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
2015-12-14 10:51:07	ga_ls8c_ard_3-1-0_105079_2015-12-14_final
2019-03-10 09:26:54	ga_ls8c_ard_3-1-0_091086_2019-03-09_final
2019-03-28 10:48:34	ga_ls8c_ard_3-1-0_105074_2019-03-28_final
2019-03-29 09:56:32	ga_ls8c_ard_3-1-0_096083_2019-03-29_final
2019-04-07 09:49:54	ga_ls8c_ard_3-1-0_095082_2019-04-07_final
2019-06-14 09:21:30	ga_ls8c_ard_3-1-0_091072_2019-06-13_final
2019-06-14 09:23:54	ga_ls8c_ard_3-1-0_091078_2019-06-13_final
2019-07-02 10:46:07	ga_ls8c_ard_3-1-0_105067_2019-07-02_final
2019-07-28 09:51:13	ga_ls8c_ard_3-1-0_095084_2019-07-28_final
2019-08-03 10:47:04	ga_ls8c_ard_3-1-0_105069_2019-08-03_final
2019-08-29 09:51:47	ga_ls8c_ard_3-1-0_095085_2019-08-29_final
2019-09-02 09:28:16	ga_ls8c_ard_3-1-0_091088_2019-09-01_final
2019-09-20 10:46:31	ga_ls8c_ard_3-1-0_105067_2019-09-20_final
2019-09-20 10:50:30	ga_ls8c_ard_3-1-0_105077_2019-09-20_final
2019-09-25 11:08:40	ga_ls8c_ard_3-1-0_108076_2019-09-25_final
2019-10-11 11:08:44	ga_ls8c_ard_3-1-0_108076_2019-10-11_final
2019-10-16 11:27:17	ga_ls8c_ard_3-1-0_111076_2019-10-16_final
2019-10-20 09:25:40	ga_ls8c_ard_3-1-0_091081_2019-10-19_final
2019-10-22 10:50:12	ga_ls8c_ard_3-1-0_105076_2019-10-22_final
2019-11-12 11:08:42	ga_ls8c_ard_3-1-0_108076_2019-11-12_final
2019-11-12 11:09:30	ga_ls8c_ard_3-1-0_108078_2019-11-12_final
2019-11-17 09:47:56	ga_ls8c_ard_3-1-0_095075_2019-11-17_final
2019-12-03 09:48:43	ga_ls8c_ard_3-1-0_095077_2019-12-03_final
2019-12-03 09:50:19	ga_ls8c_ard_3-1-0_095081_2019-12-03_final
2019-12-03 11:27:12	ga_ls8c_ard_3-1-0_111076_2019-12-03_final
2019-12-09 10:50:31	ga_ls8c_ard_3-1-0_105077_2019-12-09_final
2019-12-30 11:11:46	ga_ls8c_ard_3-1-0_108084_2019-12-30_final
2020-01-08 09:20:17	ga_ls8c_ard_3-1-0_091068_2020-01-07_final
2020-01-10 10:50:00	ga_ls8c_ard_3-1-0_105076_2020-01-10_final
2020-01-15 11:08:31	ga_ls8c_ard_3-1-0_108076_2020-01-15_final
2020-02-05 09:50:27	ga_ls8c_ard_3-1-0_095082_2020-02-05_final
2020-02-16 11:09:58	ga_ls8c_ard_3-1-0_108080_2020-02-16_final
2020-03-03 11:05:54	ga_ls8c_ard_3-1-0_108070_2020-03-03_final
2020-03-03 11:06:18	ga_ls8c_ard_3-1-0_108071_2020-03-03_final
2020-03-03 11:10:17	ga_ls8c_ard_3-1-0_108081_2020-03-03_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-03-24 09:48:11	ga_ls8c_ard_3-1-0_095077_2020-03-24_final
2020-03-31 09:56:41	ga_ls8c_ard_3-1-0_096083_2020-03-31_final
2020-04-04 11:06:01	ga_ls8c_ard_3-1-0_108071_2020-04-04_final
2020-05-01 10:45:41	ga_ls8c_ard_3-1-0_105067_2020-05-01_final
2020-05-01 10:46:04	ga_ls8c_ard_3-1-0_105068_2020-05-01_final
2022-04-01 09:35:46	ga_ls8c_ard_3-2-1_093077_2022-04-01_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-05 10:47:58	ga_ls8c_ard_3-2-1_105072_2022-04-05_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-09 10:23:17	ga_ls8c_ard_3-2-1_101072_2022-04-09_final
2022-04-11 11:52:13	ga_ls8c_ard_3-2-1_115078_2022-04-11_final
2022-04-12 09:21:43	ga_ls8c_ard_3-2-1_090088_2022-04-11_final
