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
2018-05-26 09:24:57	ga_ls8c_ard_3-0-0_091083_2018-05-25_final
2018-05-26 11:03:50	ga_ls8c_ard_3-0-0_107083_2018-05-26_final
2018-06-02 09:30:38	ga_ls8c_ard_3-0-0_092082_2018-06-02_final
2018-06-02 09:31:02	ga_ls8c_ard_3-0-0_092083_2018-06-02_final
2018-06-02 11:09:31	ga_ls8c_ard_3-0-0_108082_2018-06-02_final
2018-06-02 11:09:55	ga_ls8c_ard_3-0-0_108083_2018-06-02_final
2018-06-03 10:14:18	ga_ls8c_ard_3-0-0_099083_2018-06-03_final
2018-06-04 09:18:16	ga_ls8c_ard_3-0-0_090082_2018-06-03_final
2018-06-04 09:18:40	ga_ls8c_ard_3-0-0_090083_2018-06-03_final
2018-07-06 10:57:28	ga_ls8c_ard_3-0-0_106082_2018-07-06_final
2018-07-06 10:57:52	ga_ls8c_ard_3-0-0_106083_2018-07-06_final
2018-07-07 10:01:52	ga_ls8c_ard_3-0-0_097082_2018-07-07_final
2018-07-07 10:02:16	ga_ls8c_ard_3-0-0_097083_2018-07-07_final
2018-07-07 11:40:45	ga_ls8c_ard_3-0-0_113082_2018-07-07_final
2018-07-07 11:41:09	ga_ls8c_ard_3-0-0_113083_2018-07-07_final
2018-07-08 09:06:15	ga_ls8c_ard_3-0-0_088082_2018-07-07_final
2018-07-08 09:06:39	ga_ls8c_ard_3-0-0_088083_2018-07-07_final
2018-07-08 10:45:08	ga_ls8c_ard_3-0-0_104082_2018-07-08_final
2018-07-08 10:45:32	ga_ls8c_ard_3-0-0_104083_2018-07-08_final
2018-08-05 09:31:35	ga_ls8c_ard_3-0-0_092083_2018-08-05_final
2018-08-05 11:10:04	ga_ls8c_ard_3-0-0_108082_2018-08-05_final
2018-08-05 11:10:28	ga_ls8c_ard_3-0-0_108083_2018-08-05_final
2018-08-06 10:14:28	ga_ls8c_ard_3-0-0_099082_2018-08-06_final
2018-08-06 10:14:52	ga_ls8c_ard_3-0-0_099083_2018-08-06_final
2018-08-07 09:18:51	ga_ls8c_ard_3-0-0_090082_2018-08-06_final
2018-08-07 09:19:15	ga_ls8c_ard_3-0-0_090083_2018-08-06_final
2018-09-08 10:57:58	ga_ls8c_ard_3-0-0_106082_2018-09-08_final
2018-09-08 10:58:22	ga_ls8c_ard_3-0-0_106083_2018-09-08_final
2018-09-09 10:02:21	ga_ls8c_ard_3-0-0_097082_2018-09-09_final
2018-09-09 10:02:45	ga_ls8c_ard_3-0-0_097083_2018-09-09_final
2018-09-09 11:41:14	ga_ls8c_ard_3-0-0_113082_2018-09-09_final
2018-09-09 11:41:38	ga_ls8c_ard_3-0-0_113083_2018-09-09_final
2018-09-10 09:06:44	ga_ls8c_ard_3-0-0_088082_2018-09-09_final
2018-09-10 09:07:08	ga_ls8c_ard_3-0-0_088083_2018-09-09_final
2018-09-10 10:45:37	ga_ls8c_ard_3-0-0_104082_2018-09-10_final
2018-09-10 10:46:01	ga_ls8c_ard_3-0-0_104083_2018-09-10_final
2018-09-16 10:08:58	ga_ls8c_ard_3-0-0_098083_2018-09-16_final
2018-09-17 09:12:56	ga_ls8c_ard_3-0-0_089082_2018-09-16_final
2018-09-17 09:13:20	ga_ls8c_ard_3-0-0_089083_2018-09-16_final
2018-09-17 10:51:49	ga_ls8c_ard_3-0-0_105082_2018-09-17_final
2018-09-17 10:52:13	ga_ls8c_ard_3-0-0_105083_2018-09-17_final
2018-10-04 09:56:44	ga_ls8c_ard_3-0-0_096083_2018-10-04_final
2018-10-04 11:35:13	ga_ls8c_ard_3-0-0_112082_2018-10-04_final
2018-10-04 11:35:37	ga_ls8c_ard_3-0-0_112083_2018-10-04_final
2018-10-05 10:39:36	ga_ls8c_ard_3-0-0_103082_2018-10-05_final
2018-10-05 10:40:00	ga_ls8c_ard_3-0-0_103083_2018-10-05_final
2018-10-06 09:43:59	ga_ls8c_ard_3-0-0_094082_2018-10-06_final
2018-10-06 09:44:23	ga_ls8c_ard_3-0-0_094083_2018-10-06_final
2018-10-06 11:23:16	ga_ls8c_ard_3-0-0_110083_2018-10-06_final
