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
2022-08-21 11:30:37	ga_ls8c_ard_3-2-1_111084_2022-08-21_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-08-24 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-08-24_final
2022-08-26 10:08:40	ga_ls8c_ard_3-2-1_098080_2022-08-26_final
2022-09-01 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-09-01_final
2022-09-01 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-09-01_final
2022-09-02 10:15:38	ga_ls8c_ard_3-2-1_099082_2022-09-02_final
2022-09-04 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-09-04_final
2022-09-06 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-09-06_final
2022-09-08 09:36:13	ga_ls8c_ard_3-2-1_093076_2022-09-08_final
2022-09-08 11:13:30	ga_ls8c_ard_3-2-1_109072_2022-09-08_final
2022-09-12 09:15:31	ga_ls8c_ard_3-2-1_089086_2022-09-11_final
2022-09-13 11:35:41	ga_ls8c_ard_3-2-1_112081_2022-09-13_final
2022-09-14 10:39:16	ga_ls8c_ard_3-2-1_103079_2022-09-14_final
2022-09-15 09:46:50	ga_ls8c_ard_3-2-1_094087_2022-09-15_final
2022-09-16 10:24:07	ga_ls8c_ard_3-2-1_101072_2022-09-16_final
2022-09-24 09:37:29	ga_ls8c_ard_3-2-1_093079_2022-09-24_final
2022-09-26 11:06:00	ga_ls8c_ard_3-2-1_107084_2022-09-26_final
2022-09-28 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-09-28_final
2022-10-05 10:58:59	ga_ls8c_ard_3-2-1_106082_2022-10-05_final
2022-10-08 11:30:39	ga_ls8c_ard_3-2-1_111084_2022-10-08_final
2022-10-10 09:38:11	ga_ls8c_ard_3-2-1_093081_2022-10-10_final
2022-10-10 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-10-10_final
2022-10-10 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-10-10_final
2022-10-10 11:18:16	ga_ls8c_ard_3-2-1_109084_2022-10-10_final
2022-10-12 11:03:05	ga_ls8c_ard_3-2-1_107077_2022-10-12_final
2022-10-14 10:46:42	ga_ls8c_ard_3-2-1_105067_2022-10-14_final
2022-10-14 10:47:54	ga_ls8c_ard_3-2-1_105070_2022-10-14_final
2022-10-20 10:13:17	ga_ls8c_ard_3-2-1_099076_2022-10-20_final
2022-10-24 11:27:29	ga_ls8c_ard_3-2-1_111076_2022-10-24_final
2022-10-27 10:21:31	ga_ls8c_ard_3-2-1_100081_2022-10-27_final
2022-11-03 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-11-03_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-09 09:51:25	ga_ls8c_ard_3-2-1_095083_2022-11-09_final
2022-11-11 11:13:08	ga_ls8c_ard_3-2-1_109071_2022-11-11_final
2022-11-13 11:01:32	ga_ls8c_ard_3-2-1_107073_2022-11-13_final
2022-11-14 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-14_final
2022-11-18 09:43:55	ga_ls8c_ard_3-2-1_094080_2022-11-18_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-20 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-11-20_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-11-27 09:38:35	ga_ls8c_ard_3-2-1_093082_2022-11-27_final
2022-11-27 09:38:59	ga_ls8c_ard_3-2-1_093083_2022-11-27_final
2022-11-30 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-30_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-04 09:43:59	ga_ls8c_ard_3-2-1_094080_2022-12-04_final
2022-12-05 10:24:26	ga_ls8c_ard_3-2-1_101073_2022-12-05_final
2022-12-05 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-12-05_final
2022-12-09 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-12-09_final
2022-12-11 09:50:55	ga_ls8c_ard_3-2-1_095082_2022-12-11_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-12 10:31:47	ga_ls8c_ard_3-2-1_102076_2022-12-12_final
2022-12-18 11:32:19	ga_ls8c_ard_3-2-1_112073_2022-12-18_final
2022-12-24 10:56:46	ga_ls8c_ard_3-2-1_106077_2022-12-24_final
2022-12-31 11:02:59	ga_ls8c_ard_3-2-1_107077_2022-12-31_final
2023-01-05 09:41:26	ga_ls8c_ard_3-2-1_094074_2023-01-05_final
2023-01-06 10:25:05	ga_ls8c_ard_3-2-1_101075_2023-01-06_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-16 11:01:16	ga_ls8c_ard_3-2-1_107073_2023-01-16_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-20 10:38:57	ga_ls8c_ard_3-2-1_103079_2023-01-20_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-01-26 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-26_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-01-30 09:36:49	ga_ls8c_ard_3-2-1_093078_2023-01-30_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-01-31 10:21:41	ga_ls8c_ard_3-2-1_100082_2023-01-31_final
2023-02-05 10:38:13	ga_ls8c_ard_3-2-1_103077_2023-02-05_final
2023-02-08 11:08:42	ga_ls8c_ard_3-2-1_108076_2023-02-08_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-24 09:31:56	ga_ls8c_ard_3-2-1_092082_2023-02-24_final
2023-03-02 10:31:43	ga_ls8c_ard_3-2-1_102077_2023-03-02_final
2023-03-05 11:01:00	ga_ls8c_ard_3-2-1_107073_2023-03-05_final
2023-03-07 09:14:55	ga_ls8c_ard_3-2-1_089086_2023-03-06_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-10 09:44:59	ga_ls8c_ard_3-2-1_094084_2023-03-10_final
2023-03-12 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-03-12_final
2023-03-12 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-03-12_final
2023-03-12 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-03-12_final
2023-03-12 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-03-12_final
2023-03-14 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-03-14_final
2023-03-15 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-03-15_final
2023-03-20 10:18:00	ga_ls8c_ard_3-2-1_100074_2023-03-20_final
2023-03-24 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-03-24_final
2023-03-25 10:36:29	ga_ls8c_ard_3-2-1_103074_2023-03-25_final
2023-03-27 10:25:42	ga_ls8c_ard_3-2-1_101078_2023-03-27_final
2023-03-30 10:54:11	ga_ls8c_ard_3-2-1_106072_2023-03-30_final
2023-04-04 11:11:51	ga_ls8c_ard_3-2-1_109070_2023-04-04_final
2023-04-06 09:24:09	ga_ls8c_ard_3-2-1_091079_2023-04-05_final
2023-04-07 11:45:53	ga_ls8c_ard_3-2-1_114078_2023-04-07_final
2023-04-11 11:22:16	ga_ls8c_ard_3-2-1_110081_2023-04-11_final
2023-04-14 11:51:10	ga_ls8c_ard_3-2-1_115076_2023-04-14_final
2023-04-15 10:57:08	ga_ls8c_ard_3-2-1_106080_2023-04-15_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-05-07 10:20:41	ga_ls8c_ard_3-2-1_100082_2023-05-07_final
2023-05-08 11:03:32	ga_ls8c_ard_3-2-1_107081_2023-05-08_final
2023-05-17 09:17:09	ga_ls8c_ard_3-2-1_090078_2023-05-16_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