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
2022-07-26 10:48:34	ga_ls8c_ard_3-2-1_105072_2022-07-26_final
2022-07-28 10:35:26	ga_ls8c_ard_3-2-1_103070_2022-07-28_final
2022-07-31 11:10:45	ga_ls8c_ard_3-2-1_108081_2022-07-31_final
2022-08-01 10:11:57	ga_ls8c_ard_3-2-1_099073_2022-08-01_final
2022-08-26 10:05:53	ga_ls8c_ard_3-2-1_098073_2022-08-26_final
2022-08-30 11:19:14	ga_ls8c_ard_3-2-1_110071_2022-08-30_final
2022-08-31 10:24:49	ga_ls8c_ard_3-2-1_101074_2022-08-31_final
2022-09-01 11:06:05	ga_ls8c_ard_3-2-1_108069_2022-09-01_final
2022-09-01 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-09-01_final
2022-09-04 10:01:18	ga_ls8c_ard_3-2-1_097077_2022-09-04_final
2022-09-04 11:40:35	ga_ls8c_ard_3-2-1_113078_2022-09-04_final
2022-09-09 10:21:05	ga_ls8c_ard_3-2-1_100080_2022-09-09_final
2022-09-10 11:05:09	ga_ls8c_ard_3-2-1_107082_2022-09-10_final
2022-09-13 09:53:36	ga_ls8c_ard_3-2-1_096073_2022-09-13_final
2022-09-13 09:57:36	ga_ls8c_ard_3-2-1_096083_2022-09-13_final
2022-09-18 10:12:10	ga_ls8c_ard_3-2-1_099073_2022-09-18_final
2022-09-20 09:59:49	ga_ls8c_ard_3-2-1_097073_2022-09-20_final
2022-09-24 11:15:34	ga_ls8c_ard_3-2-1_109077_2022-09-24_final
2022-09-25 11:58:50	ga_ls8c_ard_3-2-1_116077_2022-09-25_final
2022-09-27 10:05:59	ga_ls8c_ard_3-2-1_098073_2022-09-27_final
2022-09-27 11:46:04	ga_ls8c_ard_3-2-1_114076_2022-09-27_final
2022-09-28 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-09-28_final
2022-09-29 11:36:06	ga_ls8c_ard_3-2-1_112082_2022-09-29_final
2022-09-30 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-09-30_final
2022-10-05 09:18:54	ga_ls8c_ard_3-2-1_090079_2022-10-04_final
2022-10-08 11:27:04	ga_ls8c_ard_3-2-1_111075_2022-10-08_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-14 09:13:48	ga_ls8c_ard_3-2-1_089082_2022-10-13_final
2022-10-15 11:35:58	ga_ls8c_ard_3-2-1_112082_2022-10-15_final
2022-10-17 09:45:09	ga_ls8c_ard_3-2-1_094083_2022-10-17_final
2022-10-18 10:24:50	ga_ls8c_ard_3-2-1_101074_2022-10-18_final
2022-10-19 11:06:07	ga_ls8c_ard_3-2-1_108069_2022-10-19_final
2022-10-19 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-10-19_final
2022-10-22 10:02:57	ga_ls8c_ard_3-2-1_097081_2022-10-22_final
2022-10-28 11:01:36	ga_ls8c_ard_3-2-1_107073_2022-10-28_final
2022-10-29 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-10-29_final
2022-10-29 10:06:47	ga_ls8c_ard_3-2-1_098075_2022-10-29_final
2022-10-31 09:56:25	ga_ls8c_ard_3-2-1_096080_2022-10-31_final
2022-11-01 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-11-01_final
2022-11-02 09:42:28	ga_ls8c_ard_3-2-1_094076_2022-11-02_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-04 11:08:59	ga_ls8c_ard_3-2-1_108076_2022-11-04_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-07 10:02:59	ga_ls8c_ard_3-2-1_097081_2022-11-07_final
2022-11-09 11:28:42	ga_ls8c_ard_3-2-1_111079_2022-11-09_final
2022-11-10 10:31:52	ga_ls8c_ard_3-2-1_102076_2022-11-10_final
2022-11-11 11:13:31	ga_ls8c_ard_3-2-1_109072_2022-11-11_final
