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
2018-10-03 09:10:16	ga_ls8c_ard_3-0-0_089075_2018-10-02_final
2018-10-03 09:10:40	ga_ls8c_ard_3-0-0_089076_2018-10-02_final
2018-10-03 09:11:04	ga_ls8c_ard_3-0-0_089077_2018-10-02_final
2018-10-03 09:11:28	ga_ls8c_ard_3-0-0_089078_2018-10-02_final
2018-10-03 09:11:52	ga_ls8c_ard_3-0-0_089079_2018-10-02_final
2018-10-03 09:12:16	ga_ls8c_ard_3-0-0_089080_2018-10-02_final
2018-10-19 09:09:59	ga_ls8c_ard_3-0-0_089074_2018-10-18_final
2018-10-19 09:10:23	ga_ls8c_ard_3-0-0_089075_2018-10-18_final
2018-10-19 09:10:47	ga_ls8c_ard_3-0-0_089076_2018-10-18_final
2018-10-19 09:11:11	ga_ls8c_ard_3-0-0_089077_2018-10-18_final
2018-10-19 09:11:35	ga_ls8c_ard_3-0-0_089078_2018-10-18_final
2018-10-19 09:11:59	ga_ls8c_ard_3-0-0_089079_2018-10-18_final
2018-10-19 09:12:22	ga_ls8c_ard_3-0-0_089080_2018-10-18_final
2018-10-26 09:16:12	ga_ls8c_ard_3-0-0_090074_2018-10-25_final
2018-10-26 09:16:36	ga_ls8c_ard_3-0-0_090075_2018-10-25_final
2019-06-14 09:19:54	ga_ls8c_ard_3-1-0_091068_2019-06-13_final
2019-07-11 09:05:52	ga_ls8c_ard_3-1-0_088079_2019-07-10_final
2019-07-11 09:06:16	ga_ls8c_ard_3-1-0_088080_2019-07-10_final
2019-07-11 09:06:40	ga_ls8c_ard_3-1-0_088081_2019-07-10_final
2019-07-11 09:07:04	ga_ls8c_ard_3-1-0_088082_2019-07-10_final
2019-07-11 09:07:28	ga_ls8c_ard_3-1-0_088083_2019-07-10_final
2019-07-11 09:07:52	ga_ls8c_ard_3-1-0_088084_2019-07-10_final
2019-07-27 09:05:57	ga_ls8c_ard_3-1-0_088079_2019-07-26_final
2019-07-27 09:06:21	ga_ls8c_ard_3-1-0_088080_2019-07-26_final
2019-07-27 09:06:45	ga_ls8c_ard_3-1-0_088081_2019-07-26_final
2019-07-27 09:07:09	ga_ls8c_ard_3-1-0_088082_2019-07-26_final
2019-07-27 09:07:33	ga_ls8c_ard_3-1-0_088083_2019-07-26_final
2019-07-27 09:07:57	ga_ls8c_ard_3-1-0_088084_2019-07-26_final
2019-08-01 09:20:08	ga_ls8c_ard_3-1-0_091068_2019-07-31_final
2019-08-10 09:16:24	ga_ls8c_ard_3-1-0_090074_2019-08-09_final
2019-08-10 09:16:48	ga_ls8c_ard_3-1-0_090075_2019-08-09_final
2019-08-10 09:17:12	ga_ls8c_ard_3-1-0_090076_2019-08-09_final
2019-08-26 09:16:29	ga_ls8c_ard_3-1-0_090074_2019-08-25_final
2019-08-26 09:16:53	ga_ls8c_ard_3-1-0_090075_2019-08-25_final
2019-08-26 09:17:17	ga_ls8c_ard_3-1-0_090076_2019-08-25_final
2019-08-28 09:06:07	ga_ls8c_ard_3-1-0_088079_2019-08-27_final
2019-08-28 09:06:31	ga_ls8c_ard_3-1-0_088080_2019-08-27_final
2019-08-28 09:06:55	ga_ls8c_ard_3-1-0_088081_2019-08-27_final
2019-08-28 09:07:19	ga_ls8c_ard_3-1-0_088082_2019-08-27_final
2019-08-28 09:07:43	ga_ls8c_ard_3-1-0_088083_2019-08-27_final
2019-08-28 09:08:07	ga_ls8c_ard_3-1-0_088084_2019-08-27_final
2019-09-02 09:20:17	ga_ls8c_ard_3-1-0_091068_2019-09-01_final
2019-09-11 09:16:33	ga_ls8c_ard_3-1-0_090074_2019-09-10_final
2019-09-11 09:16:57	ga_ls8c_ard_3-1-0_090075_2019-09-10_final
2019-09-11 09:17:21	ga_ls8c_ard_3-1-0_090076_2019-09-10_final
2019-09-13 09:06:12	ga_ls8c_ard_3-1-0_088079_2019-09-12_final
2019-09-13 09:06:36	ga_ls8c_ard_3-1-0_088080_2019-09-12_final
2019-09-13 09:07:00	ga_ls8c_ard_3-1-0_088081_2019-09-12_final
2019-09-13 09:07:24	ga_ls8c_ard_3-1-0_088082_2019-09-12_final
2019-09-13 09:07:48	ga_ls8c_ard_3-1-0_088083_2019-09-12_final
