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
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-08 09:07:45	ga_ls8c_ard_3-2-1_088082_2022-11-07_final
2022-11-08 10:41:27	ga_ls8c_ard_3-2-1_104069_2022-11-08_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-11-22 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-11-21_final
2022-11-22 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-11-21_final
2022-11-23 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-11-23_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-24 10:44:34	ga_ls8c_ard_3-2-1_104077_2022-11-24_final
2022-11-25 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-11-25_final
2022-11-25 11:27:02	ga_ls8c_ard_3-2-1_111075_2022-11-25_final
2022-11-26 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-11-26_final
2022-11-27 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-11-27_final
2022-11-28 11:59:09	ga_ls8c_ard_3-2-1_116078_2022-11-28_final
2022-11-29 11:05:55	ga_ls8c_ard_3-2-1_107084_2022-11-29_final
2022-12-03 10:36:48	ga_ls8c_ard_3-2-1_103073_2022-12-03_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-15 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-12-15_final
2022-12-19 10:35:29	ga_ls8c_ard_3-2-1_103070_2022-12-19_final
2022-12-19 10:36:41	ga_ls8c_ard_3-2-1_103073_2022-12-19_final
2022-12-20 09:44:14	ga_ls8c_ard_3-2-1_094081_2022-12-20_final
2022-12-20 09:46:38	ga_ls8c_ard_3-2-1_094087_2022-12-20_final
2022-12-21 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-12-21_final
2022-12-23 10:15:29	ga_ls8c_ard_3-2-1_099082_2022-12-23_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-25 10:03:57	ga_ls8c_ard_3-2-1_097084_2022-12-25_final
2022-12-25 11:39:14	ga_ls8c_ard_3-2-1_113075_2022-12-25_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2022-12-27 11:30:05	ga_ls8c_ard_3-2-1_111083_2022-12-27_final
2022-12-29 11:17:20	ga_ls8c_ard_3-2-1_109082_2022-12-29_final
2022-12-29 11:17:44	ga_ls8c_ard_3-2-1_109083_2022-12-29_final
2022-12-30 10:19:19	ga_ls8c_ard_3-2-1_100076_2022-12-30_final
2022-12-31 09:25:41	ga_ls8c_ard_3-2-1_091081_2022-12-30_final
2022-12-31 09:27:41	ga_ls8c_ard_3-2-1_091086_2022-12-30_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-06 10:23:06	ga_ls8c_ard_3-2-1_101070_2023-01-06_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-12 11:30:02	ga_ls8c_ard_3-2-1_111083_2023-01-12_final
2023-01-13 10:30:49	ga_ls8c_ard_3-2-1_102074_2023-01-13_final
2023-01-14 11:17:15	ga_ls8c_ard_3-2-1_109082_2023-01-14_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-16 09:27:34	ga_ls8c_ard_3-2-1_091086_2023-01-15_final
2023-01-16 11:04:03	ga_ls8c_ard_3-2-1_107080_2023-01-16_final
2023-01-18 09:14:23	ga_ls8c_ard_3-2-1_089084_2023-01-17_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-22 10:25:49	ga_ls8c_ard_3-2-1_101077_2023-01-22_final
2023-01-23 11:06:18	ga_ls8c_ard_3-2-1_108070_2023-01-23_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-01-26 10:03:07	ga_ls8c_ard_3-2-1_097082_2023-01-26_final
2023-01-29 10:31:38	ga_ls8c_ard_3-2-1_102076_2023-01-29_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-01-31 10:21:41	ga_ls8c_ard_3-2-1_100082_2023-01-31_final
2023-02-06 11:19:05	ga_ls8c_ard_3-2-1_110071_2023-02-06_final
2023-02-08 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-02-08_final
2023-02-08 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-02-08_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-10 09:19:50	ga_ls8c_ard_3-2-1_090082_2023-02-09_final
2023-02-10 09:20:37	ga_ls8c_ard_3-2-1_090084_2023-02-09_final
2023-02-11 09:59:29	ga_ls8c_ard_3-2-1_097073_2023-02-11_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-15 11:12:48	ga_ls8c_ard_3-2-1_109071_2023-02-15_final
2023-02-16 10:19:57	ga_ls8c_ard_3-2-1_100078_2023-02-16_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-17 09:25:07	ga_ls8c_ard_3-2-1_091080_2023-02-16_final
2023-02-17 09:25:31	ga_ls8c_ard_3-2-1_091081_2023-02-16_final
2023-02-17 11:02:48	ga_ls8c_ard_3-2-1_107077_2023-02-17_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-21 10:35:12	ga_ls8c_ard_3-2-1_103070_2023-02-21_final
2023-02-21 10:35:36	ga_ls8c_ard_3-2-1_103071_2023-02-21_final
2023-02-27 10:01:37	ga_ls8c_ard_3-2-1_097079_2023-02-27_final
2023-02-27 11:41:18	ga_ls8c_ard_3-2-1_113081_2023-02-27_final
2023-03-01 09:50:51	ga_ls8c_ard_3-2-1_095083_2023-03-01_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-03 09:34:53	ga_ls8c_ard_3-2-1_093074_2023-03-03_final
2023-03-03 09:40:28	ga_ls8c_ard_3-2-1_093088_2023-03-03_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-05 10:59:48	ga_ls8c_ard_3-2-1_107070_2023-03-05_final
2023-03-05 11:04:11	ga_ls8c_ard_3-2-1_107081_2023-03-05_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-07 09:11:43	ga_ls8c_ard_3-2-1_089078_2023-03-06_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_final
2023-03-07 10:48:36	ga_ls8c_ard_3-2-1_105073_2023-03-07_final
2023-03-10 09:44:59	ga_ls8c_ard_3-2-1_094084_2023-03-10_final
2023-03-10 09:45:23	ga_ls8c_ard_3-2-1_094085_2023-03-10_final
2023-03-12 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-03-12_final
2023-03-12 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-03-12_final
2023-03-13 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-03-13_final
2023-03-15 10:03:31	ga_ls8c_ard_3-2-1_097084_2023-03-15_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_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