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 10:06:22	ga_ls8c_ard_3-2-1_098075_2022-01-14_final
2022-02-03 09:45:33	ga_ls8c_ard_3-2-1_094085_2022-02-03_final
2022-02-08 09:58:29	ga_ls8c_ard_3-2-1_097071_2022-02-08_final
2022-02-19 09:44:39	ga_ls8c_ard_3-2-1_094083_2022-02-19_final
2022-02-21 09:30:17	ga_ls8c_ard_3-2-1_092078_2022-02-21_final
2022-03-01 10:21:19	ga_ls8c_ard_3-2-1_100082_2022-03-01_final
2022-03-02 11:03:23	ga_ls8c_ard_3-2-1_107079_2022-03-02_final
2022-03-04 10:47:25	ga_ls8c_ard_3-2-1_105070_2022-03-04_final
2022-03-10 10:12:42	ga_ls8c_ard_3-2-1_099076_2022-03-10_final
2022-03-11 10:58:45	ga_ls8c_ard_3-2-1_106083_2022-03-11_final
2022-03-14 11:28:02	ga_ls8c_ard_3-2-1_111079_2022-03-14_final
2022-03-19 10:07:38	ga_ls8c_ard_3-2-1_098079_2022-03-19_final
2022-03-23 09:43:15	ga_ls8c_ard_3-2-1_094080_2022-03-23_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2022-04-09 10:24:53	ga_ls8c_ard_3-2-1_101076_2022-04-09_final
2022-04-19 09:26:18	ga_ls8c_ard_3-2-1_091084_2022-04-18_final
2022-05-06 11:45:40	ga_ls8c_ard_3-2-1_114077_2022-05-06_final
2022-05-06 11:46:28	ga_ls8c_ard_3-2-1_114079_2022-05-06_final
2022-05-15 09:57:30	ga_ls8c_ard_3-2-1_097069_2022-05-15_final
2022-05-22 11:45:22	ga_ls8c_ard_3-2-1_114076_2022-05-22_final
2022-05-26 11:22:38	ga_ls8c_ard_3-2-1_110081_2022-05-26_final
2022-06-04 11:12:58	ga_ls8c_ard_3-2-1_109072_2022-06-04_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-11 09:42:21	ga_ls8c_ard_3-2-1_094077_2022-06-11_final
2022-06-23 10:03:10	ga_ls8c_ard_3-2-1_098067_2022-06-23_final
2022-06-23 10:06:22	ga_ls8c_ard_3-2-1_098075_2022-06-23_final
2022-06-23 11:46:27	ga_ls8c_ard_3-2-1_114078_2022-06-23_final
2022-06-27 11:22:56	ga_ls8c_ard_3-2-1_110081_2022-06-27_final
2022-07-13 11:22:31	ga_ls8c_ard_3-2-1_110080_2022-07-13_final
2022-07-17 09:20:08	ga_ls8c_ard_3-2-1_090083_2022-07-16_final
2022-07-18 09:58:37	ga_ls8c_ard_3-2-1_097071_2022-07-18_final
2022-07-22 11:13:14	ga_ls8c_ard_3-2-1_109072_2022-07-22_final
2022-07-22 11:13:38	ga_ls8c_ard_3-2-1_109073_2022-07-22_final
2022-07-29 09:42:37	ga_ls8c_ard_3-2-1_094077_2022-07-29_final
2022-08-07 11:13:00	ga_ls8c_ard_3-2-1_109071_2022-08-07_final
2022-08-11 10:47:55	ga_ls8c_ard_3-2-1_105070_2022-08-11_final
2022-08-11 10:53:06	ga_ls8c_ard_3-2-1_105083_2022-08-11_final
2022-08-26 10:10:40	ga_ls8c_ard_3-2-1_098085_2022-08-26_final
2022-08-26 11:45:34	ga_ls8c_ard_3-2-1_114075_2022-08-26_final
2022-08-30 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-08-30_final
2022-09-01 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-09-01_final
2022-09-02 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-09-02_final
2022-09-04 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-09-04_final
2022-09-13 09:56:48	ga_ls8c_ard_3-2-1_096081_2022-09-13_final
2022-09-16 10:25:19	ga_ls8c_ard_3-2-1_101075_2022-09-16_final
2022-09-17 11:06:11	ga_ls8c_ard_3-2-1_108069_2022-09-17_final
2022-09-21 10:41:53	ga_ls8c_ard_3-2-1_104070_2022-09-21_final
2022-09-29 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-09-29_final
2022-10-01 09:44:27	ga_ls8c_ard_3-2-1_094081_2022-10-01_final