2019-09-13 09:08:12	ga_ls8c_ard_3-1-0_088084_2019-09-12_final
2019-09-18 09:20:23	ga_ls8c_ard_3-1-0_091068_2019-09-17_final
2019-09-20 09:10:49	ga_ls8c_ard_3-1-0_089075_2019-09-19_final
2019-09-20 09:11:13	ga_ls8c_ard_3-1-0_089076_2019-09-19_final
2019-09-20 09:11:37	ga_ls8c_ard_3-1-0_089077_2019-09-19_final
2019-09-20 09:12:01	ga_ls8c_ard_3-1-0_089078_2019-09-19_final
2019-09-20 09:12:25	ga_ls8c_ard_3-1-0_089079_2019-09-19_final
2019-09-27 09:16:38	ga_ls8c_ard_3-1-0_090074_2019-09-26_final
2019-09-27 09:17:02	ga_ls8c_ard_3-1-0_090075_2019-09-26_final
2019-10-15 09:06:20	ga_ls8c_ard_3-1-0_088079_2019-10-14_final
2019-10-15 09:06:43	ga_ls8c_ard_3-1-0_088080_2019-10-14_final
2019-10-15 09:07:07	ga_ls8c_ard_3-1-0_088081_2019-10-14_final
2019-10-15 09:07:31	ga_ls8c_ard_3-1-0_088082_2019-10-14_final
2019-10-15 09:07:55	ga_ls8c_ard_3-1-0_088083_2019-10-14_final
2019-10-15 09:08:19	ga_ls8c_ard_3-1-0_088084_2019-10-14_final
2019-10-20 09:20:29	ga_ls8c_ard_3-1-0_091068_2019-10-19_final
2021-07-14 09:16:13	ga_ls8c_ard_3-2-0_090074_2021-07-13_final
2021-07-14 09:16:36	ga_ls8c_ard_3-2-0_090075_2021-07-13_final
2021-07-14 09:17:00	ga_ls8c_ard_3-2-0_090076_2021-07-13_final
2021-07-16 09:05:51	ga_ls8c_ard_3-2-0_088079_2021-07-15_final
2021-07-16 09:06:15	ga_ls8c_ard_3-2-0_088080_2021-07-15_final
2021-07-16 09:06:39	ga_ls8c_ard_3-2-0_088081_2021-07-15_final
2021-07-16 09:07:03	ga_ls8c_ard_3-2-0_088082_2021-07-15_final
2021-07-16 09:07:27	ga_ls8c_ard_3-2-0_088083_2021-07-15_final
2021-07-16 09:07:50	ga_ls8c_ard_3-2-0_088084_2021-07-15_final
2021-07-21 09:20:03	ga_ls8c_ard_3-2-0_091068_2021-07-20_final
2021-07-23 09:10:30	ga_ls8c_ard_3-2-0_089075_2021-07-22_final
2021-07-23 09:10:54	ga_ls8c_ard_3-2-0_089076_2021-07-22_final
2021-07-23 09:11:18	ga_ls8c_ard_3-2-0_089077_2021-07-22_final
2021-07-23 09:11:42	ga_ls8c_ard_3-2-0_089078_2021-07-22_final
2021-07-23 09:12:06	ga_ls8c_ard_3-2-0_089079_2021-07-22_final
2021-07-23 09:12:30	ga_ls8c_ard_3-2-0_089080_2021-07-22_final
2021-08-31 09:16:31	ga_ls8c_ard_3-2-0_090074_2021-08-30_final
2021-08-31 09:16:55	ga_ls8c_ard_3-2-0_090075_2021-08-30_final
2021-09-07 09:20:21	ga_ls8c_ard_3-2-0_091068_2021-09-06_final
2021-10-11 09:10:32	ga_ls8c_ard_3-2-0_089074_2021-10-10_final
2021-10-11 09:10:56	ga_ls8c_ard_3-2-0_089075_2021-10-10_final
2021-10-11 09:11:20	ga_ls8c_ard_3-2-0_089076_2021-10-10_final
2021-10-11 09:11:44	ga_ls8c_ard_3-2-0_089077_2021-10-10_final
2021-10-11 09:12:07	ga_ls8c_ard_3-2-0_089078_2021-10-10_final
2021-10-11 09:12:31	ga_ls8c_ard_3-2-0_089079_2021-10-10_final
2021-10-11 09:12:55	ga_ls8c_ard_3-2-0_089080_2021-10-10_final
2021-10-18 09:16:44	ga_ls8c_ard_3-2-0_090074_2021-10-17_final
2021-10-18 09:17:08	ga_ls8c_ard_3-2-0_090075_2021-10-17_final
2021-10-20 09:06:22	ga_ls8c_ard_3-2-0_088079_2021-10-19_final
2021-10-20 09:06:46	ga_ls8c_ard_3-2-0_088080_2021-10-19_final
2021-10-20 09:07:10	ga_ls8c_ard_3-2-0_088081_2021-10-19_final
2021-10-20 09:07:34	ga_ls8c_ard_3-2-0_088082_2021-10-19_final
2021-10-20 09:07:58	ga_ls8c_ard_3-2-0_088083_2021-10-19_final
2021-10-20 09:08:22	ga_ls8c_ard_3-2-0_088084_2021-10-19_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