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
2023-02-03 10:51:47	ga_ls8c_ard_3-2-1_105080_2023-02-03_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-02-26 09:18:45	ga_ls8c_ard_3-2-1_090080_2023-02-25_final
2023-02-27 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-02-27_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_final
2023-03-08 11:32:39	ga_ls8c_ard_3-2-1_112075_2023-03-08_final
2023-03-10 11:22:17	ga_ls8c_ard_3-2-1_110080_2023-03-10_final
2023-03-13 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-03-13_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-16 10:41:59	ga_ls8c_ard_3-2-1_104072_2023-03-16_final
2023-03-22 11:45:41	ga_ls8c_ard_3-2-1_114077_2023-03-22_final
2023-03-24 09:57:36	ga_ls8c_ard_3-2-1_096085_2023-03-24_final
2023-03-26 09:45:38	ga_ls8c_ard_3-2-1_094086_2023-03-26_final
2023-03-31 10:02:57	ga_ls8c_ard_3-2-1_097083_2023-03-31_final
2023-04-16 10:02:18	ga_ls8c_ard_3-2-1_097082_2023-04-16_final
2023-04-19 10:29:11	ga_ls8c_ard_3-2-1_102072_2023-04-19_final
2023-04-19 10:31:10	ga_ls8c_ard_3-2-1_102077_2023-04-19_final
2023-04-21 11:58:06	ga_ls8c_ard_3-2-1_116078_2023-04-21_final
2023-04-25 09:56:29	ga_ls8c_ard_3-2-1_096083_2023-04-25_final
2023-04-25 11:34:34	ga_ls8c_ard_3-2-1_112081_2023-04-25_final
2023-04-27 09:43:19	ga_ls8c_ard_3-2-1_094081_2023-04-27_final
2023-04-27 11:20:36	ga_ls8c_ard_3-2-1_110077_2023-04-27_final
2023-04-29 11:10:14	ga_ls8c_ard_3-2-1_108082_2023-04-29_final
2023-05-02 10:01:49	ga_ls8c_ard_3-2-1_097081_2023-05-02_final
2023-05-10 10:50:20	ga_ls8c_ard_3-2-1_105079_2023-05-10_final
2023-05-12 10:37:08	ga_ls8c_ard_3-2-1_103077_2023-05-12_final
2023-05-15 09:31:56	ga_ls8c_ard_3-2-1_092084_2023-05-15_final
2023-05-15 11:07:37	ga_ls8c_ard_3-2-1_108076_2023-05-15_final
2023-05-17 10:57:38	ga_ls8c_ard_3-2-1_106082_2023-05-17_final
2023-05-18 11:39:42	ga_ls8c_ard_3-2-1_113079_2023-05-18_final
2023-05-24 10:59:52	ga_ls8c_ard_3-2-1_107072_2023-05-24_final
2023-05-25 11:45:32	ga_ls8c_ard_3-2-1_114078_2023-05-25_final
2023-05-27 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-27_final
2023-05-30 10:26:23	ga_ls8c_ard_3-2-1_101081_2023-05-30_final
2023-06-05 11:25:51	ga_ls8c_ard_3-2-1_111075_2023-06-05_final
2023-06-07 09:37:49	ga_ls8c_ard_3-2-1_093083_2023-06-07_final
2023-06-09 09:23:29	ga_ls8c_ard_3-2-1_091078_2023-06-08_final
2023-06-10 11:45:39	ga_ls8c_ard_3-2-1_114078_2023-06-10_final
2023-06-11 10:47:14	ga_ls8c_ard_3-2-1_105071_2023-06-11_final
2023-06-18 10:54:39	ga_ls8c_ard_3-2-1_106074_2023-06-18_final
2023-06-21 11:26:21	ga_ls8c_ard_3-2-1_111076_2023-06-21_final
2023-06-26 10:04:52	ga_ls8c_ard_3-2-1_098073_2023-06-26_final
2023-07-06 10:43:17	ga_ls8c_ard_3-2-1_104076_2023-07-06_final
2023-07-12 10:05:03	ga_ls8c_ard_3-2-1_098073_2023-07-12_final
2023-07-13 10:52:18	ga_ls8c_ard_3-2-1_105083_2023-07-13_final
2023-07-15 10:35:57	ga_ls8c_ard_3-2-1_103073_2023-07-15_final
2023-07-15 10:36:21	ga_ls8c_ard_3-2-1_103074_2023-07-15_final
2023-07-21 11:39:21	ga_ls8c_ard_3-2-1_113077_2023-07-21_final
2023-07-26 10:20:41	ga_ls8c_ard_3-2-1_100081_2023-07-26_final
2023-07-28 10:08:20	ga_ls8c_ard_3-2-1_098081_2023-07-28_final
