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
2018-06-20 10:58:07	ga_ls8c_ard_3-0-0_106084_2018-06-20_final
2018-06-21 10:02:31	ga_ls8c_ard_3-0-0_097084_2018-06-21_final
2018-06-21 10:02:54	ga_ls8c_ard_3-0-0_097085_2018-06-21_final
2018-06-21 11:41:24	ga_ls8c_ard_3-0-0_113084_2018-06-21_final
2018-06-22 09:06:54	ga_ls8c_ard_3-1-0_088084_2018-06-21_final
2018-07-02 09:44:05	ga_ls8c_ard_3-1-0_094084_2018-07-02_final
2018-07-02 09:44:28	ga_ls8c_ard_3-0-0_094085_2018-07-02_final
2018-07-02 11:22:58	ga_ls8c_ard_3-0-0_110084_2018-07-02_final
2018-07-02 11:23:22	ga_ls8c_ard_3-0-0_110085_2018-07-02_final
2018-07-03 10:27:21	ga_ls8c_ard_3-0-0_101084_2018-07-03_final
2018-07-04 09:31:44	ga_ls8c_ard_3-0-0_092084_2018-07-04_final
2018-07-04 09:32:08	ga_ls8c_ard_3-0-0_092085_2018-07-04_final
2018-07-04 11:10:37	ga_ls8c_ard_3-0-0_108084_2018-07-04_final
2018-07-04 11:11:01	ga_ls8c_ard_3-0-0_108085_2018-07-04_final
2018-07-05 10:15:00	ga_ls8c_ard_3-0-0_099084_2018-07-05_final
2018-07-05 10:15:24	ga_ls8c_ard_3-0-0_099085_2018-07-05_final
2018-07-06 09:19:23	ga_ls8c_ard_3-0-0_090084_2018-07-05_final
2018-07-06 09:19:47	ga_ls8c_ard_3-0-0_090085_2018-07-05_final
2018-07-06 10:58:16	ga_ls8c_ard_3-0-0_106084_2018-07-06_final
2018-07-07 10:02:40	ga_ls8c_ard_3-0-0_097084_2018-07-07_final
2018-07-07 10:03:03	ga_ls8c_ard_3-0-0_097085_2018-07-07_final
2018-07-07 11:41:33	ga_ls8c_ard_3-0-0_113084_2018-07-07_final
2018-07-08 09:07:03	ga_ls8c_ard_3-0-0_088084_2018-07-07_final
2018-07-20 09:31:51	ga_ls8c_ard_3-0-0_092084_2018-07-20_final
2018-07-20 09:32:15	ga_ls8c_ard_3-0-0_092085_2018-07-20_final
2018-07-20 11:10:44	ga_ls8c_ard_3-0-0_108084_2018-07-20_final
2018-07-20 11:11:08	ga_ls8c_ard_3-0-0_108085_2018-07-20_final
2018-07-21 10:15:07	ga_ls8c_ard_3-0-0_099084_2018-07-21_final
2018-07-21 10:15:31	ga_ls8c_ard_3-0-0_099085_2018-07-21_final
2018-07-22 09:19:30	ga_ls8c_ard_3-0-0_090084_2018-07-21_final
2018-07-22 09:19:54	ga_ls8c_ard_3-0-0_090085_2018-07-21_final
2018-07-22 10:58:23	ga_ls8c_ard_3-0-0_106084_2018-07-22_final
2018-07-23 10:02:46	ga_ls8c_ard_3-0-0_097084_2018-07-23_final
2018-07-23 10:03:10	ga_ls8c_ard_3-0-0_097085_2018-07-23_final
2018-07-23 11:41:39	ga_ls8c_ard_3-0-0_113084_2018-07-23_final
2018-07-24 09:07:09	ga_ls8c_ard_3-0-0_088084_2018-07-23_final
2018-08-05 09:32:23	ga_ls8c_ard_3-0-0_092085_2018-08-05_final
2018-08-05 11:10:52	ga_ls8c_ard_3-0-0_108084_2018-08-05_final
2018-08-05 11:11:16	ga_ls8c_ard_3-0-0_108085_2018-08-05_final
2018-08-06 10:15:16	ga_ls8c_ard_3-0-0_099084_2018-08-06_final
2018-08-06 10:15:40	ga_ls8c_ard_3-0-0_099085_2018-08-06_final
2018-08-07 09:19:39	ga_ls8c_ard_3-0-0_090084_2018-08-06_final
2018-08-07 09:20:03	ga_ls8c_ard_3-0-0_090085_2018-08-06_final
2018-08-10 09:50:59	ga_ls8c_ard_3-0-0_095085_2018-08-10_final
2018-08-10 11:29:28	ga_ls8c_ard_3-0-0_111084_2018-08-10_final
