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:

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First 100 results (query limit)

Time (local)	Label
2022-10-24 09:48:36	ga_ls8c_ard_3-2-1_095076_2022-10-24_final
2022-10-24 09:50:36	ga_ls8c_ard_3-2-1_095081_2022-10-24_final
2022-10-31 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-10-31_final
2022-11-02 09:42:04	ga_ls8c_ard_3-2-1_094075_2022-11-02_final
2022-11-02 11:22:57	ga_ls8c_ard_3-2-1_110080_2022-11-02_final
2022-11-03 10:25:20	ga_ls8c_ard_3-2-1_101075_2022-11-03_final
2022-11-04 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-11-04_final
2022-11-07 11:40:16	ga_ls8c_ard_3-2-1_113077_2022-11-07_final
2022-11-07 11:41:28	ga_ls8c_ard_3-2-1_113080_2022-11-07_final
2022-11-08 10:42:15	ga_ls8c_ard_3-2-1_104071_2022-11-08_final
2022-11-10 10:31:28	ga_ls8c_ard_3-2-1_102075_2022-11-10_final
2022-11-14 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-14_final
2022-11-20 09:30:23	ga_ls8c_ard_3-2-1_092077_2022-11-20_final
2022-11-20 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-11-20_final
2022-11-20 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-11-20_final
2022-11-23 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-11-23_final
2022-11-23 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-11-23_final
2022-11-24 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-11-24_final
2022-11-24 10:44:58	ga_ls8c_ard_3-2-1_104078_2022-11-24_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-11-27 11:17:05	ga_ls8c_ard_3-2-1_109081_2022-11-27_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-12-04 09:41:59	ga_ls8c_ard_3-2-1_094075_2022-12-04_final
2022-12-04 09:42:23	ga_ls8c_ard_3-2-1_094076_2022-12-04_final
2022-12-04 09:42:47	ga_ls8c_ard_3-2-1_094077_2022-12-04_final
2022-12-04 09:44:22	ga_ls8c_ard_3-2-1_094081_2022-12-04_final
2022-12-05 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-12-05_final
2022-12-07 10:12:52	ga_ls8c_ard_3-2-1_099075_2022-12-07_final
2022-12-12 10:32:35	ga_ls8c_ard_3-2-1_102078_2022-12-12_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-15 09:26:10	ga_ls8c_ard_3-2-1_091082_2022-12-14_final
2022-12-17 10:47:28	ga_ls8c_ard_3-2-1_105069_2022-12-17_final
2022-12-18 09:53:26	ga_ls8c_ard_3-2-1_096073_2022-12-18_final
2022-12-18 09:58:13	ga_ls8c_ard_3-2-1_096085_2022-12-18_final
2022-12-20 09:43:50	ga_ls8c_ard_3-2-1_094080_2022-12-20_final
2022-12-20 11:22:43	ga_ls8c_ard_3-2-1_110080_2022-12-20_final
2022-12-20 11:23:55	ga_ls8c_ard_3-2-1_110083_2022-12-20_final
2022-12-22 09:30:14	ga_ls8c_ard_3-2-1_092077_2022-12-22_final
2022-12-23 10:15:29	ga_ls8c_ard_3-2-1_099082_2022-12-23_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-26 10:43:13	ga_ls8c_ard_3-2-1_104074_2022-12-26_final
2022-12-27 11:27:17	ga_ls8c_ard_3-2-1_111076_2022-12-27_final
2022-12-28 10:33:16	ga_ls8c_ard_3-2-1_102080_2022-12-28_final
2022-12-29 09:36:27	ga_ls8c_ard_3-2-1_093077_2022-12-29_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2023-01-03 11:35:05	ga_ls8c_ard_3-2-1_112080_2023-01-03_final
2023-01-06 10:24:41	ga_ls8c_ard_3-2-1_101074_2023-01-06_final
2023-01-07 09:32:15	ga_ls8c_ard_3-2-1_092082_2023-01-07_final
2023-01-07 11:10:20	ga_ls8c_ard_3-2-1_108080_2023-01-07_final
