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
2019-06-26 09:48:17	ga_ls8c_ard_3-1-0_095077_2019-06-26_final
2019-07-12 09:47:08	ga_ls8c_ard_3-1-0_095074_2019-07-12_final
2019-07-28 09:48:01	ga_ls8c_ard_3-1-0_095076_2019-07-28_final
2019-07-28 09:48:25	ga_ls8c_ard_3-1-0_095077_2019-07-28_final
2019-08-29 09:47:00	ga_ls8c_ard_3-1-0_095073_2019-08-29_final
2019-08-29 09:50:35	ga_ls8c_ard_3-1-0_095082_2019-08-29_final
2020-01-04 09:50:36	ga_ls8c_ard_3-1-0_095082_2020-01-04_final
2020-03-08 09:47:55	ga_ls8c_ard_3-1-0_095076_2020-03-08_final
2022-03-30 11:26:37	ga_ls8c_ard_3-2-1_111076_2022-03-30_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-02 10:19:26	ga_ls8c_ard_3-2-1_100078_2022-04-02_final
2022-04-03 10:59:54	ga_ls8c_ard_3-2-1_107071_2022-04-03_final
2022-04-04 10:04:42	ga_ls8c_ard_3-2-1_098072_2022-04-04_final
2022-04-05 10:49:34	ga_ls8c_ard_3-2-1_105076_2022-04-05_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-06 11:35:14	ga_ls8c_ard_3-2-1_112082_2022-04-06_final
2022-04-07 10:37:13	ga_ls8c_ard_3-2-1_103076_2022-04-07_final
2022-04-08 11:23:17	ga_ls8c_ard_3-2-1_110083_2022-04-08_final
2022-04-10 11:09:45	ga_ls8c_ard_3-2-1_108080_2022-04-10_final
2022-04-11 10:12:08	ga_ls8c_ard_3-2-1_099075_2022-04-11_final
2022-04-11 10:15:20	ga_ls8c_ard_3-2-1_099083_2022-04-11_final
2022-04-12 10:54:13	ga_ls8c_ard_3-2-1_106072_2022-04-12_final
2022-04-12 10:55:24	ga_ls8c_ard_3-2-1_106075_2022-04-12_final
2022-04-13 10:00:35	ga_ls8c_ard_3-2-1_097077_2022-04-13_final
2022-04-14 10:41:52	ga_ls8c_ard_3-2-1_104072_2022-04-14_final
2022-04-14 10:43:27	ga_ls8c_ard_3-2-1_104076_2022-04-14_final
2022-04-16 10:29:30	ga_ls8c_ard_3-2-1_102072_2022-04-16_final
2022-04-17 09:35:28	ga_ls8c_ard_3-2-1_093076_2022-04-17_final
2022-04-17 11:12:46	ga_ls8c_ard_3-2-1_109072_2022-04-17_final
2022-04-19 09:25:06	ga_ls8c_ard_3-2-1_091081_2022-04-18_final
2022-04-19 09:25:54	ga_ls8c_ard_3-2-1_091083_2022-04-18_final
2022-04-19 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-04-18_final
2022-04-19 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-04-19_final
2022-04-19 11:01:35	ga_ls8c_ard_3-2-1_107075_2022-04-19_final
2022-04-20 10:05:58	ga_ls8c_ard_3-2-1_098075_2022-04-20_final
2022-04-21 10:48:25	ga_ls8c_ard_3-2-1_105073_2022-04-21_final
2022-04-22 11:35:16	ga_ls8c_ard_3-2-1_112082_2022-04-22_final
2022-04-23 10:34:51	ga_ls8c_ard_3-2-1_103070_2022-04-23_final
2022-04-23 10:37:15	ga_ls8c_ard_3-2-1_103076_2022-04-23_final
2022-04-24 09:44:25	ga_ls8c_ard_3-2-1_094083_2022-04-24_final
2022-04-24 11:23:18	ga_ls8c_ard_3-2-1_110083_2022-04-24_final
2022-04-24 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-24_final
2022-04-26 09:32:26	ga_ls8c_ard_3-2-1_092084_2022-04-26_final
2022-04-26 11:06:31	ga_ls8c_ard_3-2-1_108072_2022-04-26_final
2022-04-28 10:58:08	ga_ls8c_ard_3-2-1_106082_2022-04-28_final
2022-04-29 11:41:24	ga_ls8c_ard_3-2-1_113082_2022-04-29_final
2022-04-30 10:42:59	ga_ls8c_ard_3-2-1_104075_2022-04-30_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-04-30 10:43:47	ga_ls8c_ard_3-2-1_104077_2022-04-30_final
