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
2022-07-23 11:58:54	ga_ls8c_ard_3-2-1_116078_2022-07-23_final
2022-07-29 11:23:06	ga_ls8c_ard_3-2-1_110081_2022-07-29_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-08-09 09:22:34	ga_ls8c_ard_3-2-1_091073_2022-08-08_final
2022-08-17 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-08-17_final
2022-08-25 09:28:12	ga_ls8c_ard_3-2-1_091087_2022-08-24_final
2022-08-26 10:08:16	ga_ls8c_ard_3-2-1_098079_2022-08-26_final
2022-09-12 09:16:43	ga_ls8c_ard_3-2-1_089089_2022-09-11_final
2022-09-14 10:34:52	ga_ls8c_ard_3-2-1_103068_2022-09-14_final
2022-09-19 09:17:45	ga_ls8c_ard_3-2-1_090076_2022-09-18_final
2022-09-20 09:57:25	ga_ls8c_ard_3-2-1_097067_2022-09-20_final
2022-09-26 09:27:55	ga_ls8c_ard_3-2-1_091086_2022-09-25_final
2022-09-26 09:28:43	ga_ls8c_ard_3-2-1_091088_2022-09-25_final
2022-10-02 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-10-02_final
2022-10-08 11:26:16	ga_ls8c_ard_3-2-1_111073_2022-10-08_final
2022-10-09 10:33:49	ga_ls8c_ard_3-2-1_102081_2022-10-09_final
2022-10-12 09:26:59	ga_ls8c_ard_3-2-1_091084_2022-10-11_final
2022-10-13 10:10:14	ga_ls8c_ard_3-2-1_098084_2022-10-13_final
2022-10-19 11:08:30	ga_ls8c_ard_3-2-1_108075_2022-10-19_final
2022-10-20 10:14:05	ga_ls8c_ard_3-2-1_099078_2022-10-20_final
2022-10-29 10:04:23	ga_ls8c_ard_3-2-1_098069_2022-10-29_final
2022-11-09 11:30:18	ga_ls8c_ard_3-2-1_111083_2022-11-09_final
2022-11-14 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-14_final
2022-11-21 10:10:04	ga_ls8c_ard_3-2-1_099068_2022-11-21_final
2022-11-28 10:19:28	ga_ls8c_ard_3-2-1_100076_2022-11-28_final
2022-11-30 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-30_final
2022-12-01 10:47:10	ga_ls8c_ard_3-2-1_105068_2022-12-01_final
2022-12-04 09:41:35	ga_ls8c_ard_3-2-1_094074_2022-12-04_final
2022-12-08 09:18:03	ga_ls8c_ard_3-2-1_090077_2022-12-07_final
2022-12-08 10:56:08	ga_ls8c_ard_3-2-1_106075_2022-12-08_final
2022-12-10 10:42:57	ga_ls8c_ard_3-2-1_104073_2022-12-10_final
2022-12-14 10:20:12	ga_ls8c_ard_3-2-1_100078_2022-12-14_final
2022-12-20 11:21:31	ga_ls8c_ard_3-2-1_110077_2022-12-20_final
2022-12-22 09:29:26	ga_ls8c_ard_3-2-1_092075_2022-12-21_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2022-12-24 09:22:16	ga_ls8c_ard_3-2-1_090088_2022-12-23_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2023-01-02 10:47:26	ga_ls8c_ard_3-2-1_105069_2023-01-02_final
2023-01-09 09:18:17	ga_ls8c_ard_3-2-1_090078_2023-01-08_final
2023-01-11 10:44:00	ga_ls8c_ard_3-2-1_104076_2023-01-11_final
2023-01-14 09:36:22	ga_ls8c_ard_3-2-1_093077_2023-01-14_final
2023-01-15 10:22:01	ga_ls8c_ard_3-2-1_100083_2023-01-15_final
2023-01-18 09:12:47	ga_ls8c_ard_3-2-1_089080_2023-01-17_final
2023-01-23 11:08:17	ga_ls8c_ard_3-2-1_108075_2023-01-23_final
2023-01-24 10:11:05	ga_ls8c_ard_3-2-1_099071_2023-01-24_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-01-25 09:22:15	ga_ls8c_ard_3-2-1_090088_2023-01-24_final
2023-01-25 09:23:03	ga_ls8c_ard_3-2-1_090090_2023-01-24_final
2023-02-04 11:32:39	ga_ls8c_ard_3-2-1_112074_2023-02-04_final
