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
2019-03-22 09:48:46	ga_ls8c_ard_3-1-0_095079_2019-03-22_final
2019-04-07 09:47:07	ga_ls8c_ard_3-1-0_095075_2019-04-07_final
2019-04-07 09:48:19	ga_ls8c_ard_3-1-0_095078_2019-04-07_final
2019-04-07 09:49:54	ga_ls8c_ard_3-1-0_095082_2019-04-07_final
2019-06-26 09:47:53	ga_ls8c_ard_3-1-0_095076_2019-06-26_final
2019-06-26 09:48:41	ga_ls8c_ard_3-1-0_095078_2019-06-26_final
2019-07-12 09:47:32	ga_ls8c_ard_3-1-0_095075_2019-07-12_final
2019-07-12 09:49:56	ga_ls8c_ard_3-1-0_095081_2019-07-12_final
2019-08-13 09:47:43	ga_ls8c_ard_3-1-0_095075_2019-08-13_final
2019-08-13 09:50:07	ga_ls8c_ard_3-1-0_095081_2019-08-13_final
2019-08-29 09:47:47	ga_ls8c_ard_3-1-0_095075_2019-08-29_final
2019-08-29 09:50:11	ga_ls8c_ard_3-1-0_095081_2019-08-29_final
2019-09-14 09:47:52	ga_ls8c_ard_3-1-0_095075_2019-09-14_final
2019-09-14 09:48:16	ga_ls8c_ard_3-1-0_095076_2019-09-14_final
2019-09-14 09:49:04	ga_ls8c_ard_3-1-0_095078_2019-09-14_final
2019-10-16 09:48:23	ga_ls8c_ard_3-1-0_095076_2019-10-16_final
2019-10-16 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-10-16_final
2019-10-16 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-10-16_final
2019-11-01 09:49:35	ga_ls8c_ard_3-1-0_095079_2019-11-01_final
2019-11-01 09:51:59	ga_ls8c_ard_3-1-0_095085_2019-11-01_final
2019-11-17 09:49:08	ga_ls8c_ard_3-1-0_095078_2019-11-17_final
2019-12-03 09:47:31	ga_ls8c_ard_3-1-0_095074_2019-12-03_final
2020-01-04 09:46:37	ga_ls8c_ard_3-1-0_095072_2020-01-04_final
2020-01-20 09:50:33	ga_ls8c_ard_3-1-0_095082_2020-01-20_final
2020-02-05 09:50:27	ga_ls8c_ard_3-1-0_095082_2020-02-05_final
2020-03-08 09:50:18	ga_ls8c_ard_3-1-0_095082_2020-03-08_final
2020-04-09 09:46:27	ga_ls8c_ard_3-1-0_095073_2020-04-09_final
2020-04-09 09:49:38	ga_ls8c_ard_3-1-0_095081_2020-04-09_final
2022-03-30 09:50:56	ga_ls8c_ard_3-2-1_095084_2022-03-30_final
2022-04-01 09:38:10	ga_ls8c_ard_3-2-1_093083_2022-04-01_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-06 09:55:33	ga_ls8c_ard_3-2-1_096080_2022-04-06_final
2022-04-06 09:56:21	ga_ls8c_ard_3-2-1_096082_2022-04-06_final
2022-04-06 11:32:02	ga_ls8c_ard_3-2-1_112074_2022-04-06_final
2022-04-06 11:32:26	ga_ls8c_ard_3-2-1_112075_2022-04-06_final
2022-04-07 10:38:01	ga_ls8c_ard_3-2-1_103078_2022-04-07_final
2022-04-07 10:39:37	ga_ls8c_ard_3-2-1_103082_2022-04-07_final
2022-04-08 09:41:37	ga_ls8c_ard_3-2-1_094076_2022-04-08_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-11 10:11:44	ga_ls8c_ard_3-2-1_099074_2022-04-11_final
2022-04-11 10:14:08	ga_ls8c_ard_3-2-1_099080_2022-04-11_final
2022-04-11 10:14:56	ga_ls8c_ard_3-2-1_099082_2022-04-11_final
2022-04-12 09:17:19	ga_ls8c_ard_3-2-1_090077_2022-04-11_final
2022-04-13 10:02:11	ga_ls8c_ard_3-2-1_097081_2022-04-13_final
2022-04-14 10:44:15	ga_ls8c_ard_3-2-1_104078_2022-04-14_final
2022-04-15 11:26:19	ga_ls8c_ard_3-2-1_111075_2022-04-15_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_final
2022-04-17 09:37:04	ga_ls8c_ard_3-2-1_093080_2022-04-17_final
2022-04-18 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-04-18_final
2022-04-20 11:46:51	ga_ls8c_ard_3-2-1_114080_2022-04-20_final
