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
2021-12-15 09:57:43	ga_ls8c_ard_3-2-1_096084_2021-12-15_final
2021-12-30 10:49:39	ga_ls8c_ard_3-2-1_105075_2021-12-30_final
2021-12-31 11:32:31	ga_ls8c_ard_3-2-1_112074_2021-12-31_final
2022-01-06 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-01-06_final
2022-02-13 10:20:11	ga_ls8c_ard_3-2-1_100079_2022-02-13_final
2022-02-14 09:23:22	ga_ls8c_ard_3-2-1_091076_2022-02-13_final
2022-02-15 11:47:30	ga_ls8c_ard_3-2-1_114081_2022-02-15_final
2022-03-02 11:05:22	ga_ls8c_ard_3-2-1_107084_2022-03-02_final
2022-03-07 11:23:54	ga_ls8c_ard_3-2-1_110084_2022-03-07_final
2022-03-12 10:03:55	ga_ls8c_ard_3-2-1_097085_2022-03-12_final
2022-03-20 10:49:41	ga_ls8c_ard_3-2-1_105076_2022-03-20_final
2022-04-01 11:15:03	ga_ls8c_ard_3-2-1_109078_2022-04-01_final
2022-04-07 10:39:13	ga_ls8c_ard_3-2-1_103081_2022-04-07_final
2022-04-19 11:01:59	ga_ls8c_ard_3-2-1_107076_2022-04-19_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-24 09:44:01	ga_ls8c_ard_3-2-1_094082_2022-04-24_final
2022-04-26 09:32:02	ga_ls8c_ard_3-2-1_092083_2022-04-26_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_final
2022-05-18 10:28:01	ga_ls8c_ard_3-2-1_102068_2022-05-18_final
2022-05-21 09:21:38	ga_ls8c_ard_3-2-1_091072_2022-05-20_final
2022-05-21 11:04:30	ga_ls8c_ard_3-2-1_107082_2022-05-21_final
2022-05-23 10:50:08	ga_ls8c_ard_3-2-1_105077_2022-05-23_final
2022-06-05 10:22:09	ga_ls8c_ard_3-2-1_100084_2022-06-05_final
2022-06-06 11:02:38	ga_ls8c_ard_3-2-1_107077_2022-06-06_final
2022-06-22 11:02:47	ga_ls8c_ard_3-2-1_107077_2022-06-22_final
2022-06-22 11:05:11	ga_ls8c_ard_3-2-1_107083_2022-06-22_final
2022-07-05 10:28:19	ga_ls8c_ard_3-2-1_102068_2022-07-05_final
2022-07-13 11:20:08	ga_ls8c_ard_3-2-1_110074_2022-07-13_final
2022-07-29 09:40:37	ga_ls8c_ard_3-2-1_094072_2022-07-29_final
2022-08-09 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-08-09_final
2022-08-11 09:13:49	ga_ls8c_ard_3-2-1_089082_2022-08-10_final
2022-09-03 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-09-03_final
2022-09-24 11:14:46	ga_ls8c_ard_3-2-1_109075_2022-09-24_final
2022-09-24 11:15:10	ga_ls8c_ard_3-2-1_109076_2022-09-24_final
2022-10-04 10:11:44	ga_ls8c_ard_3-2-1_099072_2022-10-04_final
2022-10-21 10:58:57	ga_ls8c_ard_3-2-1_106082_2022-10-21_final
2022-10-22 10:04:32	ga_ls8c_ard_3-2-1_097085_2022-10-22_final
2022-10-26 11:14:21	ga_ls8c_ard_3-2-1_109074_2022-10-26_final
2022-10-26 11:15:09	ga_ls8c_ard_3-2-1_109076_2022-10-26_final
2022-11-05 10:11:22	ga_ls8c_ard_3-2-1_099071_2022-11-05_final
2022-11-15 10:51:57	ga_ls8c_ard_3-2-1_105080_2022-11-15_final
2022-11-25 11:26:14	ga_ls8c_ard_3-2-1_111073_2022-11-25_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-12-01 10:50:22	ga_ls8c_ard_3-2-1_105076_2022-12-01_final
2022-12-03 10:39:36	ga_ls8c_ard_3-2-1_103080_2022-12-03_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-10 10:46:09	ga_ls8c_ard_3-2-1_104081_2022-12-10_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-26 10:46:25	ga_ls8c_ard_3-2-1_104082_2022-12-26_final
2022-12-31 09:27:17	ga_ls8c_ard_3-2-1_091085_2022-12-30_final
