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
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-20 10:14:53	ga_ls8c_ard_3-2-1_099080_2022-10-20_final
2022-10-22 10:00:57	ga_ls8c_ard_3-2-1_097076_2022-10-22_final
2022-10-22 10:01:45	ga_ls8c_ard_3-2-1_097078_2022-10-22_final
2022-10-22 10:02:33	ga_ls8c_ard_3-2-1_097080_2022-10-22_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-31 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-10-31_final
2022-10-31 11:35:42	ga_ls8c_ard_3-2-1_112081_2022-10-31_final
2022-11-01 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-11-01_final
2022-11-02 11:22:57	ga_ls8c_ard_3-2-1_110080_2022-11-02_final
2022-11-03 10:25:44	ga_ls8c_ard_3-2-1_101076_2022-11-03_final
2022-11-07 10:03:47	ga_ls8c_ard_3-2-1_097083_2022-11-07_final
2022-11-07 11:40:16	ga_ls8c_ard_3-2-1_113077_2022-11-07_final
2022-11-16 09:53:55	ga_ls8c_ard_3-2-1_096074_2022-11-16_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-22 10:57:43	ga_ls8c_ard_3-2-1_106079_2022-11-22_final
2022-11-23 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-11-23_final
2022-11-23 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-11-23_final
2022-11-25 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-11-25_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-29 09:24:38	ga_ls8c_ard_3-2-1_091078_2022-11-28_final
2022-11-29 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-29_final
2022-11-29 11:03:55	ga_ls8c_ard_3-2-1_107079_2022-11-29_final
2022-12-02 09:57:08	ga_ls8c_ard_3-2-1_096082_2022-12-02_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-04 11:22:52	ga_ls8c_ard_3-2-1_110080_2022-12-04_final
2022-12-05 10:26:50	ga_ls8c_ard_3-2-1_101079_2022-12-05_final
2022-12-05 10:27:14	ga_ls8c_ard_3-2-1_101080_2022-12-05_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-08 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-12-07_final
2022-12-08 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-12-07_final
2022-12-08 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-12-07_final
2022-12-09 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-12-09_final
2022-12-11 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-12-11_final
2022-12-11 11:29:48	ga_ls8c_ard_3-2-1_111082_2022-12-11_final
2022-12-12 10:30:35	ga_ls8c_ard_3-2-1_102073_2022-12-12_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-15 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-12-14_final
2022-12-15 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-12-14_final
2022-12-15 09:26:10	ga_ls8c_ard_3-2-1_091082_2022-12-14_final
2022-12-19 10:36:41	ga_ls8c_ard_3-2-1_103073_2022-12-19_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-20 09:43:50	ga_ls8c_ard_3-2-1_094080_2022-12-20_final
2022-12-20 11:20:19	ga_ls8c_ard_3-2-1_110074_2022-12-20_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-23 10:15:29	ga_ls8c_ard_3-2-1_099082_2022-12-23_final
2022-12-24 09:20:16	ga_ls8c_ard_3-2-1_090083_2022-12-23_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-26 10:45:13	ga_ls8c_ard_3-2-1_104079_2022-12-26_final
2022-12-31 09:27:41	ga_ls8c_ard_3-2-1_091086_2022-12-30_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-02 10:50:37	ga_ls8c_ard_3-2-1_105077_2023-01-02_final
2023-01-04 10:35:04	ga_ls8c_ard_3-2-1_103069_2023-01-04_final
2023-01-04 10:39:03	ga_ls8c_ard_3-2-1_103079_2023-01-04_final
2023-01-05 09:43:26	ga_ls8c_ard_3-2-1_094079_2023-01-05_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-10 10:03:32	ga_ls8c_ard_3-2-1_097083_2023-01-10_final
2023-01-12 09:51:09	ga_ls8c_ard_3-2-1_095083_2023-01-12_final
2023-01-14 11:17:15	ga_ls8c_ard_3-2-1_109082_2023-01-14_final
2023-01-16 09:27:34	ga_ls8c_ard_3-2-1_091086_2023-01-15_final
2023-01-16 11:02:04	ga_ls8c_ard_3-2-1_107075_2023-01-16_final
2023-01-19 09:53:40	ga_ls8c_ard_3-2-1_096074_2023-01-19_final
2023-01-19 11:35:21	ga_ls8c_ard_3-2-1_112081_2023-01-19_final
2023-01-23 11:10:17	ga_ls8c_ard_3-2-1_108080_2023-01-23_final
2023-01-25 09:18:39	ga_ls8c_ard_3-2-1_090079_2023-01-24_final
2023-01-25 09:20:39	ga_ls8c_ard_3-2-1_090084_2023-01-24_final
2023-01-26 09:59:32	ga_ls8c_ard_3-2-1_097073_2023-01-26_final
2023-01-26 10:03:07	ga_ls8c_ard_3-2-1_097082_2023-01-26_final
2023-02-01 09:25:15	ga_ls8c_ard_3-2-1_091080_2023-01-31_final
2023-02-05 10:36:37	ga_ls8c_ard_3-2-1_103073_2023-02-05_final
2023-02-07 10:26:15	ga_ls8c_ard_3-2-1_101078_2023-02-07_final
2023-02-09 11:52:21	ga_ls8c_ard_3-2-1_115077_2023-02-09_final
2023-02-11 10:00:17	ga_ls8c_ard_3-2-1_097075_2023-02-11_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-11 10:03:28	ga_ls8c_ard_3-2-1_097083_2023-02-11_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-02-15 09:36:42	ga_ls8c_ard_3-2-1_093078_2023-02-15_final
2023-02-15 11:14:23	ga_ls8c_ard_3-2-1_109075_2023-02-15_final
2023-02-16 10:21:57	ga_ls8c_ard_3-2-1_100083_2023-02-16_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-20 09:56:45	ga_ls8c_ard_3-2-1_096082_2023-02-20_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-02-24 11:10:49	ga_ls8c_ard_3-2-1_108082_2023-02-24_final
2023-02-25 10:15:58	ga_ls8c_ard_3-2-1_099084_2023-02-25_final
2023-02-27 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-02-27_final
2023-02-27 11:39:42	ga_ls8c_ard_3-2-1_113077_2023-02-27_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-02-28 09:06:47	ga_ls8c_ard_3-2-1_088081_2023-02-27_final
2023-02-28 10:45:17	ga_ls8c_ard_3-2-1_104080_2023-02-28_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-02 10:31:43	ga_ls8c_ard_3-2-1_102077_2023-03-02_final
2023-03-03 09:34:53	ga_ls8c_ard_3-2-1_093074_2023-03-03_final
2023-03-03 09:38:29	ga_ls8c_ard_3-2-1_093083_2023-03-03_final
2023-03-04 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-03-04_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-04 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-03-04_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