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
2019-08-04 09:57:27	ga_ls8c_ard_3-1-0_096084_2019-08-04_final
2019-08-04 09:57:51	ga_ls8c_ard_3-1-0_096085_2019-08-04_final
2019-08-04 11:36:20	ga_ls8c_ard_3-1-0_112084_2019-08-04_final
2019-08-04 11:36:44	ga_ls8c_ard_3-1-0_112085_2019-08-04_final
2019-08-22 09:45:11	ga_ls8c_ard_3-1-0_094084_2019-08-22_final
2019-08-22 09:45:35	ga_ls8c_ard_3-1-0_094085_2019-08-22_final
2019-08-22 11:24:04	ga_ls8c_ard_3-1-0_110084_2019-08-22_final
2019-08-22 11:24:28	ga_ls8c_ard_3-1-0_110085_2019-08-22_final
2019-08-23 10:28:27	ga_ls8c_ard_3-1-0_101084_2019-08-23_final
2019-08-24 09:32:49	ga_ls8c_ard_3-1-0_092084_2019-08-24_final
2019-08-24 09:33:13	ga_ls8c_ard_3-1-0_092085_2019-08-24_final
2019-08-24 11:11:42	ga_ls8c_ard_3-1-0_108084_2019-08-24_final
2019-08-24 11:12:06	ga_ls8c_ard_3-1-0_108085_2019-08-24_final
2019-10-30 10:03:57	ga_ls8c_ard_3-1-0_097084_2019-10-30_final
2019-10-30 10:04:21	ga_ls8c_ard_3-1-0_097085_2019-10-30_final
2019-10-30 11:42:50	ga_ls8c_ard_3-1-0_113084_2019-10-30_final
2019-10-31 09:08:19	ga_ls8c_ard_3-1-0_088084_2019-10-30_final
2019-11-01 09:51:35	ga_ls8c_ard_3-1-0_095084_2019-11-01_final
2019-11-01 09:51:59	ga_ls8c_ard_3-1-0_095085_2019-11-01_final
2019-11-01 11:30:28	ga_ls8c_ard_3-1-0_111084_2019-11-01_final
2019-11-01 11:30:52	ga_ls8c_ard_3-1-0_111085_2019-11-01_final
2019-11-22 10:10:03	ga_ls8c_ard_3-1-0_098084_2019-11-22_final
2019-11-22 10:10:27	ga_ls8c_ard_3-1-0_098085_2019-11-22_final
2019-11-23 09:14:26	ga_ls8c_ard_3-1-0_089084_2019-11-22_final
2019-11-23 09:14:50	ga_ls8c_ard_3-1-0_089085_2019-11-22_final
2019-11-24 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-11-24_final
2019-11-24 09:58:05	ga_ls8c_ard_3-1-0_096085_2019-11-24_final
2019-11-24 11:36:34	ga_ls8c_ard_3-1-0_112084_2019-11-24_final
2019-11-24 11:36:58	ga_ls8c_ard_3-1-0_112085_2019-11-24_final
2022-01-23 10:03:44	ga_ls8c_ard_3-2-1_097084_2022-01-23_final
2022-01-23 10:04:08	ga_ls8c_ard_3-2-1_097085_2022-01-23_final
2022-01-23 11:42:37	ga_ls8c_ard_3-2-1_113084_2022-01-23_final
2022-01-25 09:51:21	ga_ls8c_ard_3-2-1_095084_2022-01-25_final
2022-01-25 09:51:45	ga_ls8c_ard_3-2-1_095085_2022-01-25_final
2022-03-10 10:15:53	ga_ls8c_ard_3-2-1_099084_2022-03-10_final
2022-03-10 10:16:17	ga_ls8c_ard_3-2-1_099085_2022-03-10_final
2022-03-11 09:20:16	ga_ls8c_ard_3-2-1_090084_2022-03-10_final
2022-03-11 09:20:40	ga_ls8c_ard_3-2-1_090085_2022-03-10_final
2022-03-16 09:38:45	ga_ls8c_ard_3-2-1_093084_2022-03-16_final
2022-03-16 09:39:09	ga_ls8c_ard_3-2-1_093085_2022-03-16_final
2022-03-16 11:17:38	ga_ls8c_ard_3-2-1_109084_2022-03-16_final
2022-03-17 10:22:00	ga_ls8c_ard_3-2-1_100084_2022-03-17_final
2022-03-20 09:13:59	ga_ls8c_ard_3-2-1_089084_2022-03-19_final
2022-03-20 09:14:23	ga_ls8c_ard_3-2-1_089085_2022-03-19_final
2022-03-21 09:57:14	ga_ls8c_ard_3-2-1_096084_2022-03-21_final
2022-03-21 09:57:38	ga_ls8c_ard_3-2-1_096085_2022-03-21_final
