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 09:49:10	ga_ls8c_ard_3-1-0_095080_2019-03-22_final
2019-04-07 09:47:07	ga_ls8c_ard_3-1-0_095075_2019-04-07_final
2019-04-07 09:51:06	ga_ls8c_ard_3-1-0_095085_2019-04-07_final
2019-06-14 09:24:18	ga_ls8c_ard_3-1-0_091079_2019-06-13_final
2019-06-30 09:24:22	ga_ls8c_ard_3-1-0_091079_2019-06-29_final
2019-06-30 09:24:46	ga_ls8c_ard_3-1-0_091080_2019-06-29_final
2019-07-12 09:47:56	ga_ls8c_ard_3-1-0_095076_2019-07-12_final
2019-07-16 09:23:37	ga_ls8c_ard_3-1-0_091077_2019-07-15_final
2019-08-13 09:49:43	ga_ls8c_ard_3-1-0_095080_2019-08-13_final
2019-08-17 09:25:01	ga_ls8c_ard_3-1-0_091080_2019-08-16_final
2019-08-29 09:47:23	ga_ls8c_ard_3-1-0_095074_2019-08-29_final
2019-09-14 09:47:28	ga_ls8c_ard_3-1-0_095074_2019-09-14_final
2019-09-14 09:47:52	ga_ls8c_ard_3-1-0_095075_2019-09-14_final
2019-10-16 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-10-16_final
2019-11-01 09:48:23	ga_ls8c_ard_3-1-0_095076_2019-11-01_final
2020-01-04 09:51:48	ga_ls8c_ard_3-1-0_095085_2020-01-04_final
2020-01-20 09:49:45	ga_ls8c_ard_3-1-0_095080_2020-01-20_final
2020-01-24 09:26:12	ga_ls8c_ard_3-1-0_091083_2020-01-23_final
2020-02-05 09:48:51	ga_ls8c_ard_3-1-0_095078_2020-02-05_final
2020-03-24 09:46:59	ga_ls8c_ard_3-1-0_095074_2020-03-24_final
2020-03-28 09:24:13	ga_ls8c_ard_3-1-0_091079_2020-03-27_final
2020-04-25 09:46:43	ga_ls8c_ard_3-1-0_095074_2020-04-25_final
2020-04-25 09:47:31	ga_ls8c_ard_3-1-0_095076_2020-04-25_final
2020-04-29 09:23:58	ga_ls8c_ard_3-1-0_091079_2020-04-28_final
2022-03-29 10:41:46	ga_ls8c_ard_3-2-1_104072_2022-03-29_final
2022-04-01 09:33:23	ga_ls8c_ard_3-2-1_093071_2022-04-01_final
2022-04-01 09:35:46	ga_ls8c_ard_3-2-1_093077_2022-04-01_final
2022-04-01 09:36:10	ga_ls8c_ard_3-2-1_093078_2022-04-01_final
2022-04-02 10:18:38	ga_ls8c_ard_3-2-1_100076_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-05 10:48:22	ga_ls8c_ard_3-2-1_105073_2022-04-05_final
2022-04-08 09:41:37	ga_ls8c_ard_3-2-1_094076_2022-04-08_final
2022-04-08 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-08_final
2022-04-10 09:29:40	ga_ls8c_ard_3-2-1_092077_2022-04-09_final
2022-04-10 09:30:04	ga_ls8c_ard_3-2-1_092078_2022-04-10_final
2022-04-11 10:12:08	ga_ls8c_ard_3-2-1_099075_2022-04-11_final
2022-04-12 09:17:43	ga_ls8c_ard_3-2-1_090078_2022-04-11_final
2022-04-12 10:54:13	ga_ls8c_ard_3-2-1_106072_2022-04-12_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-14 10:43:27	ga_ls8c_ard_3-2-1_104076_2022-04-14_final
2022-04-14 10:45:03	ga_ls8c_ard_3-2-1_104080_2022-04-14_final
2022-04-14 10:45:27	ga_ls8c_ard_3-2-1_104081_2022-04-14_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-17 09:35:52	ga_ls8c_ard_3-2-1_093077_2022-04-17_final
2022-04-17 11:15:09	ga_ls8c_ard_3-2-1_109078_2022-04-17_final
2022-04-19 09:23:54	ga_ls8c_ard_3-2-1_091078_2022-04-18_final
2022-04-19 09:26:18	ga_ls8c_ard_3-2-1_091084_2022-04-18_final
2022-04-20 10:08:21	ga_ls8c_ard_3-2-1_098081_2022-04-20_final
2022-04-20 11:46:03	ga_ls8c_ard_3-2-1_114078_2022-04-20_final
2022-04-21 10:48:25	ga_ls8c_ard_3-2-1_105073_2022-04-21_final
