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
2022-07-26 10:50:58	ga_ls8c_ard_3-2-1_105078_2022-07-26_final
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-28 10:35:50	ga_ls8c_ard_3-2-1_103071_2022-07-28_final
2022-07-28 10:37:49	ga_ls8c_ard_3-2-1_103076_2022-07-28_final
2022-07-31 09:30:16	ga_ls8c_ard_3-2-1_092077_2022-07-31_final
2022-07-31 09:31:04	ga_ls8c_ard_3-2-1_092079_2022-07-31_final
2022-08-05 11:27:45	ga_ls8c_ard_3-2-1_111077_2022-08-05_final
2022-08-13 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-08-13_final
2022-08-21 09:50:56	ga_ls8c_ard_3-2-1_095082_2022-08-21_final
2022-08-26 10:05:53	ga_ls8c_ard_3-2-1_098073_2022-08-26_final
2022-09-06 09:48:10	ga_ls8c_ard_3-2-1_095075_2022-09-06_final
2022-09-10 09:24:40	ga_ls8c_ard_3-2-1_091078_2022-09-09_final
2022-09-15 09:42:51	ga_ls8c_ard_3-2-1_094077_2022-09-15_final
2022-09-20 10:01:24	ga_ls8c_ard_3-2-1_097077_2022-09-20_final
2022-09-22 11:29:08	ga_ls8c_ard_3-2-1_111080_2022-09-22_final
2022-09-26 11:03:13	ga_ls8c_ard_3-2-1_107077_2022-09-26_final
2022-09-28 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-09-28_final
2022-09-29 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-09-29_final
2022-10-01 09:42:27	ga_ls8c_ard_3-2-1_094076_2022-10-01_final
2022-10-01 09:42:51	ga_ls8c_ard_3-2-1_094077_2022-10-01_final
2022-10-08 11:29:51	ga_ls8c_ard_3-2-1_111082_2022-10-08_final
2022-10-09 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-10-09_final
2022-10-12 11:05:04	ga_ls8c_ard_3-2-1_107082_2022-10-12_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-19 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-10-19_final
2022-10-21 10:58:33	ga_ls8c_ard_3-2-1_106081_2022-10-21_final
2022-10-25 10:32:16	ga_ls8c_ard_3-2-1_102077_2022-10-25_final
2022-10-26 11:16:44	ga_ls8c_ard_3-2-1_109080_2022-10-26_final
2022-10-31 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-10-31_final
2022-10-31 11:34:30	ga_ls8c_ard_3-2-1_112078_2022-10-31_final
2022-11-01 10:37:17	ga_ls8c_ard_3-2-1_103074_2022-11-01_final
2022-11-09 11:28:18	ga_ls8c_ard_3-2-1_111078_2022-11-09_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-11 11:16:43	ga_ls8c_ard_3-2-1_109080_2022-11-11_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-18 09:42:44	ga_ls8c_ard_3-2-1_094077_2022-11-18_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-11-30 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-30_final
2022-12-09 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-12-09_final
2022-12-11 11:29:48	ga_ls8c_ard_3-2-1_111082_2022-12-11_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-16 10:09:01	ga_ls8c_ard_3-2-1_098081_2022-12-16_final
2022-12-20 09:42:38	ga_ls8c_ard_3-2-1_094077_2022-12-20_final
2022-12-26 10:43:13	ga_ls8c_ard_3-2-1_104074_2022-12-26_final
2022-12-28 10:34:04	ga_ls8c_ard_3-2-1_102082_2022-12-28_final
2022-12-29 11:16:32	ga_ls8c_ard_3-2-1_109080_2022-12-29_final
2023-01-01 10:08:57	ga_ls8c_ard_3-2-1_098081_2023-01-01_final
2023-01-12 09:49:09	ga_ls8c_ard_3-2-1_095078_2023-01-12_final
2023-01-12 11:28:02	ga_ls8c_ard_3-2-1_111078_2023-01-12_final
