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
2020-02-05 09:50:03	ga_ls8c_ard_3-1-0_095081_2020-02-05_final
2022-03-30 09:47:44	ga_ls8c_ard_3-2-1_095076_2022-03-30_final
2022-03-30 09:50:08	ga_ls8c_ard_3-2-1_095082_2022-03-30_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-03-30 11:26:13	ga_ls8c_ard_3-2-1_111075_2022-03-30_final
2022-03-31 10:31:48	ga_ls8c_ard_3-2-1_102078_2022-03-31_final
2022-04-01 11:14:39	ga_ls8c_ard_3-2-1_109077_2022-04-01_final
2022-04-01 11:17:27	ga_ls8c_ard_3-2-1_109084_2022-04-01_final
2022-04-02 10:17:26	ga_ls8c_ard_3-2-1_100073_2022-04-02_final
2022-04-02 10:21:26	ga_ls8c_ard_3-2-1_100083_2022-04-02_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-03 11:03:54	ga_ls8c_ard_3-2-1_107081_2022-04-03_final
2022-04-04 10:05:29	ga_ls8c_ard_3-2-1_098074_2022-04-04_final
2022-04-05 10:47:34	ga_ls8c_ard_3-2-1_105071_2022-04-05_final
2022-04-05 10:48:22	ga_ls8c_ard_3-2-1_105073_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
2022-04-08 09:40:25	ga_ls8c_ard_3-2-1_094073_2022-04-08_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-09 10:24:53	ga_ls8c_ard_3-2-1_101076_2022-04-09_final
2022-04-09 10:27:41	ga_ls8c_ard_3-2-1_101083_2022-04-09_final
2022-04-12 10:54:37	ga_ls8c_ard_3-2-1_106073_2022-04-12_final
2022-04-12 10:55:01	ga_ls8c_ard_3-2-1_106074_2022-04-12_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-13 10:01:47	ga_ls8c_ard_3-2-1_097080_2022-04-13_final
2022-04-13 10:03:47	ga_ls8c_ard_3-2-1_097085_2022-04-13_final
2022-04-13 11:39:52	ga_ls8c_ard_3-2-1_113078_2022-04-13_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-13 11:41:04	ga_ls8c_ard_3-2-1_113081_2022-04-13_final
2022-04-13 11:41:28	ga_ls8c_ard_3-2-1_113082_2022-04-13_final
2022-04-14 10:40:40	ga_ls8c_ard_3-2-1_104069_2022-04-14_final
2022-04-15 09:47:02	ga_ls8c_ard_3-2-1_095074_2022-04-15_final
2022-04-15 11:25:56	ga_ls8c_ard_3-2-1_111074_2022-04-15_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-16 10:31:30	ga_ls8c_ard_3-2-1_102077_2022-04-16_final
2022-04-17 09:39:28	ga_ls8c_ard_3-2-1_093086_2022-04-17_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-20 10:05:10	ga_ls8c_ard_3-2-1_098073_2022-04-20_final
2022-04-20 10:06:22	ga_ls8c_ard_3-2-1_098076_2022-04-20_final
2022-04-20 11:44:51	ga_ls8c_ard_3-2-1_114075_2022-04-20_final
2022-04-20 11:46:27	ga_ls8c_ard_3-2-1_114079_2022-04-20_final
2022-04-22 09:52:24	ga_ls8c_ard_3-2-1_096072_2022-04-22_final
2022-04-22 11:35:40	ga_ls8c_ard_3-2-1_112083_2022-04-22_final
2022-04-23 10:35:15	ga_ls8c_ard_3-2-1_103071_2022-04-23_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-23 10:39:38	ga_ls8c_ard_3-2-1_103082_2022-04-23_final
2022-04-25 10:26:28	ga_ls8c_ard_3-2-1_101080_2022-04-25_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-27 10:14:29	ga_ls8c_ard_3-2-1_099081_2022-04-27_final
2022-04-28 10:54:56	ga_ls8c_ard_3-2-1_106074_2022-04-28_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-04-30 10:44:59	ga_ls8c_ard_3-2-1_104080_2022-04-30_final
2022-05-01 09:47:47	ga_ls8c_ard_3-2-1_095076_2022-05-01_final
2022-05-01 09:50:11	ga_ls8c_ard_3-2-1_095082_2022-05-01_final
2022-05-01 11:26:16	ga_ls8c_ard_3-2-1_111075_2022-05-01_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-04 10:20:19	ga_ls8c_ard_3-2-1_100080_2022-05-04_final
2022-05-04 10:20:43	ga_ls8c_ard_3-2-1_100081_2022-05-04_final
2022-05-06 10:05:12	ga_ls8c_ard_3-2-1_098073_2022-05-06_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-07 10:52:03	ga_ls8c_ard_3-2-1_105082_2022-05-07_final
2022-05-09 10:34:32	ga_ls8c_ard_3-2-1_103069_2022-05-09_final
2022-05-09 10:39:43	ga_ls8c_ard_3-2-1_103082_2022-05-09_final
2022-05-11 10:24:59	ga_ls8c_ard_3-2-1_101076_2022-05-11_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-14 10:53:54	ga_ls8c_ard_3-2-1_106071_2022-05-14_final
2022-05-14 10:55:06	ga_ls8c_ard_3-2-1_106074_2022-05-14_final
2022-05-15 11:40:22	ga_ls8c_ard_3-2-1_113079_2022-05-15_final
2022-05-18 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-05-18_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-24 09:53:19	ga_ls8c_ard_3-2-1_096074_2022-05-24_final
2022-05-24 09:56:07	ga_ls8c_ard_3-2-1_096081_2022-05-24_final
2022-05-25 10:36:11	ga_ls8c_ard_3-2-1_103073_2022-05-25_final
2022-05-26 09:40:33	ga_ls8c_ard_3-2-1_094073_2022-05-26_final
2022-05-26 11:19:50	ga_ls8c_ard_3-2-1_110074_2022-05-26_final
2022-05-26 11:21:50	ga_ls8c_ard_3-2-1_110079_2022-05-26_final
2022-05-30 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-05-30_final
2022-05-31 09:57:09	ga_ls8c_ard_3-2-1_097068_2022-05-31_final
2022-05-31 09:59:32	ga_ls8c_ard_3-2-1_097074_2022-05-31_final
2022-06-02 09:47:36	ga_ls8c_ard_3-2-1_095075_2022-06-02_final
2022-06-02 11:26:53	ga_ls8c_ard_3-2-1_111076_2022-06-02_final
2022-06-02 11:28:53	ga_ls8c_ard_3-2-1_111081_2022-06-02_final
2022-06-04 09:37:40	ga_ls8c_ard_3-2-1_093081_2022-06-04_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-05 10:20:09	ga_ls8c_ard_3-2-1_100079_2022-06-05_final
2022-06-07 10:06:13	ga_ls8c_ard_3-2-1_098075_2022-06-07_final
2022-06-07 10:08:37	ga_ls8c_ard_3-2-1_098081_2022-06-07_final
2022-06-08 10:47:54	ga_ls8c_ard_3-2-1_105071_2022-06-08_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-13 09:30:00	ga_ls8c_ard_3-2-1_092077_2022-06-13_final
2022-06-16 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-06-16_final
2022-06-19 10:31:52	ga_ls8c_ard_3-2-1_102077_2022-06-19_final
2022-06-20 11:13:08	ga_ls8c_ard_3-2-1_109072_2022-06-20_final
2022-06-21 10:18:43	ga_ls8c_ard_3-2-1_100075_2022-06-21_final
2022-06-22 11:02:23	ga_ls8c_ard_3-2-1_107076_2022-06-22_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