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
2022-05-15 10:01:29	ga_ls8c_ard_3-2-1_097079_2022-05-15_final
2022-05-19 09:39:10	ga_ls8c_ard_3-2-1_093085_2022-05-19_final
2022-05-26 09:46:08	ga_ls8c_ard_3-2-1_094087_2022-05-26_final
2022-06-04 11:12:58	ga_ls8c_ard_3-2-1_109072_2022-06-04_final
2022-06-06 09:24:32	ga_ls8c_ard_3-2-1_091079_2022-06-05_final
2022-06-07 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-06-07_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-10 10:39:57	ga_ls8c_ard_3-2-1_103082_2022-06-10_final
2022-06-12 10:24:25	ga_ls8c_ard_3-2-1_101074_2022-06-12_final
2022-06-16 10:00:32	ga_ls8c_ard_3-2-1_097076_2022-06-16_final
2022-06-22 09:27:05	ga_ls8c_ard_3-2-1_091085_2022-06-21_final
2022-06-22 11:01:11	ga_ls8c_ard_3-2-1_107073_2022-06-22_final
2022-06-27 09:44:03	ga_ls8c_ard_3-2-1_094081_2022-06-27_final
2022-06-30 10:15:21	ga_ls8c_ard_3-2-1_099082_2022-06-30_final
2022-07-02 11:41:05	ga_ls8c_ard_3-2-1_113080_2022-07-02_final
2022-07-10 10:51:14	ga_ls8c_ard_3-2-1_105079_2022-07-10_final
2022-07-14 10:24:30	ga_ls8c_ard_3-2-1_101074_2022-07-14_final
2022-07-15 09:31:40	ga_ls8c_ard_3-2-1_092081_2022-07-15_final
2022-07-17 09:18:32	ga_ls8c_ard_3-2-1_090079_2022-07-16_final
2022-07-22 09:39:09	ga_ls8c_ard_3-2-1_093084_2022-07-22_final
2022-07-24 09:26:24	ga_ls8c_ard_3-2-1_091083_2022-07-23_final
2022-07-25 11:46:34	ga_ls8c_ard_3-2-1_114078_2022-07-25_final
2022-07-27 09:55:21	ga_ls8c_ard_3-2-1_096078_2022-07-27_final
2022-07-29 09:42:13	ga_ls8c_ard_3-2-1_094076_2022-07-29_final
2022-07-29 09:43:48	ga_ls8c_ard_3-2-1_094080_2022-07-29_final
2022-07-31 11:11:09	ga_ls8c_ard_3-2-1_108082_2022-07-31_final
2022-08-02 09:21:07	ga_ls8c_ard_3-2-1_090085_2022-08-01_final
2022-08-02 10:58:25	ga_ls8c_ard_3-2-1_106081_2022-08-02_final
2022-08-03 10:00:48	ga_ls8c_ard_3-2-1_097076_2022-08-03_final
2022-08-07 11:16:36	ga_ls8c_ard_3-2-1_109080_2022-08-07_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-12 11:34:46	ga_ls8c_ard_3-2-1_112079_2022-08-12_final
2022-08-14 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-08-14_final
2022-08-19 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-08-19_final
2022-09-03 10:58:30	ga_ls8c_ard_3-2-1_106081_2022-09-03_final
2022-09-04 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-09-04_final
2022-09-09 10:18:18	ga_ls8c_ard_3-2-1_100073_2022-09-09_final
2022-09-09 10:18:41	ga_ls8c_ard_3-2-1_100074_2022-09-09_final
2022-09-19 09:20:32	ga_ls8c_ard_3-2-1_090083_2022-09-18_final
2022-09-19 10:55:02	ga_ls8c_ard_3-2-1_106072_2022-09-19_final
2022-09-22 11:29:08	ga_ls8c_ard_3-2-1_111080_2022-09-22_final
2022-09-26 09:25:08	ga_ls8c_ard_3-2-1_091079_2022-09-25_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-20 10:15:17	ga_ls8c_ard_3-2-1_099081_2022-10-20_final
2022-10-21 10:56:58	ga_ls8c_ard_3-2-1_106077_2022-10-21_final
2022-10-26 11:16:44	ga_ls8c_ard_3-2-1_109080_2022-10-26_final
2022-10-28 09:25:54	ga_ls8c_ard_3-2-1_091081_2022-10-27_final
2022-11-02 11:23:21	ga_ls8c_ard_3-2-1_110081_2022-11-02_final
