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
2023-09-08 10:41:36	ga_ls8c_ard_3-2-1_104071_2023-09-08_final
2023-09-08 10:42:00	ga_ls8c_ard_3-2-1_104072_2023-09-08_final
2023-09-09 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-09-09_final
2023-09-09 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-09-09_final
2023-09-11 09:35:39	ga_ls8c_ard_3-2-1_093076_2023-09-11_final
2023-09-11 11:12:33	ga_ls8c_ard_3-2-1_109071_2023-09-11_final
2023-09-12 11:58:37	ga_ls8c_ard_3-2-1_116078_2023-09-12_final
2023-09-20 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-09-20_final
2023-09-20 09:32:43	ga_ls8c_ard_3-2-1_092084_2023-09-20_final
2023-09-22 09:19:34	ga_ls8c_ard_3-2-1_090082_2023-09-21_final
2023-09-23 09:58:50	ga_ls8c_ard_3-2-1_097072_2023-09-23_final
2023-09-24 10:41:42	ga_ls8c_ard_3-2-1_104071_2023-09-24_final
2023-09-24 10:42:06	ga_ls8c_ard_3-2-1_104072_2023-09-24_final
2023-09-25 09:47:42	ga_ls8c_ard_3-2-1_095075_2023-09-25_final
2023-09-25 09:51:17	ga_ls8c_ard_3-2-1_095084_2023-09-25_final
2023-09-26 10:30:34	ga_ls8c_ard_3-2-1_102074_2023-09-26_final
2023-09-26 10:30:58	ga_ls8c_ard_3-2-1_102075_2023-09-26_final
2023-09-27 11:16:38	ga_ls8c_ard_3-2-1_109081_2023-09-27_final
2023-09-29 09:25:00	ga_ls8c_ard_3-2-1_091080_2023-09-28_final
2023-09-29 09:27:23	ga_ls8c_ard_3-2-1_091086_2023-09-28_final
2023-09-29 09:28:35	ga_ls8c_ard_3-2-1_091089_2023-09-28_final
2023-09-30 10:03:52	ga_ls8c_ard_3-2-1_098069_2023-09-30_final
2023-10-02 09:53:30	ga_ls8c_ard_3-2-1_096074_2023-10-02_final
2023-10-02 09:57:54	ga_ls8c_ard_3-2-1_096085_2023-10-02_final
2023-10-03 10:39:57	ga_ls8c_ard_3-2-1_103082_2023-10-03_final
2023-10-04 09:43:08	ga_ls8c_ard_3-2-1_094079_2023-10-04_final
2023-10-05 10:23:36	ga_ls8c_ard_3-2-1_101072_2023-10-05_final
2023-10-05 10:25:36	ga_ls8c_ard_3-2-1_101077_2023-10-05_final
2023-10-06 09:31:58	ga_ls8c_ard_3-2-1_092082_2023-10-06_final
2023-10-07 10:15:38	ga_ls8c_ard_3-2-1_099083_2023-10-07_final
2023-10-08 09:19:38	ga_ls8c_ard_3-2-1_090082_2023-10-07_final
2023-10-08 10:58:07	ga_ls8c_ard_3-2-1_106081_2023-10-08_final
2023-10-08 10:58:55	ga_ls8c_ard_3-2-1_106083_2023-10-08_final
2023-10-09 09:59:19	ga_ls8c_ard_3-2-1_097073_2023-10-09_final
2023-10-09 10:00:06	ga_ls8c_ard_3-2-1_097075_2023-10-09_final
2023-10-09 10:02:54	ga_ls8c_ard_3-2-1_097082_2023-10-09_final
2023-10-09 11:40:59	ga_ls8c_ard_3-2-1_113080_2023-10-09_final
2023-10-11 09:51:45	ga_ls8c_ard_3-2-1_095085_2023-10-11_final
2023-10-12 10:29:26	ga_ls8c_ard_3-2-1_102071_2023-10-12_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-12 10:33:01	ga_ls8c_ard_3-2-1_102080_2023-10-12_final
2023-10-13 09:35:01	ga_ls8c_ard_3-2-1_093074_2023-10-13_final
2023-10-13 11:11:54	ga_ls8c_ard_3-2-1_109069_2023-10-13_final
2023-10-15 09:26:14	ga_ls8c_ard_3-2-1_091083_2023-10-14_final
2023-10-15 11:00:44	ga_ls8c_ard_3-2-1_107072_2023-10-15_final
2023-10-16 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-10-16_final
2023-10-16 10:07:54	ga_ls8c_ard_3-2-1_098079_2023-10-16_final
2023-10-16 11:45:11	ga_ls8c_ard_3-2-1_114075_2023-10-16_final
2023-10-17 09:13:52	ga_ls8c_ard_3-2-1_089083_2023-10-16_final
