2021-10-20_final
2021-11-02 10:14:44	ga_ls8c_ard_3-2-0_099080_2021-11-02_final
2021-11-10 09:25:16	ga_ls8c_ard_3-2-0_091080_2021-11-09_final
2021-11-13 11:32:38	ga_ls8c_ard_3-2-0_112074_2021-11-13_final
2021-11-18 10:09:51	ga_ls8c_ard_3-2-0_099068_2021-11-18_final
2021-11-22 09:51:08	ga_ls8c_ard_3-2-0_095083_2021-11-22_final
2021-11-25 10:22:03	ga_ls8c_ard_3-2-0_100083_2021-11-25_final
2021-11-26 11:04:31	ga_ls8c_ard_3-2-0_107081_2021-11-26_final
2021-11-28 09:16:28	ga_ls8c_ard_3-2-0_089089_2021-11-27_final
2021-12-05 10:57:56	ga_ls8c_ard_3-2-1_106080_2021-12-05_final
2021-12-09 10:33:13	ga_ls8c_ard_3-2-1_102080_2021-12-09_final
2021-12-14 10:52:09	ga_ls8c_ard_3-2-1_105081_2021-12-14_final
2021-12-18 10:25:01	ga_ls8c_ard_3-2-1_101075_2021-12-18_final
2021-12-21 09:23:00	ga_ls8c_ard_3-2-1_090090_2021-12-20_final
2021-12-22 11:42:21	ga_ls8c_ard_3-2-1_113083_2021-12-22_final
2021-12-30 10:52:03	ga_ls8c_ard_3-2-1_105081_2021-12-30_final
2022-01-02 11:19:45	ga_ls8c_ard_3-2-1_110073_2022-01-02_final
2022-01-07 09:59:48	ga_ls8c_ard_3-2-1_097074_2022-01-07_final
2022-01-12 11:58:01	ga_ls8c_ard_3-2-1_116076_2022-01-12_final
2022-01-18 09:45:13	ga_ls8c_ard_3-2-1_094084_2022-01-18_final
2022-01-20 09:29:39	ga_ls8c_ard_3-2-1_092076_2022-01-19_final
2022-01-20 09:31:39	ga_ls8c_ard_3-2-1_092081_2022-01-20_final
2022-01-20 11:08:32	ga_ls8c_ard_3-2-1_108076_2022-01-20_final
2022-02-02 10:38:46	ga_ls8c_ard_3-2-1_103079_2022-02-02_final
2022-02-05 11:11:40	ga_ls8c_ard_3-2-1_108084_2022-02-05_final
2022-02-08 09:59:41	ga_ls8c_ard_3-2-1_097074_2022-02-08_final
2022-02-14 09:26:57	ga_ls8c_ard_3-2-1_091085_2022-02-13_final
2022-03-09 09:33:50	ga_ls8c_ard_3-2-1_092087_2022-03-09_final
2022-03-11 10:53:57	ga_ls8c_ard_3-2-1_106071_2022-03-11_final
2022-03-16 11:15:15	ga_ls8c_ard_3-2-1_109078_2022-03-16_final
2022-03-19 11:47:19	ga_ls8c_ard_3-2-1_114081_2022-03-19_final
2022-03-20 09:11:36	ga_ls8c_ard_3-2-1_089078_2022-03-19_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-05 10:49:10	ga_ls8c_ard_3-2-1_105075_2022-04-05_final
2022-04-06 11:35:38	ga_ls8c_ard_3-2-1_112083_2022-04-06_final
2022-04-07 10:37:37	ga_ls8c_ard_3-2-1_103077_2022-04-07_final
2022-04-21 09:14:20	ga_ls8c_ard_3-2-1_089085_2022-04-20_final
2022-04-23 10:39:38	ga_ls8c_ard_3-2-1_103082_2022-04-23_final
2022-04-25 10:23:16	ga_ls8c_ard_3-2-1_101072_2022-04-25_final
2022-05-01 09:52:10	ga_ls8c_ard_3-2-1_095087_2022-05-01_final
2022-05-01 11:24:40	ga_ls8c_ard_3-2-1_111071_2022-05-01_final
2022-05-05 11:02:00	ga_ls8c_ard_3-2-1_107076_2022-05-05_final
2022-05-13 10:13:26	ga_ls8c_ard_3-2-1_099078_2022-05-13_final
2022-05-21 11:02:30	ga_ls8c_ard_3-2-1_107077_2022-05-21_final
2022-05-25 10:39:46	ga_ls8c_ard_3-2-1_103082_2022-05-25_final
2022-05-26 11:24:13	ga_ls8c_ard_3-2-1_110085_2022-05-26_final
