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
2022-07-29 11:20:42	ga_ls8c_ard_3-2-1_110075_2022-07-29_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-08 10:21:47	ga_ls8c_ard_3-2-1_100082_2022-08-08_final
2022-08-21 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-08-21_final
2022-08-23 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-08-23_final
2022-08-24 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-08-24_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-08-27 09:13:27	ga_ls8c_ard_3-2-1_089081_2022-08-26_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-11 10:05:57	ga_ls8c_ard_3-2-1_098073_2022-09-11_final
2022-09-12 09:17:07	ga_ls8c_ard_3-2-1_089090_2022-09-11_final
2022-09-12 10:52:49	ga_ls8c_ard_3-2-1_105082_2022-09-12_final
2022-09-14 10:38:28	ga_ls8c_ard_3-2-1_103077_2022-09-14_final
2022-09-17 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-09-16_final
2022-09-18 10:11:46	ga_ls8c_ard_3-2-1_099072_2022-09-18_final
2022-09-19 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-09-18_final
2022-09-19 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-09-18_final
2022-09-20 09:59:25	ga_ls8c_ard_3-2-1_097072_2022-09-20_final
2022-09-20 09:59:49	ga_ls8c_ard_3-2-1_097073_2022-09-20_final
2022-09-23 10:32:19	ga_ls8c_ard_3-2-1_102077_2022-09-23_final
2022-09-23 10:32:43	ga_ls8c_ard_3-2-1_102078_2022-09-23_final
2022-09-24 11:15:58	ga_ls8c_ard_3-2-1_109078_2022-09-24_final
2022-09-28 09:13:34	ga_ls8c_ard_3-2-1_089081_2022-09-27_final
2022-09-28 10:48:03	ga_ls8c_ard_3-2-1_105070_2022-09-28_final
2022-09-29 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-09-29_final
2022-10-01 11:24:32	ga_ls8c_ard_3-2-1_110084_2022-10-01_final
2022-10-04 10:13:20	ga_ls8c_ard_3-2-1_099076_2022-10-04_final
2022-10-06 09:59:46	ga_ls8c_ard_3-2-1_097073_2022-10-06_final
2022-10-14 09:15:00	ga_ls8c_ard_3-2-1_089085_2022-10-13_final
2022-10-17 09:46:21	ga_ls8c_ard_3-2-1_094086_2022-10-17_final
2022-10-18 10:25:38	ga_ls8c_ard_3-2-1_101076_2022-10-18_final
2022-10-19 11:11:42	ga_ls8c_ard_3-2-1_108083_2022-10-19_final
2022-10-20 11:51:47	ga_ls8c_ard_3-2-1_115075_2022-10-20_final
2022-10-21 09:22:52	ga_ls8c_ard_3-2-1_090089_2022-10-20_final
2022-10-22 10:04:32	ga_ls8c_ard_3-2-1_097085_2022-10-22_final
2022-10-22 11:40:38	ga_ls8c_ard_3-2-1_113078_2022-10-22_final
2022-10-24 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-10-24_final
2022-10-26 09:37:51	ga_ls8c_ard_3-2-1_093080_2022-10-26_final
2022-10-29 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-10-29_final
2022-10-30 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-10-29_final
2022-11-04 11:06:12	ga_ls8c_ard_3-2-1_108069_2022-11-04_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-11 11:13:08	ga_ls8c_ard_3-2-1_109071_2022-11-11_final
2022-11-14 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-14_final
2022-11-14 11:47:11	ga_ls8c_ard_3-2-1_114079_2022-11-14_final
2022-11-16 09:53:31	ga_ls8c_ard_3-2-1_096073_2022-11-16_final
2022-11-18 09:45:07	ga_ls8c_ard_3-2-1_094083_2022-11-18_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-23 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-11-23_final
2022-11-23 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-11-23_final
2022-11-24 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-11-24_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-26 10:29:49	ga_ls8c_ard_3-2-1_102071_2022-11-26_final
2022-11-28 10:19:04	ga_ls8c_ard_3-2-1_100075_2022-11-28_final
2022-11-29 09:27:02	ga_ls8c_ard_3-2-1_091084_2022-11-28_final
2022-11-30 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-30_final
2022-12-05 10:25:38	ga_ls8c_ard_3-2-1_101076_2022-12-05_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-08 09:18:51	ga_ls8c_ard_3-2-1_090079_2022-12-07_final
2022-12-09 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-12-09_final
2022-12-11 11:30:12	ga_ls8c_ard_3-2-1_111083_2022-12-11_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-12 10:32:35	ga_ls8c_ard_3-2-1_102078_2022-12-12_final
2022-12-13 09:35:21	ga_ls8c_ard_3-2-1_093074_2022-12-13_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-16 11:47:06	ga_ls8c_ard_3-2-1_114079_2022-12-16_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-25 11:40:50	ga_ls8c_ard_3-2-1_113079_2022-12-25_final
2022-12-26 10:42:01	ga_ls8c_ard_3-2-1_104071_2022-12-26_final
2022-12-31 09:24:53	ga_ls8c_ard_3-2-1_091079_2022-12-30_final
2022-12-31 09:25:41	ga_ls8c_ard_3-2-1_091081_2022-12-30_final
2023-01-05 11:23:31	ga_ls8c_ard_3-2-1_110082_2023-01-05_final
2023-01-07 11:08:45	ga_ls8c_ard_3-2-1_108076_2023-01-07_final
2023-01-10 11:40:49	ga_ls8c_ard_3-2-1_113079_2023-01-10_final
2023-01-13 10:32:00	ga_ls8c_ard_3-2-1_102077_2023-01-13_final
2023-01-14 11:13:16	ga_ls8c_ard_3-2-1_109072_2023-01-14_final
2023-01-16 11:00:04	ga_ls8c_ard_3-2-1_107070_2023-01-16_final
2023-01-18 09:11:59	ga_ls8c_ard_3-2-1_089078_2023-01-17_final
2023-01-21 11:23:25	ga_ls8c_ard_3-2-1_110082_2023-01-21_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-29 10:31:38	ga_ls8c_ard_3-2-1_102076_2023-01-29_final
2023-02-05 10:38:13	ga_ls8c_ard_3-2-1_103077_2023-02-05_final
2023-02-10 09:18:38	ga_ls8c_ard_3-2-1_090079_2023-02-09_final
2023-02-10 10:57:07	ga_ls8c_ard_3-2-1_106078_2023-02-10_final
2023-02-11 11:41:57	ga_ls8c_ard_3-2-1_113082_2023-02-11_final
2023-02-12 10:43:07	ga_ls8c_ard_3-2-1_104074_2023-02-12_final
2023-02-14 10:32:20	ga_ls8c_ard_3-2-1_102078_2023-02-14_final
2023-02-15 09:35:54	ga_ls8c_ard_3-2-1_093076_2023-02-15_final
2023-02-15 11:13:12	ga_ls8c_ard_3-2-1_109072_2023-02-15_final
2023-02-16 10:18:45	ga_ls8c_ard_3-2-1_100075_2023-02-16_final
2023-02-17 09:27:30	ga_ls8c_ard_3-2-1_091086_2023-02-16_final
2023-02-19 10:48:00	ga_ls8c_ard_3-2-1_105071_2023-02-19_final
2023-02-25 11:51:39	ga_ls8c_ard_3-2-1_115076_2023-02-25_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-06 11:45:50	ga_ls8c_ard_3-2-1_114077_2023-03-06_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