2023-10-17 09:16:40	ga_ls8c_ard_3-2-1_089090_2023-10-16_final
2023-10-17 10:52:45	ga_ls8c_ard_3-2-1_105083_2023-10-17_final
2023-10-19 10:35:11	ga_ls8c_ard_3-2-1_103070_2023-10-19_final
2023-10-19 10:36:47	ga_ls8c_ard_3-2-1_103074_2023-10-19_final
2023-10-19 10:37:59	ga_ls8c_ard_3-2-1_103077_2023-10-19_final
2023-10-20 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-10-20_final
2023-10-20 09:45:09	ga_ls8c_ard_3-2-1_094084_2023-10-20_final
2023-10-20 09:45:57	ga_ls8c_ard_3-2-1_094086_2023-10-20_final
2023-10-22 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-10-22_final
2023-10-22 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-10-22_final
2023-10-23 11:51:47	ga_ls8c_ard_3-2-1_115076_2023-10-23_final
2023-10-24 09:20:28	ga_ls8c_ard_3-2-1_090084_2023-10-23_final
2023-10-25 09:58:57	ga_ls8c_ard_3-2-1_097072_2023-10-25_final
2023-10-25 10:03:21	ga_ls8c_ard_3-2-1_097083_2023-10-25_final
2023-10-25 11:41:02	ga_ls8c_ard_3-2-1_113080_2023-10-25_final
2023-10-26 10:40:38	ga_ls8c_ard_3-2-1_104068_2023-10-26_final
2023-10-27 09:47:48	ga_ls8c_ard_3-2-1_095075_2023-10-27_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 11:12:21	ga_ls8c_ard_3-2-1_109070_2023-10-29_final
2023-11-01 10:07:57	ga_ls8c_ard_3-2-1_098079_2023-11-01_final
2023-11-02 09:16:43	ga_ls8c_ard_3-2-1_089090_2023-11-01_final
2023-11-02 10:50:25	ga_ls8c_ard_3-2-1_105077_2023-11-02_final
2023-11-03 09:52:24	ga_ls8c_ard_3-2-1_096071_2023-11-03_final
2023-11-03 09:56:47	ga_ls8c_ard_3-2-1_096082_2023-11-03_final
2023-11-04 10:36:51	ga_ls8c_ard_3-2-1_103074_2023-11-04_final
2023-11-04 10:39:14	ga_ls8c_ard_3-2-1_103080_2023-11-04_final
2023-11-04 10:40:02	ga_ls8c_ard_3-2-1_103082_2023-11-04_final
2023-11-05 09:41:37	ga_ls8c_ard_3-2-1_094075_2023-11-05_final
2023-11-05 11:23:41	ga_ls8c_ard_3-2-1_110083_2023-11-05_final
2023-11-06 10:24:52	ga_ls8c_ard_3-2-1_101075_2023-11-06_final
2023-11-07 11:06:55	ga_ls8c_ard_3-2-1_108072_2023-11-07_final
2023-11-08 11:51:45	ga_ls8c_ard_3-2-1_115076_2023-11-08_final
2023-11-09 09:20:25	ga_ls8c_ard_3-2-1_090084_2023-11-08_final
2023-11-10 10:00:29	ga_ls8c_ard_3-2-1_097076_2023-11-10_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-11 10:42:10	ga_ls8c_ard_3-2-1_104072_2023-11-11_final
2023-11-12 11:28:38	ga_ls8c_ard_3-2-1_111080_2023-11-12_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 09:35:01	ga_ls8c_ard_3-2-1_093074_2023-11-14_final
2023-11-14 09:37:25	ga_ls8c_ard_3-2-1_093080_2023-11-14_final
2023-11-14 11:16:42	ga_ls8c_ard_3-2-1_109081_2023-11-14_final
2023-11-15 10:17:54	ga_ls8c_ard_3-2-1_100073_2023-11-15_final
2023-11-17 10:03:57	ga_ls8c_ard_3-2-1_098069_2023-11-17_final
2023-11-17 10:05:33	ga_ls8c_ard_3-2-1_098073_2023-11-17_final
2023-11-17 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-11-17_final
2023-11-18 10:47:38	ga_ls8c_ard_3-2-1_105070_2023-11-18_final
2023-11-19 09:53:13	ga_ls8c_ard_3-2-1_096073_2023-11-19_final
2023-11-21 09:44:03	ga_ls8c_ard_3-2-1_094081_2023-11-21_final
2023-11-21 09:45:39	ga_ls8c_ard_3-2-1_094085_2023-11-21_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