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
2018-02-10 09:32:53	ga_ls8c_ard_3-0-0_092085_2018-02-10_final
2018-02-10 11:11:46	ga_ls8c_ard_3-0-0_108085_2018-02-10_final
2018-02-11 10:16:09	ga_ls8c_ard_3-0-0_099085_2018-02-11_final
2018-02-12 09:20:31	ga_ls8c_ard_3-0-0_090085_2018-02-11_final
2018-02-13 10:03:46	ga_ls8c_ard_3-0-0_097085_2018-02-13_final
2018-04-18 10:03:14	ga_ls8c_ard_3-0-0_097085_2018-04-18_final
2018-05-26 09:25:45	ga_ls8c_ard_3-0-0_091085_2018-05-25_final
2018-05-26 11:04:37	ga_ls8c_ard_3-0-0_107085_2018-05-26_final
2018-06-04 10:57:57	ga_ls8c_ard_3-0-0_106084_2018-06-04_final
2018-06-05 10:02:44	ga_ls8c_ard_3-0-0_097085_2018-06-05_final
2018-06-18 09:31:58	ga_ls8c_ard_3-0-0_092085_2018-06-18_final
2018-06-18 11:10:51	ga_ls8c_ard_3-0-0_108085_2018-06-18_final
2018-06-19 10:15:15	ga_ls8c_ard_3-0-0_099085_2018-06-19_final
2018-06-20 09:19:38	ga_ls8c_ard_3-0-0_090085_2018-06-19_final
2018-06-21 10:02:54	ga_ls8c_ard_3-0-0_097085_2018-06-21_final
2018-06-22 09:06:54	ga_ls8c_ard_3-1-0_088084_2018-06-21_final
2018-07-04 09:32:08	ga_ls8c_ard_3-0-0_092085_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 09:19:47	ga_ls8c_ard_3-0-0_090085_2018-07-05_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 10:15:31	ga_ls8c_ard_3-0-0_099085_2018-07-21_final
2018-07-22 09:19:54	ga_ls8c_ard_3-0-0_090085_2018-07-21_final
2018-07-23 10:03:10	ga_ls8c_ard_3-0-0_097085_2018-07-23_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 09:20:11	ga_ls8c_ard_3-0-0_090085_2018-08-22_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
2018-08-25 09:07:26	ga_ls8c_ard_3-0-0_088084_2018-08-24_final
2018-08-31 10:09:41	ga_ls8c_ard_3-0-0_098085_2018-08-31_final
2018-09-01 09:13:40	ga_ls8c_ard_3-0-0_089084_2018-08-31_final
2018-09-01 09:14:04	ga_ls8c_ard_3-0-0_089085_2018-08-31_final
2018-09-06 09:32:38	ga_ls8c_ard_3-0-0_092085_2018-09-06_final
2018-09-06 11:11:07	ga_ls8c_ard_3-0-0_108084_2018-09-06_final
2018-09-06 11:11:31	ga_ls8c_ard_3-0-0_108085_2018-09-06_final
2018-09-07 10:15:30	ga_ls8c_ard_3-0-0_099084_2018-09-07_final
2018-09-07 10:15:54	ga_ls8c_ard_3-0-0_099085_2018-09-07_final
2018-09-08 09:20:17	ga_ls8c_ard_3-0-0_090085_2018-09-07_final
2018-09-09 10:03:33	ga_ls8c_ard_3-0-0_097085_2018-09-09_final
2018-09-09 11:42:02	ga_ls8c_ard_3-0-0_113084_2018-09-09_final
2018-09-16 10:09:45	ga_ls8c_ard_3-0-0_098085_2018-09-16_final
2018-09-17 09:14:08	ga_ls8c_ard_3-0-0_089085_2018-09-16_final
2019-01-06 10:10:00	ga_ls8c_ard_3-0-0_098085_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-07 10:10:13	ga_ls8c_ard_3-2-1_098085_2022-06-07_final
2022-06-08 09:14:36	ga_ls8c_ard_3-2-1_089085_2022-06-07_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2022-07-29 09:45:48	ga_ls8c_ard_3-2-1_094085_2022-07-29_final
