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
2022-08-01 10:14:44	ga_ls8c_ard_3-2-1_099080_2022-08-01_final
2022-08-04 10:40:53	ga_ls8c_ard_3-2-1_104068_2022-08-04_final
2022-08-16 09:28:23	ga_ls8c_ard_3-2-1_092072_2022-08-15_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-25 09:23:01	ga_ls8c_ard_3-2-1_091074_2022-08-24_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-09-01 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-09-01_final
2022-09-02 10:14:50	ga_ls8c_ard_3-2-1_099080_2022-09-02_final
2022-09-04 09:58:54	ga_ls8c_ard_3-2-1_097071_2022-09-04_final
2022-09-04 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-09-04_final
2022-09-07 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-09-07_final
2022-09-10 09:22:17	ga_ls8c_ard_3-2-1_091072_2022-09-09_final
2022-09-11 10:03:57	ga_ls8c_ard_3-2-1_098068_2022-09-11_final
2022-09-14 10:40:04	ga_ls8c_ard_3-2-1_103081_2022-09-14_final
2022-09-18 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-09-18_final
2022-09-19 10:53:50	ga_ls8c_ard_3-2-1_106069_2022-09-19_final
2022-09-21 09:06:59	ga_ls8c_ard_3-2-1_088080_2022-09-20_final
2022-09-21 10:41:29	ga_ls8c_ard_3-2-1_104069_2022-09-21_final
2022-09-22 09:47:27	ga_ls8c_ard_3-2-1_095073_2022-09-22_final
2022-09-23 10:29:31	ga_ls8c_ard_3-2-1_102070_2022-09-23_final
2022-09-26 09:25:31	ga_ls8c_ard_3-2-1_091080_2022-09-25_final
2022-09-26 09:27:31	ga_ls8c_ard_3-2-1_091085_2022-09-25_final
2022-09-27 10:09:59	ga_ls8c_ard_3-2-1_098083_2022-09-27_final
2022-10-01 09:41:39	ga_ls8c_ard_3-2-1_094074_2022-10-01_final
2022-10-03 09:33:40	ga_ls8c_ard_3-2-1_092085_2022-10-03_final
2022-10-03 11:10:10	ga_ls8c_ard_3-2-1_108079_2022-10-03_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-08 11:26:40	ga_ls8c_ard_3-2-1_111074_2022-10-08_final
2022-10-10 09:37:47	ga_ls8c_ard_3-2-1_093080_2022-10-10_final
2022-10-11 10:21:26	ga_ls8c_ard_3-2-1_100081_2022-10-11_final
2022-10-12 09:23:48	ga_ls8c_ard_3-2-1_091076_2022-10-11_final
2022-10-12 09:27:47	ga_ls8c_ard_3-2-1_091086_2022-10-11_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-14 09:13:00	ga_ls8c_ard_3-2-1_089080_2022-10-13_final
2022-10-17 11:19:39	ga_ls8c_ard_3-2-1_110072_2022-10-17_final
2022-10-17 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-10-17_final
2022-10-21 10:54:58	ga_ls8c_ard_3-2-1_106072_2022-10-21_final
2022-10-25 10:30:17	ga_ls8c_ard_3-2-1_102072_2022-10-25_final
2022-10-25 10:30:41	ga_ls8c_ard_3-2-1_102073_2022-10-25_final
2022-10-26 09:34:16	ga_ls8c_ard_3-2-1_093071_2022-10-26_final
2022-10-26 11:13:57	ga_ls8c_ard_3-2-1_109073_2022-10-26_final
2022-10-27 10:22:43	ga_ls8c_ard_3-2-1_100084_2022-10-27_final
2022-10-29 10:03:59	ga_ls8c_ard_3-2-1_098068_2022-10-29_final
2022-10-29 11:45:40	ga_ls8c_ard_3-2-1_114075_2022-10-29_final
2022-10-29 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-10-29_final
2022-10-30 09:13:57	ga_ls8c_ard_3-2-1_089082_2022-10-29_final
2022-10-30 10:51:14	ga_ls8c_ard_3-2-1_105078_2022-10-30_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-06 10:56:37	ga_ls8c_ard_3-2-1_106076_2022-11-06_final
