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
2022-01-14 10:09:34	ga_ls8c_ard_3-2-1_098083_2022-01-14_final
2022-02-26 09:52:25	ga_ls8c_ard_3-2-1_095087_2022-02-26_final
2022-03-25 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-03-25_final
2022-04-08 11:19:42	ga_ls8c_ard_3-2-1_110074_2022-04-08_final
2022-04-18 10:19:08	ga_ls8c_ard_3-2-1_100077_2022-04-18_final
2022-04-21 10:46:02	ga_ls8c_ard_3-2-1_105067_2022-04-21_final
2022-04-26 09:34:02	ga_ls8c_ard_3-2-1_092088_2022-04-26_final
2022-04-27 11:52:58	ga_ls8c_ard_3-2-1_115080_2022-04-27_final
2022-04-29 10:01:43	ga_ls8c_ard_3-2-1_097080_2022-04-29_final
2022-04-30 10:42:12	ga_ls8c_ard_3-2-1_104073_2022-04-30_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-05 11:01:36	ga_ls8c_ard_3-2-1_107075_2022-05-05_final
2022-05-07 09:13:34	ga_ls8c_ard_3-2-1_089083_2022-05-06_final
2022-05-16 10:42:45	ga_ls8c_ard_3-2-1_104074_2022-05-16_final
2022-05-28 09:33:46	ga_ls8c_ard_3-2-1_092087_2022-05-28_final
2022-06-02 11:26:06	ga_ls8c_ard_3-2-1_111074_2022-06-02_final
2022-06-13 11:08:30	ga_ls8c_ard_3-2-1_108076_2022-06-13_final
2022-07-02 09:58:13	ga_ls8c_ard_3-2-1_097070_2022-07-02_final
2022-07-10 10:46:27	ga_ls8c_ard_3-2-1_105067_2022-07-10_final
2022-07-11 11:32:30	ga_ls8c_ard_3-2-1_112074_2022-07-11_final
2022-07-24 11:02:06	ga_ls8c_ard_3-2-1_107075_2022-07-24_final
2022-07-29 09:46:36	ga_ls8c_ard_3-2-1_094087_2022-07-29_final
2022-07-31 11:05:58	ga_ls8c_ard_3-2-1_108069_2022-07-31_final
2022-08-05 11:29:20	ga_ls8c_ard_3-2-1_111081_2022-08-05_final
2022-08-09 09:25:22	ga_ls8c_ard_3-2-1_091080_2022-08-08_final
2022-08-09 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-08-09_final
2022-08-09 11:05:27	ga_ls8c_ard_3-2-1_107083_2022-08-09_final
2022-08-11 10:46:43	ga_ls8c_ard_3-2-1_105067_2022-08-11_final
2022-08-14 11:21:37	ga_ls8c_ard_3-2-1_110077_2022-08-14_final
2022-08-19 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-08-19_final
2022-08-26 10:05:05	ga_ls8c_ard_3-2-1_098071_2022-08-26_final
2022-08-29 10:36:23	ga_ls8c_ard_3-2-1_103072_2022-08-29_final
2022-09-06 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-09-06_final
2022-09-19 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-09-18_final
2022-09-22 09:46:39	ga_ls8c_ard_3-2-1_095071_2022-09-22_final
2022-09-27 10:10:47	ga_ls8c_ard_3-2-1_098085_2022-09-27_final
2022-10-05 09:19:18	ga_ls8c_ard_3-2-1_090080_2022-10-04_final
2022-10-11 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-10-11_final
2022-10-31 09:58:01	ga_ls8c_ard_3-2-1_096084_2022-10-31_final
2022-11-03 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-11-03_final
2022-11-09 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-11-09_final
2022-11-09 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-11-09_final
2022-11-13 09:27:51	ga_ls8c_ard_3-2-1_091086_2022-11-12_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-06 09:35:36	ga_ls8c_ard_3-2-1_092090_2022-12-06_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-15 11:04:15	ga_ls8c_ard_3-2-1_107080_2022-12-15_final
2022-12-18 09:58:37	ga_ls8c_ard_3-2-1_096086_2022-12-18_final
2022-12-21 10:26:17	ga_ls8c_ard_3-2-1_101078_2022-12-21_final