2022-04-22 09:53:59	ga_ls8c_ard_3-2-1_096076_2022-04-22_final
2022-04-22 09:55:35	ga_ls8c_ard_3-2-1_096080_2022-04-22_final
2022-04-22 11:34:04	ga_ls8c_ard_3-2-1_112079_2022-04-22_final
2022-04-24 09:40:49	ga_ls8c_ard_3-2-1_094074_2022-04-24_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-24_final
2022-04-26 09:33:38	ga_ls8c_ard_3-2-1_092087_2022-04-26_final
2022-04-26 11:06:55	ga_ls8c_ard_3-2-1_108073_2022-04-26_final
2022-04-28 10:56:08	ga_ls8c_ard_3-2-1_106077_2022-04-28_final
2022-04-30 10:41:00	ga_ls8c_ard_3-2-1_104070_2022-04-30_final
2022-05-01 09:48:11	ga_ls8c_ard_3-2-1_095077_2022-05-01_final
2022-05-01 09:48:59	ga_ls8c_ard_3-2-1_095079_2022-05-01_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-02 10:30:16	ga_ls8c_ard_3-2-1_102074_2022-05-02_final
2022-05-03 09:35:27	ga_ls8c_ard_3-2-1_093076_2022-05-03_final
2022-05-03 09:36:39	ga_ls8c_ard_3-2-1_093079_2022-05-03_final
2022-05-03 09:37:03	ga_ls8c_ard_3-2-1_093080_2022-05-03_final
2022-05-03 09:37:27	ga_ls8c_ard_3-2-1_093081_2022-05-03_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-03 11:15:32	ga_ls8c_ard_3-2-1_109079_2022-05-03_final
2022-05-04 10:20:43	ga_ls8c_ard_3-2-1_100081_2022-05-04_final
2022-05-05 11:03:12	ga_ls8c_ard_3-2-1_107079_2022-05-05_final
2022-05-08 09:54:03	ga_ls8c_ard_3-2-1_096076_2022-05-08_final
2022-05-09 10:36:07	ga_ls8c_ard_3-2-1_103073_2022-05-09_final
2022-05-12 11:07:51	ga_ls8c_ard_3-2-1_108075_2022-05-12_final
2022-05-12 11:09:27	ga_ls8c_ard_3-2-1_108079_2022-05-12_final
2022-05-12 11:10:39	ga_ls8c_ard_3-2-1_108082_2022-05-12_final
2022-05-14 10:55:54	ga_ls8c_ard_3-2-1_106076_2022-05-14_final
2022-05-15 10:00:41	ga_ls8c_ard_3-2-1_097077_2022-05-15_final
2022-05-16 10:44:21	ga_ls8c_ard_3-2-1_104078_2022-05-16_final
2022-05-24 09:54:07	ga_ls8c_ard_3-2-1_096076_2022-05-24_final
2022-05-25 10:36:59	ga_ls8c_ard_3-2-1_103075_2022-05-25_final
2022-05-26 11:21:50	ga_ls8c_ard_3-2-1_110079_2022-05-26_final
2022-05-31 10:00:44	ga_ls8c_ard_3-2-1_097077_2022-05-31_final
2022-06-02 11:26:53	ga_ls8c_ard_3-2-1_111076_2022-06-02_final
2022-06-02 11:27:17	ga_ls8c_ard_3-2-1_111077_2022-06-02_final
2022-06-02 11:28:05	ga_ls8c_ard_3-2-1_111079_2022-06-02_final
2022-06-04 11:14:34	ga_ls8c_ard_3-2-1_109076_2022-06-04_final
2022-06-04 11:15:21	ga_ls8c_ard_3-2-1_109078_2022-06-04_final
2022-06-06 11:00:38	ga_ls8c_ard_3-2-1_107072_2022-06-06_final
2022-06-08 10:49:30	ga_ls8c_ard_3-2-1_105075_2022-06-08_final
2022-06-13 09:31:12	ga_ls8c_ard_3-2-1_092080_2022-06-13_final
2022-06-13 09:34:00	ga_ls8c_ard_3-2-1_092087_2022-06-13_final
2022-06-15 10:55:21	ga_ls8c_ard_3-2-1_106074_2022-06-15_final
2022-06-16 09:56:57	ga_ls8c_ard_3-2-1_097067_2022-06-16_final
2022-06-16 10:00:56	ga_ls8c_ard_3-2-1_097077_2022-06-16_final
2022-06-17 10:40:37	ga_ls8c_ard_3-2-1_104068_2022-06-17_final
2022-06-17 10:42:13	ga_ls8c_ard_3-2-1_104072_2022-06-17_final
2022-06-18 09:49:23	ga_ls8c_ard_3-2-1_095079_2022-06-18_final
2022-06-18 09:50:35	ga_ls8c_ard_3-2-1_095082_2022-06-18_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_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