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
2022-09-11 11:46:50	ga_ls8c_ard_3-2-1_114078_2022-09-11_final
2022-09-18 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-09-18_final
2022-09-20 09:59:25	ga_ls8c_ard_3-2-1_097072_2022-09-20_final
2022-09-26 11:02:49	ga_ls8c_ard_3-2-1_107076_2022-09-26_final
2022-09-27 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-09-27_final
2022-09-30 10:35:41	ga_ls8c_ard_3-2-1_103070_2022-09-30_final
2022-10-03 09:31:41	ga_ls8c_ard_3-2-1_092080_2022-10-03_final
2022-10-05 10:59:23	ga_ls8c_ard_3-2-1_106083_2022-10-05_final
2022-10-06 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-06_final
2022-10-07 10:42:13	ga_ls8c_ard_3-2-1_104071_2022-10-07_final
2022-10-07 10:45:48	ga_ls8c_ard_3-2-1_104080_2022-10-07_final
2022-10-10 11:13:29	ga_ls8c_ard_3-2-1_109072_2022-10-10_final
2022-10-11 10:18:38	ga_ls8c_ard_3-2-1_100074_2022-10-11_final
2022-10-12 11:02:17	ga_ls8c_ard_3-2-1_107075_2022-10-12_final
2022-10-14 09:13:48	ga_ls8c_ard_3-2-1_089082_2022-10-13_final
2022-10-15 09:53:05	ga_ls8c_ard_3-2-1_096072_2022-10-15_final
2022-10-15 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-10-15_final
2022-10-15 11:34:46	ga_ls8c_ard_3-2-1_112079_2022-10-15_final
2022-10-15 11:35:34	ga_ls8c_ard_3-2-1_112081_2022-10-15_final
2022-10-17 09:43:57	ga_ls8c_ard_3-2-1_094080_2022-10-17_final
2022-10-17 09:46:45	ga_ls8c_ard_3-2-1_094087_2022-10-17_final
2022-10-21 10:57:46	ga_ls8c_ard_3-2-1_106079_2022-10-21_final
2022-10-22 11:39:26	ga_ls8c_ard_3-2-1_113075_2022-10-22_final
2022-10-22 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-22_final
2022-10-23 10:45:49	ga_ls8c_ard_3-2-1_104080_2022-10-23_final
2022-10-24 09:48:12	ga_ls8c_ard_3-2-1_095075_2022-10-24_final
2022-10-26 11:13:33	ga_ls8c_ard_3-2-1_109072_2022-10-26_final
2022-10-26 11:15:33	ga_ls8c_ard_3-2-1_109077_2022-10-26_final
2022-10-27 10:19:08	ga_ls8c_ard_3-2-1_100075_2022-10-27_final
2022-10-27 11:58:25	ga_ls8c_ard_3-2-1_116076_2022-10-27_final
2022-10-28 09:24:43	ga_ls8c_ard_3-2-1_091078_2022-10-27_final
2022-10-28 09:26:18	ga_ls8c_ard_3-2-1_091082_2022-10-27_final
2022-11-02 11:23:21	ga_ls8c_ard_3-2-1_110081_2022-11-02_final
2022-11-03 10:25:20	ga_ls8c_ard_3-2-1_101075_2022-11-03_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-07 11:41:28	ga_ls8c_ard_3-2-1_113080_2022-11-07_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-09 09:51:25	ga_ls8c_ard_3-2-1_095083_2022-11-09_final
2022-11-13 11:01:32	ga_ls8c_ard_3-2-1_107073_2022-11-13_final
2022-11-14 10:05:54	ga_ls8c_ard_3-2-1_098073_2022-11-14_final
2022-11-18 09:43:55	ga_ls8c_ard_3-2-1_094080_2022-11-18_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-20 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-11-20_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-25 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-11-25_final
2022-11-26 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-11-26_final
2022-11-29 09:26:14	ga_ls8c_ard_3-2-1_091082_2022-11-28_final
2022-11-30 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-30_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-04 11:22:52	ga_ls8c_ard_3-2-1_110080_2022-12-04_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-09 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-12-09_final
2022-12-11 09:50:55	ga_ls8c_ard_3-2-1_095082_2022-12-11_final
2022-12-13 09:34:33	ga_ls8c_ard_3-2-1_093072_2022-12-13_final
2022-12-17 09:14:10	ga_ls8c_ard_3-2-1_089083_2022-12-16_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2022-12-19 10:37:52	ga_ls8c_ard_3-2-1_103076_2022-12-19_final
2022-12-19 10:40:16	ga_ls8c_ard_3-2-1_103082_2022-12-19_final
2022-12-20 11:22:43	ga_ls8c_ard_3-2-1_110080_2022-12-20_final
2022-12-27 09:50:48	ga_ls8c_ard_3-2-1_095082_2022-12-27_final
2022-12-27 09:51:12	ga_ls8c_ard_3-2-1_095083_2022-12-27_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2022-12-31 11:02:59	ga_ls8c_ard_3-2-1_107077_2022-12-31_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-09 09:20:41	ga_ls8c_ard_3-2-1_090084_2023-01-08_final
2023-01-09 10:57:58	ga_ls8c_ard_3-2-1_106080_2023-01-09_final
2023-01-10 10:03:32	ga_ls8c_ard_3-2-1_097083_2023-01-10_final
2023-01-10 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-10_final
2023-01-14 09:39:58	ga_ls8c_ard_3-2-1_093086_2023-01-14_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-21 09:41:44	ga_ls8c_ard_3-2-1_094075_2023-01-21_final
2023-01-21 09:43:44	ga_ls8c_ard_3-2-1_094080_2023-01-21_final
2023-01-22 10:24:37	ga_ls8c_ard_3-2-1_101074_2023-01-22_final
2023-01-22 10:25:25	ga_ls8c_ard_3-2-1_101076_2023-01-22_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-02-06 11:20:40	ga_ls8c_ard_3-2-1_110075_2023-02-06_final
2023-02-08 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-02-08_final
2023-02-10 09:18:38	ga_ls8c_ard_3-2-1_090079_2023-02-09_final
2023-02-10 10:57:07	ga_ls8c_ard_3-2-1_106078_2023-02-10_final
2023-02-12 10:44:19	ga_ls8c_ard_3-2-1_104077_2023-02-12_final
2023-02-15 09:39:54	ga_ls8c_ard_3-2-1_093086_2023-02-15_final
2023-02-16 10:18:45	ga_ls8c_ard_3-2-1_100075_2023-02-16_final
2023-02-17 11:02:48	ga_ls8c_ard_3-2-1_107077_2023-02-17_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-19 10:50:24	ga_ls8c_ard_3-2-1_105077_2023-02-19_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-20 11:35:38	ga_ls8c_ard_3-2-1_112082_2023-02-20_final
2023-02-22 09:45:32	ga_ls8c_ard_3-2-1_094085_2023-02-22_final
2023-02-24 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-02-24_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-03-01 11:26:32	ga_ls8c_ard_3-2-1_111075_2023-03-01_final
2023-03-06 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-03-06_final
2023-03-07 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-03-06_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-12 09:31:26	ga_ls8c_ard_3-2-1_092081_2023-03-12_final
2023-03-12 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-03-12_final
2023-03-15 09:59:08	ga_ls8c_ard_3-2-1_097073_2023-03-15_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