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
2018-09-16 10:09:21	ga_ls8c_ard_3-0-0_098084_2018-09-16_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-17 09:13:44	ga_ls8c_ard_3-0-0_089084_2018-09-16_final
2018-09-17 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-09-16_final
2019-01-06 10:09:36	ga_ls8c_ard_3-0-0_098084_2019-01-06_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-07-17 10:09:41	ga_ls8c_ard_3-1-0_098084_2019-07-17_final
2019-07-17 10:10:05	ga_ls8c_ard_3-1-0_098085_2019-07-17_final
2019-07-18 09:14:04	ga_ls8c_ard_3-1-0_089084_2019-07-17_final
2019-07-18 09:14:28	ga_ls8c_ard_3-1-0_089085_2019-07-17_final
2019-07-23 09:32:38	ga_ls8c_ard_3-1-0_092084_2019-07-23_final
2019-07-23 09:33:02	ga_ls8c_ard_3-1-0_092085_2019-07-23_final
2019-07-23 11:11:31	ga_ls8c_ard_3-1-0_108084_2019-07-23_final
2019-07-23 11:11:55	ga_ls8c_ard_3-1-0_108085_2019-07-23_final
2019-07-24 10:15:54	ga_ls8c_ard_3-1-0_099084_2019-07-24_final
2019-07-24 10:16:18	ga_ls8c_ard_3-1-0_099085_2019-07-24_final
2019-07-25 09:20:18	ga_ls8c_ard_3-1-0_090084_2019-07-24_final
2019-07-25 09:20:41	ga_ls8c_ard_3-1-0_090085_2019-07-24_final
2019-07-25 10:59:11	ga_ls8c_ard_3-1-0_106084_2019-07-25_final
2019-07-26 10:03:34	ga_ls8c_ard_3-1-0_097084_2019-07-26_final
2019-07-26 10:03:58	ga_ls8c_ard_3-1-0_097085_2019-07-26_final
2019-07-26 11:42:27	ga_ls8c_ard_3-1-0_113084_2019-07-26_final
2019-07-27 09:07:57	ga_ls8c_ard_3-1-0_088084_2019-07-26_final
2019-08-15 11:17:51	ga_ls8c_ard_3-1-0_109084_2019-08-15_final
2019-08-15 11:18:15	ga_ls8c_ard_3-1-0_109085_2019-08-15_final
2019-08-16 10:22:38	ga_ls8c_ard_3-1-0_100085_2019-08-16_final
2019-09-30 09:51:33	ga_ls8c_ard_3-1-0_095084_2019-09-30_final
2019-09-30 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-09-30_final
2019-09-30 11:30:26	ga_ls8c_ard_3-1-0_111084_2019-09-30_final
2019-09-30 11:30:50	ga_ls8c_ard_3-1-0_111085_2019-09-30_final
2019-10-02 09:39:11	ga_ls8c_ard_3-1-0_093084_2019-10-02_final
2019-10-02 09:39:35	ga_ls8c_ard_3-1-0_093085_2019-10-02_final
2019-10-02 11:18:04	ga_ls8c_ard_3-1-0_109084_2019-10-02_final
2019-10-02 11:18:28	ga_ls8c_ard_3-1-0_109085_2019-10-02_final
2019-10-03 10:22:27	ga_ls8c_ard_3-1-0_100084_2019-10-03_final
2019-10-03 10:22:51	ga_ls8c_ard_3-1-0_100085_2019-10-03_final
2019-10-21 10:10:32	ga_ls8c_ard_3-1-0_098085_2019-10-21_final
2019-10-22 09:14:30	ga_ls8c_ard_3-1-0_089084_2019-10-21_final
2019-10-22 09:14:54	ga_ls8c_ard_3-1-0_089085_2019-10-21_final
2022-11-13 09:27:03	ga_ls8c_ard_3-2-1_091084_2022-11-12_final
2022-11-13 09:27:27	ga_ls8c_ard_3-2-1_091085_2022-11-12_final
2022-11-14 10:10:18	ga_ls8c_ard_3-2-1_098084_2022-11-14_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-18 11:24:48	ga_ls8c_ard_3-2-1_110085_2022-11-18_final
2022-11-20 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-11-20_final
2022-12-04 11:24:27	ga_ls8c_ard_3-2-1_110084_2022-12-04_final
2022-12-04 11:24:51	ga_ls8c_ard_3-2-1_110085_2022-12-04_final
2022-12-06 09:33:36	ga_ls8c_ard_3-2-1_092085_2022-12-06_final
