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
2018-09-15 09:22:06	ga_ls8c_ard_3-0-0_091074_2018-09-14_final
2018-09-15 09:22:30	ga_ls8c_ard_3-0-0_091075_2018-09-14_final
2018-09-15 09:22:54	ga_ls8c_ard_3-0-0_091076_2018-09-14_final
2018-09-15 09:23:18	ga_ls8c_ard_3-0-0_091077_2018-09-14_final
2018-09-15 09:23:42	ga_ls8c_ard_3-0-0_091078_2018-09-14_final
2018-09-15 09:24:06	ga_ls8c_ard_3-0-0_091079_2018-09-14_final
2018-09-15 09:24:30	ga_ls8c_ard_3-0-0_091080_2018-09-14_final
2018-10-03 09:13:28	ga_ls8c_ard_3-0-0_089083_2018-10-02_final
2018-10-03 09:13:52	ga_ls8c_ard_3-0-0_089084_2018-10-02_final
2018-10-03 09:14:16	ga_ls8c_ard_3-0-0_089085_2018-10-02_final
2018-10-03 09:14:40	ga_ls8c_ard_3-0-0_089086_2018-10-02_final
2018-10-03 09:15:04	ga_ls8c_ard_3-0-0_089087_2018-10-02_final
2018-10-03 09:15:28	ga_ls8c_ard_3-0-0_089088_2018-10-02_final
2018-10-17 09:22:20	ga_ls8c_ard_3-0-0_091074_2018-10-16_final
2018-10-17 09:22:44	ga_ls8c_ard_3-0-0_091075_2018-10-16_final
2018-10-17 09:23:08	ga_ls8c_ard_3-0-0_091076_2018-10-16_final
2018-10-17 09:23:32	ga_ls8c_ard_3-0-0_091077_2018-10-16_final
2018-10-17 09:23:56	ga_ls8c_ard_3-0-0_091078_2018-10-16_final
2018-10-17 09:24:19	ga_ls8c_ard_3-0-0_091079_2018-10-16_final
2018-10-17 09:24:43	ga_ls8c_ard_3-0-0_091080_2018-10-16_final
2018-10-19 09:13:34	ga_ls8c_ard_3-0-0_089083_2018-10-18_final
2018-10-19 09:13:58	ga_ls8c_ard_3-0-0_089084_2018-10-18_final
2018-10-19 09:14:22	ga_ls8c_ard_3-0-0_089085_2018-10-18_final
2018-10-19 09:14:46	ga_ls8c_ard_3-0-0_089086_2018-10-18_final
2018-10-19 09:15:10	ga_ls8c_ard_3-0-0_089087_2018-10-18_final
2018-10-19 09:15:34	ga_ls8c_ard_3-0-0_089088_2018-10-18_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
2018-11-25 09:27:24	ga_ls8c_ard_3-0-0_092071_2018-11-24_final
2018-11-25 09:27:48	ga_ls8c_ard_3-0-0_092072_2018-11-24_final
2018-11-25 09:28:11	ga_ls8c_ard_3-0-0_092073_2018-11-24_final
2018-11-25 09:28:35	ga_ls8c_ard_3-0-0_092074_2018-11-24_final
2018-11-25 09:28:59	ga_ls8c_ard_3-0-0_092075_2018-11-24_final
2018-11-27 09:18:13	ga_ls8c_ard_3-0-0_090079_2018-11-26_final
2018-11-27 09:18:37	ga_ls8c_ard_3-0-0_090080_2018-11-26_final
2018-11-27 09:19:01	ga_ls8c_ard_3-0-0_090081_2018-11-26_final
2018-11-27 09:19:25	ga_ls8c_ard_3-0-0_090082_2018-11-26_final
2018-11-27 09:19:49	ga_ls8c_ard_3-0-0_090083_2018-11-26_final
2018-11-27 09:20:13	ga_ls8c_ard_3-0-0_090084_2018-11-26_final
2018-12-27 09:27:20	ga_ls8c_ard_3-0-0_092071_2018-12-26_final
2018-12-27 09:27:44	ga_ls8c_ard_3-0-0_092072_2018-12-26_final
2018-12-27 09:28:08	ga_ls8c_ard_3-0-0_092073_2018-12-26_final
2018-12-27 09:28:32	ga_ls8c_ard_3-0-0_092074_2018-12-26_final
2018-12-27 09:28:56	ga_ls8c_ard_3-0-0_092075_2018-12-26_final
