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
2019-11-05 11:03:20	ga_ls8c_ard_3-1-0_107078_2019-11-05_final
2019-11-05 11:03:44	ga_ls8c_ard_3-1-0_107079_2019-11-05_final
2019-11-05 11:04:08	ga_ls8c_ard_3-1-0_107080_2019-11-05_final
2019-11-05 11:04:32	ga_ls8c_ard_3-1-0_107081_2019-11-05_final
2019-11-05 11:04:56	ga_ls8c_ard_3-1-0_107082_2019-11-05_final
2019-11-05 11:05:20	ga_ls8c_ard_3-1-0_107083_2019-11-05_final
2019-11-05 11:05:44	ga_ls8c_ard_3-1-0_107084_2019-11-05_final
2019-11-21 11:03:17	ga_ls8c_ard_3-1-0_107078_2019-11-21_final
2019-11-21 11:03:41	ga_ls8c_ard_3-1-0_107079_2019-11-21_final
2019-11-21 11:04:05	ga_ls8c_ard_3-1-0_107080_2019-11-21_final
2019-11-21 11:04:28	ga_ls8c_ard_3-1-0_107081_2019-11-21_final
2019-11-21 11:04:52	ga_ls8c_ard_3-1-0_107082_2019-11-21_final
2019-11-21 11:05:16	ga_ls8c_ard_3-1-0_107083_2019-11-21_final
2019-11-21 11:05:40	ga_ls8c_ard_3-1-0_107084_2019-11-21_final
2019-12-07 11:03:16	ga_ls8c_ard_3-1-0_107078_2019-12-07_final
2019-12-07 11:03:40	ga_ls8c_ard_3-1-0_107079_2019-12-07_final
2019-12-07 11:04:04	ga_ls8c_ard_3-1-0_107080_2019-12-07_final
2019-12-07 11:04:28	ga_ls8c_ard_3-1-0_107081_2019-12-07_final
2019-12-07 11:04:52	ga_ls8c_ard_3-1-0_107082_2019-12-07_final
2019-12-07 11:05:16	ga_ls8c_ard_3-1-0_107083_2019-12-07_final
2019-12-07 11:05:40	ga_ls8c_ard_3-1-0_107084_2019-12-07_final
2020-01-08 11:03:09	ga_ls8c_ard_3-1-0_107078_2020-01-08_final
2020-01-08 11:03:33	ga_ls8c_ard_3-1-0_107079_2020-01-08_final
2020-01-08 11:03:57	ga_ls8c_ard_3-1-0_107080_2020-01-08_final
2020-01-08 11:04:21	ga_ls8c_ard_3-1-0_107081_2020-01-08_final
2020-01-08 11:04:45	ga_ls8c_ard_3-1-0_107082_2020-01-08_final
2020-01-08 11:05:09	ga_ls8c_ard_3-1-0_107083_2020-01-08_final
2020-01-08 11:05:33	ga_ls8c_ard_3-1-0_107084_2020-01-08_final
2022-07-29 11:18:18	ga_ls8c_ard_3-2-1_110069_2022-07-29_final
2022-07-29 11:18:42	ga_ls8c_ard_3-2-1_110070_2022-07-29_final
2022-07-31 11:07:57	ga_ls8c_ard_3-2-1_108074_2022-07-31_final
2022-07-31 11:08:21	ga_ls8c_ard_3-2-1_108075_2022-07-31_final
2022-07-31 11:08:45	ga_ls8c_ard_3-2-1_108076_2022-07-31_final
2022-07-31 11:09:09	ga_ls8c_ard_3-2-1_108077_2022-07-31_final
2022-07-31 11:09:33	ga_ls8c_ard_3-2-1_108078_2022-07-31_final
2022-07-31 11:09:57	ga_ls8c_ard_3-2-1_108079_2022-07-31_final
2022-07-31 11:10:21	ga_ls8c_ard_3-2-1_108080_2022-07-31_final
2022-08-02 10:58:49	ga_ls8c_ard_3-2-1_106082_2022-08-02_final
2022-08-02 10:59:12	ga_ls8c_ard_3-2-1_106083_2022-08-02_final
2022-08-07 11:12:12	ga_ls8c_ard_3-2-1_109069_2022-08-07_final
2022-08-07 11:12:36	ga_ls8c_ard_3-2-1_109070_2022-08-07_final
2022-08-07 11:13:00	ga_ls8c_ard_3-2-1_109071_2022-08-07_final
2022-08-07 11:13:24	ga_ls8c_ard_3-2-1_109072_2022-08-07_final
2022-08-07 11:13:48	ga_ls8c_ard_3-2-1_109073_2022-08-07_final
2022-08-07 11:14:12	ga_ls8c_ard_3-2-1_109074_2022-08-07_final
2022-08-07 11:14:36	ga_ls8c_ard_3-2-1_109075_2022-08-07_final
2022-08-14 11:18:26	ga_ls8c_ard_3-2-1_110069_2022-08-14_final
2022-08-14 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-14_final
2022-08-16 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-08-16_final
2022-08-16 11:08:28	ga_ls8c_ard_3-2-1_108075_2022-08-16_final