2018-10-07 10:27:40	ga_ls8c_ard_3-0-0_101083_2018-10-07_final
2018-12-07 09:56:52	ga_ls8c_ard_3-0-0_096083_2018-12-07_final
2018-12-07 11:35:21	ga_ls8c_ard_3-0-0_112082_2018-12-07_final
2018-12-07 11:35:45	ga_ls8c_ard_3-0-0_112083_2018-12-07_final
2018-12-08 10:40:08	ga_ls8c_ard_3-0-0_103083_2018-12-08_final
2018-12-09 09:44:30	ga_ls8c_ard_3-0-0_094083_2018-12-09_final
2018-12-09 11:23:23	ga_ls8c_ard_3-0-0_110083_2018-12-09_final
2018-12-10 10:27:21	ga_ls8c_ard_3-0-0_101082_2018-12-10_final
2018-12-10 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-12-10_final
2018-12-25 09:44:05	ga_ls8c_ard_3-0-0_094082_2018-12-25_final
2018-12-25 09:44:29	ga_ls8c_ard_3-0-0_094083_2018-12-25_final
2018-12-25 11:23:22	ga_ls8c_ard_3-0-0_110083_2018-12-25_final
2018-12-26 10:27:21	ga_ls8c_ard_3-0-0_101082_2018-12-26_final
2018-12-26 10:27:45	ga_ls8c_ard_3-0-0_101083_2018-12-26_final
2019-01-06 10:09:12	ga_ls8c_ard_3-0-0_098083_2019-01-06_final
2019-01-07 09:13:34	ga_ls8c_ard_3-0-0_089083_2019-01-06_final
2019-01-07 10:52:03	ga_ls8c_ard_3-0-0_105082_2019-01-07_final
2019-01-07 10:52:27	ga_ls8c_ard_3-0-0_105083_2019-01-07_final
2019-01-10 09:44:28	ga_ls8c_ard_3-0-0_094083_2019-01-10_final
2019-01-10 11:23:21	ga_ls8c_ard_3-0-0_110083_2019-01-10_final
2019-01-11 10:27:43	ga_ls8c_ard_3-0-0_101083_2019-01-11_final
2019-11-05 09:26:27	ga_ls8c_ard_3-1-0_091083_2019-11-04_final
2019-11-05 11:04:56	ga_ls8c_ard_3-1-0_107082_2019-11-05_final
2019-11-05 11:05:20	ga_ls8c_ard_3-1-0_107083_2019-11-05_final
2019-11-21 09:26:23	ga_ls8c_ard_3-1-0_091083_2019-11-20_final
2019-11-21 11:04:52	ga_ls8c_ard_3-1-0_107082_2019-11-21_final
2019-11-21 11:05:16	ga_ls8c_ard_3-1-0_107083_2019-11-21_final
2019-12-07 09:26:23	ga_ls8c_ard_3-1-0_091083_2019-12-06_final
2019-12-07 11:05:16	ga_ls8c_ard_3-1-0_107083_2019-12-07_final
2019-12-08 10:09:39	ga_ls8c_ard_3-1-0_098083_2019-12-08_final
2019-12-09 09:13:37	ga_ls8c_ard_3-1-0_089082_2019-12-08_final
2019-12-09 09:14:01	ga_ls8c_ard_3-1-0_089083_2019-12-08_final
2019-12-09 10:52:30	ga_ls8c_ard_3-1-0_105082_2019-12-09_final
2019-12-09 10:52:54	ga_ls8c_ard_3-1-0_105083_2019-12-09_final
2019-12-10 09:57:17	ga_ls8c_ard_3-1-0_096083_2019-12-10_final
2019-12-10 11:36:10	ga_ls8c_ard_3-1-0_112083_2019-12-10_final
2019-12-11 10:40:32	ga_ls8c_ard_3-1-0_103083_2019-12-11_final
2020-01-08 09:26:16	ga_ls8c_ard_3-1-0_091083_2020-01-07_final
2020-01-08 11:05:09	ga_ls8c_ard_3-1-0_107083_2020-01-08_final
2022-12-01 09:13:53	ga_ls8c_ard_3-2-1_089082_2022-11-30_final
2022-12-01 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-30_final
2022-12-01 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-12-01_final
2022-12-02 09:57:32	ga_ls8c_ard_3-2-1_096083_2022-12-02_final
2022-12-07 10:16:04	ga_ls8c_ard_3-2-1_099083_2022-12-07_final
2022-12-17 10:53:03	ga_ls8c_ard_3-2-1_105083_2022-12-17_final
2022-12-18 09:57:25	ga_ls8c_ard_3-2-1_096083_2022-12-18_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-02 10:53:01	ga_ls8c_ard_3-2-1_105083_2023-01-02_final
2023-01-03 09:57:23	ga_ls8c_ard_3-2-1_096083_2023-01-03_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