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
2022-10-06 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-06_final
2022-10-10 09:37:23	ga_ls8c_ard_3-2-1_093079_2022-10-10_final
2022-10-10 11:17:52	ga_ls8c_ard_3-2-1_109083_2022-10-10_final
2022-10-11 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-10-11_final
2022-10-12 11:02:17	ga_ls8c_ard_3-2-1_107075_2022-10-12_final
2022-10-13 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-10-13_final
2022-10-19 09:34:01	ga_ls8c_ard_3-2-1_092086_2022-10-19_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-20 11:52:11	ga_ls8c_ard_3-2-1_115076_2022-10-20_final
2022-10-22 10:00:09	ga_ls8c_ard_3-2-1_097074_2022-10-22_final
2022-10-22 11:39:26	ga_ls8c_ard_3-2-1_113075_2022-10-22_final
2022-10-31 09:53:38	ga_ls8c_ard_3-2-1_096073_2022-10-31_final
2022-10-31 09:57:37	ga_ls8c_ard_3-2-1_096083_2022-10-31_final
2022-11-01 10:35:42	ga_ls8c_ard_3-2-1_103070_2022-11-01_final
2022-11-01 10:39:17	ga_ls8c_ard_3-2-1_103079_2022-11-01_final
2022-11-03 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-11-03_final
2022-11-06 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-11-05_final
2022-11-06 09:22:08	ga_ls8c_ard_3-2-1_090087_2022-11-05_final
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-08 10:41:51	ga_ls8c_ard_3-2-1_104070_2022-11-08_final
2022-11-09 11:29:06	ga_ls8c_ard_3-2-1_111080_2022-11-09_final
2022-11-09 11:29:30	ga_ls8c_ard_3-2-1_111081_2022-11-09_final
2022-11-11 09:36:14	ga_ls8c_ard_3-2-1_093076_2022-11-11_final
2022-11-13 11:01:32	ga_ls8c_ard_3-2-1_107073_2022-11-13_final
2022-11-14 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-14_final
2022-11-14 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-14_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-20 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-11-20_final
2022-11-20 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-11-20_final
2022-11-20 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-11-20_final
2022-11-21 10:16:03	ga_ls8c_ard_3-2-1_099083_2022-11-21_final
2022-11-22 09:18:50	ga_ls8c_ard_3-2-1_090079_2022-11-21_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-23 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-11-23_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-23 11:42:11	ga_ls8c_ard_3-2-1_113082_2022-11-23_final
2022-11-29 11:03:07	ga_ls8c_ard_3-2-1_107077_2022-11-29_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-04 09:45:10	ga_ls8c_ard_3-2-1_094083_2022-12-04_final
2022-12-04 09:46:22	ga_ls8c_ard_3-2-1_094086_2022-12-04_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-05 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-12-05_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-09 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-12-09_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-20 09:46:14	ga_ls8c_ard_3-2-1_094086_2022-12-20_final
2022-12-22 11:11:07	ga_ls8c_ard_3-2-1_108082_2022-12-22_final
2022-12-24 09:22:40	ga_ls8c_ard_3-2-1_090089_2022-12-23_final
2022-12-24 10:58:45	ga_ls8c_ard_3-2-1_106082_2022-12-24_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2022-12-29 11:18:08	ga_ls8c_ard_3-2-1_109084_2022-12-29_final
2022-12-30 10:18:55	ga_ls8c_ard_3-2-1_100075_2022-12-30_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-12 09:47:58	ga_ls8c_ard_3-2-1_095075_2023-01-12_final
2023-01-13 10:30:49	ga_ls8c_ard_3-2-1_102074_2023-01-13_final
2023-01-16 09:28:46	ga_ls8c_ard_3-2-1_091089_2023-01-15_final
2023-01-16 11:01:16	ga_ls8c_ard_3-2-1_107073_2023-01-16_final
2023-01-20 10:35:45	ga_ls8c_ard_3-2-1_103071_2023-01-20_final
2023-01-20 10:38:57	ga_ls8c_ard_3-2-1_103079_2023-01-20_final
2023-01-21 09:42:08	ga_ls8c_ard_3-2-1_094076_2023-01-21_final
2023-01-21 09:44:56	ga_ls8c_ard_3-2-1_094083_2023-01-21_final
2023-01-23 09:33:00	ga_ls8c_ard_3-2-1_092084_2023-01-23_final
2023-01-23 11:10:41	ga_ls8c_ard_3-2-1_108081_2023-01-23_final
2023-01-24 10:13:04	ga_ls8c_ard_3-2-1_099076_2023-01-24_final
2023-01-24 11:52:22	ga_ls8c_ard_3-2-1_115077_2023-01-24_final
2023-01-26 09:59:56	ga_ls8c_ard_3-2-1_097074_2023-01-26_final
2023-01-26 10:02:19	ga_ls8c_ard_3-2-1_097080_2023-01-26_final
2023-02-01 09:25:39	ga_ls8c_ard_3-2-1_091081_2023-01-31_final
2023-02-06 09:45:47	ga_ls8c_ard_3-2-1_094085_2023-02-06_final
2023-02-07 10:28:14	ga_ls8c_ard_3-2-1_101083_2023-02-07_final
2023-02-08 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-02-08_final
2023-02-08 11:07:06	ga_ls8c_ard_3-2-1_108072_2023-02-08_final
2023-02-09 11:51:09	ga_ls8c_ard_3-2-1_115074_2023-02-09_final
2023-02-11 09:58:41	ga_ls8c_ard_3-2-1_097071_2023-02-11_final
2023-02-12 10:43:55	ga_ls8c_ard_3-2-1_104076_2023-02-12_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-17 09:28:18	ga_ls8c_ard_3-2-1_091088_2023-02-16_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-19 10:50:24	ga_ls8c_ard_3-2-1_105077_2023-02-19_final
2023-02-22 11:18:50	ga_ls8c_ard_3-2-1_110071_2023-02-22_final
2023-02-27 10:00:25	ga_ls8c_ard_3-2-1_097076_2023-02-27_final
2023-03-01 11:29:20	ga_ls8c_ard_3-2-1_111082_2023-03-01_final
2023-03-06 10:06:33	ga_ls8c_ard_3-2-1_098076_2023-03-06_final
2023-03-09 10:37:49	ga_ls8c_ard_3-2-1_103077_2023-03-09_final
2023-03-10 11:19:53	ga_ls8c_ard_3-2-1_110074_2023-03-10_final
2023-03-10 11:23:04	ga_ls8c_ard_3-2-1_110082_2023-03-10_final
2023-03-10 11:24:16	ga_ls8c_ard_3-2-1_110085_2023-03-10_final
2023-03-11 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-03-11_final
2023-03-11 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-03-11_final
2023-03-15 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-03-15_final
2023-03-15 10:03:31	ga_ls8c_ard_3-2-1_097084_2023-03-15_final
2023-03-15 11:40:48	ga_ls8c_ard_3-2-1_113080_2023-03-15_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