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
2015-08-30 10:08:56	ga_ls8c_ard_3-0-0_099067_2015-08-30_final
2015-08-30 10:09:20	ga_ls8c_ard_3-0-0_099068_2015-08-30_final
2015-08-30 10:09:44	ga_ls8c_ard_3-0-0_099069_2015-08-30_final
2015-08-30 10:10:08	ga_ls8c_ard_3-0-0_099070_2015-08-30_final
2015-08-30 10:10:32	ga_ls8c_ard_3-0-0_099071_2015-08-30_final
2015-09-01 09:59:46	ga_ls8c_ard_3-0-0_097075_2015-09-01_final
2015-09-01 10:00:10	ga_ls8c_ard_3-0-0_097076_2015-09-01_final
2015-09-01 10:00:34	ga_ls8c_ard_3-0-0_097077_2015-09-01_final
2015-09-01 10:00:58	ga_ls8c_ard_3-0-0_097078_2015-09-01_final
2015-09-01 10:01:22	ga_ls8c_ard_3-0-0_097079_2015-09-01_final
2015-09-01 10:01:46	ga_ls8c_ard_3-0-0_097080_2015-09-01_final
2015-09-01 10:02:10	ga_ls8c_ard_3-0-0_097081_2015-09-01_final
2015-10-21 09:50:51	ga_ls8c_ard_3-0-0_095083_2015-10-21_final
2015-10-21 09:51:15	ga_ls8c_ard_3-0-0_095084_2015-10-21_final
2015-10-21 09:51:39	ga_ls8c_ard_3-0-0_095085_2015-10-21_final
2015-10-21 09:52:03	ga_ls8c_ard_3-0-0_095086_2015-10-21_final
2015-10-21 09:52:27	ga_ls8c_ard_3-0-0_095087_2015-10-21_final
2015-10-21 09:52:51	ga_ls8c_ard_3-0-0_095088_2015-10-21_final
2015-10-24 10:15:23	ga_ls8c_ard_3-0-0_100067_2015-10-24_final
2018-10-04 09:55:08	ga_ls8c_ard_3-0-0_096079_2018-10-04_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
2018-10-20 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
2018-10-20 09:56:50	ga_ls8c_ard_3-0-0_096083_2018-10-20_final
2018-10-20 09:57:14	ga_ls8c_ard_3-0-0_096084_2018-10-20_final
2018-10-20 09:57:38	ga_ls8c_ard_3-0-0_096085_2018-10-20_final
2018-10-22 09:46:05	ga_ls8c_ard_3-0-0_094087_2018-10-22_final
2018-10-22 09:46:29	ga_ls8c_ard_3-0-0_094088_2018-10-22_final
2019-11-17 09:51:08	ga_ls8c_ard_3-1-0_095083_2019-11-17_final
2019-11-17 09:51:32	ga_ls8c_ard_3-1-0_095084_2019-11-17_final
2019-11-17 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-11-17_final
2019-11-17 09:52:20	ga_ls8c_ard_3-1-0_095086_2019-11-17_final
2019-11-17 09:52:44	ga_ls8c_ard_3-1-0_095087_2019-11-17_final
2019-11-17 09:53:08	ga_ls8c_ard_3-1-0_095088_2019-11-17_final
2019-11-20 10:15:38	ga_ls8c_ard_3-1-0_100067_2019-11-20_final
2019-12-03 09:51:07	ga_ls8c_ard_3-1-0_095083_2019-12-03_final
2019-12-03 09:51:31	ga_ls8c_ard_3-1-0_095084_2019-12-03_final
2019-12-03 09:51:55	ga_ls8c_ard_3-1-0_095085_2019-12-03_final
2019-12-03 09:52:18	ga_ls8c_ard_3-1-0_095086_2019-12-03_final
2019-12-03 09:52:42	ga_ls8c_ard_3-1-0_095087_2019-12-03_final
2019-12-03 09:53:06	ga_ls8c_ard_3-1-0_095088_2019-12-03_final
2019-12-06 10:15:37	ga_ls8c_ard_3-1-0_100067_2019-12-06_final
2020-01-04 09:51:00	ga_ls8c_ard_3-1-0_095083_2020-01-04_final
2020-01-04 09:51:24	ga_ls8c_ard_3-1-0_095084_2020-01-04_final
2020-01-04 09:51:48	ga_ls8c_ard_3-1-0_095085_2020-01-04_final
2020-01-04 09:52:12	ga_ls8c_ard_3-1-0_095086_2020-01-04_final
