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
2022-03-04 09:10:08	ga_ls8c_ard_3-2-1_089074_2022-03-03_final
2022-03-04 09:16:07	ga_ls8c_ard_3-2-1_089089_2022-03-03_final
2022-03-04 10:46:13	ga_ls8c_ard_3-2-1_105067_2022-03-04_final
2022-03-04 10:46:37	ga_ls8c_ard_3-2-1_105068_2022-03-04_final
2022-03-04 10:47:49	ga_ls8c_ard_3-2-1_105071_2022-03-04_final
2022-03-04 10:48:13	ga_ls8c_ard_3-2-1_105072_2022-03-04_final
2022-03-04 10:48:37	ga_ls8c_ard_3-2-1_105073_2022-03-04_final
2022-03-04 10:49:01	ga_ls8c_ard_3-2-1_105074_2022-03-04_final
2022-03-04 10:49:49	ga_ls8c_ard_3-2-1_105076_2022-03-04_final
2022-03-04 10:51:01	ga_ls8c_ard_3-2-1_105079_2022-03-04_final
2022-03-04 10:51:48	ga_ls8c_ard_3-2-1_105081_2022-03-04_final
2022-03-04 10:52:12	ga_ls8c_ard_3-2-1_105082_2022-03-04_final
2022-03-04 10:52:36	ga_ls8c_ard_3-2-1_105083_2022-03-04_final
2022-03-05 09:51:48	ga_ls8c_ard_3-2-1_096070_2022-03-05_final
2022-03-05 09:52:35	ga_ls8c_ard_3-2-1_096072_2022-03-05_final
2022-03-05 09:53:47	ga_ls8c_ard_3-2-1_096075_2022-03-05_final
2022-03-05 09:54:35	ga_ls8c_ard_3-2-1_096077_2022-03-05_final
2022-03-05 09:54:59	ga_ls8c_ard_3-2-1_096078_2022-03-05_final
2022-03-05 09:57:23	ga_ls8c_ard_3-2-1_096084_2022-03-05_final
2022-03-05 09:57:47	ga_ls8c_ard_3-2-1_096085_2022-03-05_final
2022-03-05 11:32:40	ga_ls8c_ard_3-2-1_112075_2022-03-05_final
2022-03-06 10:37:27	ga_ls8c_ard_3-2-1_103076_2022-03-06_final
2022-03-06 10:39:26	ga_ls8c_ard_3-2-1_103081_2022-03-06_final
2022-03-07 11:18:42	ga_ls8c_ard_3-2-1_110071_2022-03-07_final
2022-03-07 11:19:30	ga_ls8c_ard_3-2-1_110073_2022-03-07_final
2022-03-07 11:21:54	ga_ls8c_ard_3-2-1_110079_2022-03-07_final
2022-03-07 11:23:30	ga_ls8c_ard_3-2-1_110083_2022-03-07_final
2022-03-08 10:25:04	ga_ls8c_ard_3-2-1_101076_2022-03-08_final
2022-03-08 10:27:52	ga_ls8c_ard_3-2-1_101083_2022-03-08_final
2022-03-09 09:27:27	ga_ls8c_ard_3-2-1_092071_2022-03-08_final
2022-03-09 09:27:51	ga_ls8c_ard_3-2-1_092072_2022-03-08_final
2022-03-09 09:30:14	ga_ls8c_ard_3-2-1_092078_2022-03-09_final
2022-03-09 09:31:02	ga_ls8c_ard_3-2-1_092080_2022-03-09_final
2022-03-09 09:31:26	ga_ls8c_ard_3-2-1_092081_2022-03-09_final
2022-03-09 09:33:02	ga_ls8c_ard_3-2-1_092085_2022-03-09_final
2022-03-09 09:33:26	ga_ls8c_ard_3-2-1_092086_2022-03-09_final
2022-03-09 09:33:50	ga_ls8c_ard_3-2-1_092087_2022-03-09_final
2022-03-09 09:34:14	ga_ls8c_ard_3-2-1_092088_2022-03-09_final
2022-03-09 11:07:08	ga_ls8c_ard_3-2-1_108073_2022-03-09_final
2022-03-09 11:08:44	ga_ls8c_ard_3-2-1_108077_2022-03-09_final
2022-03-09 11:11:07	ga_ls8c_ard_3-2-1_108083_2022-03-09_final
2022-03-09 11:11:31	ga_ls8c_ard_3-2-1_108084_2022-03-09_final
2022-03-10 10:14:18	ga_ls8c_ard_3-2-1_099080_2022-03-10_final
2022-03-10 11:51:11	ga_ls8c_ard_3-2-1_115075_2022-03-10_final
2022-03-11 09:19:52	ga_ls8c_ard_3-2-1_090083_2022-03-10_final
2022-03-11 09:21:04	ga_ls8c_ard_3-2-1_090086_2022-03-10_final
2022-03-11 09:21:28	ga_ls8c_ard_3-2-1_090087_2022-03-10_final
2022-03-11 09:22:16	ga_ls8c_ard_3-2-1_090089_2022-03-10_final
2022-03-11 10:52:46	ga_ls8c_ard_3-2-1_106068_2022-03-11_final
2022-03-12 09:57:08	ga_ls8c_ard_3-2-1_097068_2022-03-12_final
