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
2022-07-27 09:52:57	ga_ls8c_ard_3-2-1_096072_2022-07-27_final
2022-07-27 09:56:57	ga_ls8c_ard_3-2-1_096082_2022-07-27_final
2022-07-29 09:41:25	ga_ls8c_ard_3-2-1_094074_2022-07-29_final
2022-08-09 09:22:58	ga_ls8c_ard_3-2-1_091074_2022-08-08_final
2022-08-09 11:05:03	ga_ls8c_ard_3-2-1_107082_2022-08-09_final
2022-08-12 09:57:05	ga_ls8c_ard_3-2-1_096082_2022-08-12_final
2022-08-14 11:24:01	ga_ls8c_ard_3-2-1_110083_2022-08-14_final
2022-08-21 09:50:56	ga_ls8c_ard_3-2-1_095082_2022-08-21_final
2022-08-21 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-08-21_final
2022-09-03 10:54:55	ga_ls8c_ard_3-2-1_106072_2022-09-03_final
2022-09-03 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-09-03_final
2022-09-04 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-09-04_final
2022-09-04 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-09-04_final
2022-09-05 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-09-05_final
2022-09-06 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-09-06_final
2022-09-10 11:01:34	ga_ls8c_ard_3-2-1_107073_2022-09-10_final
2022-09-11 10:10:44	ga_ls8c_ard_3-2-1_098085_2022-09-11_final
2022-09-12 10:52:25	ga_ls8c_ard_3-2-1_105081_2022-09-12_final
2022-09-13 09:52:24	ga_ls8c_ard_3-2-1_096070_2022-09-13_final
2022-09-13 09:53:36	ga_ls8c_ard_3-2-1_096073_2022-09-13_final
2022-09-14 10:35:16	ga_ls8c_ard_3-2-1_103069_2022-09-14_final
2022-09-14 10:39:16	ga_ls8c_ard_3-2-1_103079_2022-09-14_final
2022-09-17 09:32:06	ga_ls8c_ard_3-2-1_092081_2022-09-17_final
2022-09-19 10:53:50	ga_ls8c_ard_3-2-1_106069_2022-09-19_final
2022-09-22 09:47:51	ga_ls8c_ard_3-2-1_095074_2022-09-22_final
2022-09-24 09:40:41	ga_ls8c_ard_3-2-1_093087_2022-09-24_final
2022-09-25 10:18:45	ga_ls8c_ard_3-2-1_100074_2022-09-25_final
2022-09-27 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-09-27_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-09-29 11:36:30	ga_ls8c_ard_3-2-1_112083_2022-09-29_final
2022-10-01 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-10-01_final
2022-10-01 11:24:08	ga_ls8c_ard_3-2-1_110083_2022-10-01_final
2022-10-03 09:32:05	ga_ls8c_ard_3-2-1_092081_2022-10-03_final
2022-10-05 10:58:35	ga_ls8c_ard_3-2-1_106081_2022-10-05_final
2022-10-05 10:58:59	ga_ls8c_ard_3-2-1_106082_2022-10-05_final
2022-10-07 10:41:01	ga_ls8c_ard_3-2-1_104068_2022-10-07_final
2022-10-07 10:42:13	ga_ls8c_ard_3-2-1_104071_2022-10-07_final
2022-10-08 11:30:39	ga_ls8c_ard_3-2-1_111084_2022-10-08_final
2022-10-09 10:29:02	ga_ls8c_ard_3-2-1_102069_2022-10-09_final
2022-10-12 09:26:11	ga_ls8c_ard_3-2-1_091082_2022-10-11_final
2022-10-13 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-10-13_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_final
2022-10-21 10:58:33	ga_ls8c_ard_3-2-1_106081_2022-10-21_final
2022-10-22 09:59:21	ga_ls8c_ard_3-2-1_097072_2022-10-22_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-07 10:02:11	ga_ls8c_ard_3-2-1_097079_2022-11-07_final
2022-11-07 11:41:28	ga_ls8c_ard_3-2-1_113080_2022-11-07_final
2022-11-11 09:38:14	ga_ls8c_ard_3-2-1_093081_2022-11-11_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-14 10:05:06	ga_ls8c_ard_3-2-1_098071_2022-11-14_final
2022-11-14 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-14_final
2022-11-15 10:49:57	ga_ls8c_ard_3-2-1_105075_2022-11-15_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-23 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-11-23_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-24 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-11-24_final
2022-11-24 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-11-24_final
2022-11-29 09:24:38	ga_ls8c_ard_3-2-1_091078_2022-11-28_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-12-03 10:34:49	ga_ls8c_ard_3-2-1_103068_2022-12-03_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-12 10:29:23	ga_ls8c_ard_3-2-1_102070_2022-12-12_final
2022-12-16 10:07:25	ga_ls8c_ard_3-2-1_098077_2022-12-16_final
2022-12-18 09:58:13	ga_ls8c_ard_3-2-1_096085_2022-12-18_final
2022-12-20 09:44:14	ga_ls8c_ard_3-2-1_094081_2022-12-20_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-22 09:29:50	ga_ls8c_ard_3-2-1_092076_2022-12-21_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-26 10:46:25	ga_ls8c_ard_3-2-1_104082_2022-12-26_final
2022-12-27 09:51:12	ga_ls8c_ard_3-2-1_095083_2022-12-27_final
2022-12-27 09:52:48	ga_ls8c_ard_3-2-1_095087_2022-12-27_final
2022-12-28 10:29:16	ga_ls8c_ard_3-2-1_102070_2022-12-28_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2022-12-31 11:04:34	ga_ls8c_ard_3-2-1_107081_2022-12-31_final
2023-01-02 10:50:37	ga_ls8c_ard_3-2-1_105077_2023-01-02_final
2023-01-06 10:24:41	ga_ls8c_ard_3-2-1_101074_2023-01-06_final
2023-01-14 09:37:58	ga_ls8c_ard_3-2-1_093081_2023-01-14_final
2023-01-14 09:38:46	ga_ls8c_ard_3-2-1_093083_2023-01-14_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-14 11:14:51	ga_ls8c_ard_3-2-1_109076_2023-01-14_final
2023-01-14 11:16:51	ga_ls8c_ard_3-2-1_109081_2023-01-14_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-22 10:25:01	ga_ls8c_ard_3-2-1_101075_2023-01-22_final
2023-01-23 09:28:12	ga_ls8c_ard_3-2-1_092072_2023-01-22_final
2023-01-23 09:29:24	ga_ls8c_ard_3-2-1_092075_2023-01-22_final
2023-01-26 09:59:56	ga_ls8c_ard_3-2-1_097074_2023-01-26_final
2023-02-08 09:31:25	ga_ls8c_ard_3-2-1_092080_2023-02-08_final
2023-02-11 09:59:29	ga_ls8c_ard_3-2-1_097073_2023-02-11_final
2023-02-11 10:03:04	ga_ls8c_ard_3-2-1_097082_2023-02-11_final
2023-02-11 11:39:10	ga_ls8c_ard_3-2-1_113075_2023-02-11_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-03 09:35:17	ga_ls8c_ard_3-2-1_093075_2023-03-03_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