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
2023-09-04 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-09-04_final
2023-09-07 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-09-07_final
2023-09-08 10:44:24	ga_ls8c_ard_3-2-1_104078_2023-09-08_final
2023-09-08 10:45:12	ga_ls8c_ard_3-2-1_104080_2023-09-08_final
2023-09-09 09:49:59	ga_ls8c_ard_3-2-1_095081_2023-09-09_final
2023-09-09 09:50:47	ga_ls8c_ard_3-2-1_095083_2023-09-09_final
2023-09-09 11:28:28	ga_ls8c_ard_3-2-1_111080_2023-09-09_final
2023-09-10 10:32:52	ga_ls8c_ard_3-2-1_102080_2023-09-10_final
2023-09-11 09:36:27	ga_ls8c_ard_3-2-1_093078_2023-09-11_final
2023-09-11 11:17:20	ga_ls8c_ard_3-2-1_109083_2023-09-11_final
2023-09-21 10:12:23	ga_ls8c_ard_3-2-1_099075_2023-09-21_final
2023-09-22 10:56:27	ga_ls8c_ard_3-2-1_106077_2023-09-22_final
2023-09-24 10:42:30	ga_ls8c_ard_3-2-1_104073_2023-09-24_final
2023-09-25 11:27:23	ga_ls8c_ard_3-2-1_111077_2023-09-25_final
2023-09-25 11:29:22	ga_ls8c_ard_3-2-1_111082_2023-09-25_final
2023-09-26 10:32:10	ga_ls8c_ard_3-2-1_102078_2023-09-26_final
2023-09-27 09:36:09	ga_ls8c_ard_3-2-1_093077_2023-09-27_final
2023-09-28 10:20:37	ga_ls8c_ard_3-2-1_100080_2023-09-28_final
2023-09-29 11:02:41	ga_ls8c_ard_3-2-1_107077_2023-09-29_final
2023-10-01 09:10:15	ga_ls8c_ard_3-2-1_089074_2023-09-30_final
2023-10-01 10:51:31	ga_ls8c_ard_3-2-1_105080_2023-10-01_final
2023-10-01 10:51:55	ga_ls8c_ard_3-2-1_105081_2023-10-01_final
2023-10-02 09:55:06	ga_ls8c_ard_3-2-1_096078_2023-10-02_final
2023-10-02 09:55:30	ga_ls8c_ard_3-2-1_096079_2023-10-02_final
2023-10-02 09:56:18	ga_ls8c_ard_3-2-1_096081_2023-10-02_final
2023-10-04 09:41:32	ga_ls8c_ard_3-2-1_094075_2023-10-04_final
2023-10-04 09:42:20	ga_ls8c_ard_3-2-1_094077_2023-10-04_final
2023-10-04 11:22:49	ga_ls8c_ard_3-2-1_110081_2023-10-04_final
2023-10-06 09:30:22	ga_ls8c_ard_3-2-1_092078_2023-10-06_final
2023-10-07 10:12:27	ga_ls8c_ard_3-2-1_099075_2023-10-07_final
2023-10-07 10:15:14	ga_ls8c_ard_3-2-1_099082_2023-10-07_final
2023-10-08 10:58:07	ga_ls8c_ard_3-2-1_106081_2023-10-08_final
2023-10-09 10:00:30	ga_ls8c_ard_3-2-1_097076_2023-10-09_final
2023-10-09 11:40:11	ga_ls8c_ard_3-2-1_113078_2023-10-09_final
2023-10-10 10:41:47	ga_ls8c_ard_3-2-1_104071_2023-10-10_final
2023-10-10 10:43:47	ga_ls8c_ard_3-2-1_104076_2023-10-10_final
2023-10-11 11:27:03	ga_ls8c_ard_3-2-1_111076_2023-10-11_final
2023-10-11 11:27:27	ga_ls8c_ard_3-2-1_111077_2023-10-11_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-11 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-10-11_final
2023-10-12 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-10-12_final
2023-10-12 10:32:13	ga_ls8c_ard_3-2-1_102078_2023-10-12_final
2023-10-12 10:32:37	ga_ls8c_ard_3-2-1_102079_2023-10-12_final
2023-10-13 09:37:24	ga_ls8c_ard_3-2-1_093080_2023-10-13_final
2023-10-13 09:37:48	ga_ls8c_ard_3-2-1_093081_2023-10-13_final
2023-10-13 11:15:53	ga_ls8c_ard_3-2-1_109079_2023-10-13_final
2023-10-13 11:16:17	ga_ls8c_ard_3-2-1_109080_2023-10-13_final
2023-10-14 10:21:28	ga_ls8c_ard_3-2-1_100082_2023-10-14_final
2023-10-16 10:08:42	ga_ls8c_ard_3-2-1_098081_2023-10-16_final
2023-10-17 10:51:57	ga_ls8c_ard_3-2-1_105081_2023-10-17_final
