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
2022-09-26 11:04:24	ga_ls8c_ard_3-2-1_107080_2022-09-26_final
2022-09-28 10:52:03	ga_ls8c_ard_3-2-1_105080_2022-09-28_final
2022-09-29 09:56:25	ga_ls8c_ard_3-2-1_096080_2022-09-29_final
2022-09-29 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-09-29_final
2022-09-30 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-09-30_final
2022-10-05 09:18:30	ga_ls8c_ard_3-2-1_090078_2022-10-04_final
2022-10-07 10:46:12	ga_ls8c_ard_3-2-1_104081_2022-10-07_final
2022-10-10 11:14:40	ga_ls8c_ard_3-2-1_109075_2022-10-10_final
2022-10-10 11:16:16	ga_ls8c_ard_3-2-1_109079_2022-10-10_final
2022-10-15 09:55:05	ga_ls8c_ard_3-2-1_096077_2022-10-15_final
2022-10-15 11:32:46	ga_ls8c_ard_3-2-1_112074_2022-10-15_final
2022-10-15 11:35:10	ga_ls8c_ard_3-2-1_112080_2022-10-15_final
2022-10-17 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-10-17_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-17 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-10-17_final
2022-10-20 10:14:53	ga_ls8c_ard_3-2-1_099080_2022-10-20_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-22 10:04:32	ga_ls8c_ard_3-2-1_097085_2022-10-22_final
2022-10-23 10:46:13	ga_ls8c_ard_3-2-1_104081_2022-10-23_final
2022-10-24 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-10-24_final
2022-10-29 10:09:34	ga_ls8c_ard_3-2-1_098082_2022-10-29_final
2022-10-29 10:10:22	ga_ls8c_ard_3-2-1_098084_2022-10-29_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-01 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-11-01_final
2022-11-01 10:40:29	ga_ls8c_ard_3-2-1_103082_2022-11-01_final
2022-11-02 11:20:33	ga_ls8c_ard_3-2-1_110074_2022-11-02_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-06 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-11-05_final
2022-11-09 09:49:25	ga_ls8c_ard_3-2-1_095078_2022-11-09_final
2022-11-10 10:30:16	ga_ls8c_ard_3-2-1_102072_2022-11-10_final
2022-11-11 11:14:19	ga_ls8c_ard_3-2-1_109074_2022-11-11_final
2022-11-11 11:15:55	ga_ls8c_ard_3-2-1_109078_2022-11-11_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-16 11:35:12	ga_ls8c_ard_3-2-1_112080_2022-11-16_final
2022-11-17 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-11-17_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-20 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-11-20_final
2022-11-21 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-11-21_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-12-01 10:47:34	ga_ls8c_ard_3-2-1_105069_2022-12-01_final
2022-12-04 09:43:11	ga_ls8c_ard_3-2-1_094078_2022-12-04_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-04 11:22:04	ga_ls8c_ard_3-2-1_110078_2022-12-04_final
2022-12-13 11:15:26	ga_ls8c_ard_3-2-1_109077_2022-12-13_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-18 09:56:13	ga_ls8c_ard_3-2-1_096080_2022-12-18_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-20 09:42:38	ga_ls8c_ard_3-2-1_094077_2022-12-20_final
2022-12-20 11:22:19	ga_ls8c_ard_3-2-1_110079_2022-12-20_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-29 11:15:44	ga_ls8c_ard_3-2-1_109078_2022-12-29_final
2022-12-31 11:04:10	ga_ls8c_ard_3-2-1_107080_2022-12-31_final
2023-01-01 10:06:33	ga_ls8c_ard_3-2-1_098075_2023-01-01_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-05 11:21:07	ga_ls8c_ard_3-2-1_110076_2023-01-05_final
2023-01-06 10:27:53	ga_ls8c_ard_3-2-1_101082_2023-01-06_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-08 11:53:12	ga_ls8c_ard_3-2-1_115079_2023-01-08_final
2023-01-10 11:38:50	ga_ls8c_ard_3-2-1_113074_2023-01-10_final
2023-01-11 10:46:23	ga_ls8c_ard_3-2-1_104082_2023-01-11_final
2023-01-12 09:47:58	ga_ls8c_ard_3-2-1_095075_2023-01-12_final
2023-01-12 09:49:57	ga_ls8c_ard_3-2-1_095080_2023-01-12_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-14 09:37:34	ga_ls8c_ard_3-2-1_093080_2023-01-14_final
2023-01-14 11:13:40	ga_ls8c_ard_3-2-1_109073_2023-01-14_final
2023-01-14 11:15:15	ga_ls8c_ard_3-2-1_109077_2023-01-14_final
2023-01-14 11:16:27	ga_ls8c_ard_3-2-1_109080_2023-01-14_final
2023-01-19 09:56:04	ga_ls8c_ard_3-2-1_096080_2023-01-19_final
2023-01-19 11:34:57	ga_ls8c_ard_3-2-1_112080_2023-01-19_final
2023-01-25 09:19:03	ga_ls8c_ard_3-2-1_090080_2023-01-24_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-01-30 09:40:01	ga_ls8c_ard_3-2-1_093086_2023-01-30_final
2023-01-30 11:16:06	ga_ls8c_ard_3-2-1_109079_2023-01-30_final
2023-01-30 11:16:30	ga_ls8c_ard_3-2-1_109080_2023-01-30_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-09 10:15:04	ga_ls8c_ard_3-2-1_099081_2023-02-09_final
2023-02-10 10:56:19	ga_ls8c_ard_3-2-1_106076_2023-02-10_final
2023-02-13 11:27:10	ga_ls8c_ard_3-2-1_111076_2023-02-13_final
2023-02-15 11:14:23	ga_ls8c_ard_3-2-1_109075_2023-02-15_final
2023-02-15 11:15:11	ga_ls8c_ard_3-2-1_109077_2023-02-15_final
2023-02-16 10:21:57	ga_ls8c_ard_3-2-1_100083_2023-02-16_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-17 09:27:06	ga_ls8c_ard_3-2-1_091085_2023-02-16_final
2023-02-17 11:02:48	ga_ls8c_ard_3-2-1_107077_2023-02-17_final
2023-02-17 11:04:00	ga_ls8c_ard_3-2-1_107080_2023-02-17_final
2023-02-19 10:51:36	ga_ls8c_ard_3-2-1_105080_2023-02-19_final
2023-02-20 11:34:50	ga_ls8c_ard_3-2-1_112080_2023-02-20_final
2023-02-21 10:37:12	ga_ls8c_ard_3-2-1_103075_2023-02-21_final
2023-02-22 11:21:14	ga_ls8c_ard_3-2-1_110077_2023-02-22_final
2023-02-24 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-02-23_final
2023-02-24 09:32:20	ga_ls8c_ard_3-2-1_092083_2023-02-24_final
2023-03-03 11:14:58	ga_ls8c_ard_3-2-1_109077_2023-03-03_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-06 10:03:22	ga_ls8c_ard_3-2-1_098068_2023-03-06_final
2023-03-08 11:32:15	ga_ls8c_ard_3-2-1_112074_2023-03-08_final
2023-03-08 11:32:39	ga_ls8c_ard_3-2-1_112075_2023-03-08_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