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
2021-12-18 10:26:37	ga_ls8c_ard_3-2-1_101079_2021-12-18_final
2021-12-18 10:27:25	ga_ls8c_ard_3-2-1_101081_2021-12-18_final
2021-12-19 11:11:04	ga_ls8c_ard_3-2-1_108082_2021-12-19_final
2021-12-22 10:02:16	ga_ls8c_ard_3-2-1_097080_2021-12-22_final
2021-12-24 11:29:59	ga_ls8c_ard_3-2-1_111083_2021-12-24_final
2021-12-25 10:33:09	ga_ls8c_ard_3-2-1_102080_2021-12-25_final
2021-12-27 10:20:23	ga_ls8c_ard_3-2-1_100079_2021-12-27_final
2021-12-28 09:29:08	ga_ls8c_ard_3-2-1_091090_2021-12-27_final
2021-12-31 09:56:25	ga_ls8c_ard_3-2-1_096081_2021-12-31_final
2022-01-04 09:32:30	ga_ls8c_ard_3-2-1_092083_2022-01-04_final
2022-01-05 10:12:58	ga_ls8c_ard_3-2-1_099076_2022-01-05_final
2022-01-13 09:24:18	ga_ls8c_ard_3-2-1_091078_2022-01-12_final
2022-01-16 11:35:17	ga_ls8c_ard_3-2-1_112081_2022-01-16_final
2022-01-18 11:22:30	ga_ls8c_ard_3-2-1_110080_2022-01-18_final
2022-01-20 09:34:51	ga_ls8c_ard_3-2-1_092089_2022-01-20_final
2022-01-20 11:11:44	ga_ls8c_ard_3-2-1_108084_2022-01-20_final
2022-01-23 11:39:25	ga_ls8c_ard_3-2-1_113076_2022-01-23_final
2022-01-24 10:43:23	ga_ls8c_ard_3-2-1_104075_2022-01-24_final
2022-01-25 11:29:02	ga_ls8c_ard_3-2-1_111081_2022-01-25_final
2022-02-05 11:08:28	ga_ls8c_ard_3-2-1_108076_2022-02-05_final
2022-02-08 09:59:41	ga_ls8c_ard_3-2-1_097074_2022-02-08_final
2022-02-08 10:00:29	ga_ls8c_ard_3-2-1_097076_2022-02-08_final
2022-02-09 10:43:20	ga_ls8c_ard_3-2-1_104075_2022-02-09_final
2022-02-10 09:48:06	ga_ls8c_ard_3-2-1_095076_2022-02-10_final
2022-02-16 10:51:04	ga_ls8c_ard_3-2-1_105079_2022-02-16_final
2022-02-17 09:56:38	ga_ls8c_ard_3-2-1_096082_2022-02-17_final
2022-02-24 10:00:23	ga_ls8c_ard_3-2-1_097076_2022-02-24_final
2022-02-24 10:02:47	ga_ls8c_ard_3-2-1_097082_2022-02-24_final
2022-02-26 09:50:01	ga_ls8c_ard_3-2-1_095081_2022-02-26_final
2022-02-26 11:28:54	ga_ls8c_ard_3-2-1_111081_2022-02-26_final
2022-02-26 11:29:42	ga_ls8c_ard_3-2-1_111083_2022-02-26_final
2022-02-28 09:36:28	ga_ls8c_ard_3-2-1_093078_2022-02-28_final
2022-03-01 10:21:19	ga_ls8c_ard_3-2-1_100082_2022-03-01_final
2022-03-05 09:52:59	ga_ls8c_ard_3-2-1_096073_2022-03-05_final
2022-03-06 10:39:02	ga_ls8c_ard_3-2-1_103080_2022-03-06_final
2022-03-07 11:22:42	ga_ls8c_ard_3-2-1_110081_2022-03-07_final
2022-03-09 11:10:19	ga_ls8c_ard_3-2-1_108081_2022-03-09_final
2022-03-10 11:50:47	ga_ls8c_ard_3-2-1_115074_2022-03-10_final
2022-03-17 10:21:13	ga_ls8c_ard_3-2-1_100082_2022-03-17_final
2022-03-19 10:06:26	ga_ls8c_ard_3-2-1_098076_2022-03-19_final
2022-03-21 09:52:03	ga_ls8c_ard_3-2-1_096071_2022-03-21_final
2022-03-25 09:31:40	ga_ls8c_ard_3-2-1_092082_2022-03-25_final
2022-03-25 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-03-25_final
2022-03-26 10:11:43	ga_ls8c_ard_3-2-1_099074_2022-03-26_final
2022-03-26 10:14:55	ga_ls8c_ard_3-2-1_099082_2022-03-26_final
2022-03-27 10:54:34	ga_ls8c_ard_3-2-1_106073_2022-03-27_final
2022-03-30 09:47:20	ga_ls8c_ard_3-2-1_095075_2022-03-30_final
