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
2023-09-05 10:12:17	ga_ls8c_ard_3-2-1_099075_2023-09-05_final
2023-09-05 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-09-05_final
2023-09-05 11:51:34	ga_ls8c_ard_3-2-1_115076_2023-09-05_final
2023-09-06 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-09-05_final
2023-09-07 11:38:25	ga_ls8c_ard_3-2-1_113074_2023-09-07_final
2023-09-08 10:40:48	ga_ls8c_ard_3-2-1_104069_2023-09-08_final
2023-09-08 10:45:12	ga_ls8c_ard_3-2-1_104080_2023-09-08_final
2023-09-09 09:49:11	ga_ls8c_ard_3-2-1_095079_2023-09-09_final
2023-09-09 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-09-09_final
2023-09-09 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-09-09_final
2023-09-10 10:30:28	ga_ls8c_ard_3-2-1_102074_2023-09-10_final
2023-09-11 09:34:52	ga_ls8c_ard_3-2-1_093074_2023-09-11_final
2023-09-11 09:35:39	ga_ls8c_ard_3-2-1_093076_2023-09-11_final
2023-09-20 11:10:25	ga_ls8c_ard_3-2-1_108081_2023-09-20_final
2023-09-21 10:10:24	ga_ls8c_ard_3-2-1_099070_2023-09-21_final
2023-09-22 10:56:51	ga_ls8c_ard_3-2-1_106078_2023-09-22_final
2023-09-23 11:40:31	ga_ls8c_ard_3-2-1_113079_2023-09-23_final
2023-09-24 10:40:55	ga_ls8c_ard_3-2-1_104069_2023-09-24_final
2023-09-25 09:50:05	ga_ls8c_ard_3-2-1_095081_2023-09-25_final
2023-09-26 10:30:10	ga_ls8c_ard_3-2-1_102073_2023-09-26_final
2023-09-28 10:17:25	ga_ls8c_ard_3-2-1_100072_2023-09-28_final
2023-09-29 09:27:47	ga_ls8c_ard_3-2-1_091087_2023-09-28_final
2023-09-30 10:03:52	ga_ls8c_ard_3-2-1_098069_2023-09-30_final
2023-10-01 09:16:14	ga_ls8c_ard_3-2-1_089089_2023-09-30_final
2023-10-02 09:54:42	ga_ls8c_ard_3-2-1_096077_2023-10-02_final
2023-10-02 09:55:06	ga_ls8c_ard_3-2-1_096078_2023-10-02_final
2023-10-02 11:33:11	ga_ls8c_ard_3-2-1_112076_2023-10-02_final
2023-10-03 10:38:22	ga_ls8c_ard_3-2-1_103078_2023-10-03_final
2023-10-04 11:19:14	ga_ls8c_ard_3-2-1_110072_2023-10-04_final
2023-10-04 11:20:25	ga_ls8c_ard_3-2-1_110075_2023-10-04_final
2023-10-04 11:22:25	ga_ls8c_ard_3-2-1_110080_2023-10-04_final
2023-10-07 10:10:03	ga_ls8c_ard_3-2-1_099069_2023-10-07_final
2023-10-07 10:11:39	ga_ls8c_ard_3-2-1_099073_2023-10-07_final
2023-10-07 10:12:03	ga_ls8c_ard_3-2-1_099074_2023-10-07_final
2023-10-07 10:12:27	ga_ls8c_ard_3-2-1_099075_2023-10-07_final
2023-10-07 10:14:50	ga_ls8c_ard_3-2-1_099081_2023-10-07_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-08 10:56:55	ga_ls8c_ard_3-2-1_106078_2023-10-08_final
2023-10-09 11:40:35	ga_ls8c_ard_3-2-1_113079_2023-10-09_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-12 10:29:26	ga_ls8c_ard_3-2-1_102071_2023-10-12_final
2023-10-13 09:37:24	ga_ls8c_ard_3-2-1_093080_2023-10-13_final
2023-10-13 11:17:05	ga_ls8c_ard_3-2-1_109082_2023-10-13_final
2023-10-13 11:17:29	ga_ls8c_ard_3-2-1_109083_2023-10-13_final
2023-10-14 10:20:40	ga_ls8c_ard_3-2-1_100080_2023-10-14_final
2023-10-15 09:23:51	ga_ls8c_ard_3-2-1_091077_2023-10-14_final
2023-10-15 11:01:32	ga_ls8c_ard_3-2-1_107074_2023-10-15_final
2023-10-17 09:13:04	ga_ls8c_ard_3-2-1_089081_2023-10-16_final
2023-10-17 10:47:34	ga_ls8c_ard_3-2-1_105070_2023-10-17_final
2023-10-17 10:47:58	ga_ls8c_ard_3-2-1_105071_2023-10-17_final