2022-05-02 10:29:28	ga_ls8c_ard_3-2-1_102072_2022-05-02_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-05 09:23:55	ga_ls8c_ard_3-2-1_091078_2022-05-04_final
2022-05-07 10:47:16	ga_ls8c_ard_3-2-1_105070_2022-05-07_final
2022-05-07 10:52:03	ga_ls8c_ard_3-2-1_105082_2022-05-07_final
2022-05-08 09:57:15	ga_ls8c_ard_3-2-1_096084_2022-05-08_final
2022-05-09 10:35:20	ga_ls8c_ard_3-2-1_103071_2022-05-09_final
2022-05-10 09:44:54	ga_ls8c_ard_3-2-1_094084_2022-05-10_final
2022-05-11 10:24:35	ga_ls8c_ard_3-2-1_101075_2022-05-11_final
2022-05-13 10:14:14	ga_ls8c_ard_3-2-1_099080_2022-05-13_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-14 09:17:25	ga_ls8c_ard_3-2-1_090077_2022-05-13_final
2022-05-14 10:54:18	ga_ls8c_ard_3-2-1_106072_2022-05-14_final
2022-05-16 10:40:22	ga_ls8c_ard_3-2-1_104068_2022-05-16_final
2022-05-16 10:40:46	ga_ls8c_ard_3-2-1_104069_2022-05-16_final
2022-05-16 10:41:34	ga_ls8c_ard_3-2-1_104071_2022-05-16_final
2022-05-16 10:45:57	ga_ls8c_ard_3-2-1_104082_2022-05-16_final
2022-05-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-05-17_final
2022-05-18 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-05-18_final
2022-05-18 10:31:12	ga_ls8c_ard_3-2-1_102076_2022-05-18_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-24 09:53:43	ga_ls8c_ard_3-2-1_096075_2022-05-24_final
2022-05-24 09:56:55	ga_ls8c_ard_3-2-1_096083_2022-05-24_final
2022-05-24 11:32:12	ga_ls8c_ard_3-2-1_112074_2022-05-24_final
2022-05-26 09:44:32	ga_ls8c_ard_3-2-1_094083_2022-05-26_final
2022-05-26 11:21:26	ga_ls8c_ard_3-2-1_110078_2022-05-26_final
2022-05-26 11:22:14	ga_ls8c_ard_3-2-1_110080_2022-05-26_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-05-30 10:54:21	ga_ls8c_ard_3-2-1_106072_2022-05-30_final
2022-05-30 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-05-30_final
2022-05-30 10:56:44	ga_ls8c_ard_3-2-1_106078_2022-05-30_final
2022-05-31 10:01:56	ga_ls8c_ard_3-2-1_097080_2022-05-31_final
2022-06-02 09:47:12	ga_ls8c_ard_3-2-1_095074_2022-06-02_final
2022-06-02 11:24:54	ga_ls8c_ard_3-2-1_111071_2022-06-02_final
2022-06-03 10:32:29	ga_ls8c_ard_3-2-1_102079_2022-06-03_final
2022-06-04 09:39:40	ga_ls8c_ard_3-2-1_093086_2022-06-04_final
2022-06-05 10:18:09	ga_ls8c_ard_3-2-1_100074_2022-06-05_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-08 10:48:18	ga_ls8c_ard_3-2-1_105072_2022-06-08_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-16 10:03:44	ga_ls8c_ard_3-2-1_097084_2022-06-16_final
2022-06-16 11:39:25	ga_ls8c_ard_3-2-1_113076_2022-06-16_final
2022-06-16 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-06-16_final
2022-06-17 10:43:49	ga_ls8c_ard_3-2-1_104076_2022-06-17_final
2022-06-18 09:48:12	ga_ls8c_ard_3-2-1_095076_2022-06-18_final
2022-06-19 10:29:28	ga_ls8c_ard_3-2-1_102071_2022-06-19_final
2022-06-20 09:38:14	ga_ls8c_ard_3-2-1_093082_2022-06-20_final
2022-06-20 11:13:32	ga_ls8c_ard_3-2-1_109073_2022-06-20_final
2022-06-22 09:22:18	ga_ls8c_ard_3-2-1_091073_2022-06-21_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