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
2018-02-13 09:58:35	ga_ls8c_ard_3-0-0_097072_2018-02-13_final
2018-02-13 09:58:59	ga_ls8c_ard_3-0-0_097073_2018-02-13_final
2018-02-13 09:59:23	ga_ls8c_ard_3-0-0_097074_2018-02-13_final
2018-02-13 09:59:47	ga_ls8c_ard_3-0-0_097075_2018-02-13_final
2018-02-13 10:00:11	ga_ls8c_ard_3-0-0_097076_2018-02-13_final
2018-02-13 10:00:35	ga_ls8c_ard_3-0-0_097077_2018-02-13_final
2018-02-13 10:00:59	ga_ls8c_ard_3-0-0_097078_2018-02-13_final
2018-02-15 09:49:48	ga_ls8c_ard_3-0-0_095081_2018-02-15_final
2018-02-15 09:50:12	ga_ls8c_ard_3-0-0_095082_2018-02-15_final
2018-02-15 09:50:36	ga_ls8c_ard_3-0-0_095083_2018-02-15_final
2018-02-15 09:51:00	ga_ls8c_ard_3-0-0_095084_2018-02-15_final
2018-02-15 09:51:24	ga_ls8c_ard_3-0-0_095085_2018-02-15_final
2018-02-15 09:51:48	ga_ls8c_ard_3-0-0_095086_2018-02-15_final
2018-04-16 10:08:26	ga_ls8c_ard_3-0-0_099067_2018-04-16_final
2018-04-16 10:08:50	ga_ls8c_ard_3-0-0_099068_2018-04-16_final
2018-04-18 09:58:03	ga_ls8c_ard_3-0-0_097072_2018-04-18_final
2018-04-18 09:58:27	ga_ls8c_ard_3-0-0_097073_2018-04-18_final
2018-04-18 09:58:51	ga_ls8c_ard_3-0-0_097074_2018-04-18_final
2018-04-18 09:59:15	ga_ls8c_ard_3-0-0_097075_2018-04-18_final
2018-04-18 09:59:39	ga_ls8c_ard_3-0-0_097076_2018-04-18_final
2018-04-18 10:00:02	ga_ls8c_ard_3-0-0_097077_2018-04-18_final
2018-04-18 10:00:26	ga_ls8c_ard_3-0-0_097078_2018-04-18_final
2018-08-31 10:02:30	ga_ls8c_ard_3-0-0_098067_2018-08-31_final
2018-08-31 10:02:54	ga_ls8c_ard_3-0-0_098068_2018-08-31_final
2018-08-31 10:03:18	ga_ls8c_ard_3-0-0_098069_2018-08-31_final
2018-08-31 10:03:42	ga_ls8c_ard_3-0-0_098070_2018-08-31_final
2018-08-31 10:04:06	ga_ls8c_ard_3-0-0_098071_2018-08-31_final
2018-08-31 10:04:29	ga_ls8c_ard_3-0-0_098072_2018-08-31_final
2018-08-31 10:04:53	ga_ls8c_ard_3-0-0_098073_2018-08-31_final
2018-09-02 09:54:08	ga_ls8c_ard_3-0-0_096077_2018-09-02_final
2018-09-02 09:54:32	ga_ls8c_ard_3-0-0_096078_2018-09-02_final
2018-09-02 09:54:56	ga_ls8c_ard_3-0-0_096079_2018-09-02_final
2018-09-02 09:55:20	ga_ls8c_ard_3-0-0_096080_2018-09-02_final
2018-09-02 09:55:44	ga_ls8c_ard_3-0-0_096081_2018-09-02_final
2018-09-02 09:56:08	ga_ls8c_ard_3-0-0_096082_2018-09-02_final
2018-10-06 09:45:11	ga_ls8c_ard_3-0-0_094085_2018-10-06_final
2018-10-06 09:45:35	ga_ls8c_ard_3-0-0_094086_2018-10-06_final
2018-10-06 09:45:59	ga_ls8c_ard_3-0-0_094087_2018-10-06_final
2018-10-06 09:46:23	ga_ls8c_ard_3-0-0_094088_2018-10-06_final
2018-10-09 10:08:56	ga_ls8c_ard_3-0-0_099067_2018-10-09_final
2018-10-09 10:09:20	ga_ls8c_ard_3-0-0_099068_2018-10-09_final
2018-10-18 10:02:48	ga_ls8c_ard_3-0-0_098067_2018-10-18_final
2018-10-18 10:03:12	ga_ls8c_ard_3-0-0_098068_2018-10-18_final
2018-10-18 10:03:36	ga_ls8c_ard_3-0-0_098069_2018-10-18_final
2018-10-18 10:04:00	ga_ls8c_ard_3-0-0_098070_2018-10-18_final
2018-10-18 10:04:24	ga_ls8c_ard_3-0-0_098071_2018-10-18_final
2018-10-18 10:04:48	ga_ls8c_ard_3-0-0_098072_2018-10-18_final
2018-10-18 10:05:12	ga_ls8c_ard_3-0-0_098073_2018-10-18_final
2018-10-20 09:54:27	ga_ls8c_ard_3-0-0_096077_2018-10-20_final
2018-10-20 09:54:51	ga_ls8c_ard_3-0-0_096078_2018-10-20_final
