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
2022-05-02 10:29:04	ga_ls8c_ard_3-2-1_102071_2022-05-02_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-03 11:16:44	ga_ls8c_ard_3-2-1_109082_2022-05-03_final
2022-05-06 10:05:59	ga_ls8c_ard_3-2-1_098075_2022-05-06_final
2022-05-07 10:48:04	ga_ls8c_ard_3-2-1_105072_2022-05-07_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-09 10:34:56	ga_ls8c_ard_3-2-1_103070_2022-05-09_final
2022-05-09 10:39:43	ga_ls8c_ard_3-2-1_103082_2022-05-09_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-12 11:09:51	ga_ls8c_ard_3-2-1_108080_2022-05-12_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-05-30 09:19:51	ga_ls8c_ard_3-2-1_090083_2022-05-29_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-06 11:01:02	ga_ls8c_ard_3-2-1_107073_2022-06-06_final
2022-06-08 10:47:06	ga_ls8c_ard_3-2-1_105069_2022-06-08_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-10 10:37:10	ga_ls8c_ard_3-2-1_103075_2022-06-10_final
2022-06-22 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-06-21_final
2022-06-23 10:06:22	ga_ls8c_ard_3-2-1_098075_2022-06-23_final
2022-06-23 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-06-23_final
2022-06-28 10:24:55	ga_ls8c_ard_3-2-1_101075_2022-06-28_final
2022-06-29 11:08:35	ga_ls8c_ard_3-2-1_108076_2022-06-29_final
2022-07-03 10:43:28	ga_ls8c_ard_3-2-1_104075_2022-07-03_final
2022-07-04 09:48:15	ga_ls8c_ard_3-2-1_095076_2022-07-04_final
2022-07-06 09:35:29	ga_ls8c_ard_3-2-1_093075_2022-07-06_final
2022-07-08 11:05:12	ga_ls8c_ard_3-2-1_107083_2022-07-08_final
2022-07-09 11:45:16	ga_ls8c_ard_3-2-1_114075_2022-07-09_final
2022-07-10 09:14:21	ga_ls8c_ard_3-2-1_089084_2022-07-09_final
2022-07-11 09:52:49	ga_ls8c_ard_3-2-1_096072_2022-07-11_final
2022-07-17 09:18:08	ga_ls8c_ard_3-2-1_090078_2022-07-16_final
2022-07-18 09:59:25	ga_ls8c_ard_3-2-1_097073_2022-07-18_final
2022-09-23 10:32:19	ga_ls8c_ard_3-2-1_102077_2022-09-23_final
2022-10-02 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-10-02_final
2022-10-06 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-06_final
2022-10-09 10:30:14	ga_ls8c_ard_3-2-1_102072_2022-10-09_final
2022-10-10 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-10-10_final
2022-10-11 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-10-11_final
2022-10-20 10:15:17	ga_ls8c_ard_3-2-1_099081_2022-10-20_final
2022-10-20 10:16:53	ga_ls8c_ard_3-2-1_099085_2022-10-20_final
2023-12-03 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-12-03_final
2023-12-07 09:43:30	ga_ls8c_ard_3-2-1_094080_2023-12-07_final
2023-12-08 10:26:23	ga_ls8c_ard_3-2-1_101079_2023-12-08_final
2023-12-09 09:31:10	ga_ls8c_ard_3-2-1_092080_2023-12-09_final
2023-12-10 10:12:27	ga_ls8c_ard_3-2-1_099075_2023-12-10_final
2023-12-10 11:50:56	ga_ls8c_ard_3-2-1_115074_2023-12-10_final
2023-12-11 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-12-10_final
2023-12-11 10:56:31	ga_ls8c_ard_3-2-1_106077_2023-12-11_final
2023-12-14 09:50:58	ga_ls8c_ard_3-2-1_095083_2023-12-14_final
