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
2019-03-10 09:28:06	ga_ls8c_ard_3-1-0_091089_2019-03-09_final
2019-07-28 09:51:37	ga_ls8c_ard_3-1-0_095085_2019-07-28_final
2019-08-01 09:23:44	ga_ls8c_ard_3-1-0_091077_2019-07-31_final
2019-08-29 09:46:36	ga_ls8c_ard_3-1-0_095072_2019-08-29_final
2019-10-16 09:46:00	ga_ls8c_ard_3-1-0_095070_2019-10-16_final
2019-11-21 09:27:59	ga_ls8c_ard_3-1-0_091087_2019-11-20_final
2019-12-03 09:48:43	ga_ls8c_ard_3-1-0_095077_2019-12-03_final
2020-01-08 09:25:04	ga_ls8c_ard_3-1-0_091080_2020-01-07_final
2020-01-24 09:27:48	ga_ls8c_ard_3-1-0_091087_2020-01-23_final
2020-02-09 09:24:56	ga_ls8c_ard_3-1-0_091080_2020-02-08_final
2020-02-21 09:48:00	ga_ls8c_ard_3-1-0_095076_2020-02-21_final
2020-03-08 09:48:19	ga_ls8c_ard_3-1-0_095077_2020-03-08_final
2020-03-08 09:49:31	ga_ls8c_ard_3-1-0_095080_2020-03-08_final
2020-03-08 09:51:54	ga_ls8c_ard_3-1-0_095086_2020-03-08_final
2020-04-09 09:48:02	ga_ls8c_ard_3-1-0_095077_2020-04-09_final
2020-04-25 09:45:08	ga_ls8c_ard_3-1-0_095070_2020-04-25_final
2022-03-29 10:41:46	ga_ls8c_ard_3-2-1_104072_2022-03-29_final
2022-03-29 10:42:58	ga_ls8c_ard_3-2-1_104075_2022-03-29_final
2022-03-30 09:47:20	ga_ls8c_ard_3-2-1_095075_2022-03-30_final
2022-03-31 10:29:24	ga_ls8c_ard_3-2-1_102072_2022-03-31_final
2022-03-31 10:32:12	ga_ls8c_ard_3-2-1_102079_2022-03-31_final
2022-04-01 09:33:47	ga_ls8c_ard_3-2-1_093072_2022-04-01_final
2022-04-01 09:34:35	ga_ls8c_ard_3-2-1_093074_2022-04-01_final
2022-04-01 11:12:40	ga_ls8c_ard_3-2-1_109072_2022-04-01_final
2022-04-04 10:06:41	ga_ls8c_ard_3-2-1_098077_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-05 10:47:10	ga_ls8c_ard_3-2-1_105070_2022-04-05_final
2022-04-06 11:31:38	ga_ls8c_ard_3-2-1_112073_2022-04-06_final
2022-04-09 10:24:53	ga_ls8c_ard_3-2-1_101076_2022-04-09_final
2022-04-09 10:25:41	ga_ls8c_ard_3-2-1_101078_2022-04-09_final
2022-04-10 11:06:09	ga_ls8c_ard_3-2-1_108071_2022-04-10_final
2022-04-12 09:20:07	ga_ls8c_ard_3-2-1_090084_2022-04-11_final
2022-04-13 10:01:23	ga_ls8c_ard_3-2-1_097079_2022-04-13_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-15 11:23:56	ga_ls8c_ard_3-2-1_111069_2022-04-15_final
2022-04-16 10:29:06	ga_ls8c_ard_3-2-1_102071_2022-04-16_final
2022-04-16 10:31:54	ga_ls8c_ard_3-2-1_102078_2022-04-16_final
2022-04-16 10:32:18	ga_ls8c_ard_3-2-1_102079_2022-04-16_final
2022-04-17 09:34:41	ga_ls8c_ard_3-2-1_093074_2022-04-17_final
2022-04-18 10:16:44	ga_ls8c_ard_3-2-1_100071_2022-04-18_final
2022-04-19 09:24:18	ga_ls8c_ard_3-2-1_091079_2022-04-18_final
2022-04-20 10:04:46	ga_ls8c_ard_3-2-1_098072_2022-04-20_final
2022-04-20 10:05:34	ga_ls8c_ard_3-2-1_098074_2022-04-20_final
2022-04-20 11:46:27	ga_ls8c_ard_3-2-1_114079_2022-04-20_final
2022-04-21 09:11:32	ga_ls8c_ard_3-2-1_089078_2022-04-20_final
2022-04-21 09:14:20	ga_ls8c_ard_3-2-1_089085_2022-04-20_final
2022-04-24 11:18:06	ga_ls8c_ard_3-2-1_110070_2022-04-24_final
