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
2022-03-30 09:50:08	ga_ls8c_ard_3-2-1_095082_2022-03-30_final
2022-03-31 10:29:24	ga_ls8c_ard_3-2-1_102072_2022-03-31_final
2022-03-31 10:30:36	ga_ls8c_ard_3-2-1_102075_2022-03-31_final
2022-04-01 09:33:23	ga_ls8c_ard_3-2-1_093071_2022-04-01_final
2022-04-01 09:37:46	ga_ls8c_ard_3-2-1_093082_2022-04-01_final
2022-04-03 09:21:49	ga_ls8c_ard_3-2-1_091073_2022-04-02_final
2022-04-03 09:25:00	ga_ls8c_ard_3-2-1_091081_2022-04-02_final
2022-04-03 09:25:24	ga_ls8c_ard_3-2-1_091082_2022-04-02_final
2022-04-03 09:25:48	ga_ls8c_ard_3-2-1_091083_2022-04-02_final
2022-04-03 10:59:54	ga_ls8c_ard_3-2-1_107071_2022-04-03_final
2022-04-03 11:00:18	ga_ls8c_ard_3-2-1_107072_2022-04-03_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-05 10:50:46	ga_ls8c_ard_3-2-1_105079_2022-04-05_final
2022-04-06 09:51:57	ga_ls8c_ard_3-2-1_096071_2022-04-06_final
2022-04-06 11:32:50	ga_ls8c_ard_3-2-1_112076_2022-04-06_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-07 10:35:38	ga_ls8c_ard_3-2-1_103072_2022-04-07_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-08 09:42:49	ga_ls8c_ard_3-2-1_094079_2022-04-08_final
2022-04-09 10:23:17	ga_ls8c_ard_3-2-1_101072_2022-04-09_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-11 11:51:01	ga_ls8c_ard_3-2-1_115075_2022-04-11_final
2022-04-12 10:54:13	ga_ls8c_ard_3-2-1_106072_2022-04-12_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-17 09:37:28	ga_ls8c_ard_3-2-1_093081_2022-04-17_final
2022-04-19 09:25:30	ga_ls8c_ard_3-2-1_091082_2022-04-18_final
2022-04-19 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-04-19_final
2022-04-22 09:57:11	ga_ls8c_ard_3-2-1_096084_2022-04-22_final
2022-04-23 10:38:50	ga_ls8c_ard_3-2-1_103080_2022-04-23_final
2022-04-24 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-24_final
2022-04-24 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-24_final
2022-04-26 09:34:26	ga_ls8c_ard_3-2-1_092089_2022-04-26_final
2022-04-28 09:17:15	ga_ls8c_ard_3-2-1_090077_2022-04-27_final
2022-04-28 10:56:32	ga_ls8c_ard_3-2-1_106078_2022-04-28_final
2022-04-28 10:57:20	ga_ls8c_ard_3-2-1_106080_2022-04-28_final
2022-04-29 09:57:19	ga_ls8c_ard_3-2-1_097069_2022-04-29_final
2022-04-29 10:00:07	ga_ls8c_ard_3-2-1_097076_2022-04-29_final
2022-04-29 10:03:18	ga_ls8c_ard_3-2-1_097084_2022-04-29_final
2022-05-02 10:29:28	ga_ls8c_ard_3-2-1_102072_2022-05-02_final
2022-05-03 09:34:39	ga_ls8c_ard_3-2-1_093074_2022-05-03_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-04 10:20:43	ga_ls8c_ard_3-2-1_100081_2022-05-04_final
2022-05-05 09:25:55	ga_ls8c_ard_3-2-1_091083_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-06 10:04:24	ga_ls8c_ard_3-2-1_098071_2022-05-06_final
2022-05-06 10:06:47	ga_ls8c_ard_3-2-1_098077_2022-05-06_final
2022-05-06 10:08:47	ga_ls8c_ard_3-2-1_098082_2022-05-06_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-07 10:47:40	ga_ls8c_ard_3-2-1_105071_2022-05-07_final
