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
2022-01-15 10:46:26	ga_ls8c_ard_3-2-1_105067_2022-01-15_final
2022-02-16 10:46:17	ga_ls8c_ard_3-2-1_105067_2022-02-16_final
2022-02-17 11:35:07	ga_ls8c_ard_3-2-1_112081_2022-02-17_final
2022-02-18 10:36:41	ga_ls8c_ard_3-2-1_103074_2022-02-18_final
2022-02-20 10:23:55	ga_ls8c_ard_3-2-1_101073_2022-02-20_final
2022-02-25 10:42:27	ga_ls8c_ard_3-2-1_104073_2022-02-25_final
2022-03-02 09:24:53	ga_ls8c_ard_3-2-1_091080_2022-03-01_final
2022-03-12 11:41:36	ga_ls8c_ard_3-2-1_113082_2022-03-12_final
2022-03-17 10:18:01	ga_ls8c_ard_3-2-1_100074_2022-03-17_final
2022-03-18 09:24:47	ga_ls8c_ard_3-2-1_091080_2022-03-17_final
2022-03-19 10:03:14	ga_ls8c_ard_3-2-1_098068_2022-03-19_final
2022-03-19 10:04:50	ga_ls8c_ard_3-2-1_098072_2022-03-19_final
2022-03-20 10:51:40	ga_ls8c_ard_3-2-1_105081_2022-03-20_final
2022-03-26 10:11:43	ga_ls8c_ard_3-2-1_099074_2022-03-26_final
2022-03-30 11:27:49	ga_ls8c_ard_3-2-1_111079_2022-03-30_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-07 10:34:26	ga_ls8c_ard_3-2-1_103069_2022-04-07_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-22 09:56:47	ga_ls8c_ard_3-2-1_096083_2022-04-22_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-05 11:04:24	ga_ls8c_ard_3-2-1_107082_2022-05-05_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-22 11:46:10	ga_ls8c_ard_3-2-1_114078_2022-05-22_final
2022-06-11 09:42:21	ga_ls8c_ard_3-2-1_094077_2022-06-11_final
2022-06-13 11:05:42	ga_ls8c_ard_3-2-1_108069_2022-06-13_final
2022-06-15 10:54:33	ga_ls8c_ard_3-2-1_106072_2022-06-15_final
2022-06-20 11:17:08	ga_ls8c_ard_3-2-1_109082_2022-06-20_final
2022-06-22 09:26:17	ga_ls8c_ard_3-2-1_091083_2022-06-21_final
2022-06-24 10:48:26	ga_ls8c_ard_3-2-1_105072_2022-06-24_final
2022-06-25 09:55:36	ga_ls8c_ard_3-2-1_096079_2022-06-25_final
2022-07-06 09:35:29	ga_ls8c_ard_3-2-1_093075_2022-07-06_final
2022-07-08 11:04:00	ga_ls8c_ard_3-2-1_107080_2022-07-08_final
2022-07-09 10:09:34	ga_ls8c_ard_3-2-1_098083_2022-07-09_final
2022-07-10 10:46:27	ga_ls8c_ard_3-2-1_105067_2022-07-10_final
2022-07-11 09:56:48	ga_ls8c_ard_3-2-1_096082_2022-07-11_final
2022-07-12 10:36:28	ga_ls8c_ard_3-2-1_103073_2022-07-12_final
2022-07-13 09:46:02	ga_ls8c_ard_3-2-1_094086_2022-07-13_final
2022-07-13 11:21:20	ga_ls8c_ard_3-2-1_110077_2022-07-13_final
2022-07-24 11:03:18	ga_ls8c_ard_3-2-1_107078_2022-07-24_final
2022-07-25 11:44:59	ga_ls8c_ard_3-2-1_114074_2022-07-25_final
2022-07-26 09:14:28	ga_ls8c_ard_3-2-1_089084_2022-07-25_final
2022-07-28 10:38:37	ga_ls8c_ard_3-2-1_103078_2022-07-28_final
2022-07-29 09:42:37	ga_ls8c_ard_3-2-1_094077_2022-07-29_final
2022-07-31 11:07:57	ga_ls8c_ard_3-2-1_108074_2022-07-31_final
2022-08-02 09:19:56	ga_ls8c_ard_3-2-1_090082_2022-08-01_final
2022-08-02 09:20:43	ga_ls8c_ard_3-2-1_090084_2022-08-01_final
2022-08-07 11:17:24	ga_ls8c_ard_3-2-1_109082_2022-08-07_final
2022-08-10 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-08-10_final
