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
2018-11-16 09:31:59	ga_ls8c_ard_3-0-0_093067_2018-11-16_final
2018-11-16 09:32:23	ga_ls8c_ard_3-0-0_093068_2018-11-16_final
2018-11-20 09:13:39	ga_ls8c_ard_3-0-0_089083_2018-11-19_final
2018-11-20 09:14:03	ga_ls8c_ard_3-0-0_089084_2018-11-19_final
2018-11-20 09:14:27	ga_ls8c_ard_3-0-0_089085_2018-11-19_final
2018-11-20 09:14:51	ga_ls8c_ard_3-0-0_089086_2018-11-19_final
2018-11-20 09:15:15	ga_ls8c_ard_3-0-0_089087_2018-11-19_final
2018-11-20 09:15:39	ga_ls8c_ard_3-0-0_089088_2018-11-19_final
2019-01-07 09:13:34	ga_ls8c_ard_3-0-0_089083_2019-01-06_final
2019-01-07 09:13:58	ga_ls8c_ard_3-0-0_089084_2019-01-06_final
2019-01-07 09:14:22	ga_ls8c_ard_3-0-0_089085_2019-01-06_final
2019-01-07 09:14:46	ga_ls8c_ard_3-0-0_089086_2019-01-06_final
2019-01-07 09:15:10	ga_ls8c_ard_3-0-0_089087_2019-01-06_final
2019-01-07 09:15:34	ga_ls8c_ard_3-0-0_089088_2019-01-06_final
2021-09-30 09:28:37	ga_ls8c_ard_3-2-0_092073_2021-09-29_final
2021-09-30 09:29:01	ga_ls8c_ard_3-2-0_092074_2021-09-29_final
2021-09-30 09:29:25	ga_ls8c_ard_3-2-0_092075_2021-09-29_final
2021-10-07 09:32:26	ga_ls8c_ard_3-2-0_093067_2021-10-07_final
2021-10-07 09:32:50	ga_ls8c_ard_3-2-0_093068_2021-10-07_final
2021-10-09 09:22:53	ga_ls8c_ard_3-2-0_091074_2021-10-08_final
2021-10-09 09:23:17	ga_ls8c_ard_3-2-0_091075_2021-10-08_final
2021-10-09 09:23:41	ga_ls8c_ard_3-2-0_091076_2021-10-08_final
2021-10-09 09:24:05	ga_ls8c_ard_3-2-0_091077_2021-10-08_final
2021-10-09 09:24:29	ga_ls8c_ard_3-2-0_091078_2021-10-08_final
2021-10-09 09:24:53	ga_ls8c_ard_3-2-0_091079_2021-10-08_final
2021-10-09 09:25:16	ga_ls8c_ard_3-2-0_091080_2021-10-08_final
2021-10-25 09:22:55	ga_ls8c_ard_3-2-0_091074_2021-10-24_final
2021-10-25 09:23:19	ga_ls8c_ard_3-2-0_091075_2021-10-24_final
2021-10-25 09:23:43	ga_ls8c_ard_3-2-0_091076_2021-10-24_final
2021-10-25 09:24:07	ga_ls8c_ard_3-2-0_091077_2021-10-24_final
2021-10-25 09:24:31	ga_ls8c_ard_3-2-0_091078_2021-10-24_final
2021-10-25 09:24:55	ga_ls8c_ard_3-2-0_091079_2021-10-24_final
2021-10-25 09:25:18	ga_ls8c_ard_3-2-0_091080_2021-10-24_final
2022-03-11 09:18:16	ga_ls8c_ard_3-2-1_090079_2022-03-10_final
2022-03-11 09:18:40	ga_ls8c_ard_3-2-1_090080_2022-03-10_final
2022-03-11 09:19:04	ga_ls8c_ard_3-2-1_090081_2022-03-10_final
2022-03-11 09:19:28	ga_ls8c_ard_3-2-1_090082_2022-03-10_final
2022-03-11 09:19:52	ga_ls8c_ard_3-2-1_090083_2022-03-10_final
2022-03-11 09:20:16	ga_ls8c_ard_3-2-1_090084_2022-03-10_final
2022-03-18 09:22:23	ga_ls8c_ard_3-2-1_091074_2022-03-17_final
2022-03-18 09:22:47	ga_ls8c_ard_3-2-1_091075_2022-03-17_final
2022-03-18 09:23:11	ga_ls8c_ard_3-2-1_091076_2022-03-17_final
2022-03-18 09:23:35	ga_ls8c_ard_3-2-1_091077_2022-03-17_final
2022-03-18 09:23:59	ga_ls8c_ard_3-2-1_091078_2022-03-17_final
2022-03-18 09:24:23	ga_ls8c_ard_3-2-1_091079_2022-03-17_final
2022-03-18 09:24:47	ga_ls8c_ard_3-2-1_091080_2022-03-17_final
2022-03-25 09:27:16	ga_ls8c_ard_3-2-1_092071_2022-03-24_final
