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 10:07:58	ga_ls8c_ard_3-2-1_098079_2022-01-14_final
2022-07-29 09:44:12	ga_ls8c_ard_3-2-1_094081_2022-07-29_final
2022-07-30 10:24:41	ga_ls8c_ard_3-2-1_101074_2022-07-30_final
2022-07-30 10:26:41	ga_ls8c_ard_3-2-1_101079_2022-07-30_final
2022-08-28 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-08-28_final
2022-08-29 10:37:11	ga_ls8c_ard_3-2-1_103074_2022-08-29_final
2022-09-01 11:06:05	ga_ls8c_ard_3-2-1_108069_2022-09-01_final
2022-09-12 10:51:13	ga_ls8c_ard_3-2-1_105078_2022-09-12_final
2022-09-13 11:35:41	ga_ls8c_ard_3-2-1_112081_2022-09-13_final
2022-09-17 09:30:30	ga_ls8c_ard_3-2-1_092077_2022-09-17_final
2022-09-27 10:08:23	ga_ls8c_ard_3-2-1_098079_2022-09-27_final
2022-09-28 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-09-28_final
2022-09-28 10:52:03	ga_ls8c_ard_3-2-1_105080_2022-09-28_final
2022-10-05 10:57:47	ga_ls8c_ard_3-2-1_106079_2022-10-05_final
2022-10-07 09:06:55	ga_ls8c_ard_3-2-1_088080_2022-10-06_final
2022-10-07 10:45:48	ga_ls8c_ard_3-2-1_104080_2022-10-07_final
2022-10-10 09:39:23	ga_ls8c_ard_3-2-1_093084_2022-10-10_final
2022-10-26 11:12:21	ga_ls8c_ard_3-2-1_109069_2022-10-26_final
2022-10-27 10:21:07	ga_ls8c_ard_3-2-1_100080_2022-10-27_final
2022-11-12 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-11-12_final
2022-11-14 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-14_final
2022-11-19 10:25:36	ga_ls8c_ard_3-2-1_101076_2022-11-19_final
2022-11-19 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-11-19_final
2022-11-25 09:47:45	ga_ls8c_ard_3-2-1_095074_2022-11-25_final
2022-11-25 11:29:02	ga_ls8c_ard_3-2-1_111080_2022-11-25_final
2022-11-29 09:26:14	ga_ls8c_ard_3-2-1_091082_2022-11-28_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-14 10:20:36	ga_ls8c_ard_3-2-1_100079_2022-12-14_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-26 10:42:49	ga_ls8c_ard_3-2-1_104073_2022-12-26_final
2022-12-29 09:37:39	ga_ls8c_ard_3-2-1_093080_2022-12-29_final
2023-01-05 09:41:26	ga_ls8c_ard_3-2-1_094074_2023-01-05_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-01-24 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-01-24_final
2023-02-03 10:51:23	ga_ls8c_ard_3-2-1_105079_2023-02-03_final
2023-02-04 09:55:21	ga_ls8c_ard_3-2-1_096078_2023-02-04_final
2023-02-04 11:33:03	ga_ls8c_ard_3-2-1_112075_2023-02-04_final
2023-02-05 10:38:13	ga_ls8c_ard_3-2-1_103077_2023-02-05_final
2023-02-05 10:39:25	ga_ls8c_ard_3-2-1_103080_2023-02-05_final
2023-02-08 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-02-08_final
2023-02-10 09:18:38	ga_ls8c_ard_3-2-1_090079_2023-02-09_final
2023-02-10 09:19:02	ga_ls8c_ard_3-2-1_090080_2023-02-09_final
2023-02-10 10:57:07	ga_ls8c_ard_3-2-1_106078_2023-02-10_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-14 10:29:57	ga_ls8c_ard_3-2-1_102072_2023-02-14_final
2023-02-26 09:18:21	ga_ls8c_ard_3-2-1_090079_2023-02-25_final
2023-02-28 10:45:17	ga_ls8c_ard_3-2-1_104080_2023-02-28_final
2023-02-28 10:45:40	ga_ls8c_ard_3-2-1_104081_2023-02-28_final