2022-11-16 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-11-16_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-23 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-11-23_final
2022-11-24 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-11-24_final
2022-11-26 10:33:25	ga_ls8c_ard_3-2-1_102080_2022-11-26_final
2022-12-02 09:55:56	ga_ls8c_ard_3-2-1_096079_2022-12-02_final
2022-12-05 10:25:38	ga_ls8c_ard_3-2-1_101076_2022-12-05_final
2022-12-08 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-12-07_final
2022-12-10 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-12-10_final
2022-12-13 11:15:26	ga_ls8c_ard_3-2-1_109077_2022-12-13_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-14 10:19:00	ga_ls8c_ard_3-2-1_100075_2022-12-14_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-16 10:05:49	ga_ls8c_ard_3-2-1_098073_2022-12-16_final
2022-12-16 10:06:37	ga_ls8c_ard_3-2-1_098075_2022-12-16_final
2022-12-18 09:55:02	ga_ls8c_ard_3-2-1_096077_2022-12-18_final
2022-12-18 11:33:31	ga_ls8c_ard_3-2-1_112076_2022-12-18_final
2022-12-20 09:42:38	ga_ls8c_ard_3-2-1_094077_2022-12-20_final
2022-12-22 11:11:55	ga_ls8c_ard_3-2-1_108084_2022-12-22_final
2022-12-26 10:41:37	ga_ls8c_ard_3-2-1_104070_2022-12-26_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2022-12-27 11:27:17	ga_ls8c_ard_3-2-1_111076_2022-12-27_final
2022-12-28 10:31:16	ga_ls8c_ard_3-2-1_102075_2022-12-28_final
2022-12-30 10:20:31	ga_ls8c_ard_3-2-1_100079_2022-12-30_final
2022-12-31 11:04:10	ga_ls8c_ard_3-2-1_107080_2022-12-31_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-05 11:22:43	ga_ls8c_ard_3-2-1_110080_2023-01-05_final
2023-01-09 09:20:17	ga_ls8c_ard_3-2-1_090083_2023-01-08_final
2023-01-09 10:58:22	ga_ls8c_ard_3-2-1_106081_2023-01-09_final
2023-01-13 10:33:12	ga_ls8c_ard_3-2-1_102080_2023-01-13_final
2023-01-14 09:37:58	ga_ls8c_ard_3-2-1_093081_2023-01-14_final
2023-01-19 11:34:57	ga_ls8c_ard_3-2-1_112080_2023-01-19_final
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-01-23 09:32:12	ga_ls8c_ard_3-2-1_092082_2023-01-23_final
2023-01-24 10:12:41	ga_ls8c_ard_3-2-1_099075_2023-01-24_final
2023-01-26 09:59:32	ga_ls8c_ard_3-2-1_097073_2023-01-26_final
2023-01-26 10:03:07	ga_ls8c_ard_3-2-1_097082_2023-01-26_final
2023-02-12 10:43:31	ga_ls8c_ard_3-2-1_104075_2023-02-12_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-22 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-02-22_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-02-26 09:18:45	ga_ls8c_ard_3-2-1_090080_2023-02-25_final
2023-02-26 10:56:50	ga_ls8c_ard_3-2-1_106078_2023-02-26_final
2023-02-26 10:57:14	ga_ls8c_ard_3-2-1_106079_2023-02-26_final
2023-02-26 10:58:02	ga_ls8c_ard_3-2-1_106081_2023-02-26_final
2023-02-27 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-02-27_final
2023-02-28 10:45:17	ga_ls8c_ard_3-2-1_104080_2023-02-28_final
2023-03-01 11:26:56	ga_ls8c_ard_3-2-1_111076_2023-03-01_final
2023-03-03 09:38:05	ga_ls8c_ard_3-2-1_093082_2023-03-03_final
2023-03-09 10:39:01	ga_ls8c_ard_3-2-1_103080_2023-03-09_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_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