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
2022-10-29 10:03:35	ga_ls8c_ard_3-2-1_098067_2022-10-29_final
2022-10-29 10:04:47	ga_ls8c_ard_3-2-1_098070_2022-10-29_final
2022-11-02 09:44:04	ga_ls8c_ard_3-2-1_094080_2022-11-02_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-14 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-14_final
2022-11-16 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-11-16_final
2022-11-16 09:55:55	ga_ls8c_ard_3-2-1_096079_2022-11-16_final
2022-11-17 10:37:10	ga_ls8c_ard_3-2-1_103074_2022-11-17_final
2022-11-17 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-11-17_final
2022-11-20 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-11-20_final
2022-11-21 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-11-21_final
2022-11-22 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-11-21_final
2022-11-22 10:59:19	ga_ls8c_ard_3-2-1_106083_2022-11-22_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_final
2022-11-23 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-11-23_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-27 11:13:53	ga_ls8c_ard_3-2-1_109073_2022-11-27_final
2022-11-28 10:19:28	ga_ls8c_ard_3-2-1_100076_2022-11-28_final
2022-11-29 09:24:38	ga_ls8c_ard_3-2-1_091078_2022-11-28_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-11-30 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-30_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-07 11:52:09	ga_ls8c_ard_3-2-1_115076_2022-12-07_final
2022-12-08 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-12-07_final
2022-12-11 11:24:13	ga_ls8c_ard_3-2-1_111068_2022-12-11_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-13 11:13:26	ga_ls8c_ard_3-2-1_109072_2022-12-13_final
2022-12-14 11:59:05	ga_ls8c_ard_3-2-1_116078_2022-12-14_final
2022-12-15 09:25:22	ga_ls8c_ard_3-2-1_091080_2022-12-14_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-17 09:10:59	ga_ls8c_ard_3-2-1_089075_2022-12-16_final
2022-12-18 11:33:07	ga_ls8c_ard_3-2-1_112075_2022-12-18_final
2022-12-19 10:36:41	ga_ls8c_ard_3-2-1_103073_2022-12-19_final
2022-12-20 11:22:19	ga_ls8c_ard_3-2-1_110079_2022-12-20_final
2022-12-25 10:02:21	ga_ls8c_ard_3-2-1_097080_2022-12-25_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2022-12-26 10:42:25	ga_ls8c_ard_3-2-1_104072_2022-12-26_final
2022-12-27 11:29:17	ga_ls8c_ard_3-2-1_111081_2022-12-27_final
2022-12-30 10:18:07	ga_ls8c_ard_3-2-1_100073_2022-12-30_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-03 09:54:12	ga_ls8c_ard_3-2-1_096075_2023-01-03_final
2023-01-03 11:35:29	ga_ls8c_ard_3-2-1_112081_2023-01-03_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-08 10:13:07	ga_ls8c_ard_3-2-1_099076_2023-01-08_final
2023-01-09 09:19:29	ga_ls8c_ard_3-2-1_090081_2023-01-08_final
2023-01-12 09:52:45	ga_ls8c_ard_3-2-1_095087_2023-01-12_final
2023-01-13 10:30:49	ga_ls8c_ard_3-2-1_102074_2023-01-13_final
2023-01-13 10:31:37	ga_ls8c_ard_3-2-1_102076_2023-01-13_final
2023-01-14 11:15:15	ga_ls8c_ard_3-2-1_109077_2023-01-14_final
2023-01-16 09:26:46	ga_ls8c_ard_3-2-1_091084_2023-01-15_final
2023-01-16 09:28:46	ga_ls8c_ard_3-2-1_091089_2023-01-15_final
2023-01-17 10:08:25	ga_ls8c_ard_3-2-1_098080_2023-01-17_final
2023-01-17 11:44:54	ga_ls8c_ard_3-2-1_114074_2023-01-17_final
2023-01-18 10:50:28	ga_ls8c_ard_3-2-1_105077_2023-01-18_final
2023-01-23 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-01-23_final
2023-01-23 11:10:41	ga_ls8c_ard_3-2-1_108081_2023-01-23_final
2023-01-26 10:02:19	ga_ls8c_ard_3-2-1_097080_2023-01-26_final
2023-01-29 10:31:15	ga_ls8c_ard_3-2-1_102075_2023-01-29_final
2023-01-30 09:35:13	ga_ls8c_ard_3-2-1_093074_2023-01-30_final
2023-01-30 11:17:18	ga_ls8c_ard_3-2-1_109082_2023-01-30_final
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-05 10:36:37	ga_ls8c_ard_3-2-1_103073_2023-02-05_final
2023-02-06 11:23:52	ga_ls8c_ard_3-2-1_110083_2023-02-06_final
2023-02-08 09:31:01	ga_ls8c_ard_3-2-1_092079_2023-02-08_final
2023-02-08 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-02-08_final
2023-02-10 09:18:14	ga_ls8c_ard_3-2-1_090078_2023-02-09_final
2023-02-10 09:19:26	ga_ls8c_ard_3-2-1_090081_2023-02-09_final
2023-02-10 09:19:50	ga_ls8c_ard_3-2-1_090082_2023-02-09_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 11:27:58	ga_ls8c_ard_3-2-1_111078_2023-02-13_final
2023-02-13 11:29:10	ga_ls8c_ard_3-2-1_111081_2023-02-13_final
2023-02-14 10:31:56	ga_ls8c_ard_3-2-1_102077_2023-02-14_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-17 11:00:48	ga_ls8c_ard_3-2-1_107072_2023-02-17_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-02-19 09:16:42	ga_ls8c_ard_3-2-1_089090_2023-02-18_final
2023-02-22 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-02-22_final
2023-02-22 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-02-22_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-02-25 11:52:03	ga_ls8c_ard_3-2-1_115077_2023-02-25_final
2023-02-26 09:20:21	ga_ls8c_ard_3-2-1_090084_2023-02-25_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-05 09:23:42	ga_ls8c_ard_3-2-1_091077_2023-03-04_final
2023-03-05 09:26:06	ga_ls8c_ard_3-2-1_091083_2023-03-04_final
2023-03-05 11:01:00	ga_ls8c_ard_3-2-1_107073_2023-03-05_final
2023-03-05 11:05:23	ga_ls8c_ard_3-2-1_107084_2023-03-05_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_final
2023-03-08 09:53:22	ga_ls8c_ard_3-2-1_096074_2023-03-08_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-09 10:36:37	ga_ls8c_ard_3-2-1_103074_2023-03-09_final
2023-03-09 10:37:49	ga_ls8c_ard_3-2-1_103077_2023-03-09_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