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 11:05:23	ga_ls8c_ard_3-0-0_107085_2018-09-15_final
2018-09-27 11:23:24	ga_ls8c_ard_3-0-0_111068_2018-09-27_final
2018-09-27 11:23:48	ga_ls8c_ard_3-0-0_111069_2018-09-27_final
2018-09-27 11:24:11	ga_ls8c_ard_3-0-0_111070_2018-09-27_final
2018-09-27 11:24:35	ga_ls8c_ard_3-0-0_111071_2018-09-27_final
2018-09-27 11:24:59	ga_ls8c_ard_3-0-0_111072_2018-09-27_final
2018-09-27 11:25:23	ga_ls8c_ard_3-0-0_111073_2018-09-27_final
2018-09-29 11:14:38	ga_ls8c_ard_3-0-0_109077_2018-09-29_final
2018-09-29 11:15:02	ga_ls8c_ard_3-0-0_109078_2018-09-29_final
2018-09-29 11:15:26	ga_ls8c_ard_3-0-0_109079_2018-09-29_final
2018-09-29 11:15:50	ga_ls8c_ard_3-0-0_109080_2018-09-29_final
2018-09-29 11:16:14	ga_ls8c_ard_3-0-0_109081_2018-09-29_final
2018-09-29 11:16:38	ga_ls8c_ard_3-0-0_109082_2018-09-29_final
2018-10-04 11:29:14	ga_ls8c_ard_3-0-0_112067_2018-10-04_final
2018-10-04 11:29:38	ga_ls8c_ard_3-0-0_112068_2018-10-04_final
2018-10-06 11:18:53	ga_ls8c_ard_3-0-0_110072_2018-10-06_final
2018-10-06 11:19:17	ga_ls8c_ard_3-0-0_110073_2018-10-06_final
2018-10-06 11:19:41	ga_ls8c_ard_3-0-0_110074_2018-10-06_final
2018-10-06 11:20:05	ga_ls8c_ard_3-0-0_110075_2018-10-06_final
2018-10-06 11:20:29	ga_ls8c_ard_3-0-0_110076_2018-10-06_final
2018-10-06 11:20:53	ga_ls8c_ard_3-0-0_110077_2018-10-06_final
2018-10-06 11:21:17	ga_ls8c_ard_3-0-0_110078_2018-10-06_final
2018-10-08 11:10:08	ga_ls8c_ard_3-0-0_108081_2018-10-08_final
2018-10-15 11:14:46	ga_ls8c_ard_3-0-0_109077_2018-10-15_final
2018-10-15 11:15:10	ga_ls8c_ard_3-0-0_109078_2018-10-15_final
2018-10-15 11:15:33	ga_ls8c_ard_3-0-0_109079_2018-10-15_final
2018-10-15 11:15:57	ga_ls8c_ard_3-0-0_109080_2018-10-15_final
2018-10-15 11:16:21	ga_ls8c_ard_3-0-0_109081_2018-10-15_final
2018-10-15 11:16:45	ga_ls8c_ard_3-0-0_109082_2018-10-15_final
2018-10-17 11:05:36	ga_ls8c_ard_3-0-0_107085_2018-10-17_final
2018-10-29 11:23:12	ga_ls8c_ard_3-0-0_111067_2018-10-29_final
2018-10-29 11:23:36	ga_ls8c_ard_3-0-0_111068_2018-10-29_final
2018-10-29 11:24:00	ga_ls8c_ard_3-0-0_111069_2018-10-29_final
2018-10-29 11:24:24	ga_ls8c_ard_3-0-0_111070_2018-10-29_final
2018-10-29 11:24:48	ga_ls8c_ard_3-0-0_111071_2018-10-29_final
2018-10-29 11:25:11	ga_ls8c_ard_3-0-0_111072_2018-10-29_final
2018-10-29 11:25:35	ga_ls8c_ard_3-0-0_111073_2018-10-29_final
2018-10-31 11:14:50	ga_ls8c_ard_3-0-0_109077_2018-10-31_final
2018-10-31 11:15:14	ga_ls8c_ard_3-0-0_109078_2018-10-31_final
2018-10-31 11:15:38	ga_ls8c_ard_3-0-0_109079_2018-10-31_final
2018-10-31 11:16:02	ga_ls8c_ard_3-0-0_109080_2018-10-31_final
2018-10-31 11:16:26	ga_ls8c_ard_3-0-0_109081_2018-10-31_final
2018-10-31 11:16:50	ga_ls8c_ard_3-0-0_109082_2018-10-31_final
2018-11-18 11:05:41	ga_ls8c_ard_3-0-0_107085_2018-11-18_final
2018-11-25 11:10:16	ga_ls8c_ard_3-0-0_108081_2018-11-25_final
2018-11-25 11:10:40	ga_ls8c_ard_3-0-0_108082_2018-11-25_final
2018-11-25 11:11:04	ga_ls8c_ard_3-0-0_108083_2018-11-25_final
2018-11-25 11:11:28	ga_ls8c_ard_3-0-0_108084_2018-11-25_final
2018-11-25 11:11:52	ga_ls8c_ard_3-0-0_108085_2018-11-25_final
2018-11-30 11:23:13	ga_ls8c_ard_3-0-0_111067_2018-11-30_final