2023-10-17 10:48:46	ga_ls8c_ard_3-2-1_105073_2023-10-17_final
2023-10-17 10:51:33	ga_ls8c_ard_3-2-1_105080_2023-10-17_final
2023-10-20 11:20:26	ga_ls8c_ard_3-2-1_110075_2023-10-20_final
2023-10-21 10:26:50	ga_ls8c_ard_3-2-1_101080_2023-10-21_final
2023-10-22 09:32:49	ga_ls8c_ard_3-2-1_092084_2023-10-22_final
2023-10-23 10:15:41	ga_ls8c_ard_3-2-1_099083_2023-10-23_final
2023-10-23 11:51:47	ga_ls8c_ard_3-2-1_115076_2023-10-23_final
2023-10-24 09:19:41	ga_ls8c_ard_3-2-1_090082_2023-10-23_final
2023-10-24 10:53:22	ga_ls8c_ard_3-2-1_106069_2023-10-24_final
2023-10-24 10:56:58	ga_ls8c_ard_3-2-1_106078_2023-10-24_final
2023-10-25 11:40:38	ga_ls8c_ard_3-2-1_113079_2023-10-25_final
2023-10-26 10:41:02	ga_ls8c_ard_3-2-1_104069_2023-10-26_final
2023-10-26 10:43:49	ga_ls8c_ard_3-2-1_104076_2023-10-26_final
2023-10-26 10:44:13	ga_ls8c_ard_3-2-1_104077_2023-10-26_final
2023-10-27 09:50:12	ga_ls8c_ard_3-2-1_095081_2023-10-27_final
2023-10-29 09:36:15	ga_ls8c_ard_3-2-1_093077_2023-10-29_final
2023-10-29 09:37:27	ga_ls8c_ard_3-2-1_093080_2023-10-29_final
2023-10-29 11:11:57	ga_ls8c_ard_3-2-1_109069_2023-10-29_final
2023-10-30 10:20:43	ga_ls8c_ard_3-2-1_100080_2023-10-30_final
2023-10-31 09:28:41	ga_ls8c_ard_3-2-1_091089_2023-10-30_final
2023-11-02 10:48:01	ga_ls8c_ard_3-2-1_105071_2023-11-02_final
2023-11-03 09:54:47	ga_ls8c_ard_3-2-1_096077_2023-11-03_final
2023-11-03 11:32:28	ga_ls8c_ard_3-2-1_112074_2023-11-03_final
2023-11-04 10:36:51	ga_ls8c_ard_3-2-1_103074_2023-11-04_final
2023-11-05 09:42:25	ga_ls8c_ard_3-2-1_094077_2023-11-05_final
2023-11-06 10:23:16	ga_ls8c_ard_3-2-1_101071_2023-11-06_final
2023-11-07 09:30:02	ga_ls8c_ard_3-2-1_092077_2023-11-07_final
2023-11-07 11:06:07	ga_ls8c_ard_3-2-1_108070_2023-11-07_final
2023-11-07 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-11-07_final
2023-11-08 10:10:29	ga_ls8c_ard_3-2-1_099070_2023-11-08_final
2023-11-08 10:11:40	ga_ls8c_ard_3-2-1_099073_2023-11-08_final
2023-11-08 10:12:04	ga_ls8c_ard_3-2-1_099074_2023-11-08_final
2023-11-08 10:12:28	ga_ls8c_ard_3-2-1_099075_2023-11-08_final
2023-11-08 10:14:52	ga_ls8c_ard_3-2-1_099081_2023-11-08_final
2023-11-09 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-11-08_final
2023-11-09 10:54:07	ga_ls8c_ard_3-2-1_106071_2023-11-09_final
2023-11-09 10:58:54	ga_ls8c_ard_3-2-1_106083_2023-11-09_final
2023-11-10 11:40:34	ga_ls8c_ard_3-2-1_113079_2023-11-10_final
2023-11-11 10:43:45	ga_ls8c_ard_3-2-1_104076_2023-11-11_final
2023-11-11 10:44:09	ga_ls8c_ard_3-2-1_104077_2023-11-11_final
2023-11-12 09:48:33	ga_ls8c_ard_3-2-1_095077_2023-11-12_final
2023-11-12 09:48:57	ga_ls8c_ard_3-2-1_095078_2023-11-12_final
2023-11-16 09:25:05	ga_ls8c_ard_3-2-1_091080_2023-11-15_final
2023-11-16 09:28:16	ga_ls8c_ard_3-2-1_091088_2023-11-15_final
2023-11-17 10:03:57	ga_ls8c_ard_3-2-1_098069_2023-11-17_final
2023-11-17 10:04:21	ga_ls8c_ard_3-2-1_098070_2023-11-17_final
2023-11-17 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-11-17_final
2023-11-18 10:48:02	ga_ls8c_ard_3-2-1_105071_2023-11-18_final
2023-11-18 10:49:13	ga_ls8c_ard_3-2-1_105074_2023-11-18_final
2023-11-18 10:50:49	ga_ls8c_ard_3-2-1_105078_2023-11-18_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