2022-11-09 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-11-09_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-13 09:25:27	ga_ls8c_ard_3-2-1_091080_2022-11-12_final
2022-11-14 10:05:06	ga_ls8c_ard_3-2-1_098071_2022-11-14_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-11-18 11:19:37	ga_ls8c_ard_3-2-1_110072_2022-11-18_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-25 11:30:14	ga_ls8c_ard_3-2-1_111083_2022-11-25_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-11-27 11:14:17	ga_ls8c_ard_3-2-1_109074_2022-11-27_final
2022-11-29 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-28_final
2022-12-02 09:58:20	ga_ls8c_ard_3-2-1_096085_2022-12-02_final
2022-12-06 09:34:00	ga_ls8c_ard_3-2-1_092086_2022-12-06_final
2022-12-08 09:22:50	ga_ls8c_ard_3-2-1_090089_2022-12-07_final
2022-12-09 09:57:43	ga_ls8c_ard_3-2-1_097068_2022-12-09_final
2022-12-10 10:44:09	ga_ls8c_ard_3-2-1_104076_2022-12-10_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-25 09:59:33	ga_ls8c_ard_3-2-1_097073_2022-12-25_final
2022-12-29 09:36:03	ga_ls8c_ard_3-2-1_093076_2022-12-29_final
2023-01-02 10:48:37	ga_ls8c_ard_3-2-1_105072_2023-01-02_final
2023-01-06 10:27:53	ga_ls8c_ard_3-2-1_101082_2023-01-06_final
2023-01-07 09:29:52	ga_ls8c_ard_3-2-1_092076_2023-01-06_final
2023-01-07 09:31:28	ga_ls8c_ard_3-2-1_092080_2023-01-07_final
2023-01-08 10:15:55	ga_ls8c_ard_3-2-1_099083_2023-01-08_final
2023-01-10 10:03:56	ga_ls8c_ard_3-2-1_097084_2023-01-10_final
2023-01-13 10:30:01	ga_ls8c_ard_3-2-1_102072_2023-01-13_final
2023-01-13 10:31:37	ga_ls8c_ard_3-2-1_102076_2023-01-13_final
2023-01-17 10:03:14	ga_ls8c_ard_3-2-1_098067_2023-01-17_final
2023-01-17 11:46:06	ga_ls8c_ard_3-2-1_114077_2023-01-17_final
2023-01-18 10:50:28	ga_ls8c_ard_3-2-1_105077_2023-01-18_final
2023-01-20 10:34:33	ga_ls8c_ard_3-2-1_103068_2023-01-20_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-01-23 11:06:42	ga_ls8c_ard_3-2-1_108071_2023-01-23_final
2023-01-25 10:55:33	ga_ls8c_ard_3-2-1_106074_2023-01-25_final
2023-01-30 11:12:55	ga_ls8c_ard_3-2-1_109071_2023-01-30_final
2023-02-06 11:19:05	ga_ls8c_ard_3-2-1_110071_2023-02-06_final
2023-02-08 11:07:30	ga_ls8c_ard_3-2-1_108073_2023-02-08_final
2023-02-10 09:18:14	ga_ls8c_ard_3-2-1_090078_2023-02-09_final
2023-02-10 09:19:50	ga_ls8c_ard_3-2-1_090082_2023-02-09_final
2023-02-24 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-02-24_final
2023-02-26 10:55:14	ga_ls8c_ard_3-2-1_106074_2023-02-26_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-01 09:47:15	ga_ls8c_ard_3-2-1_095074_2023-03-01_final
2023-03-02 10:28:55	ga_ls8c_ard_3-2-1_102070_2023-03-02_final
2023-03-03 11:12:34	ga_ls8c_ard_3-2-1_109071_2023-03-03_final
2023-03-06 10:07:45	ga_ls8c_ard_3-2-1_098079_2023-03-06_final
2023-03-09 10:36:13	ga_ls8c_ard_3-2-1_103073_2023-03-09_final
2023-03-12 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-03-12_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