2018-10-20 09:55:15	ga_ls8c_ard_3-0-0_096079_2018-10-20_final
2018-10-20 09:55:38	ga_ls8c_ard_3-0-0_096080_2018-10-20_final
2018-10-20 09:56:02	ga_ls8c_ard_3-0-0_096081_2018-10-20_final
2018-10-20 09:56:26	ga_ls8c_ard_3-0-0_096082_2018-10-20_final
2018-12-25 09:45:17	ga_ls8c_ard_3-0-0_094085_2018-12-25_final
2018-12-25 09:45:41	ga_ls8c_ard_3-0-0_094086_2018-12-25_final
2018-12-25 09:46:05	ga_ls8c_ard_3-0-0_094087_2018-12-25_final
2018-12-25 09:46:29	ga_ls8c_ard_3-0-0_094088_2018-12-25_final
2018-12-28 10:09:00	ga_ls8c_ard_3-0-0_099067_2018-12-28_final
2018-12-28 10:09:24	ga_ls8c_ard_3-0-0_099068_2018-12-28_final
2019-01-26 09:45:12	ga_ls8c_ard_3-0-0_094085_2019-01-26_final
2019-01-26 09:45:36	ga_ls8c_ard_3-0-0_094086_2019-01-26_final
2019-01-26 09:46:00	ga_ls8c_ard_3-0-0_094087_2019-01-26_final
2019-01-26 09:46:24	ga_ls8c_ard_3-0-0_094088_2019-01-26_final
2019-01-29 10:08:54	ga_ls8c_ard_3-0-0_099067_2019-01-29_final
2019-01-29 10:09:18	ga_ls8c_ard_3-0-0_099068_2019-01-29_final
2023-10-09 09:59:43	ga_ls8c_ard_3-2-1_097074_2023-10-09_final
2023-10-09 10:00:06	ga_ls8c_ard_3-2-1_097075_2023-10-09_final
2023-10-09 10:01:18	ga_ls8c_ard_3-2-1_097078_2023-10-09_final
2023-10-16 10:05:30	ga_ls8c_ard_3-2-1_098073_2023-10-16_final
2023-10-18 09:54:44	ga_ls8c_ard_3-2-1_096077_2023-10-18_final
2023-10-18 09:55:08	ga_ls8c_ard_3-2-1_096078_2023-10-18_final
2023-10-18 09:55:32	ga_ls8c_ard_3-2-1_096079_2023-10-18_final
2023-10-18 09:55:56	ga_ls8c_ard_3-2-1_096080_2023-10-18_final
2023-10-18 09:56:19	ga_ls8c_ard_3-2-1_096081_2023-10-18_final
2023-10-18 09:56:43	ga_ls8c_ard_3-2-1_096082_2023-10-18_final
2023-10-20 09:45:33	ga_ls8c_ard_3-2-1_094085_2023-10-20_final
2023-10-20 09:45:57	ga_ls8c_ard_3-2-1_094086_2023-10-20_final
2023-10-20 09:46:21	ga_ls8c_ard_3-2-1_094087_2023-10-20_final
2023-10-25 09:58:57	ga_ls8c_ard_3-2-1_097072_2023-10-25_final
2023-10-25 09:59:21	ga_ls8c_ard_3-2-1_097073_2023-10-25_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-25 10:00:09	ga_ls8c_ard_3-2-1_097075_2023-10-25_final
2023-10-25 10:00:33	ga_ls8c_ard_3-2-1_097076_2023-10-25_final
2023-10-25 10:00:57	ga_ls8c_ard_3-2-1_097077_2023-10-25_final
2023-10-25 10:01:21	ga_ls8c_ard_3-2-1_097078_2023-10-25_final
2024-01-04 10:03:02	ga_ls8c_ard_3-2-1_098067_2024-01-04_final
2024-01-04 10:03:26	ga_ls8c_ard_3-2-1_098068_2024-01-04_final
2024-01-04 10:03:50	ga_ls8c_ard_3-2-1_098069_2024-01-04_final
2024-01-04 10:04:14	ga_ls8c_ard_3-2-1_098070_2024-01-04_final
2024-01-04 10:04:37	ga_ls8c_ard_3-2-1_098071_2024-01-04_final
2024-01-04 10:05:01	ga_ls8c_ard_3-2-1_098072_2024-01-04_final
2024-01-04 10:05:25	ga_ls8c_ard_3-2-1_098073_2024-01-04_final
2024-01-06 09:54:39	ga_ls8c_ard_3-2-1_096077_2024-01-06_final
2024-01-06 09:55:03	ga_ls8c_ard_3-2-1_096078_2024-01-06_final
2024-01-06 09:55:27	ga_ls8c_ard_3-2-1_096079_2024-01-06_final
2024-01-06 09:55:51	ga_ls8c_ard_3-2-1_096080_2024-01-06_final
2024-01-06 09:56:15	ga_ls8c_ard_3-2-1_096081_2024-01-06_final
2024-01-06 09:56:39	ga_ls8c_ard_3-2-1_096082_2024-01-06_final
2024-01-11 10:09:15	ga_ls8c_ard_3-2-1_099067_2024-01-11_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