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
2023-02-03 09:14:06	ga_ls8c_ard_3-2-1_089083_2023-02-02_final
2023-03-22 10:10:00	ga_ls8c_ard_3-2-1_098085_2023-03-22_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-06-28 11:35:01	ga_ls8c_ard_3-2-1_112082_2023-06-28_final
2023-06-30 09:40:37	ga_ls8c_ard_3-2-1_094074_2023-06-30_final
2023-07-01 10:25:53	ga_ls8c_ard_3-2-1_101079_2023-07-01_final
2023-07-02 09:29:05	ga_ls8c_ard_3-2-1_092076_2023-07-01_final
2023-07-12 10:04:39	ga_ls8c_ard_3-2-1_098072_2023-07-12_final
2023-07-12 10:07:50	ga_ls8c_ard_3-2-1_098080_2023-07-12_final
2023-07-13 09:13:01	ga_ls8c_ard_3-2-1_089082_2023-07-12_final
2023-07-13 10:46:43	ga_ls8c_ard_3-2-1_105069_2023-07-13_final
2023-07-14 09:57:29	ga_ls8c_ard_3-2-1_096085_2023-07-14_final
2023-07-14 11:33:58	ga_ls8c_ard_3-2-1_112079_2023-07-14_final
2023-07-16 11:18:01	ga_ls8c_ard_3-2-1_110070_2023-07-16_final
2023-07-18 09:30:45	ga_ls8c_ard_3-2-1_092080_2023-07-18_final
2023-07-20 09:17:59	ga_ls8c_ard_3-2-1_090079_2023-07-19_final
2023-07-20 09:18:47	ga_ls8c_ard_3-2-1_090081_2023-07-19_final
2023-07-27 09:25:04	ga_ls8c_ard_3-2-1_091081_2023-07-26_final
2023-07-27 11:01:57	ga_ls8c_ard_3-2-1_107076_2023-07-27_final
2023-07-28 10:06:21	ga_ls8c_ard_3-2-1_098076_2023-07-28_final
2023-08-01 09:40:28	ga_ls8c_ard_3-2-1_094073_2023-08-01_final
2023-08-06 10:03:49	ga_ls8c_ard_3-2-1_097085_2023-08-06_final
2023-08-08 09:51:27	ga_ls8c_ard_3-2-1_095085_2023-08-08_final
2023-08-10 11:15:58	ga_ls8c_ard_3-2-1_109080_2023-08-10_final
2023-08-12 11:01:14	ga_ls8c_ard_3-2-1_107074_2023-08-12_final
2023-08-13 10:04:50	ga_ls8c_ard_3-2-1_098072_2023-08-13_final
2023-08-13 10:08:01	ga_ls8c_ard_3-2-1_098080_2023-08-13_final
2023-08-17 09:40:34	ga_ls8c_ard_3-2-1_094073_2023-08-17_final
2023-08-19 11:06:18	ga_ls8c_ard_3-2-1_108071_2023-08-19_final
2023-08-20 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-08-20_final
2023-08-21 10:54:46	ga_ls8c_ard_3-2-1_106073_2023-08-21_final
2023-08-22 09:59:33	ga_ls8c_ard_3-2-1_097074_2023-08-22_final
2023-08-22 10:03:56	ga_ls8c_ard_3-2-1_097085_2023-08-22_final
2023-08-23 10:40:25	ga_ls8c_ard_3-2-1_104068_2023-08-23_final
2023-08-24 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-08-24_final
2023-08-24 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-08-24_final
2023-08-25 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-08-25_final
2023-08-27 10:18:54	ga_ls8c_ard_3-2-1_100076_2023-08-27_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-29 10:04:57	ga_ls8c_ard_3-2-1_098072_2023-08-29_final
2023-08-30 09:12:55	ga_ls8c_ard_3-2-1_089081_2023-08-29_final
2023-08-30 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-08-29_final
2023-08-30 10:48:12	ga_ls8c_ard_3-2-1_105072_2023-08-30_final
2023-09-03 10:22:40	ga_ls8c_ard_3-2-1_101070_2023-09-03_final
2023-09-05 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-09-05_final
2023-09-07 10:01:31	ga_ls8c_ard_3-2-1_097079_2023-09-07_final
2023-09-08 10:40:24	ga_ls8c_ard_3-2-1_104068_2023-09-08_final
2023-09-08 10:41:12	ga_ls8c_ard_3-2-1_104070_2023-09-08_final
2023-09-08 10:46:00	ga_ls8c_ard_3-2-1_104082_2023-09-08_final
2023-09-11 09:34:52	ga_ls8c_ard_3-2-1_093074_2023-09-11_final