2022-08-10 10:08:14	ga_ls8c_ard_3-2-1_098079_2022-08-10_final
2022-08-19 10:01:41	ga_ls8c_ard_3-2-1_097078_2022-08-19_final
2022-08-23 11:13:04	ga_ls8c_ard_3-2-1_109071_2022-08-23_final
2022-08-23 11:17:03	ga_ls8c_ard_3-2-1_109081_2022-08-23_final
2022-08-29 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-08-29_final
2022-08-31 10:26:01	ga_ls8c_ard_3-2-1_101077_2022-08-31_final
2022-09-11 10:10:44	ga_ls8c_ard_3-2-1_098085_2022-09-11_final
2022-09-12 10:48:01	ga_ls8c_ard_3-2-1_105070_2022-09-12_final
2022-09-14 10:37:16	ga_ls8c_ard_3-2-1_103074_2022-09-14_final
2022-09-29 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-09-29_final
2022-10-02 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-10-02_final
2022-10-03 11:11:22	ga_ls8c_ard_3-2-1_108082_2022-10-03_final
2022-10-04 11:52:13	ga_ls8c_ard_3-2-1_115076_2022-10-04_final
2022-10-07 09:08:07	ga_ls8c_ard_3-2-1_088083_2022-10-06_final
2022-10-08 11:30:15	ga_ls8c_ard_3-2-1_111083_2022-10-08_final
2022-10-13 11:45:31	ga_ls8c_ard_3-2-1_114075_2022-10-13_final
2022-10-20 11:53:22	ga_ls8c_ard_3-2-1_115079_2022-10-20_final
2022-10-22 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-22_final
2022-10-24 11:28:41	ga_ls8c_ard_3-2-1_111079_2022-10-24_final
2022-10-25 10:30:17	ga_ls8c_ard_3-2-1_102072_2022-10-25_final
2022-11-10 10:31:28	ga_ls8c_ard_3-2-1_102075_2022-11-10_final
2022-11-21 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-11-21_final
2022-11-27 11:17:05	ga_ls8c_ard_3-2-1_109081_2022-11-27_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-29 09:36:03	ga_ls8c_ard_3-2-1_093076_2022-12-29_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-16 11:01:16	ga_ls8c_ard_3-2-1_107073_2023-01-16_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-25 09:19:27	ga_ls8c_ard_3-2-1_090081_2023-01-24_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-11 10:01:53	ga_ls8c_ard_3-2-1_097079_2023-02-11_final
2023-02-15 09:35:54	ga_ls8c_ard_3-2-1_093076_2023-02-15_final
2023-02-15 11:12:48	ga_ls8c_ard_3-2-1_109071_2023-02-15_final
2023-02-16 10:21:33	ga_ls8c_ard_3-2-1_100082_2023-02-16_final
2023-02-17 11:01:12	ga_ls8c_ard_3-2-1_107073_2023-02-17_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-14 09:19:04	ga_ls8c_ard_3-2-1_090081_2023-03-13_final
2023-03-20 10:18:00	ga_ls8c_ard_3-2-1_100074_2023-03-20_final
2023-04-08 09:12:09	ga_ls8c_ard_3-2-1_089080_2023-04-07_final
2023-04-08 09:12:33	ga_ls8c_ard_3-2-1_089081_2023-04-07_final
2023-04-13 09:30:13	ga_ls8c_ard_3-2-1_092079_2023-04-13_final
2023-04-14 11:52:45	ga_ls8c_ard_3-2-1_115080_2023-04-14_final
2023-04-18 11:23:13	ga_ls8c_ard_3-2-1_111068_2023-04-18_final
2023-05-04 09:50:14	ga_ls8c_ard_3-2-1_095083_2023-05-04_final
2023-05-07 10:20:41	ga_ls8c_ard_3-2-1_100082_2023-05-07_final
2023-05-09 10:07:30	ga_ls8c_ard_3-2-1_098080_2023-05-09_final
2023-05-10 09:13:03	ga_ls8c_ard_3-2-1_089083_2023-05-09_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