2022-12-07 10:16:52	ga_ls8c_ard_3-2-1_099085_2022-12-07_final
2022-12-08 09:20:50	ga_ls8c_ard_3-2-1_090084_2022-12-07_final
2022-12-08 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-12-07_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2022-12-11 09:51:43	ga_ls8c_ard_3-2-1_095084_2022-12-11_final
2022-12-11 09:52:07	ga_ls8c_ard_3-2-1_095085_2022-12-11_final
2022-12-18 09:57:49	ga_ls8c_ard_3-2-1_096084_2022-12-18_final
2022-12-18 09:58:13	ga_ls8c_ard_3-2-1_096085_2022-12-18_final
2022-12-20 09:45:50	ga_ls8c_ard_3-2-1_094085_2022-12-20_final
2022-12-20 11:24:43	ga_ls8c_ard_3-2-1_110085_2022-12-20_final
2022-12-23 10:16:41	ga_ls8c_ard_3-2-1_099085_2022-12-23_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-24 09:21:04	ga_ls8c_ard_3-2-1_090085_2022-12-23_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2022-12-29 09:39:38	ga_ls8c_ard_3-2-1_093085_2022-12-29_final
2023-01-01 10:10:33	ga_ls8c_ard_3-2-1_098085_2023-01-01_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-03 09:58:11	ga_ls8c_ard_3-2-1_096085_2023-01-03_final
2023-02-03 09:14:30	ga_ls8c_ard_3-2-1_089084_2023-02-02_final
2023-06-19 10:03:01	ga_ls8c_ard_3-2-1_097084_2023-06-19_final
2023-06-19 10:03:25	ga_ls8c_ard_3-2-1_097085_2023-06-19_final
2023-06-19 11:41:54	ga_ls8c_ard_3-2-1_113084_2023-06-19_final
2023-06-21 09:50:40	ga_ls8c_ard_3-2-1_095084_2023-06-21_final
2023-06-21 09:51:04	ga_ls8c_ard_3-2-1_095085_2023-06-21_final
2023-06-21 11:29:33	ga_ls8c_ard_3-2-1_111084_2023-06-21_final
2023-06-23 09:38:18	ga_ls8c_ard_3-2-1_093084_2023-06-23_final
2023-06-23 09:38:42	ga_ls8c_ard_3-2-1_093085_2023-06-23_final
2023-06-23 11:17:11	ga_ls8c_ard_3-2-1_109084_2023-06-23_final
2023-06-24 10:21:35	ga_ls8c_ard_3-2-1_100084_2023-06-24_final
2023-06-25 09:26:23	ga_ls8c_ard_3-2-1_091085_2023-06-24_final
2023-06-26 10:09:16	ga_ls8c_ard_3-2-1_098084_2023-06-26_final
2023-06-26 10:09:40	ga_ls8c_ard_3-2-1_098085_2023-06-26_final
2023-06-27 09:13:39	ga_ls8c_ard_3-2-1_089084_2023-06-26_final
2023-06-27 09:14:03	ga_ls8c_ard_3-2-1_089085_2023-06-26_final
2023-06-28 09:56:56	ga_ls8c_ard_3-2-1_096084_2023-06-28_final
2023-06-28 09:57:20	ga_ls8c_ard_3-2-1_096085_2023-06-28_final
2023-06-30 09:44:36	ga_ls8c_ard_3-2-1_094084_2023-06-30_final
2023-06-30 09:45:00	ga_ls8c_ard_3-2-1_094085_2023-06-30_final
2023-06-30 11:23:29	ga_ls8c_ard_3-2-1_110084_2023-06-30_final
2023-06-30 11:23:53	ga_ls8c_ard_3-2-1_110085_2023-06-30_final
2023-07-02 09:32:16	ga_ls8c_ard_3-2-1_092084_2023-07-02_final
2023-07-02 09:32:40	ga_ls8c_ard_3-2-1_092085_2023-07-02_final
2023-07-02 11:11:09	ga_ls8c_ard_3-2-1_108084_2023-07-02_final
2023-07-03 10:15:33	ga_ls8c_ard_3-2-1_099084_2023-07-03_final
2023-07-03 10:15:57	ga_ls8c_ard_3-2-1_099085_2023-07-03_final
2023-07-04 09:19:56	ga_ls8c_ard_3-2-1_090084_2023-07-03_final
2023-07-04 09:20:20	ga_ls8c_ard_3-2-1_090085_2023-07-03_final
2023-07-05 10:03:12	ga_ls8c_ard_3-2-1_097084_2023-07-05_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