2022-11-04 09:30:30	ga_ls8c_ard_3-2-1_092077_2022-11-04_final
2022-11-12 11:58:22	ga_ls8c_ard_3-2-1_116076_2022-11-12_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-18 11:23:13	ga_ls8c_ard_3-2-1_110081_2022-11-18_final
2022-11-20 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-11-20_final
2022-11-27 09:36:12	ga_ls8c_ard_3-2-1_093076_2022-11-27_final
2022-11-27 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-11-27_final
2022-12-02 11:34:49	ga_ls8c_ard_3-2-1_112079_2022-12-02_final
2022-12-11 09:49:43	ga_ls8c_ard_3-2-1_095079_2022-12-11_final
2022-12-15 11:03:27	ga_ls8c_ard_3-2-1_107078_2022-12-15_final
2022-12-18 09:57:25	ga_ls8c_ard_3-2-1_096083_2022-12-18_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-22 09:30:14	ga_ls8c_ard_3-2-1_092077_2022-12-22_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2022-12-31 11:03:47	ga_ls8c_ard_3-2-1_107079_2022-12-31_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-14 11:16:03	ga_ls8c_ard_3-2-1_109079_2023-01-14_final
2023-01-19 11:35:45	ga_ls8c_ard_3-2-1_112082_2023-01-19_final
2023-01-20 10:35:45	ga_ls8c_ard_3-2-1_103071_2023-01-20_final
2023-01-20 10:38:09	ga_ls8c_ard_3-2-1_103077_2023-01-20_final
2023-01-30 09:40:49	ga_ls8c_ard_3-2-1_093088_2023-01-30_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-09 10:16:39	ga_ls8c_ard_3-2-1_099085_2023-02-09_final
2023-02-13 11:27:10	ga_ls8c_ard_3-2-1_111076_2023-02-13_final
2023-02-14 10:30:44	ga_ls8c_ard_3-2-1_102074_2023-02-14_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-16 11:58:02	ga_ls8c_ard_3-2-1_116076_2023-02-16_final
2023-02-24 11:08:49	ga_ls8c_ard_3-2-1_108077_2023-02-24_final
2023-02-26 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-02-25_final
2023-02-26 10:58:02	ga_ls8c_ard_3-2-1_106081_2023-02-26_final
2023-02-27 10:00:49	ga_ls8c_ard_3-2-1_097077_2023-02-27_final
2023-02-27 11:39:18	ga_ls8c_ard_3-2-1_113076_2023-02-27_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-06 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-03-06_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_final
2023-03-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2023-03-17_final
2023-04-02 09:51:21	ga_ls8c_ard_3-2-1_095085_2023-04-02_final
2023-04-02 11:27:26	ga_ls8c_ard_3-2-1_111078_2023-04-02_final
2023-04-04 11:17:02	ga_ls8c_ard_3-2-1_109083_2023-04-04_final
2023-04-06 11:00:15	ga_ls8c_ard_3-2-1_107072_2023-04-06_final
2023-04-07 11:45:05	ga_ls8c_ard_3-2-1_114076_2023-04-07_final
2023-04-15 09:18:15	ga_ls8c_ard_3-2-1_090080_2023-04-14_final
2023-04-15 10:55:56	ga_ls8c_ard_3-2-1_106077_2023-04-15_final
2023-04-17 10:42:45	ga_ls8c_ard_3-2-1_104075_2023-04-17_final
2023-04-18 09:51:07	ga_ls8c_ard_3-2-1_095085_2023-04-18_final
2023-04-29 11:05:50	ga_ls8c_ard_3-2-1_108071_2023-04-29_final
2023-05-01 09:17:46	ga_ls8c_ard_3-2-1_090079_2023-04-30_final
2023-05-03 10:41:05	ga_ls8c_ard_3-2-1_104071_2023-05-03_final
2023-05-07 10:19:53	ga_ls8c_ard_3-2-1_100080_2023-05-07_final
2023-05-09 11:44:23	ga_ls8c_ard_3-2-1_114075_2023-05-09_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