2023-12-14 11:29:27	ga_ls8c_ard_3-2-1_111082_2023-12-14_final
2023-12-21 09:57:12	ga_ls8c_ard_3-2-1_096083_2023-12-21_final
2023-12-21 11:36:29	ga_ls8c_ard_3-2-1_112084_2023-12-21_final
2023-12-23 09:42:26	ga_ls8c_ard_3-2-1_094077_2023-12-23_final
2023-12-23 09:46:02	ga_ls8c_ard_3-2-1_094086_2023-12-23_final
2023-12-25 09:30:28	ga_ls8c_ard_3-2-1_092078_2023-12-25_final
2023-12-28 10:02:32	ga_ls8c_ard_3-2-1_097081_2023-12-28_final
2023-12-29 10:42:12	ga_ls8c_ard_3-2-1_104072_2023-12-29_final
2023-12-31 10:31:00	ga_ls8c_ard_3-2-1_102075_2023-12-31_final
2024-01-01 09:37:46	ga_ls8c_ard_3-2-1_093081_2024-01-01_final
2024-01-01 09:39:46	ga_ls8c_ard_3-2-1_093086_2024-01-01_final
2024-01-02 10:18:37	ga_ls8c_ard_3-2-1_100075_2024-01-02_final
2024-01-08 09:41:55	ga_ls8c_ard_3-2-1_094076_2024-01-08_final
2024-01-08 11:22:24	ga_ls8c_ard_3-2-1_110080_2024-01-08_final
2024-01-11 10:15:14	ga_ls8c_ard_3-2-1_099082_2024-01-11_final
2024-01-12 09:18:25	ga_ls8c_ard_3-2-1_090079_2024-01-11_final
2024-01-15 09:51:43	ga_ls8c_ard_3-2-1_095085_2024-01-15_final
2024-01-17 09:37:45	ga_ls8c_ard_3-2-1_093081_2024-01-17_final
2024-01-18 11:58:18	ga_ls8c_ard_3-2-1_116077_2024-01-18_final
2024-01-19 11:04:40	ga_ls8c_ard_3-2-1_107082_2024-01-19_final
2024-01-20 11:47:07	ga_ls8c_ard_3-2-1_114080_2024-01-20_final
2024-01-24 09:41:28	ga_ls8c_ard_3-2-1_094075_2024-01-24_final
2024-01-24 11:23:32	ga_ls8c_ard_3-2-1_110083_2024-01-24_final
2024-01-26 09:32:15	ga_ls8c_ard_3-2-1_092083_2024-01-26_final
2024-01-28 09:19:54	ga_ls8c_ard_3-2-1_090083_2024-01-27_final
2024-01-30 10:40:52	ga_ls8c_ard_3-2-1_104069_2024-01-30_final
2024-02-01 10:30:55	ga_ls8c_ard_3-2-1_102075_2024-02-01_final
2024-02-02 09:37:18	ga_ls8c_ard_3-2-1_093080_2024-02-02_final
2024-02-03 11:58:16	ga_ls8c_ard_3-2-1_116077_2024-02-03_final
2024-02-06 10:51:30	ga_ls8c_ard_3-2-1_105080_2024-02-06_final
2024-02-09 09:43:55	ga_ls8c_ard_3-2-1_094081_2024-02-09_final
2024-02-09 09:45:07	ga_ls8c_ard_3-2-1_094084_2024-02-09_final
2024-02-09 11:22:48	ga_ls8c_ard_3-2-1_110081_2024-02-09_final
2024-02-10 10:27:11	ga_ls8c_ard_3-2-1_101081_2024-02-10_final
2024-02-15 10:44:29	ga_ls8c_ard_3-2-1_104078_2024-02-15_final
2024-02-16 09:49:39	ga_ls8c_ard_3-2-1_095080_2024-02-16_final
2024-02-18 09:36:06	ga_ls8c_ard_3-2-1_093077_2024-02-18_final
2024-02-20 11:03:25	ga_ls8c_ard_3-2-1_107079_2024-02-20_final
2024-02-21 11:47:29	ga_ls8c_ard_3-2-1_114081_2024-02-21_final
2024-02-27 11:06:22	ga_ls8c_ard_3-2-1_108071_2024-02-27_final
2024-02-29 09:18:41	ga_ls8c_ard_3-2-1_090080_2024-02-28_final
2024-03-12 09:44:52	ga_ls8c_ard_3-2-1_094084_2024-03-12_nrt
2024-03-13 10:24:31	ga_ls8c_ard_3-2-1_101075_2024-03-13_nrt
2024-03-21 09:34:59	ga_ls8c_ard_3-2-1_093075_2024-03-21_nrt
2024-03-25 09:13:46	ga_ls8c_ard_3-2-1_089084_2024-03-24_nrt
2024-04-04 09:47:13	ga_ls8c_ard_3-2-1_095075_2024-04-04_nrt
2024-04-04 09:51:12	ga_ls8c_ard_3-2-1_095085_2024-04-04_nrt
2024-04-11 09:56:33	ga_ls8c_ard_3-2-1_096083_2024-04-11_nrt
2024-04-14 10:27:01	ga_ls8c_ard_3-2-1_101082_2024-04-14_nrt

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