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
2022-05-30 10:57:08	ga_ls8c_ard_3-2-1_106079_2022-05-30_final
2022-05-31 10:03:08	ga_ls8c_ard_3-2-1_097083_2022-05-31_final
2022-06-03 10:32:29	ga_ls8c_ard_3-2-1_102079_2022-06-03_final
2022-06-05 10:18:33	ga_ls8c_ard_3-2-1_100075_2022-06-05_final
2022-06-07 10:04:37	ga_ls8c_ard_3-2-1_098071_2022-06-07_final
2022-06-08 09:12:36	ga_ls8c_ard_3-2-1_089080_2022-06-07_final
2022-06-13 09:29:37	ga_ls8c_ard_3-2-1_092076_2022-06-12_final
2022-06-16 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-06-16_final
2022-06-20 09:34:15	ga_ls8c_ard_3-2-1_093072_2022-06-20_final
2022-06-21 10:21:54	ga_ls8c_ard_3-2-1_100083_2022-06-21_final
2022-06-22 10:59:59	ga_ls8c_ard_3-2-1_107070_2022-06-22_final
2022-06-22 11:05:11	ga_ls8c_ard_3-2-1_107083_2022-06-22_final
2022-06-25 09:57:36	ga_ls8c_ard_3-2-1_096084_2022-06-25_final
2022-06-27 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-06-27_final
2022-07-02 10:03:48	ga_ls8c_ard_3-2-1_097084_2022-07-02_final
2022-07-07 10:21:56	ga_ls8c_ard_3-2-1_100083_2022-07-07_final
2022-07-09 10:04:23	ga_ls8c_ard_3-2-1_098070_2022-07-09_final
2022-07-09 10:07:59	ga_ls8c_ard_3-2-1_098079_2022-07-09_final
2022-07-13 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-07-13_final
2022-07-15 11:11:45	ga_ls8c_ard_3-2-1_108084_2022-07-15_final
2022-07-16 10:09:45	ga_ls8c_ard_3-2-1_099068_2022-07-16_final
2022-07-16 11:52:13	ga_ls8c_ard_3-2-1_115077_2022-07-16_final
2022-07-17 09:20:32	ga_ls8c_ard_3-2-1_090084_2022-07-16_final
2022-07-27 09:52:09	ga_ls8c_ard_3-2-1_096070_2022-07-27_final
2022-08-01 10:09:33	ga_ls8c_ard_3-2-1_099067_2022-08-01_final
2022-08-02 10:53:37	ga_ls8c_ard_3-2-1_106069_2022-08-02_final
2022-08-02 10:54:01	ga_ls8c_ard_3-2-1_106070_2022-08-02_final
2022-08-06 10:29:44	ga_ls8c_ard_3-2-1_102071_2022-08-06_final
2022-08-09 11:00:15	ga_ls8c_ard_3-2-1_107070_2022-08-09_final
2022-08-10 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-08-10_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-17 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-08-17_final
2022-08-25 11:01:54	ga_ls8c_ard_3-2-1_107074_2022-08-25_final
2022-08-28 11:36:48	ga_ls8c_ard_3-2-1_112084_2022-08-28_final
2022-09-02 10:14:50	ga_ls8c_ard_3-2-1_099080_2022-09-02_final
2022-09-06 09:52:57	ga_ls8c_ard_3-2-1_095087_2022-09-06_final
2022-09-07 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-09-07_final
2022-09-19 10:54:38	ga_ls8c_ard_3-2-1_106071_2022-09-19_final
2022-09-22 09:47:27	ga_ls8c_ard_3-2-1_095073_2022-09-22_final
2022-09-27 10:08:23	ga_ls8c_ard_3-2-1_098079_2022-09-27_final
2022-09-29 11:36:54	ga_ls8c_ard_3-2-1_112084_2022-09-29_final
2022-10-01 09:46:51	ga_ls8c_ard_3-2-1_094087_2022-10-01_final
2022-10-01 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-10-01_final
2022-10-05 10:55:24	ga_ls8c_ard_3-2-1_106073_2022-10-05_final
2022-10-08 09:52:34	ga_ls8c_ard_3-2-1_095086_2022-10-08_final
2022-10-12 11:01:05	ga_ls8c_ard_3-2-1_107072_2022-10-12_final
