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 10:07:34	ga_ls8c_ard_3-2-1_098078_2022-01-14_final
2022-07-15 09:33:16	ga_ls8c_ard_3-2-1_092085_2022-07-15_final
2022-07-15 09:33:40	ga_ls8c_ard_3-2-1_092086_2022-07-15_final
2022-07-17 09:22:55	ga_ls8c_ard_3-2-1_090090_2022-07-16_final
2022-07-20 11:26:22	ga_ls8c_ard_3-2-1_111074_2022-07-20_final
2022-07-29 11:19:30	ga_ls8c_ard_3-2-1_110072_2022-07-29_final
2022-07-31 11:07:57	ga_ls8c_ard_3-2-1_108074_2022-07-31_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-21 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-08-21_final
2022-08-21 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-08-21_final
2022-08-26 10:07:29	ga_ls8c_ard_3-2-1_098077_2022-08-26_final
2022-08-27 09:15:27	ga_ls8c_ard_3-2-1_089086_2022-08-26_final
2022-08-28 09:57:54	ga_ls8c_ard_3-2-1_096084_2022-08-28_final
2022-09-01 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-09-01_final
2022-09-03 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-09-03_final
2022-09-04 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-09-04_final
2022-09-06 11:25:27	ga_ls8c_ard_3-2-1_111071_2022-09-06_final
2022-09-10 09:23:29	ga_ls8c_ard_3-2-1_091075_2022-09-09_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-10 11:01:58	ga_ls8c_ard_3-2-1_107074_2022-09-10_final
2022-09-11 10:05:09	ga_ls8c_ard_3-2-1_098071_2022-09-11_final
2022-09-15 11:20:08	ga_ls8c_ard_3-2-1_110073_2022-09-15_final
2022-09-17 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-09-17_final
2022-09-18 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-09-18_final
2022-09-26 09:23:56	ga_ls8c_ard_3-2-1_091076_2022-09-25_final
2022-09-26 09:27:07	ga_ls8c_ard_3-2-1_091084_2022-09-25_final
2022-09-28 10:52:27	ga_ls8c_ard_3-2-1_105081_2022-09-28_final
2022-10-01 09:46:27	ga_ls8c_ard_3-2-1_094086_2022-10-01_final
2022-10-03 09:34:04	ga_ls8c_ard_3-2-1_092086_2022-10-03_final
2022-10-03 09:34:28	ga_ls8c_ard_3-2-1_092087_2022-10-03_final
2022-10-05 09:23:18	ga_ls8c_ard_3-2-1_090090_2022-10-04_final
2022-10-08 09:46:35	ga_ls8c_ard_3-2-1_095071_2022-10-08_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-11 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-10-11_final
2022-10-17 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-10-17_final
2022-10-17 09:46:45	ga_ls8c_ard_3-2-1_094087_2022-10-17_final
2022-10-19 09:33:13	ga_ls8c_ard_3-2-1_092084_2022-10-19_final
2022-10-20 10:14:29	ga_ls8c_ard_3-2-1_099079_2022-10-20_final
2022-10-28 11:02:24	ga_ls8c_ard_3-2-1_107075_2022-10-28_final
2022-11-02 11:18:33	ga_ls8c_ard_3-2-1_110069_2022-11-02_final
2022-11-09 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-11-09_final
2022-11-13 09:28:15	ga_ls8c_ard_3-2-1_091087_2022-11-12_final
2022-11-18 11:23:36	ga_ls8c_ard_3-2-1_110082_2022-11-18_final
2022-11-20 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-11-20_final
2022-11-21 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-11-21_final
2022-11-23 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-11-23_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-26 10:29:49	ga_ls8c_ard_3-2-1_102071_2022-11-26_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-11-27 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-11-27_final
2022-11-27 11:15:05	ga_ls8c_ard_3-2-1_109076_2022-11-27_final
2022-11-29 09:29:02	ga_ls8c_ard_3-2-1_091089_2022-11-28_final
2022-12-02 09:58:44	ga_ls8c_ard_3-2-1_096086_2022-12-02_final
2022-12-04 11:19:40	ga_ls8c_ard_3-2-1_110072_2022-12-04_final
2022-12-09 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-12-09_final
2022-12-13 11:13:02	ga_ls8c_ard_3-2-1_109071_2022-12-13_final
2022-12-13 11:13:50	ga_ls8c_ard_3-2-1_109073_2022-12-13_final
2022-12-15 11:00:39	ga_ls8c_ard_3-2-1_107071_2022-12-15_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-19 10:38:16	ga_ls8c_ard_3-2-1_103077_2022-12-19_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2023-01-02 09:12:32	ga_ls8c_ard_3-2-1_089079_2023-01-01_final
2023-01-03 09:58:11	ga_ls8c_ard_3-2-1_096085_2023-01-03_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-08 10:13:31	ga_ls8c_ard_3-2-1_099077_2023-01-08_final
2023-01-13 10:28:49	ga_ls8c_ard_3-2-1_102069_2023-01-13_final
2023-01-16 09:27:10	ga_ls8c_ard_3-2-1_091085_2023-01-15_final
2023-01-16 11:02:04	ga_ls8c_ard_3-2-1_107075_2023-01-16_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-18 09:13:11	ga_ls8c_ard_3-2-1_089081_2023-01-17_final
2023-01-25 09:17:28	ga_ls8c_ard_3-2-1_090076_2023-01-24_final
2023-01-26 09:57:56	ga_ls8c_ard_3-2-1_097069_2023-01-26_final
2023-01-26 11:38:01	ga_ls8c_ard_3-2-1_113072_2023-01-26_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-18 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-02-18_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-03-07 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-03-07_final
2023-03-12 09:34:14	ga_ls8c_ard_3-2-1_092088_2023-03-12_final
2023-03-13 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-03-13_final
2023-03-15 11:37:37	ga_ls8c_ard_3-2-1_113072_2023-03-15_final
2023-03-31 11:41:02	ga_ls8c_ard_3-2-1_113081_2023-03-31_final
2023-04-01 10:40:12	ga_ls8c_ard_3-2-1_104068_2023-04-01_final
2023-04-01 10:42:12	ga_ls8c_ard_3-2-1_104073_2023-04-01_final
2023-04-05 10:17:00	ga_ls8c_ard_3-2-1_100072_2023-04-05_final
2023-04-07 10:03:48	ga_ls8c_ard_3-2-1_098070_2023-04-07_final
2023-04-11 09:40:35	ga_ls8c_ard_3-2-1_094074_2023-04-11_final
2023-04-11 11:19:52	ga_ls8c_ard_3-2-1_110075_2023-04-11_final
2023-04-13 09:31:49	ga_ls8c_ard_3-2-1_092083_2023-04-13_final
2023-04-13 09:32:13	ga_ls8c_ard_3-2-1_092084_2023-04-13_final
2023-04-19 10:32:46	ga_ls8c_ard_3-2-1_102081_2023-04-19_final
2023-04-24 10:48:31	ga_ls8c_ard_3-2-1_105074_2023-04-24_final
2023-04-27 11:19:49	ga_ls8c_ard_3-2-1_110075_2023-04-27_final
2023-04-30 11:51:05	ga_ls8c_ard_3-2-1_115076_2023-04-30_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-08 11:01:32	ga_ls8c_ard_3-2-1_107076_2023-05-08_final
2023-05-11 09:57:29	ga_ls8c_ard_3-2-1_096086_2023-05-11_final
2023-05-13 11:22:23	ga_ls8c_ard_3-2-1_110082_2023-05-13_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