2018-11-30 11:23:37	ga_ls8c_ard_3-0-0_111068_2018-11-30_final
2018-11-30 11:24:01	ga_ls8c_ard_3-0-0_111069_2018-11-30_final
2018-11-30 11:24:24	ga_ls8c_ard_3-0-0_111070_2018-11-30_final
2018-11-30 11:24:48	ga_ls8c_ard_3-0-0_111071_2018-11-30_final
2018-11-30 11:25:12	ga_ls8c_ard_3-0-0_111072_2018-11-30_final
2018-11-30 11:25:36	ga_ls8c_ard_3-0-0_111073_2018-11-30_final
2018-12-02 11:14:50	ga_ls8c_ard_3-0-0_109077_2018-12-02_final
2018-12-02 11:15:14	ga_ls8c_ard_3-0-0_109078_2018-12-02_final
2018-12-02 11:15:38	ga_ls8c_ard_3-0-0_109079_2018-12-02_final
2018-12-02 11:16:02	ga_ls8c_ard_3-0-0_109080_2018-12-02_final
2018-12-02 11:16:26	ga_ls8c_ard_3-0-0_109081_2018-12-02_final
2018-12-02 11:16:50	ga_ls8c_ard_3-0-0_109082_2018-12-02_final
2018-12-16 11:23:34	ga_ls8c_ard_3-0-0_111068_2018-12-16_final
2018-12-16 11:23:58	ga_ls8c_ard_3-0-0_111069_2018-12-16_final
2018-12-16 11:24:22	ga_ls8c_ard_3-0-0_111070_2018-12-16_final
2018-12-16 11:24:45	ga_ls8c_ard_3-0-0_111071_2018-12-16_final
2018-12-16 11:25:09	ga_ls8c_ard_3-0-0_111072_2018-12-16_final
2018-12-16 11:25:33	ga_ls8c_ard_3-0-0_111073_2018-12-16_final
2018-12-18 11:14:48	ga_ls8c_ard_3-0-0_109077_2018-12-18_final
2018-12-18 11:15:12	ga_ls8c_ard_3-0-0_109078_2018-12-18_final
2018-12-18 11:15:35	ga_ls8c_ard_3-0-0_109079_2018-12-18_final
2018-12-18 11:15:59	ga_ls8c_ard_3-0-0_109080_2018-12-18_final
2018-12-18 11:16:23	ga_ls8c_ard_3-0-0_109081_2018-12-18_final
2018-12-18 11:16:47	ga_ls8c_ard_3-0-0_109082_2018-12-18_final
2018-12-23 11:29:21	ga_ls8c_ard_3-0-0_112067_2018-12-23_final
2018-12-23 11:29:45	ga_ls8c_ard_3-0-0_112068_2018-12-23_final
2018-12-25 11:18:59	ga_ls8c_ard_3-0-0_110072_2018-12-25_final
2018-12-25 11:19:23	ga_ls8c_ard_3-0-0_110073_2018-12-25_final
2018-12-25 11:19:47	ga_ls8c_ard_3-0-0_110074_2018-12-25_final
2018-12-25 11:20:11	ga_ls8c_ard_3-0-0_110075_2018-12-25_final
2018-12-25 11:20:35	ga_ls8c_ard_3-0-0_110076_2018-12-25_final
2018-12-25 11:20:59	ga_ls8c_ard_3-0-0_110077_2018-12-25_final
2018-12-25 11:21:23	ga_ls8c_ard_3-0-0_110078_2018-12-25_final
2018-12-27 11:10:13	ga_ls8c_ard_3-0-0_108081_2018-12-27_final
2018-12-27 11:10:37	ga_ls8c_ard_3-0-0_108082_2018-12-27_final
2018-12-27 11:11:01	ga_ls8c_ard_3-0-0_108083_2018-12-27_final
2018-12-27 11:11:25	ga_ls8c_ard_3-0-0_108084_2018-12-27_final
2018-12-27 11:11:49	ga_ls8c_ard_3-0-0_108085_2018-12-27_final
2019-01-05 11:05:37	ga_ls8c_ard_3-0-0_107085_2019-01-05_final
2023-08-24 11:23:41	ga_ls8c_ard_3-2-1_111068_2023-08-24_final
2023-08-24 11:24:05	ga_ls8c_ard_3-2-1_111069_2023-08-24_final
2023-08-24 11:24:29	ga_ls8c_ard_3-2-1_111070_2023-08-24_final
2023-08-24 11:24:53	ga_ls8c_ard_3-2-1_111071_2023-08-24_final
2023-08-24 11:25:17	ga_ls8c_ard_3-2-1_111072_2023-08-24_final
2023-08-24 11:25:41	ga_ls8c_ard_3-2-1_111073_2023-08-24_final
2023-08-26 11:14:55	ga_ls8c_ard_3-2-1_109077_2023-08-26_final
2023-08-26 11:15:19	ga_ls8c_ard_3-2-1_109078_2023-08-26_final
2023-08-26 11:15:43	ga_ls8c_ard_3-2-1_109079_2023-08-26_final
2023-08-26 11:16:07	ga_ls8c_ard_3-2-1_109080_2023-08-26_final
2023-08-26 11:16:31	ga_ls8c_ard_3-2-1_109081_2023-08-26_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