2022-04-12 10:53:01	ga_ls8c_ard_3-2-1_106069_2022-04-12_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-15 09:47:50	ga_ls8c_ard_3-2-1_095076_2022-04-15_final
2022-04-16 10:29:54	ga_ls8c_ard_3-2-1_102073_2022-04-16_final
2022-04-16 10:31:30	ga_ls8c_ard_3-2-1_102077_2022-04-16_final
2022-04-16 10:31:54	ga_ls8c_ard_3-2-1_102078_2022-04-16_final
2022-04-17 09:35:52	ga_ls8c_ard_3-2-1_093077_2022-04-17_final
2022-04-17 11:12:46	ga_ls8c_ard_3-2-1_109072_2022-04-17_final
2022-04-18 10:16:44	ga_ls8c_ard_3-2-1_100071_2022-04-18_final
2022-04-20 10:05:34	ga_ls8c_ard_3-2-1_098074_2022-04-20_final
2022-04-20 10:07:58	ga_ls8c_ard_3-2-1_098080_2022-04-20_final
2022-04-22 11:32:05	ga_ls8c_ard_3-2-1_112074_2022-04-22_final
2022-04-22 11:36:04	ga_ls8c_ard_3-2-1_112084_2022-04-22_final
2022-04-23 10:35:15	ga_ls8c_ard_3-2-1_103071_2022-04-23_final
2022-04-23 10:36:03	ga_ls8c_ard_3-2-1_103073_2022-04-23_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-24_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-27 10:10:54	ga_ls8c_ard_3-2-1_099072_2022-04-27_final
2022-04-29 09:59:19	ga_ls8c_ard_3-2-1_097074_2022-04-29_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-04-30 10:42:36	ga_ls8c_ard_3-2-1_104074_2022-04-30_final
2022-05-04 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-05-04_final
2022-05-07 10:48:04	ga_ls8c_ard_3-2-1_105072_2022-05-07_final
2022-05-08 09:56:03	ga_ls8c_ard_3-2-1_096081_2022-05-08_final
2022-05-10 11:24:11	ga_ls8c_ard_3-2-1_110085_2022-05-10_final
2022-05-13 10:13:50	ga_ls8c_ard_3-2-1_099079_2022-05-13_final
2022-05-14 10:54:18	ga_ls8c_ard_3-2-1_106072_2022-05-14_final
2022-05-15 10:02:17	ga_ls8c_ard_3-2-1_097081_2022-05-15_final
2022-05-15 10:03:05	ga_ls8c_ard_3-2-1_097083_2022-05-15_final
2022-05-15 11:39:58	ga_ls8c_ard_3-2-1_113078_2022-05-15_final
2022-05-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-05-17_final
2022-05-19 11:16:52	ga_ls8c_ard_3-2-1_109082_2022-05-19_final
2022-05-20 10:18:27	ga_ls8c_ard_3-2-1_100075_2022-05-20_final
2022-05-26 11:18:38	ga_ls8c_ard_3-2-1_110071_2022-05-26_final
2022-05-31 09:59:08	ga_ls8c_ard_3-2-1_097073_2022-05-31_final
2022-05-31 10:02:44	ga_ls8c_ard_3-2-1_097082_2022-05-31_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-02 11:24:54	ga_ls8c_ard_3-2-1_111071_2022-06-02_final
2022-06-02 11:28:53	ga_ls8c_ard_3-2-1_111081_2022-06-02_final
2022-06-03 10:32:53	ga_ls8c_ard_3-2-1_102080_2022-06-03_final
2022-06-07 10:06:13	ga_ls8c_ard_3-2-1_098075_2022-06-07_final
2022-06-08 10:47:30	ga_ls8c_ard_3-2-1_105070_2022-06-08_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-15 10:54:09	ga_ls8c_ard_3-2-1_106071_2022-06-15_final
2022-06-16 11:39:02	ga_ls8c_ard_3-2-1_113075_2022-06-16_final
2022-06-16 11:40:13	ga_ls8c_ard_3-2-1_113078_2022-06-16_final
2022-06-17 10:41:25	ga_ls8c_ard_3-2-1_104070_2022-06-17_final
2022-06-19 10:31:52	ga_ls8c_ard_3-2-1_102077_2022-06-19_final
2022-06-20 11:13:32	ga_ls8c_ard_3-2-1_109073_2022-06-20_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