2022-05-31 09:59:32	ga_ls8c_ard_3-2-1_097074_2022-05-31_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-05 10:16:57	ga_ls8c_ard_3-2-1_100071_2022-06-05_final
2022-06-11 09:43:57	ga_ls8c_ard_3-2-1_094081_2022-06-11_final
2022-06-11 11:23:38	ga_ls8c_ard_3-2-1_110083_2022-06-11_final
2022-06-19 10:29:04	ga_ls8c_ard_3-2-1_102070_2022-06-19_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_2022-06-20_final
2022-06-27 09:44:27	ga_ls8c_ard_3-2-1_094082_2022-06-27_final
2022-06-28 10:23:43	ga_ls8c_ard_3-2-1_101072_2022-06-28_final
2022-07-06 09:37:53	ga_ls8c_ard_3-2-1_093081_2022-07-06_final
2022-07-07 10:19:09	ga_ls8c_ard_3-2-1_100076_2022-07-07_final
2022-07-24 09:23:37	ga_ls8c_ard_3-2-1_091076_2022-07-23_final
2022-08-01 10:13:56	ga_ls8c_ard_3-2-1_099078_2022-08-01_final
2022-08-02 10:58:25	ga_ls8c_ard_3-2-1_106081_2022-08-02_final
2022-08-07 11:12:12	ga_ls8c_ard_3-2-1_109069_2022-08-07_final
2022-08-09 09:26:58	ga_ls8c_ard_3-2-1_091084_2022-08-08_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-09-18 10:14:10	ga_ls8c_ard_3-2-1_099078_2022-09-18_final
2022-09-18 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-09-18_final
2022-09-20 11:41:29	ga_ls8c_ard_3-2-1_113080_2022-09-20_final
2022-09-22 09:48:15	ga_ls8c_ard_3-2-1_095075_2022-09-22_final
2022-10-01 11:19:44	ga_ls8c_ard_3-2-1_110072_2022-10-01_final
2022-10-10 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-10-10_final
2022-10-14 09:15:24	ga_ls8c_ard_3-2-1_089086_2022-10-13_final
2022-10-30 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-10-29_final
2022-11-10 10:31:04	ga_ls8c_ard_3-2-1_102074_2022-11-10_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-26 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-11-26_final
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-06 11:11:17	ga_ls8c_ard_3-2-1_108082_2022-12-06_final
2022-12-09 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-12-09_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-20 09:45:50	ga_ls8c_ard_3-2-1_094085_2022-12-20_final
2022-12-27 09:50:48	ga_ls8c_ard_3-2-1_095082_2022-12-27_final
2023-01-02 10:52:13	ga_ls8c_ard_3-2-1_105081_2023-01-02_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-25 09:17:04	ga_ls8c_ard_3-2-1_090075_2023-01-24_final
2023-01-25 09:21:03	ga_ls8c_ard_3-2-1_090085_2023-01-24_final
2023-01-25 10:58:20	ga_ls8c_ard_3-2-1_106081_2023-01-25_final
2023-01-26 09:57:08	ga_ls8c_ard_3-2-1_097067_2023-01-26_final
2023-02-01 09:26:27	ga_ls8c_ard_3-2-1_091083_2023-01-31_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-02-11 09:59:53	ga_ls8c_ard_3-2-1_097074_2023-02-11_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-03-07 09:13:43	ga_ls8c_ard_3-2-1_089083_2023-03-06_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