2022-05-07 10:48:04	ga_ls8c_ard_3-2-1_105072_2022-05-07_final
2022-05-08 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-05-08_final
2022-05-09 10:34:08	ga_ls8c_ard_3-2-1_103068_2022-05-09_final
2022-05-09 10:36:07	ga_ls8c_ard_3-2-1_103073_2022-05-09_final
2022-05-11 10:23:23	ga_ls8c_ard_3-2-1_101072_2022-05-11_final
2022-05-13 10:13:26	ga_ls8c_ard_3-2-1_099078_2022-05-13_final
2022-05-13 11:51:07	ga_ls8c_ard_3-2-1_115075_2022-05-13_final
2022-05-14 09:20:13	ga_ls8c_ard_3-2-1_090084_2022-05-13_final
2022-05-14 10:57:30	ga_ls8c_ard_3-2-1_106080_2022-05-14_final
2022-05-15 09:59:05	ga_ls8c_ard_3-2-1_097073_2022-05-15_final
2022-05-15 10:00:17	ga_ls8c_ard_3-2-1_097076_2022-05-15_final
2022-05-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2022-05-17_final
2022-05-17 09:51:32	ga_ls8c_ard_3-2-1_095085_2022-05-17_final
2022-05-18 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-05-18_final
2022-05-18 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-05-18_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-20 10:20:50	ga_ls8c_ard_3-2-1_100081_2022-05-20_final
2022-05-24 09:57:43	ga_ls8c_ard_3-2-1_096085_2022-05-24_final
2022-05-24 11:32:12	ga_ls8c_ard_3-2-1_112074_2022-05-24_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_2022-05-24_final
2022-05-25 10:35:47	ga_ls8c_ard_3-2-1_103072_2022-05-25_final
2022-05-30 10:56:20	ga_ls8c_ard_3-2-1_106077_2022-05-30_final
2022-05-31 10:00:20	ga_ls8c_ard_3-2-1_097076_2022-05-31_final
2022-05-31 10:01:32	ga_ls8c_ard_3-2-1_097079_2022-05-31_final
2022-05-31 11:41:37	ga_ls8c_ard_3-2-1_113082_2022-05-31_final
2022-06-02 09:46:25	ga_ls8c_ard_3-2-1_095072_2022-06-02_final
2022-06-02 11:24:54	ga_ls8c_ard_3-2-1_111071_2022-06-02_final
2022-06-04 11:16:09	ga_ls8c_ard_3-2-1_109080_2022-06-04_final
2022-06-04 11:16:57	ga_ls8c_ard_3-2-1_109082_2022-06-04_final
2022-06-05 10:22:09	ga_ls8c_ard_3-2-1_100084_2022-06-05_final
2022-06-07 10:07:25	ga_ls8c_ard_3-2-1_098078_2022-06-07_final
2022-06-13 09:31:36	ga_ls8c_ard_3-2-1_092081_2022-06-13_final
2022-06-13 11:08:06	ga_ls8c_ard_3-2-1_108075_2022-06-13_final
2022-06-13 11:10:53	ga_ls8c_ard_3-2-1_108082_2022-06-13_final
2022-06-15 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-06-15_final
2022-06-15 10:57:21	ga_ls8c_ard_3-2-1_106079_2022-06-15_final
2022-06-16 09:59:21	ga_ls8c_ard_3-2-1_097073_2022-06-16_final
2022-06-16 10:01:20	ga_ls8c_ard_3-2-1_097078_2022-06-16_final
2022-06-16 10:02:56	ga_ls8c_ard_3-2-1_097082_2022-06-16_final
2022-06-16 10:03:20	ga_ls8c_ard_3-2-1_097083_2022-06-16_final
2022-06-16 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-06-16_final
2022-06-18 09:49:47	ga_ls8c_ard_3-2-1_095080_2022-06-18_final
2022-06-18 09:50:59	ga_ls8c_ard_3-2-1_095083_2022-06-18_final
2022-06-19 10:30:16	ga_ls8c_ard_3-2-1_102073_2022-06-19_final
2022-06-20 09:39:50	ga_ls8c_ard_3-2-1_093086_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