2022-10-03 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-10-03_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-17 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-10-17_final
2022-10-27 10:20:43	ga_ls8c_ard_3-2-1_100079_2022-10-27_final
2022-11-14 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-14_final
2022-11-16 09:55:31	ga_ls8c_ard_3-2-1_096078_2022-11-16_final
2022-11-19 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-11-19_final
2022-11-20 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-11-20_final
2022-11-25 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-11-25_final
2022-12-03 10:38:24	ga_ls8c_ard_3-2-1_103077_2022-12-03_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-14 10:19:00	ga_ls8c_ard_3-2-1_100075_2022-12-14_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-30 11:58:12	ga_ls8c_ard_3-2-1_116076_2022-12-30_final
2023-01-12 11:27:15	ga_ls8c_ard_3-2-1_111076_2023-01-12_final
2023-01-21 11:20:38	ga_ls8c_ard_3-2-1_110075_2023-01-21_final
2023-01-25 09:18:39	ga_ls8c_ard_3-2-1_090079_2023-01-24_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-15 11:17:35	ga_ls8c_ard_3-2-1_109083_2023-02-15_final
2023-03-03 09:37:41	ga_ls8c_ard_3-2-1_093081_2023-03-03_final
2023-03-05 09:25:18	ga_ls8c_ard_3-2-1_091081_2023-03-04_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-19 09:35:33	ga_ls8c_ard_3-2-1_093076_2023-03-19_final
2023-04-02 09:51:21	ga_ls8c_ard_3-2-1_095085_2023-04-02_final
2023-04-05 10:19:24	ga_ls8c_ard_3-2-1_100078_2023-04-05_final
2023-04-15 10:56:20	ga_ls8c_ard_3-2-1_106078_2023-04-15_final
2023-04-20 09:35:57	ga_ls8c_ard_3-2-1_093078_2023-04-20_final
2023-05-04 09:51:02	ga_ls8c_ard_3-2-1_095085_2023-05-04_final
2023-05-14 10:23:34	ga_ls8c_ard_3-2-1_101074_2023-05-14_final
2023-05-18 10:00:01	ga_ls8c_ard_3-2-1_097077_2023-05-18_final
2023-06-07 11:12:43	ga_ls8c_ard_3-2-1_109073_2023-06-07_final
2023-06-08 10:20:18	ga_ls8c_ard_3-2-1_100081_2023-06-08_final
2023-06-16 09:32:07	ga_ls8c_ard_3-2-1_092084_2023-06-16_final
2023-06-18 09:19:22	ga_ls8c_ard_3-2-1_090083_2023-06-17_final
2023-06-28 09:52:09	ga_ls8c_ard_3-2-1_096072_2023-06-28_final
2023-06-28 11:35:01	ga_ls8c_ard_3-2-1_112082_2023-06-28_final
2023-06-30 11:20:42	ga_ls8c_ard_3-2-1_110077_2023-06-30_final
2023-07-02 09:31:52	ga_ls8c_ard_3-2-1_092083_2023-07-02_final
2023-07-02 11:09:10	ga_ls8c_ard_3-2-1_108079_2023-07-02_final
2023-07-12 11:45:31	ga_ls8c_ard_3-2-1_114077_2023-07-12_final
2023-07-18 11:09:38	ga_ls8c_ard_3-2-1_108080_2023-07-18_final
2023-07-21 11:41:20	ga_ls8c_ard_3-2-1_113082_2023-07-21_final
2023-08-11 10:20:21	ga_ls8c_ard_3-2-1_100080_2023-08-11_final
2023-08-21 09:19:04	ga_ls8c_ard_3-2-1_090081_2023-08-20_final
2023-08-22 10:02:20	ga_ls8c_ard_3-2-1_097081_2023-08-22_final
2023-09-04 09:35:02	ga_ls8c_ard_3-2-1_092090_2023-09-04_final
2023-09-04 11:09:55	ga_ls8c_ard_3-2-1_108080_2023-09-04_final
2023-09-06 09:19:03	ga_ls8c_ard_3-2-1_090081_2023-09-05_final
2023-09-06 10:57:32	ga_ls8c_ard_3-2-1_106080_2023-09-06_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