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
2022-07-08 11:00:48	ga_ls8c_ard_3-2-1_107072_2022-07-08_final
2022-07-13 09:42:27	ga_ls8c_ard_3-2-1_094077_2022-07-13_final
2022-07-25 10:08:53	ga_ls8c_ard_3-2-1_098081_2022-07-25_final
2022-07-25 11:45:22	ga_ls8c_ard_3-2-1_114075_2022-07-25_final
2022-07-27 09:56:33	ga_ls8c_ard_3-2-1_096081_2022-07-27_final
2022-08-02 10:57:37	ga_ls8c_ard_3-2-1_106079_2022-08-02_final
2022-08-04 10:44:28	ga_ls8c_ard_3-2-1_104077_2022-08-04_final
2022-08-05 11:29:44	ga_ls8c_ard_3-2-1_111082_2022-08-05_final
2022-08-07 11:13:24	ga_ls8c_ard_3-2-1_109072_2022-08-07_final
2022-08-10 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-08-10_final
2022-08-12 09:57:05	ga_ls8c_ard_3-2-1_096082_2022-08-12_final
2022-08-18 10:57:19	ga_ls8c_ard_3-2-1_106078_2022-08-18_final
2022-09-15 09:42:03	ga_ls8c_ard_3-2-1_094075_2022-09-15_final
2022-09-18 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-09-18_final
2022-09-19 10:57:02	ga_ls8c_ard_3-2-1_106077_2022-09-19_final
2022-09-21 10:42:16	ga_ls8c_ard_3-2-1_104071_2022-09-21_final
2022-09-21 10:43:52	ga_ls8c_ard_3-2-1_104075_2022-09-21_final
2022-09-30 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-09-30_final
2022-10-01 09:45:15	ga_ls8c_ard_3-2-1_094083_2022-10-01_final
2022-10-05 10:56:59	ga_ls8c_ard_3-2-1_106077_2022-10-05_final
2022-10-08 09:49:46	ga_ls8c_ard_3-2-1_095079_2022-10-08_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-16 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-10-16_final
2022-10-19 11:10:06	ga_ls8c_ard_3-2-1_108079_2022-10-19_final
2022-10-25 10:31:53	ga_ls8c_ard_3-2-1_102076_2022-10-25_final
2022-11-09 11:27:54	ga_ls8c_ard_3-2-1_111077_2022-11-09_final
2022-11-10 10:33:04	ga_ls8c_ard_3-2-1_102079_2022-11-10_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-16 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-11-16_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-18 09:42:20	ga_ls8c_ard_3-2-1_094076_2022-11-18_final
2022-11-19 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-11-19_final
2022-11-20 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-11-20_final
2022-12-11 09:50:31	ga_ls8c_ard_3-2-1_095081_2022-12-11_final
2022-12-11 11:28:12	ga_ls8c_ard_3-2-1_111078_2022-12-11_final
2022-12-16 10:09:25	ga_ls8c_ard_3-2-1_098082_2022-12-16_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-18 09:55:49	ga_ls8c_ard_3-2-1_096079_2022-12-18_final
2022-12-18 11:33:55	ga_ls8c_ard_3-2-1_112077_2022-12-18_final
2022-12-26 10:41:37	ga_ls8c_ard_3-2-1_104070_2022-12-26_final
2022-12-28 10:32:52	ga_ls8c_ard_3-2-1_102079_2022-12-28_final
2022-12-29 09:37:15	ga_ls8c_ard_3-2-1_093079_2022-12-29_final
2022-12-30 10:21:19	ga_ls8c_ard_3-2-1_100081_2022-12-30_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2023-01-09 10:56:46	ga_ls8c_ard_3-2-1_106077_2023-01-09_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-12 11:28:02	ga_ls8c_ard_3-2-1_111078_2023-01-12_final
2023-01-17 10:09:13	ga_ls8c_ard_3-2-1_098082_2023-01-17_final
2023-01-19 09:54:04	ga_ls8c_ard_3-2-1_096075_2023-01-19_final