2023-10-18 09:53:56	ga_ls8c_ard_3-2-1_096075_2023-10-18_final
2023-10-18 09:54:44	ga_ls8c_ard_3-2-1_096077_2023-10-18_final
2023-10-18 09:56:43	ga_ls8c_ard_3-2-1_096082_2023-10-18_final
2023-10-20 09:41:57	ga_ls8c_ard_3-2-1_094076_2023-10-20_final
2023-10-20 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-10-20_final
2023-10-20 11:22:02	ga_ls8c_ard_3-2-1_110079_2023-10-20_final
2023-10-20 11:22:50	ga_ls8c_ard_3-2-1_110081_2023-10-20_final
2023-10-20 11:23:38	ga_ls8c_ard_3-2-1_110083_2023-10-20_final
2023-10-22 09:30:25	ga_ls8c_ard_3-2-1_092078_2023-10-22_final
2023-10-22 09:35:13	ga_ls8c_ard_3-2-1_092090_2023-10-22_final
2023-10-22 11:08:54	ga_ls8c_ard_3-2-1_108077_2023-10-22_final
2023-10-23 10:12:06	ga_ls8c_ard_3-2-1_099074_2023-10-23_final
2023-10-26 10:45:49	ga_ls8c_ard_3-2-1_104081_2023-10-26_final
2023-10-27 09:49:48	ga_ls8c_ard_3-2-1_095080_2023-10-27_final
2023-10-27 11:27:29	ga_ls8c_ard_3-2-1_111077_2023-10-27_final
2023-10-28 10:32:16	ga_ls8c_ard_3-2-1_102078_2023-10-28_final
2023-10-29 09:37:03	ga_ls8c_ard_3-2-1_093079_2023-10-29_final
2023-10-29 09:37:51	ga_ls8c_ard_3-2-1_093081_2023-10-29_final
2023-10-29 11:15:56	ga_ls8c_ard_3-2-1_109079_2023-10-29_final
2023-10-29 11:16:20	ga_ls8c_ard_3-2-1_109080_2023-10-29_final
2023-10-30 10:21:07	ga_ls8c_ard_3-2-1_100081_2023-10-30_final
2023-10-30 11:58:48	ga_ls8c_ard_3-2-1_116078_2023-10-30_final
2023-10-31 11:03:11	ga_ls8c_ard_3-2-1_107078_2023-10-31_final
2023-11-01 10:06:45	ga_ls8c_ard_3-2-1_098076_2023-11-01_final
2023-11-01 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-11-01_final
2023-11-02 10:51:13	ga_ls8c_ard_3-2-1_105079_2023-11-02_final
2023-11-03 09:53:59	ga_ls8c_ard_3-2-1_096075_2023-11-03_final
2023-11-03 09:55:11	ga_ls8c_ard_3-2-1_096078_2023-11-03_final
2023-11-03 11:34:04	ga_ls8c_ard_3-2-1_112078_2023-11-03_final
2023-11-04 10:38:50	ga_ls8c_ard_3-2-1_103079_2023-11-04_final
2023-11-05 09:42:25	ga_ls8c_ard_3-2-1_094077_2023-11-05_final
2023-11-05 09:43:37	ga_ls8c_ard_3-2-1_094080_2023-11-05_final
2023-11-05 11:21:42	ga_ls8c_ard_3-2-1_110078_2023-11-05_final
2023-11-05 11:22:06	ga_ls8c_ard_3-2-1_110079_2023-11-05_final
2023-11-06 10:27:16	ga_ls8c_ard_3-2-1_101081_2023-11-06_final
2023-11-07 09:30:02	ga_ls8c_ard_3-2-1_092077_2023-11-07_final
2023-11-07 09:32:49	ga_ls8c_ard_3-2-1_092084_2023-11-07_final
2023-11-07 11:08:55	ga_ls8c_ard_3-2-1_108077_2023-11-07_final
2023-11-10 11:39:46	ga_ls8c_ard_3-2-1_113077_2023-11-10_final
2023-11-10 11:40:34	ga_ls8c_ard_3-2-1_113079_2023-11-10_final
2023-11-11 10:44:57	ga_ls8c_ard_3-2-1_104079_2023-11-11_final
2023-11-12 09:49:45	ga_ls8c_ard_3-2-1_095080_2023-11-12_final
2023-11-12 09:50:09	ga_ls8c_ard_3-2-1_095081_2023-11-12_final
2023-11-16 09:28:16	ga_ls8c_ard_3-2-1_091088_2023-11-15_final
2023-11-16 11:03:10	ga_ls8c_ard_3-2-1_107078_2023-11-16_final
2023-11-19 11:34:05	ga_ls8c_ard_3-2-1_112078_2023-11-19_final
2023-11-19 11:34:29	ga_ls8c_ard_3-2-1_112079_2023-11-19_final
2023-11-20 10:37:17	ga_ls8c_ard_3-2-1_103075_2023-11-20_final
2023-11-21 09:44:03	ga_ls8c_ard_3-2-1_094081_2023-11-21_final
2023-11-21 11:21:45	ga_ls8c_ard_3-2-1_110078_2023-11-21_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