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
2022-01-14 10:07:58	ga_ls8c_ard_3-2-1_098079_2022-01-14_final
2022-01-14 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-01-14_final
2022-10-24 11:26:42	ga_ls8c_ard_3-2-1_111074_2022-10-24_final
2022-10-28 09:23:07	ga_ls8c_ard_3-2-1_091074_2022-10-27_final
2022-10-28 09:25:30	ga_ls8c_ard_3-2-1_091080_2022-10-27_final
2022-10-30 09:15:33	ga_ls8c_ard_3-2-1_089086_2022-10-29_final
2022-10-30 10:46:51	ga_ls8c_ard_3-2-1_105067_2022-10-30_final
2022-11-01 10:34:54	ga_ls8c_ard_3-2-1_103068_2022-11-01_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-02 11:20:57	ga_ls8c_ard_3-2-1_110075_2022-11-02_final
2022-11-05 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-11-05_final
2022-11-05 11:52:15	ga_ls8c_ard_3-2-1_115076_2022-11-05_final
2022-11-12 10:17:30	ga_ls8c_ard_3-2-1_100071_2022-11-12_final
2022-11-28 10:22:39	ga_ls8c_ard_3-2-1_100084_2022-11-28_final
2022-12-02 11:36:25	ga_ls8c_ard_3-2-1_112083_2022-12-02_final
2022-12-13 11:12:14	ga_ls8c_ard_3-2-1_109069_2022-12-13_final
2022-12-13 11:12:38	ga_ls8c_ard_3-2-1_109070_2022-12-13_final
2022-12-27 11:29:17	ga_ls8c_ard_3-2-1_111081_2022-12-27_final
2023-01-08 11:52:48	ga_ls8c_ard_3-2-1_115078_2023-01-08_final
2023-01-09 09:22:17	ga_ls8c_ard_3-2-1_090088_2023-01-08_final
2023-01-10 11:42:25	ga_ls8c_ard_3-2-1_113083_2023-01-10_final
2023-01-12 11:26:03	ga_ls8c_ard_3-2-1_111073_2023-01-12_final
2023-01-17 11:46:30	ga_ls8c_ard_3-2-1_114078_2023-01-17_final
2023-01-18 09:11:35	ga_ls8c_ard_3-2-1_089077_2023-01-17_final
2023-01-18 09:12:23	ga_ls8c_ard_3-2-1_089079_2023-01-17_final
2023-01-21 11:21:02	ga_ls8c_ard_3-2-1_110076_2023-01-21_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-26 11:42:24	ga_ls8c_ard_3-2-1_113083_2023-01-26_final
2023-01-31 10:17:17	ga_ls8c_ard_3-2-1_100071_2023-01-31_final
2023-02-25 11:52:03	ga_ls8c_ard_3-2-1_115077_2023-02-25_final
2023-02-27 10:04:01	ga_ls8c_ard_3-2-1_097085_2023-02-27_final
2023-03-02 10:33:42	ga_ls8c_ard_3-2-1_102082_2023-03-02_final
2023-03-03 11:12:34	ga_ls8c_ard_3-2-1_109071_2023-03-03_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-30 10:54:59	ga_ls8c_ard_3-2-1_106074_2023-03-30_final
2023-04-01 10:42:12	ga_ls8c_ard_3-2-1_104073_2023-04-01_final
2023-04-02 11:24:15	ga_ls8c_ard_3-2-1_111070_2023-04-02_final
2023-04-07 10:06:36	ga_ls8c_ard_3-2-1_098077_2023-04-07_final
2023-04-08 10:46:38	ga_ls8c_ard_3-2-1_105069_2023-04-08_final
2023-04-15 10:55:32	ga_ls8c_ard_3-2-1_106076_2023-04-15_final
2023-04-19 10:28:23	ga_ls8c_ard_3-2-1_102070_2023-04-19_final
2023-05-02 09:57:50	ga_ls8c_ard_3-2-1_097071_2023-05-02_final
2023-05-03 09:06:35	ga_ls8c_ard_3-2-1_088082_2023-05-02_final
2023-05-04 11:24:44	ga_ls8c_ard_3-2-1_111072_2023-05-04_final
2023-05-07 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-05-07_final
2023-05-08 09:22:15	ga_ls8c_ard_3-2-1_091075_2023-05-07_final
2023-05-20 11:24:58	ga_ls8c_ard_3-2-1_111073_2023-05-20_final
2023-05-20 11:25:46	ga_ls8c_ard_3-2-1_111075_2023-05-20_final
2023-05-22 09:39:19	ga_ls8c_ard_3-2-1_093087_2023-05-22_final
2023-05-24 09:26:58	ga_ls8c_ard_3-2-1_091087_2023-05-23_final