2022-03-25 09:27:40	ga_ls8c_ard_3-2-1_092072_2022-03-24_final
2022-03-25 09:28:04	ga_ls8c_ard_3-2-1_092073_2022-03-24_final
2022-03-25 09:28:28	ga_ls8c_ard_3-2-1_092074_2022-03-24_final
2022-03-25 09:28:52	ga_ls8c_ard_3-2-1_092075_2022-03-24_final
2022-04-03 09:22:13	ga_ls8c_ard_3-2-1_091074_2022-04-02_final
2022-04-03 09:22:37	ga_ls8c_ard_3-2-1_091075_2022-04-02_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-03 09:24:13	ga_ls8c_ard_3-2-1_091079_2022-04-02_final
2022-04-03 09:24:37	ga_ls8c_ard_3-2-1_091080_2022-04-02_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-05 09:13:52	ga_ls8c_ard_3-2-1_089084_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-05 09:15:28	ga_ls8c_ard_3-2-1_089088_2022-04-04_final
2022-05-12 09:27:22	ga_ls8c_ard_3-2-1_092071_2022-05-11_final
2022-05-12 09:27:46	ga_ls8c_ard_3-2-1_092072_2022-05-11_final
2022-05-12 09:28:10	ga_ls8c_ard_3-2-1_092073_2022-05-11_final
2022-05-12 09:28:34	ga_ls8c_ard_3-2-1_092074_2022-05-11_final
2022-05-12 09:28:58	ga_ls8c_ard_3-2-1_092075_2022-05-11_final
2022-05-14 09:18:13	ga_ls8c_ard_3-2-1_090079_2022-05-13_final
2022-05-14 09:18:37	ga_ls8c_ard_3-2-1_090080_2022-05-13_final
2022-05-14 09:19:01	ga_ls8c_ard_3-2-1_090081_2022-05-13_final
2022-05-14 09:19:25	ga_ls8c_ard_3-2-1_090082_2022-05-13_final
2022-05-14 09:19:49	ga_ls8c_ard_3-2-1_090083_2022-05-13_final
2022-05-14 09:20:13	ga_ls8c_ard_3-2-1_090084_2022-05-13_final
2022-05-30 09:18:15	ga_ls8c_ard_3-2-1_090079_2022-05-29_final
2022-05-30 09:18:39	ga_ls8c_ard_3-2-1_090080_2022-05-29_final
2022-05-30 09:19:03	ga_ls8c_ard_3-2-1_090081_2022-05-29_final
2022-05-30 09:19:27	ga_ls8c_ard_3-2-1_090082_2022-05-29_final
2022-05-30 09:19:51	ga_ls8c_ard_3-2-1_090083_2022-05-29_final
2022-05-30 09:20:15	ga_ls8c_ard_3-2-1_090084_2022-05-29_final
2022-06-08 09:13:24	ga_ls8c_ard_3-2-1_089082_2022-06-07_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-08 09:14:36	ga_ls8c_ard_3-2-1_089085_2022-06-07_final
2022-06-08 09:15:00	ga_ls8c_ard_3-2-1_089086_2022-06-07_final
2022-11-29 09:23:03	ga_ls8c_ard_3-2-1_091074_2022-11-28_final
2022-11-29 09:23:26	ga_ls8c_ard_3-2-1_091075_2022-11-28_final
2022-11-29 09:23:50	ga_ls8c_ard_3-2-1_091076_2022-11-28_final
2022-11-29 09:24:14	ga_ls8c_ard_3-2-1_091077_2022-11-28_final
2022-11-29 09:24:38	ga_ls8c_ard_3-2-1_091078_2022-11-28_final
2022-11-29 09:25:02	ga_ls8c_ard_3-2-1_091079_2022-11-28_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2024-04-17 09:19:24	ga_ls8c_ard_3-2-1_090083_2024-04-16_final
2024-04-17 09:19:48	ga_ls8c_ard_3-2-1_090084_2024-04-16_final
2024-04-24 09:21:56	ga_ls8c_ard_3-2-1_091074_2024-04-23_final
2024-04-24 09:22:20	ga_ls8c_ard_3-2-1_091075_2024-04-23_final
2024-04-24 09:22:44	ga_ls8c_ard_3-2-1_091076_2024-04-23_final
2024-04-24 09:23:08	ga_ls8c_ard_3-2-1_091077_2024-04-23_final
2024-04-24 09:23:32	ga_ls8c_ard_3-2-1_091078_2024-04-23_final
2024-04-24 09:23:56	ga_ls8c_ard_3-2-1_091079_2024-04-23_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