2022-08-16 11:08:52	ga_ls8c_ard_3-2-1_108076_2022-08-16_final
2022-08-16 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-08-16_final
2022-08-16 11:09:40	ga_ls8c_ard_3-2-1_108078_2022-08-16_final
2022-08-16 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-08-16_final
2022-08-18 10:58:54	ga_ls8c_ard_3-2-1_106082_2022-08-18_final
2022-08-18 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-08-18_final
2023-01-16 11:05:15	ga_ls8c_ard_3-2-1_107083_2023-01-16_final
2023-01-16 11:05:39	ga_ls8c_ard_3-2-1_107084_2023-01-16_final
2023-01-21 11:18:14	ga_ls8c_ard_3-2-1_110069_2023-01-21_final
2023-01-21 11:18:38	ga_ls8c_ard_3-2-1_110070_2023-01-21_final
2023-01-23 11:07:53	ga_ls8c_ard_3-2-1_108074_2023-01-23_final
2023-01-23 11:08:17	ga_ls8c_ard_3-2-1_108075_2023-01-23_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-23 11:09:05	ga_ls8c_ard_3-2-1_108077_2023-01-23_final
2023-01-23 11:09:29	ga_ls8c_ard_3-2-1_108078_2023-01-23_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-23 11:10:17	ga_ls8c_ard_3-2-1_108080_2023-01-23_final
2023-02-01 11:03:21	ga_ls8c_ard_3-2-1_107078_2023-02-01_final
2023-02-01 11:03:45	ga_ls8c_ard_3-2-1_107079_2023-02-01_final
2023-02-01 11:04:08	ga_ls8c_ard_3-2-1_107080_2023-02-01_final
2023-02-01 11:04:32	ga_ls8c_ard_3-2-1_107081_2023-02-01_final
2023-02-01 11:04:56	ga_ls8c_ard_3-2-1_107082_2023-02-01_final
2023-02-01 11:05:20	ga_ls8c_ard_3-2-1_107083_2023-02-01_final
2023-02-01 11:05:44	ga_ls8c_ard_3-2-1_107084_2023-02-01_final
2023-02-08 11:07:54	ga_ls8c_ard_3-2-1_108074_2023-02-08_final
2023-02-08 11:08:18	ga_ls8c_ard_3-2-1_108075_2023-02-08_final
2023-02-08 11:08:42	ga_ls8c_ard_3-2-1_108076_2023-02-08_final
2023-02-08 11:09:06	ga_ls8c_ard_3-2-1_108077_2023-02-08_final
2023-02-08 11:09:30	ga_ls8c_ard_3-2-1_108078_2023-02-08_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-08 11:10:18	ga_ls8c_ard_3-2-1_108080_2023-02-08_final
2023-02-10 10:58:43	ga_ls8c_ard_3-2-1_106082_2023-02-10_final
2023-02-10 10:59:06	ga_ls8c_ard_3-2-1_106083_2023-02-10_final
2023-06-25 11:02:28	ga_ls8c_ard_3-2-1_107078_2023-06-25_final
2023-06-25 11:02:52	ga_ls8c_ard_3-2-1_107079_2023-06-25_final
2023-06-25 11:03:16	ga_ls8c_ard_3-2-1_107080_2023-06-25_final
2023-06-25 11:03:40	ga_ls8c_ard_3-2-1_107081_2023-06-25_final
2023-06-25 11:04:04	ga_ls8c_ard_3-2-1_107082_2023-06-25_final
2023-06-25 11:04:28	ga_ls8c_ard_3-2-1_107083_2023-06-25_final
2023-06-25 11:04:52	ga_ls8c_ard_3-2-1_107084_2023-06-25_final
2023-06-30 11:17:30	ga_ls8c_ard_3-2-1_110069_2023-06-30_final
2023-06-30 11:17:54	ga_ls8c_ard_3-2-1_110070_2023-06-30_final
2023-07-02 11:07:10	ga_ls8c_ard_3-2-1_108074_2023-07-02_final
2023-07-02 11:07:34	ga_ls8c_ard_3-2-1_108075_2023-07-02_final
2023-07-02 11:07:58	ga_ls8c_ard_3-2-1_108076_2023-07-02_final
2023-07-02 11:08:22	ga_ls8c_ard_3-2-1_108077_2023-07-02_final
2023-07-02 11:08:46	ga_ls8c_ard_3-2-1_108078_2023-07-02_final
2023-07-02 11:09:10	ga_ls8c_ard_3-2-1_108079_2023-07-02_final
2023-07-02 11:09:33	ga_ls8c_ard_3-2-1_108080_2023-07-02_final
2023-07-04 10:58:01	ga_ls8c_ard_3-2-1_106082_2023-07-04_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