2023-05-26 09:12:13	ga_ls8c_ard_3-2-1_089081_2023-05-25_final
2023-05-26 09:12:37	ga_ls8c_ard_3-2-1_089082_2023-05-25_final
2023-06-01 10:08:50	ga_ls8c_ard_3-2-1_099068_2023-06-01_final
2023-06-02 10:55:17	ga_ls8c_ard_3-2-1_106076_2023-06-02_final
2023-06-03 10:02:29	ga_ls8c_ard_3-2-1_097083_2023-06-03_final
2023-06-06 10:29:26	ga_ls8c_ard_3-2-1_102073_2023-06-06_final
2023-06-08 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-06-08_final
2023-06-09 09:26:17	ga_ls8c_ard_3-2-1_091085_2023-06-08_final
2023-06-10 10:07:09	ga_ls8c_ard_3-2-1_098079_2023-06-10_final
2023-06-11 09:11:09	ga_ls8c_ard_3-2-1_089078_2023-06-10_final
2023-06-11 10:45:38	ga_ls8c_ard_3-2-1_105067_2023-06-11_final
2023-06-14 09:40:28	ga_ls8c_ard_3-2-1_094074_2023-06-14_final
2023-06-16 09:33:19	ga_ls8c_ard_3-2-1_092087_2023-06-16_final
2023-06-26 11:46:57	ga_ls8c_ard_3-2-1_114081_2023-06-26_final
2023-07-22 09:06:27	ga_ls8c_ard_3-2-1_088081_2023-07-21_final
2023-07-23 11:29:25	ga_ls8c_ard_3-2-1_111083_2023-07-23_final
2023-07-24 10:27:49	ga_ls8c_ard_3-2-1_102068_2023-07-24_final
2023-07-28 10:03:33	ga_ls8c_ard_3-2-1_098069_2023-07-28_final
2023-07-28 10:04:45	ga_ls8c_ard_3-2-1_098072_2023-07-28_final
2023-07-29 09:11:32	ga_ls8c_ard_3-2-1_089078_2023-07-28_final
2023-08-01 11:19:21	ga_ls8c_ard_3-2-1_110073_2023-08-01_final
2023-08-04 10:14:58	ga_ls8c_ard_3-2-1_099082_2023-08-04_final
2023-08-28 09:26:04	ga_ls8c_ard_3-2-1_091083_2023-08-27_final
2023-09-02 09:45:00	ga_ls8c_ard_3-2-1_094084_2023-09-02_final
2023-09-05 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-09-05_final
2023-09-06 09:22:39	ga_ls8c_ard_3-2-1_090090_2023-09-05_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-09-09 09:47:36	ga_ls8c_ard_3-2-1_095075_2023-09-09_final
2023-09-15 09:12:10	ga_ls8c_ard_3-2-1_089079_2023-09-14_final
2023-09-15 10:52:39	ga_ls8c_ard_3-2-1_105083_2023-09-15_final
2023-09-18 09:41:05	ga_ls8c_ard_3-2-1_094074_2023-09-18_final
2023-09-18 09:45:53	ga_ls8c_ard_3-2-1_094086_2023-09-18_final
2023-09-20 11:06:01	ga_ls8c_ard_3-2-1_108070_2023-09-20_final
2023-09-24 10:44:30	ga_ls8c_ard_3-2-1_104078_2023-09-24_final
2023-09-25 11:24:59	ga_ls8c_ard_3-2-1_111071_2023-09-25_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-11 09:52:33	ga_ls8c_ard_3-2-1_095087_2023-10-11_final
2023-10-17 09:12:16	ga_ls8c_ard_3-2-1_089079_2023-10-16_final
2023-10-20 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-10-20_final
2023-10-21 10:27:37	ga_ls8c_ard_3-2-1_101082_2023-10-21_final
2023-10-22 09:29:37	ga_ls8c_ard_3-2-1_092076_2023-10-21_final
2023-10-22 09:34:25	ga_ls8c_ard_3-2-1_092088_2023-10-22_final
2023-10-22 09:35:13	ga_ls8c_ard_3-2-1_092090_2023-10-22_final
2023-10-24 09:16:53	ga_ls8c_ard_3-2-1_090075_2023-10-23_final
2023-11-03 11:36:04	ga_ls8c_ard_3-2-1_112083_2023-11-03_final
2023-11-07 11:06:31	ga_ls8c_ard_3-2-1_108071_2023-11-07_final
2023-11-08 10:15:40	ga_ls8c_ard_3-2-1_099083_2023-11-08_final
2023-11-10 09:59:41	ga_ls8c_ard_3-2-1_097074_2023-11-10_final
2023-11-10 11:38:34	ga_ls8c_ard_3-2-1_113074_2023-11-10_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