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
2018-06-14 09:54:39	ga_ls8c_ard_3-0-0_096080_2018-06-14_final
2018-06-14 09:55:03	ga_ls8c_ard_3-0-0_096081_2018-06-14_final
2018-06-14 09:55:27	ga_ls8c_ard_3-0-0_096082_2018-06-14_final
2018-06-14 09:55:51	ga_ls8c_ard_3-0-0_096083_2018-06-14_final
2018-06-14 09:56:15	ga_ls8c_ard_3-0-0_096084_2018-06-14_final
2018-06-14 09:56:39	ga_ls8c_ard_3-0-0_096085_2018-06-14_final
2018-06-16 09:45:07	ga_ls8c_ard_3-0-0_094087_2018-06-16_final
2018-06-16 09:45:31	ga_ls8c_ard_3-0-0_094088_2018-06-16_final
2018-06-30 09:54:49	ga_ls8c_ard_3-0-0_096080_2018-06-30_final
2018-06-30 09:55:13	ga_ls8c_ard_3-0-0_096081_2018-06-30_final
2018-06-30 09:55:37	ga_ls8c_ard_3-0-0_096082_2018-06-30_final
2018-06-30 09:56:01	ga_ls8c_ard_3-0-0_096083_2018-06-30_final
2018-06-30 09:56:25	ga_ls8c_ard_3-0-0_096084_2018-06-30_final
2018-06-30 09:56:49	ga_ls8c_ard_3-0-0_096085_2018-06-30_final
2018-07-02 09:45:16	ga_ls8c_ard_3-0-0_094087_2018-07-02_final
2018-07-02 09:45:40	ga_ls8c_ard_3-0-0_094088_2018-07-02_final
2018-07-16 09:54:57	ga_ls8c_ard_3-0-0_096080_2018-07-16_final
2018-07-16 09:55:21	ga_ls8c_ard_3-0-0_096081_2018-07-16_final
2018-07-16 09:55:45	ga_ls8c_ard_3-0-0_096082_2018-07-16_final
2018-07-18 09:45:24	ga_ls8c_ard_3-0-0_094087_2018-07-18_final
2018-07-18 09:45:48	ga_ls8c_ard_3-0-0_094088_2018-07-18_final
2018-08-03 09:45:32	ga_ls8c_ard_3-0-0_094087_2018-08-03_final
2018-08-03 09:45:56	ga_ls8c_ard_3-0-0_094088_2018-08-03_final
2018-08-17 09:55:13	ga_ls8c_ard_3-0-0_096080_2018-08-17_final
2018-08-17 09:55:37	ga_ls8c_ard_3-0-0_096081_2018-08-17_final
2018-08-17 09:56:01	ga_ls8c_ard_3-0-0_096082_2018-08-17_final
2018-08-17 09:56:25	ga_ls8c_ard_3-0-0_096083_2018-08-17_final
2018-08-17 09:56:49	ga_ls8c_ard_3-0-0_096084_2018-08-17_final
2018-08-17 09:57:13	ga_ls8c_ard_3-0-0_096085_2018-08-17_final
2018-08-19 09:45:40	ga_ls8c_ard_3-0-0_094087_2018-08-19_final
2018-08-19 09:46:04	ga_ls8c_ard_3-0-0_094088_2018-08-19_final
2018-08-26 09:50:42	ga_ls8c_ard_3-0-0_095084_2018-08-26_final
2018-08-26 09:51:06	ga_ls8c_ard_3-0-0_095085_2018-08-26_final
2018-08-26 09:51:30	ga_ls8c_ard_3-0-0_095086_2018-08-26_final
2018-08-26 09:51:54	ga_ls8c_ard_3-0-0_095087_2018-08-26_final
2018-08-26 09:52:18	ga_ls8c_ard_3-0-0_095088_2018-08-26_final
2018-08-29 10:14:51	ga_ls8c_ard_3-0-0_100067_2018-08-29_final
2018-09-16 10:04:10	ga_ls8c_ard_3-0-0_098071_2018-09-16_final
2018-09-16 10:04:34	ga_ls8c_ard_3-0-0_098072_2018-09-16_final
2018-09-16 10:04:58	ga_ls8c_ard_3-0-0_098073_2018-09-16_final
2018-09-16 10:05:22	ga_ls8c_ard_3-0-0_098074_2018-09-16_final
2018-09-16 10:05:46	ga_ls8c_ard_3-0-0_098075_2018-09-16_final
2018-09-16 10:06:10	ga_ls8c_ard_3-0-0_098076_2018-09-16_final
2018-09-16 10:06:34	ga_ls8c_ard_3-0-0_098077_2018-09-16_final
2018-10-04 09:55:32	ga_ls8c_ard_3-0-0_096080_2018-10-04_final
2018-10-04 09:55:56	ga_ls8c_ard_3-0-0_096081_2018-10-04_final
2018-10-04 09:56:20	ga_ls8c_ard_3-0-0_096082_2018-10-04_final
2018-10-04 09:56:44	ga_ls8c_ard_3-0-0_096083_2018-10-04_final
2018-10-04 09:57:08	ga_ls8c_ard_3-0-0_096084_2018-10-04_final
