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
2022-03-09 09:33:50	ga_ls8c_ard_3-2-1_092087_2022-03-09_final
2022-03-20 10:46:53	ga_ls8c_ard_3-2-1_105069_2022-03-20_final
2022-03-21 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-03-21_final
2022-03-26 11:51:48	ga_ls8c_ard_3-2-1_115077_2022-03-26_final
2022-03-30 09:45:44	ga_ls8c_ard_3-2-1_095071_2022-03-30_final
2022-04-11 10:10:57	ga_ls8c_ard_3-2-1_099072_2022-04-11_final
2022-04-12 10:55:48	ga_ls8c_ard_3-2-1_106076_2022-04-12_final
2022-04-14 09:06:34	ga_ls8c_ard_3-2-1_088081_2022-04-13_final
2022-04-19 11:01:11	ga_ls8c_ard_3-2-1_107074_2022-04-19_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-04 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-05-04_final
2022-05-08 09:57:15	ga_ls8c_ard_3-2-1_096084_2022-05-08_final
2022-05-13 10:14:14	ga_ls8c_ard_3-2-1_099080_2022-05-13_final
2022-05-17 09:46:44	ga_ls8c_ard_3-2-1_095073_2022-05-17_final
2022-05-28 09:33:46	ga_ls8c_ard_3-2-1_092087_2022-05-28_final
2022-05-28 11:11:04	ga_ls8c_ard_3-2-1_108083_2022-05-28_final
2022-05-30 10:53:09	ga_ls8c_ard_3-2-1_106069_2022-05-30_final
2022-06-03 10:32:53	ga_ls8c_ard_3-2-1_102080_2022-06-03_final
2022-06-04 11:13:22	ga_ls8c_ard_3-2-1_109073_2022-06-04_final
2022-06-18 09:47:00	ga_ls8c_ard_3-2-1_095073_2022-06-18_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-06-18 09:52:35	ga_ls8c_ard_3-2-1_095087_2022-06-18_final
2022-06-25 11:31:42	ga_ls8c_ard_3-2-1_112072_2022-06-25_final
2022-06-25 11:36:29	ga_ls8c_ard_3-2-1_112084_2022-06-25_final
2022-06-28 10:27:43	ga_ls8c_ard_3-2-1_101082_2022-06-28_final
2022-07-01 10:58:37	ga_ls8c_ard_3-2-1_106082_2022-07-01_final
2022-07-07 11:58:02	ga_ls8c_ard_3-2-1_116076_2022-07-07_final
2022-07-09 10:04:47	ga_ls8c_ard_3-2-1_098071_2022-07-09_final
2022-07-17 10:53:25	ga_ls8c_ard_3-2-1_106069_2022-07-17_final
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-08-03 10:02:00	ga_ls8c_ard_3-2-1_097079_2022-08-03_final
2022-08-06 10:30:32	ga_ls8c_ard_3-2-1_102073_2022-08-06_final
2022-08-12 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-08-12_final
2022-08-14 09:44:44	ga_ls8c_ard_3-2-1_094082_2022-08-14_final
2022-08-25 09:23:01	ga_ls8c_ard_3-2-1_091074_2022-08-24_final
2022-09-10 11:05:57	ga_ls8c_ard_3-2-1_107084_2022-09-10_final
2022-09-18 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-09-18_final
2022-09-30 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-09-30_final
2022-10-04 10:15:44	ga_ls8c_ard_3-2-1_099082_2022-10-04_final
2022-10-12 11:01:53	ga_ls8c_ard_3-2-1_107074_2022-10-12_final
2022-10-14 09:14:36	ga_ls8c_ard_3-2-1_089084_2022-10-13_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-22 09:58:33	ga_ls8c_ard_3-2-1_097070_2022-10-22_final
2022-10-25 10:29:53	ga_ls8c_ard_3-2-1_102071_2022-10-25_final
2022-11-06 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-11-05_final
2022-11-06 09:22:55	ga_ls8c_ard_3-2-1_090089_2022-11-05_final
2022-11-07 09:59:00	ga_ls8c_ard_3-2-1_097071_2022-11-07_final
2022-11-15 10:47:33	ga_ls8c_ard_3-2-1_105069_2022-11-15_final
2022-11-20 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-11-19_final