2022-12-31 11:04:58	ga_ls8c_ard_3-2-1_107082_2022-12-31_final
2023-01-01 10:10:09	ga_ls8c_ard_3-2-1_098084_2023-01-01_final
2023-01-07 11:11:08	ga_ls8c_ard_3-2-1_108082_2023-01-07_final
2023-01-10 10:04:20	ga_ls8c_ard_3-2-1_097085_2023-01-10_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-12 09:47:58	ga_ls8c_ard_3-2-1_095075_2023-01-12_final
2023-01-12 09:52:21	ga_ls8c_ard_3-2-1_095086_2023-01-12_final
2023-01-14 11:14:03	ga_ls8c_ard_3-2-1_109074_2023-01-14_final
2023-01-20 10:38:33	ga_ls8c_ard_3-2-1_103078_2023-01-20_final
2023-01-23 09:31:24	ga_ls8c_ard_3-2-1_092080_2023-01-23_final
2023-01-24 10:14:16	ga_ls8c_ard_3-2-1_099079_2023-01-24_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-09 10:11:04	ga_ls8c_ard_3-2-1_099071_2023-02-09_final
2023-02-09 10:16:15	ga_ls8c_ard_3-2-1_099084_2023-02-09_final
2023-02-26 10:52:51	ga_ls8c_ard_3-2-1_106068_2023-02-26_final
2023-03-03 09:39:17	ga_ls8c_ard_3-2-1_093085_2023-03-03_final
2023-03-04 10:22:08	ga_ls8c_ard_3-2-1_100084_2023-03-04_final
2023-03-15 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-03-15_final
2023-03-19 11:14:02	ga_ls8c_ard_3-2-1_109075_2023-03-19_final
2023-03-21 09:22:22	ga_ls8c_ard_3-2-1_091074_2023-03-20_final
2023-03-21 09:27:57	ga_ls8c_ard_3-2-1_091088_2023-03-20_final
2023-04-01 10:45:23	ga_ls8c_ard_3-2-1_104081_2023-04-01_final
2023-04-01 10:45:47	ga_ls8c_ard_3-2-1_104082_2023-04-01_final
2023-04-06 11:02:14	ga_ls8c_ard_3-2-1_107077_2023-04-06_final
2023-04-10 10:33:50	ga_ls8c_ard_3-2-1_103068_2023-04-10_final
2023-04-14 10:15:28	ga_ls8c_ard_3-2-1_099084_2023-04-14_final
2023-04-15 09:21:50	ga_ls8c_ard_3-2-1_090089_2023-04-14_final
2023-04-15 10:55:32	ga_ls8c_ard_3-2-1_106076_2023-04-15_final
2023-04-18 09:51:07	ga_ls8c_ard_3-2-1_095085_2023-04-18_final
2023-04-18 09:51:55	ga_ls8c_ard_3-2-1_095087_2023-04-18_final
2023-04-18 11:25:13	ga_ls8c_ard_3-2-1_111073_2023-04-18_final
2023-05-03 10:44:16	ga_ls8c_ard_3-2-1_104079_2023-05-03_final
2023-05-08 11:01:56	ga_ls8c_ard_3-2-1_107077_2023-05-08_final
2023-05-13 11:21:11	ga_ls8c_ard_3-2-1_110079_2023-05-13_final
2023-05-21 10:27:21	ga_ls8c_ard_3-2-1_102068_2023-05-21_final
2023-06-08 10:21:29	ga_ls8c_ard_3-2-1_100084_2023-06-08_final
2023-06-09 09:21:53	ga_ls8c_ard_3-2-1_091074_2023-06-08_final
2023-06-09 11:02:22	ga_ls8c_ard_3-2-1_107078_2023-06-09_final
2023-06-10 10:09:33	ga_ls8c_ard_3-2-1_098085_2023-06-10_final
2023-06-23 11:13:36	ga_ls8c_ard_3-2-1_109075_2023-06-23_final
2023-06-25 11:02:28	ga_ls8c_ard_3-2-1_107078_2023-06-25_final
2023-06-28 09:57:20	ga_ls8c_ard_3-2-1_096085_2023-06-28_final
2023-07-01 10:26:41	ga_ls8c_ard_3-2-1_101081_2023-07-01_final
2023-07-06 10:44:29	ga_ls8c_ard_3-2-1_104079_2023-07-06_final
2023-07-23 09:51:20	ga_ls8c_ard_3-2-1_095085_2023-07-23_final
2023-07-23 11:24:13	ga_ls8c_ard_3-2-1_111070_2023-07-23_final
2023-07-27 11:02:45	ga_ls8c_ard_3-2-1_107078_2023-07-27_final
2023-08-11 11:58:02	ga_ls8c_ard_3-2-1_116077_2023-08-11_final
2023-08-12 11:04:49	ga_ls8c_ard_3-2-1_107083_2023-08-12_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