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 10:52:33	ga_ls8c_ard_3-2-1_105082_2022-07-26_final
2022-07-29 09:45:24	ga_ls8c_ard_3-2-1_094084_2022-07-29_final
2022-08-01 10:14:44	ga_ls8c_ard_3-2-1_099080_2022-08-01_final
2022-08-03 11:42:05	ga_ls8c_ard_3-2-1_113082_2022-08-03_final
2022-08-07 11:15:24	ga_ls8c_ard_3-2-1_109077_2022-08-07_final
2022-08-15 10:23:36	ga_ls8c_ard_3-2-1_101071_2022-08-15_final
2022-08-19 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-08-19_final
2022-08-24 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-08-24_final
2022-08-24 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-08-24_final
2022-08-26 11:47:33	ga_ls8c_ard_3-2-1_114080_2022-08-26_final
2022-08-30 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-08-30_final
2022-08-31 10:26:01	ga_ls8c_ard_3-2-1_101077_2022-08-31_final
2022-09-01 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-09-01_final
2022-09-02 10:14:50	ga_ls8c_ard_3-2-1_099080_2022-09-02_final
2022-09-04 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-09-04_final
2022-09-08 09:36:13	ga_ls8c_ard_3-2-1_093076_2022-09-08_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-12 10:46:49	ga_ls8c_ard_3-2-1_105067_2022-09-12_final
2022-09-15 11:23:44	ga_ls8c_ard_3-2-1_110082_2022-09-15_final
2022-09-16 10:23:43	ga_ls8c_ard_3-2-1_101071_2022-09-16_final
2022-09-19 10:54:38	ga_ls8c_ard_3-2-1_106071_2022-09-19_final
2022-09-21 09:06:59	ga_ls8c_ard_3-2-1_088080_2022-09-20_final
2022-09-22 11:30:20	ga_ls8c_ard_3-2-1_111083_2022-09-22_final
2022-09-26 11:00:49	ga_ls8c_ard_3-2-1_107071_2022-09-26_final
2022-09-27 10:05:36	ga_ls8c_ard_3-2-1_098072_2022-09-27_final
2022-10-01 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-10-01_final
2022-10-01 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-10-01_final
2022-10-03 09:31:17	ga_ls8c_ard_3-2-1_092079_2022-10-03_final
2022-10-06 09:58:58	ga_ls8c_ard_3-2-1_097071_2022-10-06_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-12 11:03:05	ga_ls8c_ard_3-2-1_107077_2022-10-12_final
2022-10-12 11:05:52	ga_ls8c_ard_3-2-1_107084_2022-10-12_final
2022-10-13 10:05:27	ga_ls8c_ard_3-2-1_098072_2022-10-13_final
2022-10-13 11:45:07	ga_ls8c_ard_3-2-1_114074_2022-10-13_final
2022-10-14 09:15:00	ga_ls8c_ard_3-2-1_089085_2022-10-13_final
2022-10-15 09:52:18	ga_ls8c_ard_3-2-1_096070_2022-10-15_final
2022-10-17 11:19:39	ga_ls8c_ard_3-2-1_110072_2022-10-17_final
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-18 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-10-18_final
2022-10-20 10:16:29	ga_ls8c_ard_3-2-1_099084_2022-10-20_final
2022-10-25 10:29:29	ga_ls8c_ard_3-2-1_102070_2022-10-25_final
2022-10-26 09:35:52	ga_ls8c_ard_3-2-1_093075_2022-10-26_final
2022-10-28 09:26:42	ga_ls8c_ard_3-2-1_091083_2022-10-27_final
2022-10-31 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-10-31_final
2022-11-02 09:42:52	ga_ls8c_ard_3-2-1_094077_2022-11-02_final
2022-11-04 09:34:06	ga_ls8c_ard_3-2-1_092086_2022-11-04_final
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-11 09:37:50	ga_ls8c_ard_3-2-1_093080_2022-11-11_final
2022-11-14 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-14_final
2022-11-14 11:45:11	ga_ls8c_ard_3-2-1_114074_2022-11-14_final
2022-11-15 10:47:57	ga_ls8c_ard_3-2-1_105070_2022-11-15_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-29 11:05:31	ga_ls8c_ard_3-2-1_107083_2022-11-29_final
2022-12-01 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-30_final
2022-12-02 11:33:14	ga_ls8c_ard_3-2-1_112075_2022-12-02_final
2022-12-04 09:45:58	ga_ls8c_ard_3-2-1_094085_2022-12-04_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-08 10:55:44	ga_ls8c_ard_3-2-1_106074_2022-12-08_final
2022-12-09 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-12-09_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-20 09:45:50	ga_ls8c_ard_3-2-1_094085_2022-12-20_final
2022-12-26 10:44:25	ga_ls8c_ard_3-2-1_104077_2022-12-26_final
2022-12-26 10:44:49	ga_ls8c_ard_3-2-1_104078_2022-12-26_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2023-01-01 11:47:50	ga_ls8c_ard_3-2-1_114081_2023-01-01_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-02 09:15:20	ga_ls8c_ard_3-2-1_089086_2023-01-01_final
2023-01-07 09:33:03	ga_ls8c_ard_3-2-1_092084_2023-01-07_final
2023-01-09 09:21:53	ga_ls8c_ard_3-2-1_090087_2023-01-08_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-11 10:44:47	ga_ls8c_ard_3-2-1_104078_2023-01-11_final
2023-01-13 10:31:37	ga_ls8c_ard_3-2-1_102076_2023-01-13_final
2023-01-14 09:36:46	ga_ls8c_ard_3-2-1_093078_2023-01-14_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-17 10:03:14	ga_ls8c_ard_3-2-1_098067_2023-01-17_final
2023-01-19 11:34:09	ga_ls8c_ard_3-2-1_112078_2023-01-19_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-22 10:26:13	ga_ls8c_ard_3-2-1_101078_2023-01-22_final
2023-01-26 11:42:24	ga_ls8c_ard_3-2-1_113083_2023-01-26_final
2023-01-30 11:15:18	ga_ls8c_ard_3-2-1_109077_2023-01-30_final
2023-02-01 09:28:51	ga_ls8c_ard_3-2-1_091089_2023-01-31_final
2023-02-08 09:29:25	ga_ls8c_ard_3-2-1_092075_2023-02-07_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-11 09:59:29	ga_ls8c_ard_3-2-1_097073_2023-02-11_final
2023-02-13 09:47:29	ga_ls8c_ard_3-2-1_095074_2023-02-13_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-15 11:12:48	ga_ls8c_ard_3-2-1_109071_2023-02-15_final
2023-02-15 11:13:35	ga_ls8c_ard_3-2-1_109073_2023-02-15_final
2023-02-17 11:05:35	ga_ls8c_ard_3-2-1_107084_2023-02-17_final
2023-02-19 10:51:59	ga_ls8c_ard_3-2-1_105081_2023-02-19_final
2023-02-20 09:58:21	ga_ls8c_ard_3-2-1_096086_2023-02-20_final
2023-02-25 11:53:15	ga_ls8c_ard_3-2-1_115080_2023-02-25_final
2023-02-27 11:40:54	ga_ls8c_ard_3-2-1_113080_2023-02-27_final
2023-03-01 09:50:27	ga_ls8c_ard_3-2-1_095082_2023-03-01_final
2023-03-01 11:30:08	ga_ls8c_ard_3-2-1_111084_2023-03-01_final
2023-03-06 10:10:09	ga_ls8c_ard_3-2-1_098085_2023-03-06_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