2023-08-02 10:23:20	ga_ls8c_ard_3-2-1_101072_2023-08-02_final
2023-08-03 09:29:43	ga_ls8c_ard_3-2-1_092077_2023-08-02_final
2023-08-08 11:26:44	ga_ls8c_ard_3-2-1_111076_2023-08-08_final
2023-08-13 11:44:55	ga_ls8c_ard_3-2-1_114075_2023-08-13_final
2023-08-17 11:22:38	ga_ls8c_ard_3-2-1_110081_2023-08-17_final
2023-08-19 11:10:18	ga_ls8c_ard_3-2-1_108081_2023-08-19_final
2023-08-25 10:30:28	ga_ls8c_ard_3-2-1_102074_2023-08-25_final
2023-08-25 10:31:39	ga_ls8c_ard_3-2-1_102077_2023-08-25_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-08-31 09:52:35	ga_ls8c_ard_3-2-1_096072_2023-08-31_final
2023-08-31 09:52:59	ga_ls8c_ard_3-2-1_096073_2023-08-31_final
2023-09-01 10:34:39	ga_ls8c_ard_3-2-1_103069_2023-09-01_final
2023-09-04 09:31:02	ga_ls8c_ard_3-2-1_092080_2023-09-04_final
2023-09-06 10:56:44	ga_ls8c_ard_3-2-1_106078_2023-09-06_final
2023-09-06 10:58:20	ga_ls8c_ard_3-2-1_106082_2023-09-06_final
2023-09-10 10:30:52	ga_ls8c_ard_3-2-1_102075_2023-09-10_final
2023-09-10 10:32:04	ga_ls8c_ard_3-2-1_102078_2023-09-10_final
2023-09-12 10:21:20	ga_ls8c_ard_3-2-1_100082_2023-09-12_final
2023-09-14 11:45:28	ga_ls8c_ard_3-2-1_114076_2023-09-14_final
2023-09-16 09:53:27	ga_ls8c_ard_3-2-1_096074_2023-09-16_final
2023-09-17 10:35:31	ga_ls8c_ard_3-2-1_103071_2023-09-17_final
2023-09-22 10:57:15	ga_ls8c_ard_3-2-1_106079_2023-09-22_final
2023-09-23 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-09-23_final
2023-09-23 11:40:55	ga_ls8c_ard_3-2-1_113080_2023-09-23_final
2023-09-24 10:42:06	ga_ls8c_ard_3-2-1_104072_2023-09-24_final
2023-09-27 09:38:33	ga_ls8c_ard_3-2-1_093083_2023-09-27_final
2023-10-02 09:57:54	ga_ls8c_ard_3-2-1_096085_2023-10-02_final
2023-10-08 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-10-07_final
2023-10-09 10:04:06	ga_ls8c_ard_3-2-1_097085_2023-10-09_final
2023-10-10 10:43:23	ga_ls8c_ard_3-2-1_104075_2023-10-10_final
2023-10-10 10:45:22	ga_ls8c_ard_3-2-1_104080_2023-10-10_final
2023-10-11 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-10-11_final
2023-10-15 09:24:38	ga_ls8c_ard_3-2-1_091079_2023-10-14_final
2023-10-15 09:24:38	ga_ls8c_ard_3-2-1_091079_2023-10-14_nrt
2023-10-15 11:03:55	ga_ls8c_ard_3-2-1_107080_2023-10-15_final
2023-10-15 11:03:55	ga_ls8c_ard_3-2-1_107080_2023-10-15_nrt
2023-10-20 11:22:50	ga_ls8c_ard_3-2-1_110081_2023-10-20_final
2023-10-20 11:23:38	ga_ls8c_ard_3-2-1_110083_2023-10-20_final
2023-10-25 10:00:57	ga_ls8c_ard_3-2-1_097077_2023-10-25_final
2023-10-25 10:03:21	ga_ls8c_ard_3-2-1_097083_2023-10-25_final
2023-10-26 10:41:50	ga_ls8c_ard_3-2-1_104071_2023-10-26_final
2023-10-27 09:50:36	ga_ls8c_ard_3-2-1_095082_2023-10-27_final
2023-10-27 11:28:41	ga_ls8c_ard_3-2-1_111080_2023-10-27_final
2023-10-28 10:31:28	ga_ls8c_ard_3-2-1_102076_2023-10-28_final
2023-10-29 09:36:39	ga_ls8c_ard_3-2-1_093078_2023-10-29_final
2023-10-30 10:18:43	ga_ls8c_ard_3-2-1_100075_2023-10-30_final
2023-10-31 09:25:30	ga_ls8c_ard_3-2-1_091081_2023-10-30_final
2023-11-03 09:55:59	ga_ls8c_ard_3-2-1_096080_2023-11-03_final
2023-11-05 09:41:37	ga_ls8c_ard_3-2-1_094075_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years