2018-10-04 09:57:32	ga_ls8c_ard_3-0-0_096085_2018-10-04_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
2018-11-05 09:55:42	ga_ls8c_ard_3-0-0_096080_2018-11-05_final
2018-11-05 09:56:06	ga_ls8c_ard_3-0-0_096081_2018-11-05_final
2018-11-05 09:56:30	ga_ls8c_ard_3-0-0_096082_2018-11-05_final
2018-11-05 09:56:54	ga_ls8c_ard_3-0-0_096083_2018-11-05_final
2018-11-05 09:57:18	ga_ls8c_ard_3-0-0_096084_2018-11-05_final
2018-11-05 09:57:42	ga_ls8c_ard_3-0-0_096085_2018-11-05_final
2018-11-07 09:46:08	ga_ls8c_ard_3-0-0_094087_2018-11-07_final
2018-11-07 09:46:32	ga_ls8c_ard_3-0-0_094088_2018-11-07_final
2018-12-23 09:55:39	ga_ls8c_ard_3-0-0_096080_2018-12-23_final
2018-12-23 09:56:03	ga_ls8c_ard_3-0-0_096081_2018-12-23_final
2018-12-23 09:56:27	ga_ls8c_ard_3-0-0_096082_2018-12-23_final
2018-12-23 09:56:51	ga_ls8c_ard_3-0-0_096083_2018-12-23_final
2018-12-23 09:57:15	ga_ls8c_ard_3-0-0_096084_2018-12-23_final
2018-12-23 09:57:39	ga_ls8c_ard_3-0-0_096085_2018-12-23_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
2019-01-06 10:04:25	ga_ls8c_ard_3-0-0_098071_2019-01-06_final
2019-01-06 10:04:48	ga_ls8c_ard_3-0-0_098072_2019-01-06_final
2019-01-06 10:05:12	ga_ls8c_ard_3-0-0_098073_2019-01-06_final
2019-01-06 10:05:36	ga_ls8c_ard_3-0-0_098074_2019-01-06_final
2019-01-06 10:06:00	ga_ls8c_ard_3-0-0_098075_2019-01-06_final
2019-01-06 10:06:24	ga_ls8c_ard_3-0-0_098076_2019-01-06_final
2019-01-06 10:06:48	ga_ls8c_ard_3-0-0_098077_2019-01-06_final
2023-08-22 09:59:57	ga_ls8c_ard_3-2-1_097075_2023-08-22_final
2023-08-22 10:00:21	ga_ls8c_ard_3-2-1_097076_2023-08-22_final
2023-08-22 10:00:44	ga_ls8c_ard_3-2-1_097077_2023-08-22_final
2023-08-22 10:01:08	ga_ls8c_ard_3-2-1_097078_2023-08-22_final
2023-08-22 10:01:32	ga_ls8c_ard_3-2-1_097079_2023-08-22_final
2023-08-22 10:01:56	ga_ls8c_ard_3-2-1_097080_2023-08-22_final
2023-08-22 10:02:20	ga_ls8c_ard_3-2-1_097081_2023-08-22_final
2023-08-29 10:04:33	ga_ls8c_ard_3-2-1_098071_2023-08-29_final
2023-08-29 10:04:57	ga_ls8c_ard_3-2-1_098072_2023-08-29_final
2023-08-29 10:05:21	ga_ls8c_ard_3-2-1_098073_2023-08-29_final
2023-08-29 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-08-29_final
2023-08-29 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-08-29_final
2023-08-29 10:06:32	ga_ls8c_ard_3-2-1_098076_2023-08-29_final
2023-08-31 09:55:46	ga_ls8c_ard_3-2-1_096080_2023-08-31_final
2023-08-31 09:56:10	ga_ls8c_ard_3-2-1_096081_2023-08-31_final
2023-08-31 09:56:34	ga_ls8c_ard_3-2-1_096082_2023-08-31_final
2023-08-31 09:56:58	ga_ls8c_ard_3-2-1_096083_2023-08-31_final
2023-08-31 09:57:22	ga_ls8c_ard_3-2-1_096084_2023-08-31_final
2023-08-31 09:57:46	ga_ls8c_ard_3-2-1_096085_2023-08-31_final
2023-09-05 10:08:42	ga_ls8c_ard_3-2-1_099066_2023-09-05_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-05 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-09-05_final
2023-09-05 10:09:54	ga_ls8c_ard_3-2-1_099069_2023-09-05_final
2023-09-05 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-09-05_final
2023-09-05 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-09-05_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