2018-08-10 11:29:52	ga_ls8c_ard_3-0-0_111085_2018-08-10_final
2018-08-12 09:38:14	ga_ls8c_ard_3-0-0_093084_2018-08-12_final
2018-08-12 09:38:38	ga_ls8c_ard_3-0-0_093085_2018-08-12_final
2018-08-12 11:17:07	ga_ls8c_ard_3-0-0_109084_2018-08-12_final
2018-08-12 11:17:31	ga_ls8c_ard_3-0-0_109085_2018-08-12_final
2018-08-13 10:21:54	ga_ls8c_ard_3-0-0_100085_2018-08-13_final
2018-08-21 09:32:08	ga_ls8c_ard_3-0-0_092084_2018-08-21_final
2018-08-21 09:32:32	ga_ls8c_ard_3-0-0_092085_2018-08-21_final
2018-08-21 11:11:01	ga_ls8c_ard_3-0-0_108084_2018-08-21_final
2018-08-21 11:11:25	ga_ls8c_ard_3-0-0_108085_2018-08-21_final
2018-08-22 10:15:48	ga_ls8c_ard_3-0-0_099085_2018-08-22_final
2018-08-23 09:19:47	ga_ls8c_ard_3-0-0_090084_2018-08-22_final
2018-08-23 09:20:11	ga_ls8c_ard_3-0-0_090085_2018-08-22_final
2018-08-23 10:58:40	ga_ls8c_ard_3-0-0_106084_2018-08-23_final
2018-08-24 10:03:03	ga_ls8c_ard_3-0-0_097084_2018-08-24_final
2018-08-24 10:03:27	ga_ls8c_ard_3-0-0_097085_2018-08-24_final
2018-08-24 11:41:56	ga_ls8c_ard_3-0-0_113084_2018-08-24_final
2018-08-25 09:07:26	ga_ls8c_ard_3-0-0_088084_2018-08-24_final
2018-09-02 09:56:56	ga_ls8c_ard_3-0-0_096084_2018-09-02_final
2018-09-02 09:57:20	ga_ls8c_ard_3-0-0_096085_2018-09-02_final
2018-09-02 11:35:49	ga_ls8c_ard_3-0-0_112084_2018-09-02_final
2018-09-02 11:36:13	ga_ls8c_ard_3-0-0_112085_2018-09-02_final
2018-09-04 09:44:35	ga_ls8c_ard_3-0-0_094084_2018-09-04_final
2018-09-04 09:44:59	ga_ls8c_ard_3-0-0_094085_2018-09-04_final
2018-09-04 11:23:28	ga_ls8c_ard_3-0-0_110084_2018-09-04_final
2018-09-04 11:23:52	ga_ls8c_ard_3-0-0_110085_2018-09-04_final
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
2022-08-19 10:04:05	ga_ls8c_ard_3-2-1_097084_2022-08-19_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-08-21 09:51:44	ga_ls8c_ard_3-2-1_095084_2022-08-21_final
2022-08-21 09:52:08	ga_ls8c_ard_3-2-1_095085_2022-08-21_final
2022-09-24 09:39:29	ga_ls8c_ard_3-2-1_093084_2022-09-24_final
2022-09-24 09:39:53	ga_ls8c_ard_3-2-1_093085_2022-09-24_final
2022-10-03 09:33:17	ga_ls8c_ard_3-2-1_092084_2022-10-03_final
2022-10-03 09:33:40	ga_ls8c_ard_3-2-1_092085_2022-10-03_final
2022-10-04 10:16:32	ga_ls8c_ard_3-2-1_099084_2022-10-04_final
2022-10-04 10:16:56	ga_ls8c_ard_3-2-1_099085_2022-10-04_final
2022-10-05 09:20:54	ga_ls8c_ard_3-2-1_090084_2022-10-04_final
2022-10-05 09:21:18	ga_ls8c_ard_3-2-1_090085_2022-10-04_final
2022-10-06 10:04:09	ga_ls8c_ard_3-2-1_097084_2022-10-06_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-07 11:43:04	ga_ls8c_ard_3-2-1_113084_2022-11-07_final
2023-09-02 09:45:00	ga_ls8c_ard_3-2-1_094084_2023-09-02_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-10-02 09:57:30	ga_ls8c_ard_3-2-1_096084_2023-10-02_final
2023-10-02 09:57:54	ga_ls8c_ard_3-2-1_096085_2023-10-02_final
2023-10-02 11:36:23	ga_ls8c_ard_3-2-1_112084_2023-10-02_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