2018-12-29 09:18:10	ga_ls8c_ard_3-0-0_090079_2018-12-28_final
2018-12-29 09:18:34	ga_ls8c_ard_3-0-0_090080_2018-12-28_final
2018-12-29 09:18:58	ga_ls8c_ard_3-0-0_090081_2018-12-28_final
2018-12-29 09:19:22	ga_ls8c_ard_3-0-0_090082_2018-12-28_final
2018-12-29 09:19:46	ga_ls8c_ard_3-0-0_090083_2018-12-28_final
2018-12-29 09:20:10	ga_ls8c_ard_3-0-0_090084_2018-12-28_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
2023-01-07 09:29:04	ga_ls8c_ard_3-2-1_092074_2023-01-06_final
2023-01-07 09:29:28	ga_ls8c_ard_3-2-1_092075_2023-01-06_final
2023-01-25 09:18:39	ga_ls8c_ard_3-2-1_090079_2023-01-24_final
2023-01-25 09:19:03	ga_ls8c_ard_3-2-1_090080_2023-01-24_final
2023-01-25 09:19:27	ga_ls8c_ard_3-2-1_090081_2023-01-24_final
2023-01-25 09:19:51	ga_ls8c_ard_3-2-1_090082_2023-01-24_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-25 09:20:39	ga_ls8c_ard_3-2-1_090084_2023-01-24_final
2023-02-01 09:22:52	ga_ls8c_ard_3-2-1_091074_2023-01-31_final
2023-02-01 09:23:16	ga_ls8c_ard_3-2-1_091075_2023-01-31_final
2023-02-01 09:23:40	ga_ls8c_ard_3-2-1_091076_2023-01-31_final
2023-02-01 09:24:04	ga_ls8c_ard_3-2-1_091077_2023-01-31_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-01 09:24:52	ga_ls8c_ard_3-2-1_091079_2023-01-31_final
2023-02-01 09:25:15	ga_ls8c_ard_3-2-1_091080_2023-01-31_final
2023-02-03 09:13:42	ga_ls8c_ard_3-2-1_089082_2023-02-02_final
2023-02-03 09:14:06	ga_ls8c_ard_3-2-1_089083_2023-02-02_final
2023-02-03 09:14:30	ga_ls8c_ard_3-2-1_089084_2023-02-02_final
2023-02-03 09:14:53	ga_ls8c_ard_3-2-1_089085_2023-02-02_final
2023-02-03 09:15:17	ga_ls8c_ard_3-2-1_089086_2023-02-02_final
2023-02-03 09:16:05	ga_ls8c_ard_3-2-1_089088_2023-02-02_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 09:15:54	ga_ls8c_ard_3-2-1_089088_2023-02-18_final
2023-02-26 09:18:21	ga_ls8c_ard_3-2-1_090079_2023-02-25_final
2023-02-26 09:18:45	ga_ls8c_ard_3-2-1_090080_2023-02-25_final
2023-02-26 09:19:09	ga_ls8c_ard_3-2-1_090081_2023-02-25_final
2023-02-26 09:19:33	ga_ls8c_ard_3-2-1_090082_2023-02-25_final
2023-02-26 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-02-25_final
2023-02-26 09:20:21	ga_ls8c_ard_3-2-1_090084_2023-02-25_final
2024-04-26 09:13:09	ga_ls8c_ard_3-2-1_089083_2024-04-25_nrt
2024-04-26 09:13:33	ga_ls8c_ard_3-2-1_089084_2024-04-25_nrt
2024-04-26 09:13:57	ga_ls8c_ard_3-2-1_089085_2024-04-25_nrt
2024-04-26 09:14:21	ga_ls8c_ard_3-2-1_089086_2024-04-25_nrt
2024-05-01 09:26:49	ga_ls8c_ard_3-2-1_092071_2024-04-30_nrt
2024-05-01 09:27:12	ga_ls8c_ard_3-2-1_092072_2024-04-30_nrt
2024-05-01 09:27:36	ga_ls8c_ard_3-2-1_092073_2024-04-30_nrt
2024-05-01 09:28:00	ga_ls8c_ard_3-2-1_092074_2024-04-30_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