2023-02-09 10:11:52	ga_ls8c_ard_3-2-1_099073_2023-02-09_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-10 10:54:43	ga_ls8c_ard_3-2-1_106072_2023-02-10_final
2023-02-16 10:19:09	ga_ls8c_ard_3-2-1_100076_2023-02-16_final
2023-02-19 10:50:00	ga_ls8c_ard_3-2-1_105076_2023-02-19_final
2023-02-23 10:23:11	ga_ls8c_ard_3-2-1_101071_2023-02-23_final
2023-02-26 09:17:33	ga_ls8c_ard_3-2-1_090077_2023-02-25_final
2023-02-26 09:21:57	ga_ls8c_ard_3-2-1_090088_2023-02-25_final
2023-03-06 10:07:21	ga_ls8c_ard_3-2-1_098078_2023-03-06_final
2023-03-14 09:16:40	ga_ls8c_ard_3-2-1_090075_2023-03-13_final
2023-03-14 10:53:57	ga_ls8c_ard_3-2-1_106071_2023-03-14_final
2023-03-17 11:24:50	ga_ls8c_ard_3-2-1_111071_2023-03-17_final
2023-03-22 10:03:37	ga_ls8c_ard_3-2-1_098069_2023-03-22_final
2023-03-22 10:09:36	ga_ls8c_ard_3-2-1_098084_2023-03-22_final
2023-03-31 11:38:14	ga_ls8c_ard_3-2-1_113074_2023-03-31_final
2023-04-01 09:06:31	ga_ls8c_ard_3-2-1_088081_2023-03-31_final
2023-04-13 09:31:49	ga_ls8c_ard_3-2-1_092083_2023-04-13_final
2023-04-13 11:05:07	ga_ls8c_ard_3-2-1_108069_2023-04-13_final
2023-04-15 09:16:15	ga_ls8c_ard_3-2-1_090075_2023-04-14_final
2023-04-16 09:57:31	ga_ls8c_ard_3-2-1_097070_2023-04-16_final
2023-04-27 09:45:19	ga_ls8c_ard_3-2-1_094086_2023-04-27_final
2023-05-01 09:22:10	ga_ls8c_ard_3-2-1_090090_2023-04-30_final
2023-05-18 11:37:42	ga_ls8c_ard_3-2-1_113074_2023-05-18_final
2023-05-19 09:05:36	ga_ls8c_ard_3-2-1_088080_2023-05-18_final
2023-05-22 09:32:56	ga_ls8c_ard_3-2-1_093071_2023-05-22_final
2023-05-24 09:26:58	ga_ls8c_ard_3-2-1_091087_2023-05-23_final
2023-06-03 09:57:17	ga_ls8c_ard_3-2-1_097070_2023-06-03_final
2023-06-05 11:25:03	ga_ls8c_ard_3-2-1_111073_2023-06-05_final
2023-06-08 10:16:18	ga_ls8c_ard_3-2-1_100071_2023-06-08_final
2023-06-09 09:22:17	ga_ls8c_ard_3-2-1_091075_2023-06-08_final
2023-06-10 11:46:50	ga_ls8c_ard_3-2-1_114081_2023-06-10_final
2023-06-11 09:09:33	ga_ls8c_ard_3-2-1_089074_2023-06-10_final
2023-06-20 09:05:48	ga_ls8c_ard_3-2-1_088080_2023-06-19_final
2023-06-26 10:03:41	ga_ls8c_ard_3-2-1_098070_2023-06-26_final
2023-07-05 11:41:41	ga_ls8c_ard_3-2-1_113083_2023-07-05_final
2023-07-06 09:06:24	ga_ls8c_ard_3-2-1_088081_2023-07-05_final
2023-07-07 11:24:10	ga_ls8c_ard_3-2-1_111070_2023-07-07_final
2023-07-09 11:12:13	ga_ls8c_ard_3-2-1_109071_2023-07-09_final
2023-07-25 11:14:17	ga_ls8c_ard_3-2-1_109076_2023-07-25_final
2023-07-31 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-07-31_final
2023-08-01 11:23:44	ga_ls8c_ard_3-2-1_110084_2023-08-01_final
2023-08-04 10:09:23	ga_ls8c_ard_3-2-1_099068_2023-08-04_final
2023-08-04 10:15:22	ga_ls8c_ard_3-2-1_099083_2023-08-04_final
2023-08-07 09:07:00	ga_ls8c_ard_3-2-1_088082_2023-08-06_final
2023-08-08 09:51:51	ga_ls8c_ard_3-2-1_095086_2023-08-08_final
2023-08-12 09:28:20	ga_ls8c_ard_3-2-1_091089_2023-08-11_final
2023-08-22 11:38:26	ga_ls8c_ard_3-2-1_113074_2023-08-22_final
2023-08-23 10:42:25	ga_ls8c_ard_3-2-1_104073_2023-08-23_final
2023-08-26 11:13:43	ga_ls8c_ard_3-2-1_109074_2023-08-26_final
2023-09-04 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-09-04_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