2022-07-29 11:24:41	ga_ls8c_ard_3-2-1_110085_2022-07-29_final
2022-07-31 09:33:28	ga_ls8c_ard_3-2-1_092085_2022-07-31_final
2022-08-05 09:52:03	ga_ls8c_ard_3-2-1_095085_2022-08-05_final
2022-08-14 09:45:56	ga_ls8c_ard_3-2-1_094085_2022-08-14_final
2022-08-14 11:24:49	ga_ls8c_ard_3-2-1_110085_2022-08-14_final
2022-08-16 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-08-16_final
2022-08-30 09:45:57	ga_ls8c_ard_3-2-1_094085_2022-08-30_final
2022-08-30 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-08-30_final
2022-09-01 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-09-01_final
2022-09-02 10:16:50	ga_ls8c_ard_3-2-1_099085_2022-09-02_final
2022-09-29 09:58:25	ga_ls8c_ard_3-2-1_096085_2022-09-29_final
2022-10-01 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-10-01_final
2022-10-01 11:24:56	ga_ls8c_ard_3-2-1_110085_2022-10-01_final
2022-10-03 09:33:40	ga_ls8c_ard_3-2-1_092085_2022-10-03_final
2022-10-04 10:16:56	ga_ls8c_ard_3-2-1_099085_2022-10-04_final
2022-10-05 09:21:18	ga_ls8c_ard_3-2-1_090085_2022-10-04_final
2022-10-06 10:04:33	ga_ls8c_ard_3-2-1_097085_2022-10-06_final
2022-10-08 09:52:10	ga_ls8c_ard_3-2-1_095085_2022-10-08_final
2022-10-10 09:39:47	ga_ls8c_ard_3-2-1_093085_2022-10-10_final
2022-10-12 09:27:23	ga_ls8c_ard_3-2-1_091085_2022-10-11_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2022-10-17 11:24:50	ga_ls8c_ard_3-2-1_110085_2022-10-17_final
2022-10-19 09:33:37	ga_ls8c_ard_3-2-1_092085_2022-10-19_final
2022-10-20 10:16:53	ga_ls8c_ard_3-2-1_099085_2022-10-20_final
2022-10-21 09:21:16	ga_ls8c_ard_3-2-1_090085_2022-10-20_final
2022-10-22 10:04:32	ga_ls8c_ard_3-2-1_097085_2022-10-22_final
2022-10-24 09:52:12	ga_ls8c_ard_3-2-1_095085_2022-10-24_final
2022-10-26 09:39:51	ga_ls8c_ard_3-2-1_093085_2022-10-26_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-10-30 09:15:09	ga_ls8c_ard_3-2-1_089085_2022-10-29_final
2023-01-21 11:24:37	ga_ls8c_ard_3-2-1_110085_2023-01-21_final
2023-01-23 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-01-23_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-02 10:10:31	ga_ls8c_ard_3-2-1_098085_2023-02-02_final
2023-02-03 09:14:53	ga_ls8c_ard_3-2-1_089085_2023-02-02_final
2023-02-04 09:58:09	ga_ls8c_ard_3-2-1_096085_2023-02-04_final
2023-02-06 09:45:47	ga_ls8c_ard_3-2-1_094085_2023-02-06_final
2023-02-06 11:24:40	ga_ls8c_ard_3-2-1_110085_2023-02-06_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-02-11 10:04:16	ga_ls8c_ard_3-2-1_097085_2023-02-11_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-02-20 09:57:57	ga_ls8c_ard_3-2-1_096085_2023-02-20_final
2023-02-22 11:24:25	ga_ls8c_ard_3-2-1_110085_2023-02-22_final
2023-02-24 09:33:08	ga_ls8c_ard_3-2-1_092085_2023-02-24_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