2022-10-13 11:45:07	ga_ls8c_ard_3-2-1_114074_2022-10-13_final
2022-10-14 10:48:18	ga_ls8c_ard_3-2-1_105071_2022-10-14_final
2022-10-15 09:52:42	ga_ls8c_ard_3-2-1_096071_2022-10-15_final
2022-10-15 11:36:22	ga_ls8c_ard_3-2-1_112083_2022-10-15_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-17 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-10-17_final
2022-10-17 11:23:14	ga_ls8c_ard_3-2-1_110081_2022-10-17_final
2022-10-28 11:01:12	ga_ls8c_ard_3-2-1_107072_2022-10-28_final
2022-11-12 10:19:29	ga_ls8c_ard_3-2-1_100076_2022-11-12_final
2022-11-13 11:02:20	ga_ls8c_ard_3-2-1_107075_2022-11-13_final
2022-11-18 09:45:07	ga_ls8c_ard_3-2-1_094083_2022-11-18_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-25 11:27:02	ga_ls8c_ard_3-2-1_111075_2022-11-25_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-06 09:30:01	ga_ls8c_ard_3-2-1_092076_2022-12-06_final
2022-12-08 09:18:27	ga_ls8c_ard_3-2-1_090078_2022-12-07_final
2022-12-09 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-12-09_final
2022-12-15 09:24:34	ga_ls8c_ard_3-2-1_091078_2022-12-14_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-25 11:39:38	ga_ls8c_ard_3-2-1_113076_2022-12-25_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2022-12-31 09:24:06	ga_ls8c_ard_3-2-1_091077_2022-12-30_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-10 09:59:57	ga_ls8c_ard_3-2-1_097074_2023-01-10_final
2023-01-10 10:03:08	ga_ls8c_ard_3-2-1_097082_2023-01-10_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-21 09:46:32	ga_ls8c_ard_3-2-1_094087_2023-01-21_final
2023-01-31 10:22:05	ga_ls8c_ard_3-2-1_100083_2023-01-31_final
2023-02-10 09:18:14	ga_ls8c_ard_3-2-1_090078_2023-02-09_final
2023-02-17 11:00:24	ga_ls8c_ard_3-2-1_107071_2023-02-17_final
2023-02-17 11:01:36	ga_ls8c_ard_3-2-1_107074_2023-02-17_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-02-24 09:33:55	ga_ls8c_ard_3-2-1_092087_2023-02-24_final
2023-02-26 10:56:02	ga_ls8c_ard_3-2-1_106076_2023-02-26_final
2023-02-26 10:58:50	ga_ls8c_ard_3-2-1_106083_2023-02-26_final
2023-02-27 10:01:37	ga_ls8c_ard_3-2-1_097079_2023-02-27_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-05 09:26:54	ga_ls8c_ard_3-2-1_091085_2023-03-04_final
2023-03-07 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-03-07_final
2023-03-09 10:36:13	ga_ls8c_ard_3-2-1_103073_2023-03-09_final
2023-03-12 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-03-11_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-23 09:12:22	ga_ls8c_ard_3-2-1_089080_2023-03-22_final
2023-03-30 10:54:59	ga_ls8c_ard_3-2-1_106074_2023-03-30_final
2023-04-02 09:46:10	ga_ls8c_ard_3-2-1_095072_2023-04-02_final
2023-04-06 09:21:46	ga_ls8c_ard_3-2-1_091073_2023-04-05_final
2023-04-06 11:01:03	ga_ls8c_ard_3-2-1_107074_2023-04-06_final
2023-04-11 11:19:52	ga_ls8c_ard_3-2-1_110075_2023-04-11_final
2023-04-13 09:34:12	ga_ls8c_ard_3-2-1_092089_2023-04-13_final
2023-04-19 10:27:35	ga_ls8c_ard_3-2-1_102068_2023-04-19_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