2022-03-30 09:50:56	ga_ls8c_ard_3-2-1_095084_2022-03-30_final
2022-03-30 09:51:20	ga_ls8c_ard_3-2-1_095085_2022-03-30_final
2022-03-30 11:29:49	ga_ls8c_ard_3-2-1_111084_2022-03-30_final
2022-04-01 09:38:34	ga_ls8c_ard_3-2-1_093084_2022-04-01_final
2022-04-01 09:38:58	ga_ls8c_ard_3-2-1_093085_2022-04-01_final
2022-04-01 11:17:27	ga_ls8c_ard_3-2-1_109084_2022-04-01_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-06 09:57:09	ga_ls8c_ard_3-2-1_096084_2022-04-06_final
2022-04-06 09:57:33	ga_ls8c_ard_3-2-1_096085_2022-04-06_final
2022-04-06 11:36:02	ga_ls8c_ard_3-2-1_112084_2022-04-06_final
2022-04-26 09:32:26	ga_ls8c_ard_3-2-1_092084_2022-04-26_final
2022-04-26 09:32:50	ga_ls8c_ard_3-2-1_092085_2022-04-26_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-27 10:15:41	ga_ls8c_ard_3-2-1_099084_2022-04-27_final
2022-04-27 10:16:05	ga_ls8c_ard_3-2-1_099085_2022-04-27_final
2022-04-28 09:20:03	ga_ls8c_ard_3-2-1_090084_2022-04-27_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-29 10:03:18	ga_ls8c_ard_3-2-1_097084_2022-04-29_final
2022-04-29 10:03:42	ga_ls8c_ard_3-2-1_097085_2022-04-29_final
2022-04-29 11:42:11	ga_ls8c_ard_3-2-1_113084_2022-04-29_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-01 11:29:52	ga_ls8c_ard_3-2-1_111084_2022-05-01_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-06-02 09:51:12	ga_ls8c_ard_3-2-1_095084_2022-06-02_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-02 11:30:05	ga_ls8c_ard_3-2-1_111084_2022-06-02_final
2022-06-04 09:38:52	ga_ls8c_ard_3-2-1_093084_2022-06-04_final
2022-06-04 09:39:16	ga_ls8c_ard_3-2-1_093085_2022-06-04_final
2022-06-04 11:17:45	ga_ls8c_ard_3-2-1_109084_2022-06-04_final
2022-06-05 10:22:09	ga_ls8c_ard_3-2-1_100084_2022-06-05_final
2022-06-06 09:26:32	ga_ls8c_ard_3-2-1_091084_2022-06-05_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-06 11:05:25	ga_ls8c_ard_3-2-1_107084_2022-06-06_final
2022-06-07 10:09:49	ga_ls8c_ard_3-2-1_098084_2022-06-07_final
2022-06-07 10:10:13	ga_ls8c_ard_3-2-1_098085_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-08 09:14:36	ga_ls8c_ard_3-2-1_089085_2022-06-07_final
2022-06-09 09:57:29	ga_ls8c_ard_3-2-1_096084_2022-06-09_final
2022-06-09 09:57:53	ga_ls8c_ard_3-2-1_096085_2022-06-09_final
2022-06-09 11:36:22	ga_ls8c_ard_3-2-1_112084_2022-06-09_final
2022-06-11 09:45:08	ga_ls8c_ard_3-2-1_094084_2022-06-11_final
2022-06-11 09:45:32	ga_ls8c_ard_3-2-1_094085_2022-06-11_final
2022-06-11 11:24:01	ga_ls8c_ard_3-2-1_110084_2022-06-11_final
2022-06-11 11:24:25	ga_ls8c_ard_3-2-1_110085_2022-06-11_final
2022-06-13 09:32:48	ga_ls8c_ard_3-2-1_092084_2022-06-13_final
2022-06-13 09:33:12	ga_ls8c_ard_3-2-1_092085_2022-06-13_final
2022-06-13 11:11:41	ga_ls8c_ard_3-2-1_108084_2022-06-13_final
2022-06-18 11:30:16	ga_ls8c_ard_3-2-1_111084_2022-06-18_final
2022-06-20 09:39:02	ga_ls8c_ard_3-2-1_093084_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years