2023-01-16 09:25:58	ga_ls8c_ard_3-2-1_091082_2023-01-15_final
2023-01-23 09:31:00	ga_ls8c_ard_3-2-1_092079_2023-01-23_final
2023-01-26 10:03:31	ga_ls8c_ard_3-2-1_097083_2023-01-26_final
2023-01-30 11:16:30	ga_ls8c_ard_3-2-1_109080_2023-01-30_final
2023-02-05 10:37:25	ga_ls8c_ard_3-2-1_103075_2023-02-05_final
2023-02-06 11:22:16	ga_ls8c_ard_3-2-1_110079_2023-02-06_final
2023-02-08 09:32:13	ga_ls8c_ard_3-2-1_092082_2023-02-08_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-11 10:00:41	ga_ls8c_ard_3-2-1_097076_2023-02-11_final
2023-02-13 09:51:29	ga_ls8c_ard_3-2-1_095084_2023-02-13_final
2023-02-17 09:25:55	ga_ls8c_ard_3-2-1_091082_2023-02-16_final
2023-02-17 11:03:12	ga_ls8c_ard_3-2-1_107078_2023-02-17_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-26 10:54:26	ga_ls8c_ard_3-2-1_106072_2023-02-26_final
2023-02-27 10:00:01	ga_ls8c_ard_3-2-1_097075_2023-02-27_final
2023-02-28 10:44:29	ga_ls8c_ard_3-2-1_104078_2023-02-28_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-02 10:31:19	ga_ls8c_ard_3-2-1_102076_2023-03-02_final
2023-03-02 10:32:31	ga_ls8c_ard_3-2-1_102079_2023-03-02_final
2023-03-03 09:38:29	ga_ls8c_ard_3-2-1_093083_2023-03-03_final
2023-03-05 09:24:06	ga_ls8c_ard_3-2-1_091078_2023-03-04_final
2023-03-08 11:35:02	ga_ls8c_ard_3-2-1_112081_2023-03-08_final
2023-03-10 11:22:17	ga_ls8c_ard_3-2-1_110080_2023-03-10_final
2023-03-14 10:57:09	ga_ls8c_ard_3-2-1_106079_2023-03-14_final
2023-03-26 09:41:39	ga_ls8c_ard_3-2-1_094076_2023-03-26_final
2023-03-28 11:09:45	ga_ls8c_ard_3-2-1_108080_2023-03-28_final
2023-04-01 10:41:24	ga_ls8c_ard_3-2-1_104071_2023-04-01_final
2023-04-07 10:06:12	ga_ls8c_ard_3-2-1_098076_2023-04-07_final
2023-04-07 10:08:12	ga_ls8c_ard_3-2-1_098081_2023-04-07_final
2023-04-14 10:11:29	ga_ls8c_ard_3-2-1_099074_2023-04-14_final
2023-04-15 09:19:03	ga_ls8c_ard_3-2-1_090082_2023-04-14_final
2023-04-16 11:38:23	ga_ls8c_ard_3-2-1_113075_2023-04-16_final
2023-04-18 09:48:43	ga_ls8c_ard_3-2-1_095079_2023-04-18_final
2023-04-19 10:31:34	ga_ls8c_ard_3-2-1_102078_2023-04-19_final
2023-04-20 09:37:32	ga_ls8c_ard_3-2-1_093082_2023-04-20_final
2023-04-20 09:38:20	ga_ls8c_ard_3-2-1_093084_2023-04-20_final
2023-04-29 11:07:50	ga_ls8c_ard_3-2-1_108076_2023-04-29_final
2023-04-30 10:11:24	ga_ls8c_ard_3-2-1_099074_2023-04-30_final
2023-05-02 11:39:54	ga_ls8c_ard_3-2-1_113079_2023-05-02_final
2023-05-03 10:41:05	ga_ls8c_ard_3-2-1_104071_2023-05-03_final
2023-05-03 10:44:16	ga_ls8c_ard_3-2-1_104079_2023-05-03_final
2023-05-04 11:26:43	ga_ls8c_ard_3-2-1_111077_2023-05-04_final
2023-05-06 11:11:08	ga_ls8c_ard_3-2-1_109069_2023-05-06_final
2023-05-09 11:45:35	ga_ls8c_ard_3-2-1_114078_2023-05-09_final
2023-05-11 09:52:42	ga_ls8c_ard_3-2-1_096074_2023-05-11_final
2023-05-12 10:35:32	ga_ls8c_ard_3-2-1_103073_2023-05-12_final
2023-05-12 10:36:20	ga_ls8c_ard_3-2-1_103075_2023-05-12_final
2023-05-13 11:20:48	ga_ls8c_ard_3-2-1_110078_2023-05-13_final
2023-05-15 09:30:20	ga_ls8c_ard_3-2-1_092080_2023-05-15_final
2023-05-17 10:57:14	ga_ls8c_ard_3-2-1_106081_2023-05-17_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