2023-01-09 09:20:17	ga_ls8c_ard_3-2-1_090083_2023-01-08_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-12 11:27:15	ga_ls8c_ard_3-2-1_111076_2023-01-12_final
2023-01-15 10:21:13	ga_ls8c_ard_3-2-1_100081_2023-01-15_final
2023-01-18 10:51:16	ga_ls8c_ard_3-2-1_105079_2023-01-18_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_2023-01-19_final
2023-01-21 09:43:20	ga_ls8c_ard_3-2-1_094079_2023-01-21_final
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-01-22 10:26:37	ga_ls8c_ard_3-2-1_101079_2023-01-22_final
2023-01-23 09:31:48	ga_ls8c_ard_3-2-1_092081_2023-01-23_final
2023-01-24 11:51:10	ga_ls8c_ard_3-2-1_115074_2023-01-24_final
2023-01-26 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-26_final
2023-01-31 10:21:17	ga_ls8c_ard_3-2-1_100081_2023-01-31_final
2023-02-01 09:25:15	ga_ls8c_ard_3-2-1_091080_2023-01-31_final
2023-02-05 10:35:49	ga_ls8c_ard_3-2-1_103071_2023-02-05_final
2023-02-05 10:37:49	ga_ls8c_ard_3-2-1_103076_2023-02-05_final
2023-02-06 11:22:40	ga_ls8c_ard_3-2-1_110080_2023-02-06_final
2023-02-07 10:26:38	ga_ls8c_ard_3-2-1_101079_2023-02-07_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-08 09:31:01	ga_ls8c_ard_3-2-1_092079_2023-02-08_final
2023-02-08 09:33:00	ga_ls8c_ard_3-2-1_092084_2023-02-08_final
2023-02-08 11:10:42	ga_ls8c_ard_3-2-1_108081_2023-02-08_final
2023-02-10 10:57:07	ga_ls8c_ard_3-2-1_106078_2023-02-10_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-12 10:42:20	ga_ls8c_ard_3-2-1_104072_2023-02-12_final
2023-02-13 11:27:58	ga_ls8c_ard_3-2-1_111078_2023-02-13_final
2023-02-14 10:31:32	ga_ls8c_ard_3-2-1_102076_2023-02-14_final
2023-02-16 10:21:33	ga_ls8c_ard_3-2-1_100082_2023-02-16_final
2023-02-16 11:58:50	ga_ls8c_ard_3-2-1_116078_2023-02-16_final
2023-02-21 10:37:36	ga_ls8c_ard_3-2-1_103076_2023-02-21_final
2023-02-22 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-02-22_final
2023-02-22 09:45:32	ga_ls8c_ard_3-2-1_094085_2023-02-22_final
2023-02-23 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-02-23_final
2023-02-24 09:33:31	ga_ls8c_ard_3-2-1_092086_2023-02-24_final
2023-02-26 10:57:14	ga_ls8c_ard_3-2-1_106079_2023-02-26_final
2023-02-27 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-02-27_final
2023-02-27 11:38:54	ga_ls8c_ard_3-2-1_113075_2023-02-27_final
2023-02-27 11:40:30	ga_ls8c_ard_3-2-1_113079_2023-02-27_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-03-01 09:50:51	ga_ls8c_ard_3-2-1_095083_2023-03-01_final
2023-03-03 11:16:34	ga_ls8c_ard_3-2-1_109081_2023-03-03_final
2023-03-06 11:46:38	ga_ls8c_ard_3-2-1_114079_2023-03-06_final
2023-03-07 09:14:07	ga_ls8c_ard_3-2-1_089084_2023-03-06_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_final
2023-03-10 11:20:41	ga_ls8c_ard_3-2-1_110076_2023-03-10_final
2023-03-12 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-03-12_final
2023-03-13 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-03-13_final
2023-03-14 10:57:57	ga_ls8c_ard_3-2-1_106081_2023-03-14_final
2023-03-15 09:59:08	ga_ls8c_ard_3-2-1_097073_2023-03-15_final
2023-03-15 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-03-15_final
2023-03-16 10:41:59	ga_ls8c_ard_3-2-1_104072_2023-03-16_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