2022-11-26 10:29:49	ga_ls8c_ard_3-2-1_102071_2022-11-26_final
2022-12-02 11:32:26	ga_ls8c_ard_3-2-1_112073_2022-12-02_final
2022-12-07 10:11:41	ga_ls8c_ard_3-2-1_099072_2022-12-07_final
2022-12-19 10:35:05	ga_ls8c_ard_3-2-1_103069_2022-12-19_final
2022-12-27 11:25:41	ga_ls8c_ard_3-2-1_111072_2022-12-27_final
2022-12-30 10:19:19	ga_ls8c_ard_3-2-1_100076_2022-12-30_final
2023-01-05 11:21:07	ga_ls8c_ard_3-2-1_110076_2023-01-05_final
2023-01-17 10:09:37	ga_ls8c_ard_3-2-1_098083_2023-01-17_final
2023-01-18 09:13:35	ga_ls8c_ard_3-2-1_089082_2023-01-17_final
2023-01-18 09:13:59	ga_ls8c_ard_3-2-1_089083_2023-01-17_final
2023-01-25 10:55:33	ga_ls8c_ard_3-2-1_106074_2023-01-25_final
2023-02-04 09:58:09	ga_ls8c_ard_3-2-1_096085_2023-02-04_final
2023-02-17 09:27:06	ga_ls8c_ard_3-2-1_091085_2023-02-16_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-03-03 11:14:34	ga_ls8c_ard_3-2-1_109076_2023-03-03_final
2023-03-05 09:28:30	ga_ls8c_ard_3-2-1_091089_2023-03-04_final
2023-03-07 09:11:43	ga_ls8c_ard_3-2-1_089078_2023-03-06_final
2023-03-07 09:12:55	ga_ls8c_ard_3-2-1_089081_2023-03-06_final
2023-03-14 09:21:04	ga_ls8c_ard_3-2-1_090086_2023-03-13_final
2023-03-20 10:18:48	ga_ls8c_ard_3-2-1_100076_2023-03-20_final
2023-03-22 10:04:48	ga_ls8c_ard_3-2-1_098072_2023-03-22_final
2023-03-22 11:44:29	ga_ls8c_ard_3-2-1_114074_2023-03-22_final
2023-03-22 11:44:29	ga_ls8c_ard_3-2-1_114074_2023-03-22_nrt
2023-03-31 09:58:09	ga_ls8c_ard_3-2-1_097071_2023-03-31_final
2023-04-01 09:07:18	ga_ls8c_ard_3-2-1_088083_2023-03-31_final
2023-04-02 11:25:03	ga_ls8c_ard_3-2-1_111072_2023-04-02_final
2023-04-03 10:29:48	ga_ls8c_ard_3-2-1_102073_2023-04-03_final
2023-04-13 09:31:49	ga_ls8c_ard_3-2-1_092083_2023-04-13_final
2023-04-21 10:21:36	ga_ls8c_ard_3-2-1_100084_2023-04-21_final
2023-04-24 10:48:55	ga_ls8c_ard_3-2-1_105075_2023-04-24_final
2023-05-01 09:22:10	ga_ls8c_ard_3-2-1_090090_2023-04-30_final
2023-05-25 10:03:27	ga_ls8c_ard_3-2-1_098070_2023-05-25_final
2023-05-26 09:13:01	ga_ls8c_ard_3-2-1_089083_2023-05-25_final
2023-05-26 09:15:49	ga_ls8c_ard_3-2-1_089090_2023-05-25_final
2023-05-29 09:45:07	ga_ls8c_ard_3-2-1_094086_2023-05-29_final
2023-06-03 11:41:22	ga_ls8c_ard_3-2-1_113083_2023-06-03_final
2023-06-18 09:17:46	ga_ls8c_ard_3-2-1_090079_2023-06-17_final
2023-06-21 11:28:21	ga_ls8c_ard_3-2-1_111081_2023-06-21_final
2023-06-26 11:44:09	ga_ls8c_ard_3-2-1_114074_2023-06-26_final
2023-07-01 10:26:17	ga_ls8c_ard_3-2-1_101080_2023-07-01_final
2023-07-01 10:27:29	ga_ls8c_ard_3-2-1_101083_2023-07-01_final
2023-07-02 09:32:16	ga_ls8c_ard_3-2-1_092084_2023-07-02_final
2023-07-17 10:25:11	ga_ls8c_ard_3-2-1_101077_2023-07-17_final
2023-07-27 09:23:04	ga_ls8c_ard_3-2-1_091076_2023-07-26_final
2023-08-01 09:45:15	ga_ls8c_ard_3-2-1_094085_2023-08-01_final
2023-08-05 09:20:57	ga_ls8c_ard_3-2-1_090086_2023-08-04_final
2023-08-05 10:53:03	ga_ls8c_ard_3-2-1_106069_2023-08-05_final
2023-08-21 09:21:52	ga_ls8c_ard_3-2-1_090088_2023-08-20_final
2023-08-27 10:17:18	ga_ls8c_ard_3-2-1_100072_2023-08-27_nrt
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_nrt
2023-09-06 10:55:09	ga_ls8c_ard_3-2-1_106074_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