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
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-16 10:37:34	ga_ls8c_ard_3-2-1_103075_2022-10-16_final
2022-10-21 10:54:58	ga_ls8c_ard_3-2-1_106072_2022-10-21_final
2022-10-24 11:25:30	ga_ls8c_ard_3-2-1_111071_2022-10-24_final
2022-10-26 09:35:52	ga_ls8c_ard_3-2-1_093075_2022-10-26_final
2022-10-26 11:17:56	ga_ls8c_ard_3-2-1_109083_2022-10-26_final
2022-10-31 11:36:06	ga_ls8c_ard_3-2-1_112082_2022-10-31_final
2022-11-11 09:37:50	ga_ls8c_ard_3-2-1_093080_2022-11-11_final
2022-11-15 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-14_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-23 09:58:31	ga_ls8c_ard_3-2-1_097070_2022-11-23_final
2022-11-23 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-11-23_final
2022-11-23 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-11-23_final
2022-11-27 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-11-27_final
2022-12-02 11:36:25	ga_ls8c_ard_3-2-1_112083_2022-12-02_final
2022-12-06 09:30:01	ga_ls8c_ard_3-2-1_092076_2022-12-06_final
2022-12-07 11:52:09	ga_ls8c_ard_3-2-1_115076_2022-12-07_final
2022-12-11 09:51:19	ga_ls8c_ard_3-2-1_095083_2022-12-11_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-24 09:22:40	ga_ls8c_ard_3-2-1_090089_2022-12-23_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2022-12-30 10:21:43	ga_ls8c_ard_3-2-1_100082_2022-12-30_final
2022-12-30 11:58:12	ga_ls8c_ard_3-2-1_116076_2022-12-30_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2023-01-01 11:47:26	ga_ls8c_ard_3-2-1_114080_2023-01-01_final
2023-01-03 09:57:47	ga_ls8c_ard_3-2-1_096084_2023-01-03_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-05 09:44:38	ga_ls8c_ard_3-2-1_094082_2023-01-05_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-17 10:07:13	ga_ls8c_ard_3-2-1_098077_2023-01-17_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-30 09:35:13	ga_ls8c_ard_3-2-1_093074_2023-01-30_final
2023-02-03 09:14:06	ga_ls8c_ard_3-2-1_089083_2023-02-02_final
2023-02-04 11:36:14	ga_ls8c_ard_3-2-1_112083_2023-02-04_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-21 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-02-21_final
2023-03-16 09:07:29	ga_ls8c_ard_3-2-1_088083_2023-03-15_final
2023-03-26 11:18:32	ga_ls8c_ard_3-2-1_110071_2023-03-26_final
2023-03-29 10:14:08	ga_ls8c_ard_3-2-1_099080_2023-03-29_final
2023-04-02 09:51:45	ga_ls8c_ard_3-2-1_095086_2023-04-02_final
2023-04-07 11:46:17	ga_ls8c_ard_3-2-1_114079_2023-04-07_final
2023-04-08 09:12:33	ga_ls8c_ard_3-2-1_089081_2023-04-07_final
2023-04-15 09:20:14	ga_ls8c_ard_3-2-1_090085_2023-04-14_final
2023-04-20 09:34:21	ga_ls8c_ard_3-2-1_093074_2023-04-20_final
2023-04-27 11:23:48	ga_ls8c_ard_3-2-1_110085_2023-04-27_final
2023-05-01 10:52:40	ga_ls8c_ard_3-2-1_106069_2023-05-01_final
2023-05-06 11:16:20	ga_ls8c_ard_3-2-1_109082_2023-05-06_final
