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
2023-08-10 09:35:06	ga_ls8c_ard_3-2-1_093075_2023-08-10_final
2023-08-10 09:37:53	ga_ls8c_ard_3-2-1_093082_2023-08-10_final
2023-08-11 10:17:57	ga_ls8c_ard_3-2-1_100074_2023-08-11_final
2023-08-11 10:18:45	ga_ls8c_ard_3-2-1_100076_2023-08-11_final
2023-08-11 10:19:57	ga_ls8c_ard_3-2-1_100079_2023-08-11_final
2023-08-12 11:04:49	ga_ls8c_ard_3-2-1_107083_2023-08-12_final
2023-08-13 10:06:49	ga_ls8c_ard_3-2-1_098077_2023-08-13_final
2023-08-13 11:46:30	ga_ls8c_ard_3-2-1_114079_2023-08-13_final
2023-08-19 11:10:18	ga_ls8c_ard_3-2-1_108081_2023-08-19_final
2023-08-22 09:57:57	ga_ls8c_ard_3-2-1_097070_2023-08-22_final
2023-08-24 09:46:24	ga_ls8c_ard_3-2-1_095072_2023-08-24_final
2023-08-26 09:38:50	ga_ls8c_ard_3-2-1_093084_2023-08-26_final
2023-08-27 10:21:18	ga_ls8c_ard_3-2-1_100082_2023-08-27_final
2023-08-28 09:25:17	ga_ls8c_ard_3-2-1_091081_2023-08-27_final
2023-08-30 09:11:19	ga_ls8c_ard_3-2-1_089077_2023-08-29_final
2023-08-31 11:35:51	ga_ls8c_ard_3-2-1_112083_2023-08-31_final
2023-09-01 10:35:02	ga_ls8c_ard_3-2-1_103070_2023-09-01_final
2023-09-03 10:25:52	ga_ls8c_ard_3-2-1_101078_2023-09-03_final
2023-09-04 09:31:50	ga_ls8c_ard_3-2-1_092082_2023-09-04_final
2023-09-05 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-09-05_final
2023-09-07 11:40:48	ga_ls8c_ard_3-2-1_113080_2023-09-07_final
2023-09-09 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-09-09_final
2023-09-09 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-09-09_final
2023-09-11 11:17:44	ga_ls8c_ard_3-2-1_109084_2023-09-11_final
2023-09-12 10:22:07	ga_ls8c_ard_3-2-1_100084_2023-09-12_final
2023-09-13 09:23:43	ga_ls8c_ard_3-2-1_091077_2023-09-12_final
2023-09-13 09:24:55	ga_ls8c_ard_3-2-1_091080_2023-09-12_final
2023-09-13 09:26:55	ga_ls8c_ard_3-2-1_091085_2023-09-12_final
2023-09-13 11:03:24	ga_ls8c_ard_3-2-1_107079_2023-09-13_final
2023-09-13 11:03:48	ga_ls8c_ard_3-2-1_107080_2023-09-13_final
2023-09-14 10:03:48	ga_ls8c_ard_3-2-1_098069_2023-09-14_final
2023-09-15 09:13:46	ga_ls8c_ard_3-2-1_089083_2023-09-14_final
2023-09-15 10:48:16	ga_ls8c_ard_3-2-1_105072_2023-09-15_final
2023-09-16 09:57:50	ga_ls8c_ard_3-2-1_096085_2023-09-16_final
2023-09-17 10:34:19	ga_ls8c_ard_3-2-1_103068_2023-09-17_final
2023-09-17 10:36:43	ga_ls8c_ard_3-2-1_103074_2023-09-17_final
2023-09-20 09:31:55	ga_ls8c_ard_3-2-1_092082_2023-09-20_final
2023-09-20 11:10:25	ga_ls8c_ard_3-2-1_108081_2023-09-20_final
2023-09-21 10:16:23	ga_ls8c_ard_3-2-1_099085_2023-09-21_final
2023-09-23 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-09-23_final
2023-09-25 09:46:54	ga_ls8c_ard_3-2-1_095073_2023-09-25_final
2023-09-25 11:30:10	ga_ls8c_ard_3-2-1_111084_2023-09-25_final
2023-09-26 10:30:58	ga_ls8c_ard_3-2-1_102075_2023-09-26_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-09-27 11:17:02	ga_ls8c_ard_3-2-1_109082_2023-09-27_final
2023-09-28 10:20:13	ga_ls8c_ard_3-2-1_100079_2023-09-28_final
2023-09-29 09:25:24	ga_ls8c_ard_3-2-1_091081_2023-09-28_final
2023-09-30 10:04:16	ga_ls8c_ard_3-2-1_098070_2023-09-30_final
2023-09-30 10:07:04	ga_ls8c_ard_3-2-1_098077_2023-09-30_final
2023-09-30 10:07:28	ga_ls8c_ard_3-2-1_098078_2023-09-30_final