2023-01-19 09:54:52	ga_ls8c_ard_3-2-1_096077_2023-01-19_final
2023-02-06 09:43:23	ga_ls8c_ard_3-2-1_094079_2023-02-06_final
2023-02-10 10:58:43	ga_ls8c_ard_3-2-1_106082_2023-02-10_final
2023-02-13 09:48:41	ga_ls8c_ard_3-2-1_095077_2023-02-13_final
2023-02-13 11:28:46	ga_ls8c_ard_3-2-1_111080_2023-02-13_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-22 09:45:56	ga_ls8c_ard_3-2-1_094086_2023-02-22_final
2023-02-26 10:56:26	ga_ls8c_ard_3-2-1_106077_2023-02-26_final
2023-02-27 10:03:13	ga_ls8c_ard_3-2-1_097083_2023-02-27_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-02-28 10:44:53	ga_ls8c_ard_3-2-1_104079_2023-02-28_final
2023-03-01 09:50:03	ga_ls8c_ard_3-2-1_095081_2023-03-01_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-06 10:08:33	ga_ls8c_ard_3-2-1_098081_2023-03-06_final
2023-03-09 10:37:01	ga_ls8c_ard_3-2-1_103075_2023-03-09_final
2023-03-09 10:37:25	ga_ls8c_ard_3-2-1_103076_2023-03-09_final
2023-03-12 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-03-12_final
2023-03-14 10:56:21	ga_ls8c_ard_3-2-1_106077_2023-03-14_final
2023-03-16 10:45:10	ga_ls8c_ard_3-2-1_104080_2023-03-16_final
2023-03-18 10:31:11	ga_ls8c_ard_3-2-1_102076_2023-03-18_final
2023-03-19 11:14:50	ga_ls8c_ard_3-2-1_109077_2023-03-19_final
2023-03-26 09:41:39	ga_ls8c_ard_3-2-1_094076_2023-03-26_final
2023-03-26 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-03-26_final
2023-03-28 09:29:41	ga_ls8c_ard_3-2-1_092077_2023-03-27_final
2023-03-31 11:39:02	ga_ls8c_ard_3-2-1_113076_2023-03-31_final
2023-04-02 09:48:09	ga_ls8c_ard_3-2-1_095077_2023-04-02_final
2023-04-02 11:27:02	ga_ls8c_ard_3-2-1_111077_2023-04-02_final
2023-04-03 10:31:00	ga_ls8c_ard_3-2-1_102076_2023-04-03_nrt
2023-04-04 09:36:58	ga_ls8c_ard_3-2-1_093080_2023-04-04_final
2023-04-05 10:17:24	ga_ls8c_ard_3-2-1_100073_2023-04-05_final
2023-04-08 10:50:14	ga_ls8c_ard_3-2-1_105078_2023-04-08_final
2023-04-10 10:39:25	ga_ls8c_ard_3-2-1_103082_2023-04-10_final
2023-04-11 09:40:59	ga_ls8c_ard_3-2-1_094075_2023-04-11_final
2023-04-13 09:29:25	ga_ls8c_ard_3-2-1_092077_2023-04-12_final
2023-04-15 09:19:27	ga_ls8c_ard_3-2-1_090083_2023-04-14_final
2023-04-16 11:39:59	ga_ls8c_ard_3-2-1_113079_2023-04-16_final
2023-04-18 09:47:32	ga_ls8c_ard_3-2-1_095076_2023-04-18_final
2023-04-20 09:33:09	ga_ls8c_ard_3-2-1_093071_2023-04-20_final
2023-04-20 09:38:20	ga_ls8c_ard_3-2-1_093084_2023-04-20_final
2023-04-24 10:50:31	ga_ls8c_ard_3-2-1_105079_2023-04-24_final
2023-04-25 09:55:41	ga_ls8c_ard_3-2-1_096081_2023-04-25_final
2023-04-25 09:56:05	ga_ls8c_ard_3-2-1_096082_2023-04-25_final
2023-05-02 09:59:26	ga_ls8c_ard_3-2-1_097075_2023-05-02_final
2023-05-03 10:40:17	ga_ls8c_ard_3-2-1_104069_2023-05-03_final
2023-05-03 10:41:29	ga_ls8c_ard_3-2-1_104072_2023-05-03_final
2023-05-06 09:37:27	ga_ls8c_ard_3-2-1_093082_2023-05-06_final
2023-05-08 09:23:27	ga_ls8c_ard_3-2-1_091078_2023-05-07_final
2023-05-08 10:59:57	ga_ls8c_ard_3-2-1_107072_2023-05-08_final
2023-05-15 11:10:01	ga_ls8c_ard_3-2-1_108082_2023-05-15_final
2023-05-21 10:30:33	ga_ls8c_ard_3-2-1_102076_2023-05-21_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