2022-12-25 10:02:45	ga_ls8c_ard_3-2-1_097081_2022-12-25_final
2022-12-29 11:18:08	ga_ls8c_ard_3-2-1_109084_2022-12-29_final
2022-12-31 09:22:06	ga_ls8c_ard_3-2-1_091072_2022-12-30_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-09 10:53:11	ga_ls8c_ard_3-2-1_106068_2023-01-09_final
2023-01-14 11:13:16	ga_ls8c_ard_3-2-1_109072_2023-01-14_final
2023-01-26 09:57:32	ga_ls8c_ard_3-2-1_097068_2023-01-26_final
2023-02-23 10:24:47	ga_ls8c_ard_3-2-1_101075_2023-02-23_final
2023-02-27 10:00:25	ga_ls8c_ard_3-2-1_097076_2023-02-27_final
2023-03-05 09:22:31	ga_ls8c_ard_3-2-1_091074_2023-03-04_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-27 10:26:30	ga_ls8c_ard_3-2-1_101080_2023-03-27_final
2023-04-16 10:03:06	ga_ls8c_ard_3-2-1_097084_2023-04-16_final
2023-04-24 10:46:32	ga_ls8c_ard_3-2-1_105069_2023-04-24_final
2023-04-27 11:20:36	ga_ls8c_ard_3-2-1_110077_2023-04-27_final
2023-04-29 09:29:45	ga_ls8c_ard_3-2-1_092078_2023-04-28_final
2023-05-02 10:01:01	ga_ls8c_ard_3-2-1_097079_2023-05-02_final
2023-05-03 09:06:11	ga_ls8c_ard_3-2-1_088081_2023-05-02_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-16 10:10:23	ga_ls8c_ard_3-2-1_099072_2023-05-16_final
2023-05-16 11:51:16	ga_ls8c_ard_3-2-1_115077_2023-05-16_final
2023-05-26 09:12:37	ga_ls8c_ard_3-2-1_089082_2023-05-25_final
2023-05-29 11:22:25	ga_ls8c_ard_3-2-1_110082_2023-05-29_final
2023-05-29 11:22:49	ga_ls8c_ard_3-2-1_110083_2023-05-29_final
2023-06-05 09:45:46	ga_ls8c_ard_3-2-1_095072_2023-06-05_final
2023-06-05 11:25:27	ga_ls8c_ard_3-2-1_111074_2023-06-05_final
2023-06-15 10:24:08	ga_ls8c_ard_3-2-1_101075_2023-06-15_final
2023-06-15 10:26:56	ga_ls8c_ard_3-2-1_101082_2023-06-15_final
2023-06-25 09:22:23	ga_ls8c_ard_3-2-1_091075_2023-06-24_final
2023-06-26 10:06:52	ga_ls8c_ard_3-2-1_098078_2023-06-26_final
2023-07-13 09:11:01	ga_ls8c_ard_3-2-1_089077_2023-07-12_final
2023-07-29 10:46:02	ga_ls8c_ard_3-2-1_105067_2023-07-29_final
2023-08-03 11:07:48	ga_ls8c_ard_3-2-1_108075_2023-08-03_final
2023-08-13 11:46:54	ga_ls8c_ard_3-2-1_114080_2023-08-13_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-08-26 09:39:38	ga_ls8c_ard_3-2-1_093086_2023-08-26_final
2023-09-05 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-09-05_final
2023-09-23 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-09-23_final
2023-09-25 11:25:23	ga_ls8c_ard_3-2-1_111072_2023-09-25_final
2023-09-26 10:30:10	ga_ls8c_ard_3-2-1_102073_2023-09-26_final
2023-09-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2023-09-30_final
2023-10-01 09:12:14	ga_ls8c_ard_3-2-1_089079_2023-09-30_final
2023-10-04 09:43:56	ga_ls8c_ard_3-2-1_094081_2023-10-04_final
2023-10-17 09:12:16	ga_ls8c_ard_3-2-1_089079_2023-10-16_final
2023-10-18 09:57:31	ga_ls8c_ard_3-2-1_096084_2023-10-18_final
2023-10-23 10:14:05	ga_ls8c_ard_3-2-1_099079_2023-10-23_final
2023-10-24 09:16:53	ga_ls8c_ard_3-2-1_090075_2023-10-23_final
2023-10-27 11:25:30	ga_ls8c_ard_3-2-1_111072_2023-10-27_final
2023-10-28 10:30:17	ga_ls8c_ard_3-2-1_102073_2023-10-28_final
2023-11-03 09:58:23	ga_ls8c_ard_3-2-1_096086_2023-11-03_final
2023-11-05 11:20:54	ga_ls8c_ard_3-2-1_110076_2023-11-05_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