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
2022-10-19 09:34:01	ga_ls8c_ard_3-2-1_092086_2022-10-19_final
2022-10-20 10:13:17	ga_ls8c_ard_3-2-1_099076_2022-10-20_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-22 09:59:45	ga_ls8c_ard_3-2-1_097073_2022-10-22_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-29 11:46:28	ga_ls8c_ard_3-2-1_114077_2022-10-29_final
2022-11-02 09:42:52	ga_ls8c_ard_3-2-1_094077_2022-11-02_final
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-09 09:48:13	ga_ls8c_ard_3-2-1_095075_2022-11-09_final
2022-11-09 11:29:30	ga_ls8c_ard_3-2-1_111081_2022-11-09_final
2022-11-11 11:15:07	ga_ls8c_ard_3-2-1_109076_2022-11-11_final
2022-11-12 10:19:05	ga_ls8c_ard_3-2-1_100075_2022-11-12_final
2022-11-12 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-11-12_final
2022-11-14 11:46:47	ga_ls8c_ard_3-2-1_114078_2022-11-14_final
2022-11-16 09:53:31	ga_ls8c_ard_3-2-1_096073_2022-11-16_final
2022-11-19 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-11-19_final
2022-11-19 10:26:24	ga_ls8c_ard_3-2-1_101078_2022-11-19_final
2022-11-23 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-11-23_final
2022-11-23 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-11-23_final
2022-11-23 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-11-23_final
2022-11-23 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-11-23_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-11-25 11:27:26	ga_ls8c_ard_3-2-1_111076_2022-11-25_final
2022-11-27 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-11-27_final
2022-11-27 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-11-27_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-29 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-29_final
2022-11-29 11:01:56	ga_ls8c_ard_3-2-1_107074_2022-11-29_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-11-30 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-30_final
2022-12-02 09:58:20	ga_ls8c_ard_3-2-1_096085_2022-12-02_final
2022-12-03 10:35:37	ga_ls8c_ard_3-2-1_103070_2022-12-03_final
2022-12-04 11:21:40	ga_ls8c_ard_3-2-1_110077_2022-12-04_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-09 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-12-09_final
2022-12-10 10:41:22	ga_ls8c_ard_3-2-1_104069_2022-12-10_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-12 10:30:11	ga_ls8c_ard_3-2-1_102072_2022-12-12_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-16 10:07:01	ga_ls8c_ard_3-2-1_098076_2022-12-16_final
2022-12-16 11:45:30	ga_ls8c_ard_3-2-1_114075_2022-12-16_final
2022-12-20 09:45:26	ga_ls8c_ard_3-2-1_094084_2022-12-20_final
2022-12-21 10:28:16	ga_ls8c_ard_3-2-1_101083_2022-12-21_final
2022-12-22 09:35:02	ga_ls8c_ard_3-2-1_092089_2022-12-22_final
2022-12-22 11:10:43	ga_ls8c_ard_3-2-1_108081_2022-12-22_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-25 11:41:38	ga_ls8c_ard_3-2-1_113081_2022-12-25_final
2022-12-27 11:29:17	ga_ls8c_ard_3-2-1_111081_2022-12-27_final
2023-01-01 10:08:33	ga_ls8c_ard_3-2-1_098080_2023-01-01_final
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-03 11:35:29	ga_ls8c_ard_3-2-1_112081_2023-01-03_final
2023-01-05 09:45:49	ga_ls8c_ard_3-2-1_094085_2023-01-05_final
2023-01-05 09:46:13	ga_ls8c_ard_3-2-1_094086_2023-01-05_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-11 10:45:11	ga_ls8c_ard_3-2-1_104079_2023-01-11_final
2023-01-13 10:32:00	ga_ls8c_ard_3-2-1_102077_2023-01-13_final
2023-01-14 11:17:39	ga_ls8c_ard_3-2-1_109083_2023-01-14_final
2023-01-18 09:14:23	ga_ls8c_ard_3-2-1_089084_2023-01-17_final
2023-01-19 09:52:52	ga_ls8c_ard_3-2-1_096072_2023-01-19_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-24 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-01-24_final
2023-01-25 09:19:27	ga_ls8c_ard_3-2-1_090081_2023-01-24_final
2023-01-26 09:59:56	ga_ls8c_ard_3-2-1_097074_2023-01-26_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-02-07 10:23:03	ga_ls8c_ard_3-2-1_101070_2023-02-07_final
2023-02-07 10:28:14	ga_ls8c_ard_3-2-1_101083_2023-02-07_final
2023-02-08 09:29:49	ga_ls8c_ard_3-2-1_092076_2023-02-07_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-13 11:29:34	ga_ls8c_ard_3-2-1_111082_2023-02-13_final
2023-02-14 10:29:57	ga_ls8c_ard_3-2-1_102072_2023-02-14_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-18 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-02-18_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-02-22 11:18:50	ga_ls8c_ard_3-2-1_110071_2023-02-22_final
2023-02-22 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-02-22_final
2023-02-24 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-02-24_final
2023-02-24 11:10:49	ga_ls8c_ard_3-2-1_108082_2023-02-24_final
2023-02-27 11:40:54	ga_ls8c_ard_3-2-1_113080_2023-02-27_final
2023-02-28 10:41:17	ga_ls8c_ard_3-2-1_104070_2023-02-28_final
2023-03-03 09:34:53	ga_ls8c_ard_3-2-1_093074_2023-03-03_final
2023-03-03 11:17:22	ga_ls8c_ard_3-2-1_109083_2023-03-03_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-05 10:59:48	ga_ls8c_ard_3-2-1_107070_2023-03-05_final
2023-03-05 11:00:12	ga_ls8c_ard_3-2-1_107071_2023-03-05_final
2023-03-05 11:01:23	ga_ls8c_ard_3-2-1_107074_2023-03-05_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-11 10:25:04	ga_ls8c_ard_3-2-1_101076_2023-03-11_final
2023-03-12 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-03-12_final
2023-03-12 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-03-12_final
2023-03-14 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-03-13_final
2023-03-15 10:03:55	ga_ls8c_ard_3-2-1_097085_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