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
2018-11-30 08:10:38	ga_ls8c_ard_3-2-1_079080_2018-11-29_final
2023-02-02 11:45:24	ga_ls8c_ard_3-2-1_114075_2023-02-02_final
2023-02-03 09:14:06	ga_ls8c_ard_3-2-1_089083_2023-02-02_final
2023-03-14 10:54:21	ga_ls8c_ard_3-2-1_106072_2023-03-14_final
2023-04-02 09:50:57	ga_ls8c_ard_3-2-1_095084_2023-04-02_final
2023-04-04 09:39:45	ga_ls8c_ard_3-2-1_093087_2023-04-04_final
2023-04-10 10:34:38	ga_ls8c_ard_3-2-1_103070_2023-04-10_final
2023-04-12 10:24:15	ga_ls8c_ard_3-2-1_101075_2023-04-12_final
2023-04-20 11:16:49	ga_ls8c_ard_3-2-1_109083_2023-04-20_final
2023-04-25 09:51:18	ga_ls8c_ard_3-2-1_096070_2023-04-25_final
2023-04-27 09:40:32	ga_ls8c_ard_3-2-1_094074_2023-04-27_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-04-28 10:23:47	ga_ls8c_ard_3-2-1_101074_2023-04-28_final
2023-05-01 09:19:46	ga_ls8c_ard_3-2-1_090084_2023-04-30_final
2023-05-05 10:27:54	ga_ls8c_ard_3-2-1_102069_2023-05-05_final
2023-05-08 09:22:39	ga_ls8c_ard_3-2-1_091076_2023-05-07_final
2023-05-08 11:01:32	ga_ls8c_ard_3-2-1_107076_2023-05-08_final
2023-05-13 09:45:30	ga_ls8c_ard_3-2-1_094087_2023-05-13_final
2023-05-21 10:28:09	ga_ls8c_ard_3-2-1_102070_2023-05-21_final
2023-05-27 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-27_final
2023-05-30 10:24:23	ga_ls8c_ard_3-2-1_101076_2023-05-30_final
2023-06-06 10:30:14	ga_ls8c_ard_3-2-1_102075_2023-06-06_final
2023-06-13 10:39:17	ga_ls8c_ard_3-2-1_103082_2023-06-13_final
2023-06-16 11:05:01	ga_ls8c_ard_3-2-1_108069_2023-06-16_final
2023-06-26 10:03:41	ga_ls8c_ard_3-2-1_098070_2023-06-26_final
2023-06-27 09:12:04	ga_ls8c_ard_3-2-1_089080_2023-06-26_final
2023-06-30 11:19:30	ga_ls8c_ard_3-2-1_110074_2023-06-30_final
2023-07-02 09:29:05	ga_ls8c_ard_3-2-1_092076_2023-07-01_final
2023-07-02 11:06:22	ga_ls8c_ard_3-2-1_108072_2023-07-02_final
2023-07-07 11:24:57	ga_ls8c_ard_3-2-1_111072_2023-07-07_final
2023-07-13 09:12:37	ga_ls8c_ard_3-2-1_089081_2023-07-12_final
2023-07-15 10:33:57	ga_ls8c_ard_3-2-1_103068_2023-07-15_final
2023-07-16 11:18:25	ga_ls8c_ard_3-2-1_110071_2023-07-16_final
2023-07-20 09:19:59	ga_ls8c_ard_3-2-1_090084_2023-07-19_final
2023-07-21 09:58:52	ga_ls8c_ard_3-2-1_097073_2023-07-21_final
2023-07-29 09:13:32	ga_ls8c_ard_3-2-1_089083_2023-07-28_final
2023-07-30 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-07-30_final
2023-07-30 11:36:05	ga_ls8c_ard_3-2-1_112084_2023-07-30_final
2023-08-06 11:41:30	ga_ls8c_ard_3-2-1_113082_2023-08-06_final
2023-08-08 11:29:32	ga_ls8c_ard_3-2-1_111083_2023-08-08_final
2023-08-10 09:39:53	ga_ls8c_ard_3-2-1_093087_2023-08-10_final
2023-08-11 10:21:33	ga_ls8c_ard_3-2-1_100083_2023-08-11_final
2023-08-12 09:26:44	ga_ls8c_ard_3-2-1_091085_2023-08-11_final
2023-08-12 11:03:38	ga_ls8c_ard_3-2-1_107080_2023-08-12_final
2023-08-18 10:27:50	ga_ls8c_ard_3-2-1_101083_2023-08-18_final
2023-08-21 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-08-20_final
2023-08-21 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-08-20_final
2023-08-26 11:13:19	ga_ls8c_ard_3-2-1_109073_2023-08-26_final
2023-08-28 11:00:10	ga_ls8c_ard_3-2-1_107071_2023-08-28_final
2023-08-29 10:04:09	ga_ls8c_ard_3-2-1_098070_2023-08-29_final
