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
2022-05-26 09:40:57	ga_ls8c_ard_3-2-1_094074_2022-05-26_final
2022-05-28 09:28:59	ga_ls8c_ard_3-2-1_092075_2022-05-27_final
2022-06-04 09:34:53	ga_ls8c_ard_3-2-1_093074_2022-06-04_final
2022-06-04 09:37:40	ga_ls8c_ard_3-2-1_093081_2022-06-04_final
2022-06-13 11:07:42	ga_ls8c_ard_3-2-1_108074_2022-06-13_final
2022-06-16 10:01:44	ga_ls8c_ard_3-2-1_097079_2022-06-16_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-06-22 09:25:06	ga_ls8c_ard_3-2-1_091080_2022-06-21_final
2022-06-27 09:45:15	ga_ls8c_ard_3-2-1_094084_2022-06-27_final
2022-07-02 09:58:37	ga_ls8c_ard_3-2-1_097071_2022-07-02_final
2022-07-07 10:21:32	ga_ls8c_ard_3-2-1_100082_2022-07-07_final
2022-07-08 11:02:00	ga_ls8c_ard_3-2-1_107075_2022-07-08_final
2022-07-13 11:20:32	ga_ls8c_ard_3-2-1_110075_2022-07-13_final
2022-07-16 10:14:32	ga_ls8c_ard_3-2-1_099080_2022-07-16_final
2022-07-17 09:20:32	ga_ls8c_ard_3-2-1_090084_2022-07-16_final
2022-07-17 10:59:01	ga_ls8c_ard_3-2-1_106083_2022-07-17_final
2022-07-20 11:25:34	ga_ls8c_ard_3-2-1_111072_2022-07-20_final
2022-07-21 10:30:22	ga_ls8c_ard_3-2-1_102073_2022-07-21_final
2022-07-26 09:12:52	ga_ls8c_ard_3-2-1_089080_2022-07-25_final
2022-07-29 09:40:13	ga_ls8c_ard_3-2-1_094071_2022-07-29_final
2022-07-29 11:23:29	ga_ls8c_ard_3-2-1_110082_2022-07-29_final
2022-08-01 10:09:33	ga_ls8c_ard_3-2-1_099067_2022-08-01_final
2022-08-02 10:59:12	ga_ls8c_ard_3-2-1_106083_2022-08-02_final
2022-08-11 09:12:13	ga_ls8c_ard_3-2-1_089078_2022-08-10_final
2022-08-13 10:39:33	ga_ls8c_ard_3-2-1_103080_2022-08-13_final
2022-08-14 09:45:56	ga_ls8c_ard_3-2-1_094085_2022-08-14_final
2022-08-15 10:23:13	ga_ls8c_ard_3-2-1_101070_2022-08-15_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-17 10:10:03	ga_ls8c_ard_3-2-1_099068_2022-08-17_final
2022-08-25 11:00:42	ga_ls8c_ard_3-2-1_107071_2022-08-25_final
2022-08-27 09:15:03	ga_ls8c_ard_3-2-1_089085_2022-08-26_final
2022-09-02 10:14:50	ga_ls8c_ard_3-2-1_099080_2022-09-02_final
2022-09-04 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-09-04_final
2022-09-06 11:26:39	ga_ls8c_ard_3-2-1_111074_2022-09-06_final
2022-09-07 10:28:38	ga_ls8c_ard_3-2-1_102068_2022-09-07_final
2022-09-15 11:20:08	ga_ls8c_ard_3-2-1_110073_2022-09-15_final
2022-09-17 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-09-17_final
2022-09-24 11:12:47	ga_ls8c_ard_3-2-1_109070_2022-09-24_final
2022-09-26 09:24:20	ga_ls8c_ard_3-2-1_091077_2022-09-25_final
2022-09-28 09:13:10	ga_ls8c_ard_3-2-1_089080_2022-09-27_final
2022-09-29 09:57:37	ga_ls8c_ard_3-2-1_096083_2022-09-29_final
2022-10-06 09:58:34	ga_ls8c_ard_3-2-1_097070_2022-10-06_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-11-04 09:34:06	ga_ls8c_ard_3-2-1_092086_2022-11-04_final
2022-11-05 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-11-05_final
2022-11-06 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-11-05_final
2022-11-07 11:42:40	ga_ls8c_ard_3-2-1_113083_2022-11-07_final
2022-11-09 09:47:49	ga_ls8c_ard_3-2-1_095074_2022-11-09_final