2020-01-04 09:52:36	ga_ls8c_ard_3-1-0_095087_2020-01-04_final
2020-01-04 09:53:00	ga_ls8c_ard_3-1-0_095088_2020-01-04_final
2020-01-07 10:15:31	ga_ls8c_ard_3-1-0_100067_2020-01-07_final
2023-11-08 10:08:53	ga_ls8c_ard_3-2-1_099066_2023-11-08_final
2023-11-08 10:09:17	ga_ls8c_ard_3-2-1_099067_2023-11-08_final
2023-11-08 10:09:41	ga_ls8c_ard_3-2-1_099068_2023-11-08_final
2023-11-08 10:10:05	ga_ls8c_ard_3-2-1_099069_2023-11-08_final
2023-11-08 10:10:29	ga_ls8c_ard_3-2-1_099070_2023-11-08_final
2023-11-08 10:10:53	ga_ls8c_ard_3-2-1_099071_2023-11-08_final
2023-11-10 10:00:05	ga_ls8c_ard_3-2-1_097075_2023-11-10_final
2023-11-10 10:00:29	ga_ls8c_ard_3-2-1_097076_2023-11-10_final
2023-11-10 10:00:53	ga_ls8c_ard_3-2-1_097077_2023-11-10_final
2023-11-10 10:01:17	ga_ls8c_ard_3-2-1_097078_2023-11-10_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-10 10:02:04	ga_ls8c_ard_3-2-1_097080_2023-11-10_final
2023-11-10 10:02:28	ga_ls8c_ard_3-2-1_097081_2023-11-10_final
2023-11-12 09:50:57	ga_ls8c_ard_3-2-1_095083_2023-11-12_final
2023-11-12 09:51:21	ga_ls8c_ard_3-2-1_095084_2023-11-12_final
2023-11-12 09:51:45	ga_ls8c_ard_3-2-1_095085_2023-11-12_final
2023-11-12 09:52:09	ga_ls8c_ard_3-2-1_095086_2023-11-12_final
2023-11-12 09:52:32	ga_ls8c_ard_3-2-1_095087_2023-11-12_final
2023-12-03 10:04:43	ga_ls8c_ard_3-2-1_098071_2023-12-03_final
2023-12-03 10:05:07	ga_ls8c_ard_3-2-1_098072_2023-12-03_final
2023-12-03 10:05:30	ga_ls8c_ard_3-2-1_098073_2023-12-03_final
2023-12-03 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-12-03_final
2023-12-03 10:06:18	ga_ls8c_ard_3-2-1_098075_2023-12-03_final
2023-12-03 10:06:42	ga_ls8c_ard_3-2-1_098076_2023-12-03_final
2023-12-05 09:55:30	ga_ls8c_ard_3-2-1_096079_2023-12-05_final
2023-12-05 09:55:54	ga_ls8c_ard_3-2-1_096080_2023-12-05_final
2023-12-05 09:56:18	ga_ls8c_ard_3-2-1_096081_2023-12-05_final
2023-12-05 09:56:42	ga_ls8c_ard_3-2-1_096082_2023-12-05_final
2023-12-05 09:57:06	ga_ls8c_ard_3-2-1_096083_2023-12-05_final
2023-12-05 09:57:30	ga_ls8c_ard_3-2-1_096084_2023-12-05_final
2023-12-05 09:57:54	ga_ls8c_ard_3-2-1_096085_2023-12-05_final
2023-12-07 09:46:18	ga_ls8c_ard_3-2-1_094087_2023-12-07_final
2024-05-20 09:59:28	ga_ls8c_ard_3-2-1_097076_2024-05-20_nrt
2024-05-20 09:59:52	ga_ls8c_ard_3-2-1_097077_2024-05-20_nrt
2024-05-20 10:00:16	ga_ls8c_ard_3-2-1_097078_2024-05-20_nrt
2024-05-20 10:00:40	ga_ls8c_ard_3-2-1_097079_2024-05-20_nrt
2024-05-20 10:01:04	ga_ls8c_ard_3-2-1_097080_2024-05-20_nrt
2024-05-20 10:01:28	ga_ls8c_ard_3-2-1_097081_2024-05-20_nrt
2024-05-22 09:49:53	ga_ls8c_ard_3-2-1_095083_2024-05-22_nrt
2024-05-22 09:50:17	ga_ls8c_ard_3-2-1_095084_2024-05-22_nrt
2024-05-22 09:50:41	ga_ls8c_ard_3-2-1_095085_2024-05-22_nrt
2024-05-22 09:51:05	ga_ls8c_ard_3-2-1_095086_2024-05-22_nrt

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