2022-04-24 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-24_final
2022-04-25 10:26:28	ga_ls8c_ard_3-2-1_101080_2022-04-25_final
2022-04-28 09:18:27	ga_ls8c_ard_3-2-1_090080_2022-04-27_final
2022-04-28 09:19:15	ga_ls8c_ard_3-2-1_090082_2022-04-27_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-28 10:53:21	ga_ls8c_ard_3-2-1_106070_2022-04-28_final
2022-04-29 11:39:48	ga_ls8c_ard_3-2-1_113078_2022-04-29_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-02 10:33:27	ga_ls8c_ard_3-2-1_102082_2022-05-02_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-05 09:25:31	ga_ls8c_ard_3-2-1_091082_2022-05-04_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-05 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-05-05_final
2022-05-06 10:05:12	ga_ls8c_ard_3-2-1_098073_2022-05-06_final
2022-05-07 10:46:28	ga_ls8c_ard_3-2-1_105068_2022-05-07_final
2022-05-07 10:47:40	ga_ls8c_ard_3-2-1_105071_2022-05-07_final
2022-05-08 09:56:03	ga_ls8c_ard_3-2-1_096081_2022-05-08_final
2022-05-08 11:32:08	ga_ls8c_ard_3-2-1_112074_2022-05-08_final
2022-05-12 09:33:21	ga_ls8c_ard_3-2-1_092086_2022-05-12_final
2022-05-14 09:19:25	ga_ls8c_ard_3-2-1_090082_2022-05-13_final
2022-05-15 09:59:29	ga_ls8c_ard_3-2-1_097074_2022-05-15_final
2022-05-15 10:03:05	ga_ls8c_ard_3-2-1_097083_2022-05-15_final
2022-05-15 11:40:46	ga_ls8c_ard_3-2-1_113080_2022-05-15_final
2022-05-17 09:47:08	ga_ls8c_ard_3-2-1_095074_2022-05-17_final
2022-05-17 09:47:32	ga_ls8c_ard_3-2-1_095075_2022-05-17_final
2022-05-19 09:38:23	ga_ls8c_ard_3-2-1_093083_2022-05-19_final
2022-05-24 09:53:19	ga_ls8c_ard_3-2-1_096074_2022-05-24_final
2022-05-24 11:35:00	ga_ls8c_ard_3-2-1_112081_2022-05-24_final
2022-05-25 10:35:47	ga_ls8c_ard_3-2-1_103072_2022-05-25_final
2022-05-26 09:43:21	ga_ls8c_ard_3-2-1_094080_2022-05-26_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
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-06 09:28:32	ga_ls8c_ard_3-2-1_091089_2022-06-05_final
2022-06-07 10:05:25	ga_ls8c_ard_3-2-1_098073_2022-06-07_final
2022-06-07 10:06:37	ga_ls8c_ard_3-2-1_098076_2022-06-07_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-07 11:46:42	ga_ls8c_ard_3-2-1_114079_2022-06-07_final
2022-06-13 09:30:00	ga_ls8c_ard_3-2-1_092077_2022-06-13_final
2022-06-15 10:54:09	ga_ls8c_ard_3-2-1_106071_2022-06-15_final
2022-06-15 10:54:33	ga_ls8c_ard_3-2-1_106072_2022-06-15_final
2022-06-16 09:59:21	ga_ls8c_ard_3-2-1_097073_2022-06-16_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
2022-06-19 10:31:52	ga_ls8c_ard_3-2-1_102077_2022-06-19_final
2022-06-20 11:11:56	ga_ls8c_ard_3-2-1_109069_2022-06-20_final
2022-06-21 10:17:55	ga_ls8c_ard_3-2-1_100073_2022-06-21_final
2022-06-21 10:18:43	ga_ls8c_ard_3-2-1_100075_2022-06-21_final
2022-06-22 09:23:54	ga_ls8c_ard_3-2-1_091077_2022-06-21_final
2022-06-22 09:25:30	ga_ls8c_ard_3-2-1_091081_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