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
2018-09-16 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
2018-09-16 10:06:58	ga_ls8c_ard_3-0-0_098078_2018-09-16_final
2018-09-16 10:07:22	ga_ls8c_ard_3-0-0_098079_2018-09-16_final
2018-09-16 10:07:46	ga_ls8c_ard_3-0-0_098080_2018-09-16_final
2018-09-16 10:08:10	ga_ls8c_ard_3-0-0_098081_2018-09-16_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
2019-01-06 10:07:12	ga_ls8c_ard_3-0-0_098078_2019-01-06_final
2019-01-06 10:07:36	ga_ls8c_ard_3-0-0_098079_2019-01-06_final
2019-01-06 10:08:00	ga_ls8c_ard_3-0-0_098080_2019-01-06_final
2019-01-06 10:08:24	ga_ls8c_ard_3-0-0_098081_2019-01-06_final
2019-10-28 10:11:07	ga_ls8c_ard_3-1-0_099071_2019-10-28_final
2019-10-28 10:11:31	ga_ls8c_ard_3-1-0_099072_2019-10-28_final
2019-10-28 10:11:55	ga_ls8c_ard_3-1-0_099073_2019-10-28_final
2019-10-28 10:12:19	ga_ls8c_ard_3-1-0_099074_2019-10-28_final
2019-10-28 10:12:43	ga_ls8c_ard_3-1-0_099075_2019-10-28_final
2019-10-28 10:13:07	ga_ls8c_ard_3-1-0_099076_2019-10-28_final
2019-10-28 10:13:31	ga_ls8c_ard_3-1-0_099077_2019-10-28_final
2019-10-30 10:02:21	ga_ls8c_ard_3-1-0_097080_2019-10-30_final
2019-10-30 10:02:45	ga_ls8c_ard_3-1-0_097081_2019-10-30_final
2019-10-30 10:03:09	ga_ls8c_ard_3-1-0_097082_2019-10-30_final
2019-10-30 10:03:33	ga_ls8c_ard_3-1-0_097083_2019-10-30_final
2019-10-30 10:03:57	ga_ls8c_ard_3-1-0_097084_2019-10-30_final
2019-10-30 10:04:21	ga_ls8c_ard_3-1-0_097085_2019-10-30_final
2019-11-13 10:11:29	ga_ls8c_ard_3-1-0_099072_2019-11-13_final
2019-11-13 10:11:53	ga_ls8c_ard_3-1-0_099073_2019-11-13_final
2019-11-13 10:12:17	ga_ls8c_ard_3-1-0_099074_2019-11-13_final
2019-11-13 10:12:41	ga_ls8c_ard_3-1-0_099075_2019-11-13_final
2019-11-13 10:13:05	ga_ls8c_ard_3-1-0_099076_2019-11-13_final
2019-11-13 10:13:28	ga_ls8c_ard_3-1-0_099077_2019-11-13_final
2019-11-15 10:02:18	ga_ls8c_ard_3-1-0_097080_2019-11-15_final
2019-11-15 10:02:42	ga_ls8c_ard_3-1-0_097081_2019-11-15_final
2019-11-15 10:03:06	ga_ls8c_ard_3-1-0_097082_2019-11-15_final
2019-11-15 10:03:30	ga_ls8c_ard_3-1-0_097083_2019-11-15_final
2019-11-15 10:03:54	ga_ls8c_ard_3-1-0_097084_2019-11-15_final
2019-11-15 10:04:18	ga_ls8c_ard_3-1-0_097085_2019-11-15_final
2019-11-15 10:04:42	ga_ls8c_ard_3-1-0_097086_2019-11-15_final
2019-12-08 10:06:51	ga_ls8c_ard_3-1-0_098076_2019-12-08_final
2019-12-08 10:07:15	ga_ls8c_ard_3-1-0_098077_2019-12-08_final
2019-12-08 10:07:39	ga_ls8c_ard_3-1-0_098078_2019-12-08_final
2019-12-08 10:08:03	ga_ls8c_ard_3-1-0_098079_2019-12-08_final
2019-12-08 10:08:27	ga_ls8c_ard_3-1-0_098080_2019-12-08_final
2019-12-08 10:08:51	ga_ls8c_ard_3-1-0_098081_2019-12-08_final
2019-12-10 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-12-10_final
2019-12-10 09:58:05	ga_ls8c_ard_3-1-0_096085_2019-12-10_final
2019-12-10 09:58:29	ga_ls8c_ard_3-1-0_096086_2019-12-10_final
2019-12-10 09:58:53	ga_ls8c_ard_3-1-0_096087_2019-12-10_final
2020-02-19 10:01:58	ga_ls8c_ard_3-1-0_097080_2020-02-19_final
2020-02-19 10:02:22	ga_ls8c_ard_3-1-0_097081_2020-02-19_final
2020-02-19 10:02:46	ga_ls8c_ard_3-1-0_097082_2020-02-19_final