2022-03-12 09:57:32	ga_ls8c_ard_3-2-1_097069_2022-03-12_final
2022-03-12 09:58:20	ga_ls8c_ard_3-2-1_097071_2022-03-12_final
2022-03-12 11:38:48	ga_ls8c_ard_3-2-1_113075_2022-03-12_final
2022-03-12 11:40:00	ga_ls8c_ard_3-2-1_113078_2022-03-12_final
2022-03-12 11:41:12	ga_ls8c_ard_3-2-1_113081_2022-03-12_final
2022-03-13 09:06:41	ga_ls8c_ard_3-2-1_088081_2022-03-12_final
2022-03-13 09:07:29	ga_ls8c_ard_3-2-1_088083_2022-03-12_final
2022-03-13 10:43:35	ga_ls8c_ard_3-2-1_104076_2022-03-13_final
2022-03-13 10:43:58	ga_ls8c_ard_3-2-1_104077_2022-03-13_final
2022-03-13 10:44:22	ga_ls8c_ard_3-2-1_104078_2022-03-13_final
2022-03-13 10:45:10	ga_ls8c_ard_3-2-1_104080_2022-03-13_final
2022-03-13 10:45:58	ga_ls8c_ard_3-2-1_104082_2022-03-13_final
2022-03-14 09:48:45	ga_ls8c_ard_3-2-1_095078_2022-03-14_final
2022-03-14 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-03-14_final
2022-03-14 09:50:20	ga_ls8c_ard_3-2-1_095082_2022-03-14_final
2022-03-14 09:51:32	ga_ls8c_ard_3-2-1_095085_2022-03-14_final
2022-03-14 11:25:38	ga_ls8c_ard_3-2-1_111073_2022-03-14_final
2022-03-14 11:30:01	ga_ls8c_ard_3-2-1_111084_2022-03-14_final
2022-03-15 10:29:12	ga_ls8c_ard_3-2-1_102071_2022-03-15_final
2022-03-15 10:30:00	ga_ls8c_ard_3-2-1_102073_2022-03-15_final
2022-03-15 10:30:24	ga_ls8c_ard_3-2-1_102074_2022-03-15_final
2022-03-15 10:31:12	ga_ls8c_ard_3-2-1_102076_2022-03-15_final
2022-03-15 10:32:24	ga_ls8c_ard_3-2-1_102079_2022-03-15_final
2022-03-15 10:33:11	ga_ls8c_ard_3-2-1_102081_2022-03-15_final
2022-03-16 09:33:34	ga_ls8c_ard_3-2-1_093071_2022-03-16_final
2022-03-16 09:34:22	ga_ls8c_ard_3-2-1_093073_2022-03-16_final
2022-03-16 09:34:46	ga_ls8c_ard_3-2-1_093074_2022-03-16_final
2022-03-16 09:35:34	ga_ls8c_ard_3-2-1_093076_2022-03-16_final
2022-03-16 09:38:45	ga_ls8c_ard_3-2-1_093084_2022-03-16_final
2022-03-16 09:39:33	ga_ls8c_ard_3-2-1_093086_2022-03-16_final
2022-03-16 11:12:51	ga_ls8c_ard_3-2-1_109072_2022-03-16_final
2022-03-16 11:14:03	ga_ls8c_ard_3-2-1_109075_2022-03-16_final
2022-03-16 11:14:51	ga_ls8c_ard_3-2-1_109077_2022-03-16_final
2022-03-16 11:15:15	ga_ls8c_ard_3-2-1_109078_2022-03-16_final
2022-03-16 11:16:03	ga_ls8c_ard_3-2-1_109080_2022-03-16_final
2022-03-16 11:16:50	ga_ls8c_ard_3-2-1_109082_2022-03-16_final
2022-03-17 10:17:13	ga_ls8c_ard_3-2-1_100072_2022-03-17_final
2022-03-17 10:19:37	ga_ls8c_ard_3-2-1_100078_2022-03-17_final
2022-03-17 10:20:25	ga_ls8c_ard_3-2-1_100080_2022-03-17_final
2022-03-17 10:20:49	ga_ls8c_ard_3-2-1_100081_2022-03-17_final
2022-03-17 10:21:13	ga_ls8c_ard_3-2-1_100082_2022-03-17_final
2022-03-17 11:57:42	ga_ls8c_ard_3-2-1_116076_2022-03-17_final
2022-03-17 11:58:06	ga_ls8c_ard_3-2-1_116077_2022-03-17_final
2022-03-17 11:58:30	ga_ls8c_ard_3-2-1_116078_2022-03-17_final
2022-03-18 09:21:35	ga_ls8c_ard_3-2-1_091072_2022-03-17_final
2022-03-18 09:22:23	ga_ls8c_ard_3-2-1_091074_2022-03-17_final
2022-03-18 09:25:11	ga_ls8c_ard_3-2-1_091081_2022-03-17_final
2022-03-18 09:26:22	ga_ls8c_ard_3-2-1_091084_2022-03-17_final
2022-03-18 09:28:46	ga_ls8c_ard_3-2-1_091090_2022-03-17_final
2022-03-18 11:03:40	ga_ls8c_ard_3-2-1_107080_2022-03-18_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