2022-04-02 10:17:50	ga_ls8c_ard_3-2-1_100074_2022-04-02_final
2022-04-06 09:52:45	ga_ls8c_ard_3-2-1_096073_2022-04-06_final
2022-04-11 11:50:38	ga_ls8c_ard_3-2-1_115074_2022-04-11_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-17 09:36:16	ga_ls8c_ard_3-2-1_093078_2022-04-17_final
2022-04-17 09:39:28	ga_ls8c_ard_3-2-1_093086_2022-04-17_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-18 10:20:20	ga_ls8c_ard_3-2-1_100080_2022-04-18_final
2022-04-19 11:03:59	ga_ls8c_ard_3-2-1_107081_2022-04-19_final
2022-04-24 09:43:37	ga_ls8c_ard_3-2-1_094081_2022-04-24_final
2022-05-01 09:50:35	ga_ls8c_ard_3-2-1_095083_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-02 10:29:04	ga_ls8c_ard_3-2-1_102071_2022-05-02_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-03 11:16:44	ga_ls8c_ard_3-2-1_109082_2022-05-03_final
2022-05-06 10:05:59	ga_ls8c_ard_3-2-1_098075_2022-05-06_final
2022-05-07 10:48:04	ga_ls8c_ard_3-2-1_105072_2022-05-07_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-09 10:34:56	ga_ls8c_ard_3-2-1_103070_2022-05-09_final
2022-05-09 10:39:43	ga_ls8c_ard_3-2-1_103082_2022-05-09_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-12 11:09:51	ga_ls8c_ard_3-2-1_108080_2022-05-12_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-05-30 09:19:51	ga_ls8c_ard_3-2-1_090083_2022-05-29_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-06 11:01:02	ga_ls8c_ard_3-2-1_107073_2022-06-06_final
2022-06-08 10:47:06	ga_ls8c_ard_3-2-1_105069_2022-06-08_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-10 10:37:10	ga_ls8c_ard_3-2-1_103075_2022-06-10_final
2022-06-22 09:25:54	ga_ls8c_ard_3-2-1_091082_2022-06-21_final
2022-06-23 10:06:22	ga_ls8c_ard_3-2-1_098075_2022-06-23_final
2022-06-23 11:45:15	ga_ls8c_ard_3-2-1_114075_2022-06-23_final
2022-06-28 10:24:55	ga_ls8c_ard_3-2-1_101075_2022-06-28_final
2022-06-29 11:08:35	ga_ls8c_ard_3-2-1_108076_2022-06-29_final
2022-07-03 10:43:28	ga_ls8c_ard_3-2-1_104075_2022-07-03_final
2022-07-04 09:48:15	ga_ls8c_ard_3-2-1_095076_2022-07-04_final
2022-07-06 09:35:29	ga_ls8c_ard_3-2-1_093075_2022-07-06_final
2022-07-08 11:05:12	ga_ls8c_ard_3-2-1_107083_2022-07-08_final
2022-07-09 11:45:16	ga_ls8c_ard_3-2-1_114075_2022-07-09_final
2022-07-10 09:14:21	ga_ls8c_ard_3-2-1_089084_2022-07-09_final
2022-07-11 09:52:49	ga_ls8c_ard_3-2-1_096072_2022-07-11_final
2022-07-17 09:18:08	ga_ls8c_ard_3-2-1_090078_2022-07-16_final
2022-07-18 09:59:25	ga_ls8c_ard_3-2-1_097073_2022-07-18_final
2022-09-23 10:32:19	ga_ls8c_ard_3-2-1_102077_2022-09-23_final
2022-10-02 10:25:43	ga_ls8c_ard_3-2-1_101076_2022-10-02_final
2022-10-06 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-06_final
2022-10-09 10:30:14	ga_ls8c_ard_3-2-1_102072_2022-10-09_final
2022-10-10 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-10-10_final
2022-10-11 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-10-11_final
2022-10-20 10:15:17	ga_ls8c_ard_3-2-1_099081_2022-10-20_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