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
2022-05-02 10:30:40	ga_ls8c_ard_3-2-1_102075_2022-05-02_final
2022-05-07 09:13:34	ga_ls8c_ard_3-2-1_089083_2022-05-06_final
2022-05-16 10:40:22	ga_ls8c_ard_3-2-1_104068_2022-05-16_final
2022-05-19 09:35:35	ga_ls8c_ard_3-2-1_093076_2022-05-19_final
2022-05-21 11:01:18	ga_ls8c_ard_3-2-1_107074_2022-05-21_final
2022-05-24 11:35:24	ga_ls8c_ard_3-2-1_112082_2022-05-24_final
2022-06-03 10:33:41	ga_ls8c_ard_3-2-1_102082_2022-06-03_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-07 10:05:01	ga_ls8c_ard_3-2-1_098072_2022-06-07_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-13 09:29:37	ga_ls8c_ard_3-2-1_092076_2022-06-12_final
2022-06-13 11:05:42	ga_ls8c_ard_3-2-1_108069_2022-06-13_final
2022-06-13 11:06:30	ga_ls8c_ard_3-2-1_108071_2022-06-13_final
2022-06-15 09:20:52	ga_ls8c_ard_3-2-1_090085_2022-06-14_final
2022-06-22 09:25:30	ga_ls8c_ard_3-2-1_091081_2022-06-21_final
2022-06-22 11:01:59	ga_ls8c_ard_3-2-1_107075_2022-06-22_final
2022-06-23 11:47:39	ga_ls8c_ard_3-2-1_114081_2022-06-23_final
2022-06-25 09:52:01	ga_ls8c_ard_3-2-1_096070_2022-06-25_final
2022-06-27 09:45:39	ga_ls8c_ard_3-2-1_094085_2022-06-27_final
2022-07-04 11:25:32	ga_ls8c_ard_3-2-1_111072_2022-07-04_final
2022-07-08 11:01:36	ga_ls8c_ard_3-2-1_107074_2022-07-08_final
2022-07-10 10:46:27	ga_ls8c_ard_3-2-1_105067_2022-07-10_final
2022-07-11 11:36:29	ga_ls8c_ard_3-2-1_112084_2022-07-11_final
2022-07-13 09:45:38	ga_ls8c_ard_3-2-1_094085_2022-07-13_final
2022-07-13 11:24:07	ga_ls8c_ard_3-2-1_110084_2022-07-13_final
2022-07-14 10:23:18	ga_ls8c_ard_3-2-1_101071_2022-07-14_final
2022-07-15 11:05:46	ga_ls8c_ard_3-2-1_108069_2022-07-15_final
2022-07-20 09:52:40	ga_ls8c_ard_3-2-1_095087_2022-07-20_final
2022-07-20 11:25:58	ga_ls8c_ard_3-2-1_111073_2022-07-20_final
2022-07-24 11:00:06	ga_ls8c_ard_3-2-1_107070_2022-07-24_final
2022-07-26 09:15:16	ga_ls8c_ard_3-2-1_089086_2022-07-25_final
2022-08-04 10:40:53	ga_ls8c_ard_3-2-1_104068_2022-08-04_final
2022-08-07 09:35:19	ga_ls8c_ard_3-2-1_093074_2022-08-07_final
2022-08-07 09:37:43	ga_ls8c_ard_3-2-1_093080_2022-08-07_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-15 10:23:36	ga_ls8c_ard_3-2-1_101071_2022-08-15_final
2022-08-17 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-08-17_final
2022-08-23 09:37:46	ga_ls8c_ard_3-2-1_093080_2022-08-23_final
2022-08-24 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-08-24_final
2022-08-25 09:27:24	ga_ls8c_ard_3-2-1_091085_2022-08-24_final
2022-09-01 11:06:52	ga_ls8c_ard_3-2-1_108071_2022-09-01_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-10 11:05:57	ga_ls8c_ard_3-2-1_107084_2022-09-10_final
2022-09-13 11:36:29	ga_ls8c_ard_3-2-1_112083_2022-09-13_final
2022-09-17 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-09-17_final
2022-09-23 10:29:07	ga_ls8c_ard_3-2-1_102069_2022-09-23_final
2022-09-23 10:29:31	ga_ls8c_ard_3-2-1_102070_2022-09-23_final
2022-10-04 10:15:44	ga_ls8c_ard_3-2-1_099082_2022-10-04_final
2022-10-12 09:23:48	ga_ls8c_ard_3-2-1_091076_2022-10-11_final
2022-10-12 09:25:47	ga_ls8c_ard_3-2-1_091081_2022-10-11_final
2022-10-13 10:05:27	ga_ls8c_ard_3-2-1_098072_2022-10-13_final
2022-10-14 09:14:12	ga_ls8c_ard_3-2-1_089083_2022-10-13_final
2022-10-14 09:15:00	ga_ls8c_ard_3-2-1_089085_2022-10-13_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-17 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-10-17_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-20 10:15:41	ga_ls8c_ard_3-2-1_099082_2022-10-20_final
2022-10-25 10:29:29	ga_ls8c_ard_3-2-1_102070_2022-10-25_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-11-03 10:26:55	ga_ls8c_ard_3-2-1_101079_2022-11-03_final
2022-11-13 11:05:56	ga_ls8c_ard_3-2-1_107084_2022-11-13_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-15 09:15:28	ga_ls8c_ard_3-2-1_089086_2022-11-14_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-18 11:20:25	ga_ls8c_ard_3-2-1_110074_2022-11-18_final
2022-11-22 09:18:50	ga_ls8c_ard_3-2-1_090079_2022-11-21_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-30 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-30_final
2022-12-02 11:33:14	ga_ls8c_ard_3-2-1_112075_2022-12-02_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-09 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-12-09_final
2022-12-14 11:58:17	ga_ls8c_ard_3-2-1_116076_2022-12-14_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-18 09:52:38	ga_ls8c_ard_3-2-1_096071_2022-12-18_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-06 10:27:53	ga_ls8c_ard_3-2-1_101082_2023-01-06_final
2023-01-07 11:10:44	ga_ls8c_ard_3-2-1_108081_2023-01-07_final
2023-01-08 10:11:55	ga_ls8c_ard_3-2-1_099073_2023-01-08_final
2023-01-10 10:03:56	ga_ls8c_ard_3-2-1_097084_2023-01-10_final
2023-01-15 11:58:06	ga_ls8c_ard_3-2-1_116076_2023-01-15_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-20 10:34:33	ga_ls8c_ard_3-2-1_103068_2023-01-20_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-01-24 11:52:22	ga_ls8c_ard_3-2-1_115077_2023-01-24_final
2023-01-30 09:40:01	ga_ls8c_ard_3-2-1_093086_2023-01-30_final
2023-01-31 10:18:29	ga_ls8c_ard_3-2-1_100074_2023-01-31_final
2023-02-07 10:25:51	ga_ls8c_ard_3-2-1_101077_2023-02-07_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-17 09:28:18	ga_ls8c_ard_3-2-1_091088_2023-02-16_final
2023-02-20 09:58:21	ga_ls8c_ard_3-2-1_096086_2023-02-20_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_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