2023-08-31 09:51:47	ga_ls8c_ard_3-2-1_096070_2023-08-31_final
2023-08-31 09:52:11	ga_ls8c_ard_3-2-1_096071_2023-08-31_final
2023-09-05 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-09-05_final
2023-09-08 10:42:24	ga_ls8c_ard_3-2-1_104073_2023-09-08_final
2023-09-14 10:04:12	ga_ls8c_ard_3-2-1_098070_2023-09-14_final
2023-09-14 10:05:00	ga_ls8c_ard_3-2-1_098072_2023-09-14_final
2023-11-08 11:51:45	ga_ls8c_ard_3-2-1_115076_2023-11-08_final
2023-11-11 10:40:58	ga_ls8c_ard_3-2-1_104069_2023-11-11_final
2023-11-17 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-11-17_final
2023-11-19 09:52:01	ga_ls8c_ard_3-2-1_096070_2023-11-19_final
2023-11-21 09:44:27	ga_ls8c_ard_3-2-1_094082_2023-11-21_final
2023-11-24 11:51:51	ga_ls8c_ard_3-2-1_115076_2023-11-24_final
2023-12-03 11:47:35	ga_ls8c_ard_3-2-1_114081_2023-12-03_final
2023-12-11 10:54:32	ga_ls8c_ard_3-2-1_106072_2023-12-11_final
2023-12-13 10:41:00	ga_ls8c_ard_3-2-1_104069_2023-12-13_final
2023-12-15 10:28:39	ga_ls8c_ard_3-2-1_102069_2023-12-15_final
2023-12-21 09:57:59	ga_ls8c_ard_3-2-1_096085_2023-12-21_final
2023-12-26 10:15:19	ga_ls8c_ard_3-2-1_099082_2023-12-26_final
2024-01-05 09:11:23	ga_ls8c_ard_3-2-1_089077_2024-01-04_final
2024-01-08 09:40:43	ga_ls8c_ard_3-2-1_094073_2024-01-08_final
2024-01-08 11:18:48	ga_ls8c_ard_3-2-1_110071_2024-01-08_final
2024-01-09 10:27:59	ga_ls8c_ard_3-2-1_101083_2024-01-09_final
2024-01-11 10:11:39	ga_ls8c_ard_3-2-1_099073_2024-01-11_final
2024-01-12 10:57:42	ga_ls8c_ard_3-2-1_106080_2024-01-12_final
2024-01-15 11:30:12	ga_ls8c_ard_3-2-1_111084_2024-01-15_final
2024-01-16 10:31:47	ga_ls8c_ard_3-2-1_102077_2024-01-16_final
2024-01-26 11:10:44	ga_ls8c_ard_3-2-1_108082_2024-01-26_final
2024-01-28 10:57:35	ga_ls8c_ard_3-2-1_106080_2024-01-28_final
2024-02-03 10:21:46	ga_ls8c_ard_3-2-1_100083_2024-02-03_final
2024-02-04 09:23:46	ga_ls8c_ard_3-2-1_091077_2024-02-03_final
2024-02-05 10:05:26	ga_ls8c_ard_3-2-1_098073_2024-02-05_final
2024-02-05 10:05:50	ga_ls8c_ard_3-2-1_098074_2024-02-05_final
2024-02-13 10:58:52	ga_ls8c_ard_3-2-1_106083_2024-02-13_final
2024-02-15 10:41:18	ga_ls8c_ard_3-2-1_104070_2024-02-15_final
2024-02-20 09:26:32	ga_ls8c_ard_3-2-1_091084_2024-02-19_final
2024-02-22 10:52:39	ga_ls8c_ard_3-2-1_105083_2024-02-22_final
2024-02-24 10:35:29	ga_ls8c_ard_3-2-1_103071_2024-02-24_final
2024-02-25 11:23:56	ga_ls8c_ard_3-2-1_110084_2024-02-25_final
2024-02-29 10:54:46	ga_ls8c_ard_3-2-1_106073_2024-02-29_final
2024-03-07 09:23:32	ga_ls8c_ard_3-2-1_091077_2024-03-06_final
2024-03-07 11:05:13	ga_ls8c_ard_3-2-1_107084_2024-03-07_final
2024-03-12 09:45:16	ga_ls8c_ard_3-2-1_094085_2024-03-12_nrt
2024-03-21 11:17:04	ga_ls8c_ard_3-2-1_109083_2024-03-21_final
2024-03-24 10:07:50	ga_ls8c_ard_3-2-1_098080_2024-03-24_final
2024-04-02 11:41:15	ga_ls8c_ard_3-2-1_113082_2024-04-02_nrt
2024-04-07 10:20:54	ga_ls8c_ard_3-2-1_100082_2024-04-07_nrt
2024-04-10 10:46:36	ga_ls8c_ard_3-2-1_105069_2024-04-10_nrt
2024-04-13 11:21:28	ga_ls8c_ard_3-2-1_110079_2024-04-13_nrt
2024-04-15 11:11:04	ga_ls8c_ard_3-2-1_108084_2024-04-15_nrt
2024-04-17 10:53:05	ga_ls8c_ard_3-2-1_106070_2024-04-17_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