2022-04-21 10:51:13	ga_ls8c_ard_3-2-1_105080_2022-04-21_final
2022-04-22 11:32:29	ga_ls8c_ard_3-2-1_112075_2022-04-22_final
2022-04-22 11:34:28	ga_ls8c_ard_3-2-1_112080_2022-04-22_final
2022-04-24 09:42:49	ga_ls8c_ard_3-2-1_094079_2022-04-24_final
2022-04-24 11:22:30	ga_ls8c_ard_3-2-1_110081_2022-04-24_final
2022-04-27 10:14:29	ga_ls8c_ard_3-2-1_099081_2022-04-27_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-05-02 10:29:28	ga_ls8c_ard_3-2-1_102072_2022-05-02_final
2022-05-02 10:31:04	ga_ls8c_ard_3-2-1_102076_2022-05-02_final
2022-05-02 10:31:28	ga_ls8c_ard_3-2-1_102077_2022-05-02_final
2022-05-04 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-05-04_final
2022-05-05 11:00:24	ga_ls8c_ard_3-2-1_107072_2022-05-05_final
2022-05-05 11:04:00	ga_ls8c_ard_3-2-1_107081_2022-05-05_final
2022-05-06 11:45:40	ga_ls8c_ard_3-2-1_114077_2022-05-06_final
2022-05-07 09:12:46	ga_ls8c_ard_3-2-1_089081_2022-05-06_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-07 10:50:52	ga_ls8c_ard_3-2-1_105079_2022-05-07_final
2022-05-08 09:56:03	ga_ls8c_ard_3-2-1_096081_2022-05-08_final
2022-05-10 11:21:23	ga_ls8c_ard_3-2-1_110078_2022-05-10_final
2022-05-11 10:25:47	ga_ls8c_ard_3-2-1_101078_2022-05-11_final
2022-05-12 11:08:39	ga_ls8c_ard_3-2-1_108077_2022-05-12_final
2022-05-13 10:11:26	ga_ls8c_ard_3-2-1_099073_2022-05-13_final
2022-05-13 10:15:02	ga_ls8c_ard_3-2-1_099082_2022-05-13_final
2022-05-15 09:57:30	ga_ls8c_ard_3-2-1_097069_2022-05-15_final
2022-05-15 10:00:17	ga_ls8c_ard_3-2-1_097076_2022-05-15_final
2022-05-16 10:43:57	ga_ls8c_ard_3-2-1_104077_2022-05-16_final
2022-05-17 11:28:25	ga_ls8c_ard_3-2-1_111080_2022-05-17_final
2022-05-19 09:36:23	ga_ls8c_ard_3-2-1_093078_2022-05-19_final
2022-05-19 09:37:35	ga_ls8c_ard_3-2-1_093081_2022-05-19_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-25 10:38:34	ga_ls8c_ard_3-2-1_103079_2022-05-25_final
2022-05-26 09:42:09	ga_ls8c_ard_3-2-1_094077_2022-05-26_final
2022-05-26 09:43:45	ga_ls8c_ard_3-2-1_094081_2022-05-26_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-02 09:49:12	ga_ls8c_ard_3-2-1_095079_2022-06-02_final
2022-06-02 11:27:17	ga_ls8c_ard_3-2-1_111077_2022-06-02_final
2022-06-04 11:15:45	ga_ls8c_ard_3-2-1_109079_2022-06-04_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-06 09:24:08	ga_ls8c_ard_3-2-1_091078_2022-06-05_final
2022-06-07 11:45:30	ga_ls8c_ard_3-2-1_114076_2022-06-07_final
2022-06-08 10:47:54	ga_ls8c_ard_3-2-1_105071_2022-06-08_final
2022-06-08 10:51:05	ga_ls8c_ard_3-2-1_105079_2022-06-08_final
2022-06-13 11:08:54	ga_ls8c_ard_3-2-1_108077_2022-06-13_final
2022-06-13 11:10:53	ga_ls8c_ard_3-2-1_108082_2022-06-13_final
2022-06-17 10:42:13	ga_ls8c_ard_3-2-1_104072_2022-06-17_final
2022-06-17 10:43:01	ga_ls8c_ard_3-2-1_104074_2022-06-17_final
2022-06-17 10:45:00	ga_ls8c_ard_3-2-1_104079_2022-06-17_final
2022-06-18 09:50:11	ga_ls8c_ard_3-2-1_095081_2022-06-18_final
2022-06-20 09:38:38	ga_ls8c_ard_3-2-1_093083_2022-06-20_final
2022-06-20 11:16:20	ga_ls8c_ard_3-2-1_109080_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