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
2022-10-23 10:45:49	ga_ls8c_ard_3-2-1_104080_2022-10-23_final
2022-10-24 11:29:53	ga_ls8c_ard_3-2-1_111082_2022-10-24_final
2022-10-26 11:12:21	ga_ls8c_ard_3-2-1_109069_2022-10-26_final
2022-11-04 11:10:35	ga_ls8c_ard_3-2-1_108080_2022-11-04_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-11 09:36:38	ga_ls8c_ard_3-2-1_093077_2022-11-11_final
2022-11-20 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-11-20_final
2022-11-20 09:35:34	ga_ls8c_ard_3-2-1_092090_2022-11-20_final
2022-11-22 09:18:50	ga_ls8c_ard_3-2-1_090079_2022-11-21_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-25 11:29:26	ga_ls8c_ard_3-2-1_111081_2022-11-25_final
2022-11-26 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-11-26_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-11-27 11:17:29	ga_ls8c_ard_3-2-1_109082_2022-11-27_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-12-02 09:52:21	ga_ls8c_ard_3-2-1_096070_2022-12-02_final
2022-12-02 11:32:26	ga_ls8c_ard_3-2-1_112073_2022-12-02_final
2022-12-04 09:42:23	ga_ls8c_ard_3-2-1_094076_2022-12-04_final
2022-12-05 10:24:26	ga_ls8c_ard_3-2-1_101073_2022-12-05_final
2022-12-05 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-12-05_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-06 11:12:05	ga_ls8c_ard_3-2-1_108084_2022-12-06_final
2022-12-08 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-12-07_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-11 11:29:24	ga_ls8c_ard_3-2-1_111081_2022-12-11_final
2022-12-13 11:15:50	ga_ls8c_ard_3-2-1_109078_2022-12-13_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-17 10:48:16	ga_ls8c_ard_3-2-1_105071_2022-12-17_final
2022-12-18 09:58:13	ga_ls8c_ard_3-2-1_096085_2022-12-18_final
2022-12-20 09:43:50	ga_ls8c_ard_3-2-1_094080_2022-12-20_final
2022-12-23 10:15:05	ga_ls8c_ard_3-2-1_099081_2022-12-23_final
2022-12-25 10:02:45	ga_ls8c_ard_3-2-1_097081_2022-12-25_final
2022-12-27 09:51:12	ga_ls8c_ard_3-2-1_095083_2022-12-27_final
2022-12-28 10:30:04	ga_ls8c_ard_3-2-1_102072_2022-12-28_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2022-12-29 11:16:56	ga_ls8c_ard_3-2-1_109081_2022-12-29_final
2023-01-06 10:25:05	ga_ls8c_ard_3-2-1_101075_2023-01-06_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-13 10:32:00	ga_ls8c_ard_3-2-1_102077_2023-01-13_final
2023-01-16 11:03:40	ga_ls8c_ard_3-2-1_107079_2023-01-16_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-20 10:35:45	ga_ls8c_ard_3-2-1_103071_2023-01-20_final
2023-01-20 10:38:57	ga_ls8c_ard_3-2-1_103079_2023-01-20_final
2023-01-21 09:41:44	ga_ls8c_ard_3-2-1_094075_2023-01-21_final
2023-02-08 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-02-08_final
2023-02-08 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-02-08_final
2023-02-08 11:10:42	ga_ls8c_ard_3-2-1_108081_2023-02-08_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-11 10:02:16	ga_ls8c_ard_3-2-1_097080_2023-02-11_final
2023-02-11 11:41:33	ga_ls8c_ard_3-2-1_113081_2023-02-11_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-18 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-02-18_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-22 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-02-22_final
2023-02-22 09:46:20	ga_ls8c_ard_3-2-1_094087_2023-02-22_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-03 11:17:46	ga_ls8c_ard_3-2-1_109084_2023-03-03_final
2023-03-06 11:44:38	ga_ls8c_ard_3-2-1_114074_2023-03-06_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-10 09:44:59	ga_ls8c_ard_3-2-1_094084_2023-03-10_final
2023-03-10 11:18:41	ga_ls8c_ard_3-2-1_110071_2023-03-10_final
2023-03-11 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-03-11_final
2023-03-12 11:06:20	ga_ls8c_ard_3-2-1_108071_2023-03-12_final
2023-03-13 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-03-13_final
2023-03-13 11:50:47	ga_ls8c_ard_3-2-1_115074_2023-03-13_final
2023-03-15 09:58:20	ga_ls8c_ard_3-2-1_097071_2023-03-15_final
2023-03-15 10:01:31	ga_ls8c_ard_3-2-1_097079_2023-03-15_final
2023-03-17 11:26:26	ga_ls8c_ard_3-2-1_111075_2023-03-17_final
2023-03-22 10:05:12	ga_ls8c_ard_3-2-1_098073_2023-03-22_final
2023-03-22 11:46:05	ga_ls8c_ard_3-2-1_114078_2023-03-22_final
2023-03-25 10:36:05	ga_ls8c_ard_3-2-1_103073_2023-03-25_final
2023-03-28 09:29:17	ga_ls8c_ard_3-2-1_092076_2023-03-27_final
2023-03-30 09:18:30	ga_ls8c_ard_3-2-1_090080_2023-03-29_final
2023-03-30 09:20:05	ga_ls8c_ard_3-2-1_090084_2023-03-29_final
2023-04-04 11:13:03	ga_ls8c_ard_3-2-1_109073_2023-04-04_final
2023-04-08 10:48:14	ga_ls8c_ard_3-2-1_105073_2023-04-08_final
2023-04-11 11:20:16	ga_ls8c_ard_3-2-1_110076_2023-04-11_final
2023-04-12 10:23:03	ga_ls8c_ard_3-2-1_101072_2023-04-12_final
2023-04-13 09:34:36	ga_ls8c_ard_3-2-1_092090_2023-04-13_final
2023-04-13 11:09:06	ga_ls8c_ard_3-2-1_108079_2023-04-13_final
2023-04-18 09:51:07	ga_ls8c_ard_3-2-1_095085_2023-04-18_final
2023-04-21 10:18:25	ga_ls8c_ard_3-2-1_100076_2023-04-21_final
2023-04-21 11:57:42	ga_ls8c_ard_3-2-1_116077_2023-04-21_final
2023-04-27 09:43:43	ga_ls8c_ard_3-2-1_094082_2023-04-27_final
2023-04-29 09:29:21	ga_ls8c_ard_3-2-1_092077_2023-04-28_final
2023-05-04 09:49:50	ga_ls8c_ard_3-2-1_095082_2023-05-04_final
2023-05-04 09:51:02	ga_ls8c_ard_3-2-1_095085_2023-05-04_final
2023-05-06 09:34:15	ga_ls8c_ard_3-2-1_093074_2023-05-06_final
2023-05-10 10:51:32	ga_ls8c_ard_3-2-1_105082_2023-05-10_final
2023-05-13 11:21:11	ga_ls8c_ard_3-2-1_110079_2023-05-13_final
2023-05-15 11:05:13	ga_ls8c_ard_3-2-1_108070_2023-05-15_final
2023-05-15 11:07:37	ga_ls8c_ard_3-2-1_108076_2023-05-15_final
2023-05-17 10:53:15	ga_ls8c_ard_3-2-1_106071_2023-05-17_final
2023-05-18 11:40:06	ga_ls8c_ard_3-2-1_113080_2023-05-18_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