2023-03-13 10:11:54	ga_ls8c_ard_3-2-1_099074_2023-03-13_final
2023-03-14 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-03-14_final
2023-03-18 10:29:36	ga_ls8c_ard_3-2-1_102072_2023-03-18_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-02 11:29:02	ga_ls8c_ard_3-2-1_111082_2023-04-02_final
2023-04-08 10:50:14	ga_ls8c_ard_3-2-1_105078_2023-04-08_final
2023-04-09 11:33:52	ga_ls8c_ard_3-2-1_112079_2023-04-09_final
2023-04-13 09:31:49	ga_ls8c_ard_3-2-1_092083_2023-04-13_final
2023-04-13 11:08:42	ga_ls8c_ard_3-2-1_108078_2023-04-13_final
2023-04-13 11:09:54	ga_ls8c_ard_3-2-1_108081_2023-04-13_final
2023-04-18 09:48:43	ga_ls8c_ard_3-2-1_095079_2023-04-18_final
2023-04-25 09:54:54	ga_ls8c_ard_3-2-1_096079_2023-04-25_final
2023-05-06 11:12:20	ga_ls8c_ard_3-2-1_109072_2023-05-06_final
2023-05-07 10:17:54	ga_ls8c_ard_3-2-1_100075_2023-05-07_final
2023-05-18 10:00:25	ga_ls8c_ard_3-2-1_097078_2023-05-18_final
2023-05-18 10:01:13	ga_ls8c_ard_3-2-1_097080_2023-05-18_final
2023-05-20 09:48:28	ga_ls8c_ard_3-2-1_095079_2023-05-20_final
2023-05-26 09:13:49	ga_ls8c_ard_3-2-1_089085_2023-05-25_final
2023-05-27 11:34:46	ga_ls8c_ard_3-2-1_112082_2023-05-27_final
2023-05-28 10:37:57	ga_ls8c_ard_3-2-1_103079_2023-05-28_final
2023-06-03 09:59:41	ga_ls8c_ard_3-2-1_097076_2023-06-03_final
2023-06-03 10:01:17	ga_ls8c_ard_3-2-1_097080_2023-06-03_final
2023-06-09 09:23:29	ga_ls8c_ard_3-2-1_091078_2023-06-08_final
2023-06-11 10:50:26	ga_ls8c_ard_3-2-1_105079_2023-06-11_final
2023-06-16 11:08:12	ga_ls8c_ard_3-2-1_108077_2023-06-16_final
2023-06-18 09:18:58	ga_ls8c_ard_3-2-1_090082_2023-06-17_final
2023-06-20 10:40:18	ga_ls8c_ard_3-2-1_104069_2023-06-20_final
2023-06-30 11:23:05	ga_ls8c_ard_3-2-1_110083_2023-06-30_final
2023-07-06 10:43:41	ga_ls8c_ard_3-2-1_104077_2023-07-06_final
2023-07-07 09:46:28	ga_ls8c_ard_3-2-1_095073_2023-07-07_final
2023-07-30 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-07-30_final
2023-08-09 10:30:43	ga_ls8c_ard_3-2-1_102075_2023-08-09_final
2023-08-10 09:38:41	ga_ls8c_ard_3-2-1_093084_2023-08-10_final
2023-08-13 11:45:43	ga_ls8c_ard_3-2-1_114077_2023-08-13_final
2023-08-14 10:52:30	ga_ls8c_ard_3-2-1_105083_2023-08-14_final
2023-08-15 09:55:41	ga_ls8c_ard_3-2-1_096080_2023-08-15_final
2023-08-17 11:21:03	ga_ls8c_ard_3-2-1_110077_2023-08-17_final
2023-08-21 09:18:16	ga_ls8c_ard_3-2-1_090079_2023-08-20_final
2023-08-23 10:40:49	ga_ls8c_ard_3-2-1_104069_2023-08-23_final
2023-09-02 09:41:25	ga_ls8c_ard_3-2-1_094075_2023-09-02_final
2023-09-04 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-09-04_final
2023-09-04 09:35:02	ga_ls8c_ard_3-2-1_092090_2023-09-04_final
2023-09-06 09:18:15	ga_ls8c_ard_3-2-1_090079_2023-09-05_final
2023-09-07 10:01:31	ga_ls8c_ard_3-2-1_097079_2023-09-07_final
2023-09-08 10:42:48	ga_ls8c_ard_3-2-1_104074_2023-09-08_final
2023-09-09 11:26:53	ga_ls8c_ard_3-2-1_111076_2023-09-09_final
2023-09-09 11:29:16	ga_ls8c_ard_3-2-1_111082_2023-09-09_final
2023-09-11 11:15:20	ga_ls8c_ard_3-2-1_109078_2023-09-11_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