2023-09-12 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-09-12_final
2023-09-13 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-09-13_final
2023-09-13 11:01:48	ga_ls8c_ard_3-2-1_107075_2023-09-13_final
2023-09-14 10:05:00	ga_ls8c_ard_3-2-1_098072_2023-09-14_final
2023-09-15 10:48:40	ga_ls8c_ard_3-2-1_105073_2023-09-15_final
2023-09-16 09:52:15	ga_ls8c_ard_3-2-1_096071_2023-09-16_final
2023-09-19 10:25:09	ga_ls8c_ard_3-2-1_101076_2023-09-19_final
2023-09-21 11:50:53	ga_ls8c_ard_3-2-1_115074_2023-09-21_final
2023-09-23 09:59:38	ga_ls8c_ard_3-2-1_097074_2023-09-23_final
2023-09-26 10:28:34	ga_ls8c_ard_3-2-1_102069_2023-09-26_final
2023-09-26 10:29:22	ga_ls8c_ard_3-2-1_102071_2023-09-26_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-09-27 11:12:38	ga_ls8c_ard_3-2-1_109071_2023-09-27_final
2023-09-28 10:21:49	ga_ls8c_ard_3-2-1_100083_2023-09-28_final
2023-09-28 11:58:42	ga_ls8c_ard_3-2-1_116078_2023-09-28_final
2023-09-29 11:00:17	ga_ls8c_ard_3-2-1_107071_2023-09-29_final
2023-10-04 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-10-04_final
2023-10-04 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-10-04_final
2023-10-05 10:24:00	ga_ls8c_ard_3-2-1_101073_2023-10-05_final
2023-10-07 10:14:26	ga_ls8c_ard_3-2-1_099080_2023-10-07_final
2023-10-16 10:03:31	ga_ls8c_ard_3-2-1_098068_2023-10-16_final
2023-10-16 10:07:54	ga_ls8c_ard_3-2-1_098079_2023-10-16_final
2023-10-17 10:47:10	ga_ls8c_ard_3-2-1_105069_2023-10-17_final
2023-10-20 09:44:21	ga_ls8c_ard_3-2-1_094082_2023-10-20_final
2023-10-20 11:24:26	ga_ls8c_ard_3-2-1_110085_2023-10-20_final
2023-10-21 10:23:38	ga_ls8c_ard_3-2-1_101072_2023-10-21_final
2023-10-21 10:24:02	ga_ls8c_ard_3-2-1_101073_2023-10-21_final
2023-10-23 10:15:41	ga_ls8c_ard_3-2-1_099083_2023-10-23_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-25 10:04:09	ga_ls8c_ard_3-2-1_097085_2023-10-25_final
2023-10-26 10:41:02	ga_ls8c_ard_3-2-1_104069_2023-10-26_final
2023-10-27 11:29:53	ga_ls8c_ard_3-2-1_111083_2023-10-27_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-10-30 10:18:19	ga_ls8c_ard_3-2-1_100074_2023-10-30_final
2023-11-01 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-11-01_final
2023-11-01 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-11-01_final
2023-11-03 09:52:48	ga_ls8c_ard_3-2-1_096072_2023-11-03_final
2023-11-05 11:20:54	ga_ls8c_ard_3-2-1_110076_2023-11-05_final
2023-11-05 11:24:05	ga_ls8c_ard_3-2-1_110084_2023-11-05_final
2023-11-06 10:28:03	ga_ls8c_ard_3-2-1_101083_2023-11-06_final
2023-11-08 10:15:40	ga_ls8c_ard_3-2-1_099083_2023-11-08_final
2023-11-09 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-11-08_final
2023-11-12 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-11-12_final
2023-11-14 11:17:06	ga_ls8c_ard_3-2-1_109082_2023-11-14_final
2023-11-16 09:28:16	ga_ls8c_ard_3-2-1_091088_2023-11-15_final
2023-11-17 10:05:09	ga_ls8c_ard_3-2-1_098072_2023-11-17_final
2023-11-17 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-17_final
2023-11-19 09:57:36	ga_ls8c_ard_3-2-1_096084_2023-11-19_final
2023-11-20 10:37:41	ga_ls8c_ard_3-2-1_103076_2023-11-20_final
2023-11-21 11:22:56	ga_ls8c_ard_3-2-1_110081_2023-11-21_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