2023-05-08 11:04:44	ga_ls8c_ard_3-2-1_107084_2023-05-08_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-13 11:21:59	ga_ls8c_ard_3-2-1_110081_2023-05-13_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_2023-05-15_final
2023-05-16 10:13:35	ga_ls8c_ard_3-2-1_099080_2023-05-16_final
2023-05-16 11:51:16	ga_ls8c_ard_3-2-1_115077_2023-05-16_final
2023-05-17 10:57:38	ga_ls8c_ard_3-2-1_106082_2023-05-17_final
2023-05-20 09:50:52	ga_ls8c_ard_3-2-1_095085_2023-05-20_final
2023-05-23 10:16:36	ga_ls8c_ard_3-2-1_100072_2023-05-23_final
2023-05-30 10:23:36	ga_ls8c_ard_3-2-1_101074_2023-05-30_final
2023-06-01 10:13:37	ga_ls8c_ard_3-2-1_099080_2023-06-01_final
2023-06-09 09:23:05	ga_ls8c_ard_3-2-1_091077_2023-06-08_final
2023-06-10 10:09:33	ga_ls8c_ard_3-2-1_098085_2023-06-10_final
2023-06-15 10:22:09	ga_ls8c_ard_3-2-1_101070_2023-06-15_final
2023-06-15 10:27:20	ga_ls8c_ard_3-2-1_101083_2023-06-15_final
2023-06-19 09:58:14	ga_ls8c_ard_3-2-1_097072_2023-06-19_final
2023-07-02 09:29:05	ga_ls8c_ard_3-2-1_092076_2023-07-01_final
2023-07-13 09:12:13	ga_ls8c_ard_3-2-1_089080_2023-07-12_final
2023-07-16 11:19:13	ga_ls8c_ard_3-2-1_110073_2023-07-16_final
2023-07-28 10:06:45	ga_ls8c_ard_3-2-1_098077_2023-07-28_final
2023-08-01 11:18:33	ga_ls8c_ard_3-2-1_110071_2023-08-01_final
2023-08-03 11:06:12	ga_ls8c_ard_3-2-1_108071_2023-08-03_final
2023-08-05 10:53:51	ga_ls8c_ard_3-2-1_106071_2023-08-05_final
2023-08-06 11:41:54	ga_ls8c_ard_3-2-1_113083_2023-08-06_final
2023-08-08 09:52:15	ga_ls8c_ard_3-2-1_095087_2023-08-08_final
2023-08-19 11:09:54	ga_ls8c_ard_3-2-1_108080_2023-08-19_final
2023-08-20 10:12:41	ga_ls8c_ard_3-2-1_099076_2023-08-20_final
2023-08-21 10:54:46	ga_ls8c_ard_3-2-1_106073_2023-08-21_final
2023-08-25 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-08-25_final
2023-08-28 10:59:46	ga_ls8c_ard_3-2-1_107070_2023-08-28_final
2023-09-03 10:23:04	ga_ls8c_ard_3-2-1_101071_2023-09-03_final
2023-09-04 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-09-04_final
2023-09-05 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-09-05_final
2023-09-15 10:47:04	ga_ls8c_ard_3-2-1_105069_2023-09-15_final
2023-09-22 10:54:03	ga_ls8c_ard_3-2-1_106071_2023-09-22_final
2023-09-27 11:11:50	ga_ls8c_ard_3-2-1_109069_2023-09-27_final
2023-10-01 10:46:20	ga_ls8c_ard_3-2-1_105067_2023-10-01_final
2023-10-09 11:41:23	ga_ls8c_ard_3-2-1_113081_2023-10-09_final
2023-10-17 09:13:52	ga_ls8c_ard_3-2-1_089083_2023-10-16_final
2023-10-22 09:29:13	ga_ls8c_ard_3-2-1_092075_2023-10-21_final
2023-10-22 09:29:37	ga_ls8c_ard_3-2-1_092076_2023-10-21_final
2023-11-02 10:46:25	ga_ls8c_ard_3-2-1_105067_2023-11-02_final
2023-11-03 09:52:24	ga_ls8c_ard_3-2-1_096071_2023-11-03_final
2023-11-07 11:05:43	ga_ls8c_ard_3-2-1_108069_2023-11-07_final
2023-11-09 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-11-08_final
2023-11-10 11:41:22	ga_ls8c_ard_3-2-1_113081_2023-11-10_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