2020-02-19 10:03:10	ga_ls8c_ard_3-1-0_097083_2020-02-19_final
2020-02-19 10:03:34	ga_ls8c_ard_3-1-0_097084_2020-02-19_final
2020-02-19 10:03:58	ga_ls8c_ard_3-1-0_097085_2020-02-19_final
2020-02-19 10:04:22	ga_ls8c_ard_3-1-0_097086_2020-02-19_final
2020-02-21 09:52:48	ga_ls8c_ard_3-1-0_095088_2020-02-21_final
2022-07-25 10:06:53	ga_ls8c_ard_3-2-1_098076_2022-07-25_final
2022-07-25 10:07:17	ga_ls8c_ard_3-2-1_098077_2022-07-25_final
2022-07-25 10:07:41	ga_ls8c_ard_3-2-1_098078_2022-07-25_final
2022-07-25 10:08:05	ga_ls8c_ard_3-2-1_098079_2022-07-25_final
2022-07-25 10:08:29	ga_ls8c_ard_3-2-1_098080_2022-07-25_final
2022-07-25 10:08:53	ga_ls8c_ard_3-2-1_098081_2022-07-25_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-07-27 09:58:09	ga_ls8c_ard_3-2-1_096085_2022-07-27_final
2022-07-27 09:58:33	ga_ls8c_ard_3-2-1_096086_2022-07-27_final
2022-08-01 10:11:09	ga_ls8c_ard_3-2-1_099071_2022-08-01_final
2022-08-01 10:11:33	ga_ls8c_ard_3-2-1_099072_2022-08-01_final
2022-08-01 10:11:57	ga_ls8c_ard_3-2-1_099073_2022-08-01_final
2022-08-01 10:12:21	ga_ls8c_ard_3-2-1_099074_2022-08-01_final
2022-08-01 10:12:45	ga_ls8c_ard_3-2-1_099075_2022-08-01_final
2022-08-01 10:13:09	ga_ls8c_ard_3-2-1_099076_2022-08-01_final
2022-08-01 10:13:33	ga_ls8c_ard_3-2-1_099077_2022-08-01_final
2022-08-03 10:02:24	ga_ls8c_ard_3-2-1_097080_2022-08-03_final
2022-08-03 10:02:48	ga_ls8c_ard_3-2-1_097081_2022-08-03_final
2022-08-03 10:03:12	ga_ls8c_ard_3-2-1_097082_2022-08-03_final
2022-08-03 10:03:36	ga_ls8c_ard_3-2-1_097083_2022-08-03_final
2022-08-03 10:04:00	ga_ls8c_ard_3-2-1_097084_2022-08-03_final
2022-08-03 10:04:24	ga_ls8c_ard_3-2-1_097085_2022-08-03_final
2022-08-05 09:52:51	ga_ls8c_ard_3-2-1_095087_2022-08-05_final
2022-08-08 10:17:23	ga_ls8c_ard_3-2-1_100071_2022-08-08_final
2022-08-08 10:17:47	ga_ls8c_ard_3-2-1_100072_2022-08-08_final
2022-08-10 10:07:02	ga_ls8c_ard_3-2-1_098076_2022-08-10_final
2022-08-10 10:07:26	ga_ls8c_ard_3-2-1_098077_2022-08-10_final
2022-08-10 10:07:50	ga_ls8c_ard_3-2-1_098078_2022-08-10_final
2022-08-10 10:08:14	ga_ls8c_ard_3-2-1_098079_2022-08-10_final
2022-08-10 10:08:38	ga_ls8c_ard_3-2-1_098080_2022-08-10_final
2022-08-10 10:09:02	ga_ls8c_ard_3-2-1_098081_2022-08-10_final
2022-08-12 09:57:53	ga_ls8c_ard_3-2-1_096084_2022-08-12_final
2022-08-12 09:58:17	ga_ls8c_ard_3-2-1_096085_2022-08-12_final
2022-08-12 09:58:41	ga_ls8c_ard_3-2-1_096086_2022-08-12_final
2022-08-28 09:57:54	ga_ls8c_ard_3-2-1_096084_2022-08-28_final
2022-08-28 09:58:18	ga_ls8c_ard_3-2-1_096085_2022-08-28_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-09-02 10:11:15	ga_ls8c_ard_3-2-1_099071_2022-09-02_final
2022-09-02 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-09-02_final
2022-09-02 10:12:03	ga_ls8c_ard_3-2-1_099073_2022-09-02_final
2022-09-02 10:12:27	ga_ls8c_ard_3-2-1_099074_2022-09-02_final
2022-09-02 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-09-02_final
2022-09-02 10:13:15	ga_ls8c_ard_3-2-1_099076_2022-09-02_final
2022-09-02 10:13:39	ga_ls8c_ard_3-2-1_099077_2022-09-02_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