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
2022-07-28 10:39:25	ga_ls8c_ard_3-2-1_103080_2022-07-28_final
2022-07-29 09:46:36	ga_ls8c_ard_3-2-1_094087_2022-07-29_final
2022-07-29 11:21:30	ga_ls8c_ard_3-2-1_110077_2022-07-29_final
2022-07-31 09:31:28	ga_ls8c_ard_3-2-1_092080_2022-07-31_final
2022-07-31 09:33:04	ga_ls8c_ard_3-2-1_092084_2022-07-31_final
2022-08-01 10:16:20	ga_ls8c_ard_3-2-1_099084_2022-08-01_final
2022-08-09 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-08-09_final
2022-08-11 10:51:30	ga_ls8c_ard_3-2-1_105079_2022-08-11_final
2022-08-12 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-08-12_final
2022-08-19 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-08-19_final
2022-08-25 11:05:30	ga_ls8c_ard_3-2-1_107083_2022-08-25_final
2022-08-27 10:52:20	ga_ls8c_ard_3-2-1_105081_2022-08-27_final
2022-08-29 10:34:47	ga_ls8c_ard_3-2-1_103068_2022-08-29_final
2022-08-30 11:22:02	ga_ls8c_ard_3-2-1_110078_2022-08-30_final
2022-09-01 09:29:59	ga_ls8c_ard_3-2-1_092076_2022-08-31_final
2022-09-01 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-09-01_final
2022-09-01 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-09-01_final
2022-09-04 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-09-04_final
2022-09-04 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-09-04_final
2022-09-08 11:15:30	ga_ls8c_ard_3-2-1_109077_2022-09-08_final
2022-09-08 11:15:54	ga_ls8c_ard_3-2-1_109078_2022-09-08_final
2022-09-09 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-09-09_final
2022-09-10 11:05:33	ga_ls8c_ard_3-2-1_107083_2022-09-10_final
2022-09-12 10:50:01	ga_ls8c_ard_3-2-1_105075_2022-09-12_final
2022-09-13 11:34:29	ga_ls8c_ard_3-2-1_112078_2022-09-13_final
2022-09-15 11:20:32	ga_ls8c_ard_3-2-1_110074_2022-09-15_final
2022-09-19 10:56:14	ga_ls8c_ard_3-2-1_106075_2022-09-19_final
2022-09-22 11:26:20	ga_ls8c_ard_3-2-1_111073_2022-09-22_final
2022-09-23 10:29:07	ga_ls8c_ard_3-2-1_102069_2022-09-23_final
2022-09-24 09:34:18	ga_ls8c_ard_3-2-1_093071_2022-09-24_final
2022-09-25 10:20:21	ga_ls8c_ard_3-2-1_100078_2022-09-25_final
2022-09-25 10:20:45	ga_ls8c_ard_3-2-1_100079_2022-09-25_final
2022-09-29 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-09-29_final
2022-09-29 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-09-29_final
2022-10-01 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-10-01_final
2022-10-03 09:34:28	ga_ls8c_ard_3-2-1_092087_2022-10-03_final
2022-10-04 10:14:56	ga_ls8c_ard_3-2-1_099080_2022-10-04_final
2022-10-05 10:58:59	ga_ls8c_ard_3-2-1_106082_2022-10-05_final
2022-10-06 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-06_final
2022-10-08 09:51:46	ga_ls8c_ard_3-2-1_095084_2022-10-08_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-10 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-10-10_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-21 09:18:05	ga_ls8c_ard_3-2-1_090077_2022-10-20_final
2022-10-23 10:41:26	ga_ls8c_ard_3-2-1_104069_2022-10-23_final
2022-10-23 10:46:13	ga_ls8c_ard_3-2-1_104081_2022-10-23_final
2022-10-25 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-10-25_final
2022-11-01 10:35:18	ga_ls8c_ard_3-2-1_103069_2022-11-01_final
2022-11-02 09:41:16	ga_ls8c_ard_3-2-1_094073_2022-11-02_final
2022-11-02 09:41:40	ga_ls8c_ard_3-2-1_094074_2022-11-02_final
2022-11-03 10:23:20	ga_ls8c_ard_3-2-1_101070_2022-11-03_final
2022-11-06 10:56:13	ga_ls8c_ard_3-2-1_106075_2022-11-06_final
2022-11-07 10:04:11	ga_ls8c_ard_3-2-1_097084_2022-11-07_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-08 10:46:38	ga_ls8c_ard_3-2-1_104082_2022-11-08_final
2022-11-10 10:29:05	ga_ls8c_ard_3-2-1_102069_2022-11-10_final
2022-11-11 11:16:43	ga_ls8c_ard_3-2-1_109080_2022-11-11_final
2022-11-13 11:03:08	ga_ls8c_ard_3-2-1_107077_2022-11-13_final
2022-11-13 11:03:32	ga_ls8c_ard_3-2-1_107078_2022-11-13_final
2022-11-18 11:22:25	ga_ls8c_ard_3-2-1_110079_2022-11-18_final
2022-11-20 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-11-20_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-28 10:20:39	ga_ls8c_ard_3-2-1_100079_2022-11-28_final
2022-12-04 09:44:46	ga_ls8c_ard_3-2-1_094082_2022-12-04_final
2022-12-04 11:22:28	ga_ls8c_ard_3-2-1_110079_2022-12-04_final
2022-12-06 09:29:37	ga_ls8c_ard_3-2-1_092075_2022-12-05_final
2022-12-09 10:04:06	ga_ls8c_ard_3-2-1_097084_2022-12-09_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-22 09:29:26	ga_ls8c_ard_3-2-1_092075_2022-12-21_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-28 10:31:16	ga_ls8c_ard_3-2-1_102075_2022-12-28_final
2023-01-01 11:47:50	ga_ls8c_ard_3-2-1_114081_2023-01-01_final
2023-01-03 11:32:41	ga_ls8c_ard_3-2-1_112074_2023-01-03_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-04 10:35:28	ga_ls8c_ard_3-2-1_103070_2023-01-04_final
2023-01-09 10:55:10	ga_ls8c_ard_3-2-1_106073_2023-01-09_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-14 11:13:40	ga_ls8c_ard_3-2-1_109073_2023-01-14_final
2023-01-19 09:55:40	ga_ls8c_ard_3-2-1_096079_2023-01-19_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-21 09:40:57	ga_ls8c_ard_3-2-1_094073_2023-01-21_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-23 09:31:48	ga_ls8c_ard_3-2-1_092081_2023-01-23_final
2023-01-23 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-01-23_final
2023-01-23 11:10:41	ga_ls8c_ard_3-2-1_108081_2023-01-23_final
2023-01-30 11:14:54	ga_ls8c_ard_3-2-1_109076_2023-01-30_final
2023-02-06 11:20:16	ga_ls8c_ard_3-2-1_110074_2023-02-06_final
2023-02-06 11:20:40	ga_ls8c_ard_3-2-1_110075_2023-02-06_final
2023-02-08 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-02-08_final
2023-02-08 11:07:54	ga_ls8c_ard_3-2-1_108074_2023-02-08_final
2023-02-08 11:08:18	ga_ls8c_ard_3-2-1_108075_2023-02-08_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-02-17 09:27:06	ga_ls8c_ard_3-2-1_091085_2023-02-16_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-19 10:51:36	ga_ls8c_ard_3-2-1_105080_2023-02-19_final
2023-02-20 09:53:33	ga_ls8c_ard_3-2-1_096074_2023-02-20_final
2023-02-24 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-02-24_final
2023-03-05 11:02:59	ga_ls8c_ard_3-2-1_107078_2023-03-05_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