2022-11-11 11:14:19	ga_ls8c_ard_3-2-1_109074_2022-11-11_final
2022-11-12 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-11-12_final
2022-11-13 09:23:51	ga_ls8c_ard_3-2-1_091076_2022-11-12_final
2022-11-15 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-14_final
2022-11-18 09:44:43	ga_ls8c_ard_3-2-1_094082_2022-11-18_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-25 09:47:45	ga_ls8c_ard_3-2-1_095074_2022-11-25_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-29 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-29_final
2022-12-06 09:30:01	ga_ls8c_ard_3-2-1_092076_2022-12-06_final
2022-12-07 11:52:33	ga_ls8c_ard_3-2-1_115077_2022-12-07_final
2022-12-08 09:18:27	ga_ls8c_ard_3-2-1_090078_2022-12-07_final
2022-12-11 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-12-11_final
2022-12-13 11:13:50	ga_ls8c_ard_3-2-1_109073_2022-12-13_final
2022-12-22 09:32:14	ga_ls8c_ard_3-2-1_092082_2022-12-22_final
2022-12-24 09:22:40	ga_ls8c_ard_3-2-1_090089_2022-12-23_final
2022-12-25 09:58:21	ga_ls8c_ard_3-2-1_097070_2022-12-25_final
2022-12-25 11:39:38	ga_ls8c_ard_3-2-1_113076_2022-12-25_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2023-01-05 11:21:31	ga_ls8c_ard_3-2-1_110077_2023-01-05_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-12 11:26:51	ga_ls8c_ard_3-2-1_111075_2023-01-12_final
2023-01-14 11:14:03	ga_ls8c_ard_3-2-1_109074_2023-01-14_final
2023-01-23 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-01-23_final
2023-01-26 10:02:19	ga_ls8c_ard_3-2-1_097080_2023-01-26_final
2023-01-31 10:19:17	ga_ls8c_ard_3-2-1_100076_2023-01-31_final
2023-02-20 09:57:33	ga_ls8c_ard_3-2-1_096084_2023-02-20_final
2023-02-21 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-02-21_final
2023-02-27 11:41:18	ga_ls8c_ard_3-2-1_113081_2023-02-27_final
2023-03-03 11:13:46	ga_ls8c_ard_3-2-1_109074_2023-03-03_final
2023-03-05 11:00:36	ga_ls8c_ard_3-2-1_107072_2023-03-05_final
2023-03-06 10:07:45	ga_ls8c_ard_3-2-1_098079_2023-03-06_final
2023-03-21 09:27:09	ga_ls8c_ard_3-2-1_091086_2023-03-20_final
2023-04-06 10:59:27	ga_ls8c_ard_3-2-1_107070_2023-04-06_final
2023-04-20 09:34:21	ga_ls8c_ard_3-2-1_093074_2023-04-20_final
2023-04-27 11:19:49	ga_ls8c_ard_3-2-1_110075_2023-04-27_final
2023-04-27 11:22:36	ga_ls8c_ard_3-2-1_110082_2023-04-27_final
2023-05-01 10:52:40	ga_ls8c_ard_3-2-1_106069_2023-05-01_final
2023-05-04 11:25:31	ga_ls8c_ard_3-2-1_111074_2023-05-04_final
2023-05-05 10:29:29	ga_ls8c_ard_3-2-1_102073_2023-05-05_final
2023-05-06 11:17:08	ga_ls8c_ard_3-2-1_109084_2023-05-06_final
2023-05-07 10:18:18	ga_ls8c_ard_3-2-1_100076_2023-05-07_final
2023-05-08 09:26:15	ga_ls8c_ard_3-2-1_091085_2023-05-07_final
2023-05-11 09:56:41	ga_ls8c_ard_3-2-1_096084_2023-05-11_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-16 11:51:16	ga_ls8c_ard_3-2-1_115077_2023-05-16_final
2023-05-20 09:46:05	ga_ls8c_ard_3-2-1_095073_2023-05-20_final
2023-05-20 09:46:53	ga_ls8c_ard_3-2-1_095075_2023-05-20_final
2023-05-20 11:25:46	ga_ls8c_ard_3-2-1_111075_2023-05-20_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