2023-10-01 09:13:02	ga_ls8c_ard_3-2-1_089081_2023-09-30_final
2023-10-02 09:53:30	ga_ls8c_ard_3-2-1_096074_2023-10-02_final
2023-10-02 09:55:54	ga_ls8c_ard_3-2-1_096080_2023-10-02_final
2023-10-06 09:31:10	ga_ls8c_ard_3-2-1_092080_2023-10-06_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-07 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-10-07_final
2023-10-08 09:19:38	ga_ls8c_ard_3-2-1_090082_2023-10-07_final
2023-10-08 10:58:55	ga_ls8c_ard_3-2-1_106083_2023-10-08_final
2023-10-09 09:58:55	ga_ls8c_ard_3-2-1_097072_2023-10-09_final
2023-10-10 10:41:23	ga_ls8c_ard_3-2-1_104070_2023-10-10_final
2023-10-11 09:50:33	ga_ls8c_ard_3-2-1_095082_2023-10-11_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-12 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-10-12_final
2023-10-12 10:33:01	ga_ls8c_ard_3-2-1_102080_2023-10-12_final
2023-10-13 11:11:54	ga_ls8c_ard_3-2-1_109069_2023-10-13_final
2023-10-15 09:25:02	ga_ls8c_ard_3-2-1_091080_2023-10-14_final
2023-10-15 09:26:14	ga_ls8c_ard_3-2-1_091083_2023-10-14_final
2023-10-15 11:04:43	ga_ls8c_ard_3-2-1_107082_2023-10-15_final
2023-10-16 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-10-16_final
2023-10-17 09:12:40	ga_ls8c_ard_3-2-1_089080_2023-10-16_final
2023-10-18 09:57:55	ga_ls8c_ard_3-2-1_096085_2023-10-18_final
2023-10-21 10:23:38	ga_ls8c_ard_3-2-1_101072_2023-10-21_final
2023-10-21 10:25:38	ga_ls8c_ard_3-2-1_101077_2023-10-21_final
2023-10-24 09:20:28	ga_ls8c_ard_3-2-1_090084_2023-10-23_final
2023-10-25 10:02:33	ga_ls8c_ard_3-2-1_097081_2023-10-25_final
2023-10-28 10:30:41	ga_ls8c_ard_3-2-1_102074_2023-10-28_final
2023-10-29 11:11:57	ga_ls8c_ard_3-2-1_109069_2023-10-29_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-10-31 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-10-31_final
2023-11-02 09:14:19	ga_ls8c_ard_3-2-1_089084_2023-11-01_final
2023-11-02 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-02_final
2023-11-04 10:37:39	ga_ls8c_ard_3-2-1_103076_2023-11-04_final
2023-11-05 09:44:01	ga_ls8c_ard_3-2-1_094081_2023-11-05_final
2023-11-07 09:31:13	ga_ls8c_ard_3-2-1_092080_2023-11-07_final
2023-11-09 09:20:25	ga_ls8c_ard_3-2-1_090084_2023-11-08_final
2023-11-10 09:59:41	ga_ls8c_ard_3-2-1_097074_2023-11-10_final
2023-11-13 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-11-13_final
2023-11-13 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-11-13_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-16 09:27:28	ga_ls8c_ard_3-2-1_091086_2023-11-15_final
2023-11-16 09:28:16	ga_ls8c_ard_3-2-1_091088_2023-11-15_final
2023-11-16 11:02:46	ga_ls8c_ard_3-2-1_107077_2023-11-16_final
2023-11-17 10:04:21	ga_ls8c_ard_3-2-1_098070_2023-11-17_final
2023-11-17 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-11-17_final
2023-11-17 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-11-17_final
2023-11-19 09:53:13	ga_ls8c_ard_3-2-1_096073_2023-11-19_final
2023-11-21 09:46:03	ga_ls8c_ard_3-2-1_094086_2023-11-21_final
2023-11-21 11:23:20	ga_ls8c_ard_3-2-1_110082_2023-11-21_final
2023-11-22 10:24:32	ga_ls8c_ard_3-2-1_101074_2023-11-22_final
2023-11-23 11:09:47	ga_ls8c_ard_3-2-1_108079_2023-11-23_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