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
2018-11-25 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
2018-11-25 09:29:23	ga_ls8c_ard_3-0-0_092076_2018-11-24_final
2018-11-25 09:29:47	ga_ls8c_ard_3-0-0_092077_2018-11-24_final
2018-11-25 09:30:11	ga_ls8c_ard_3-0-0_092078_2018-11-25_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
2018-11-27 09:20:37	ga_ls8c_ard_3-0-0_090085_2018-11-26_final
2018-11-27 09:21:01	ga_ls8c_ard_3-0-0_090086_2018-11-26_final
2018-11-27 09:21:25	ga_ls8c_ard_3-0-0_090087_2018-11-26_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
2018-12-27 09:29:20	ga_ls8c_ard_3-0-0_092076_2018-12-26_final
2018-12-27 09:29:44	ga_ls8c_ard_3-0-0_092077_2018-12-26_final
2018-12-27 09:30:08	ga_ls8c_ard_3-0-0_092078_2018-12-27_final
2018-12-27 09:30:32	ga_ls8c_ard_3-0-0_092079_2018-12-27_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
2018-12-29 09:20:34	ga_ls8c_ard_3-0-0_090085_2018-12-28_final
2018-12-29 09:20:58	ga_ls8c_ard_3-0-0_090086_2018-12-28_final
2018-12-29 09:21:22	ga_ls8c_ard_3-0-0_090087_2018-12-28_final
2019-01-30 09:19:16	ga_ls8c_ard_3-0-0_090082_2019-01-29_final
2019-01-30 09:19:40	ga_ls8c_ard_3-0-0_090083_2019-01-29_final
2019-01-30 09:20:04	ga_ls8c_ard_3-0-0_090084_2019-01-29_final
2019-01-30 09:20:28	ga_ls8c_ard_3-0-0_090085_2019-01-29_final
2019-01-30 09:20:52	ga_ls8c_ard_3-0-0_090086_2019-01-29_final
2019-01-30 09:21:16	ga_ls8c_ard_3-0-0_090087_2019-01-29_final
2019-03-01 09:27:57	ga_ls8c_ard_3-0-0_092073_2019-02-28_final
2019-03-01 09:28:21	ga_ls8c_ard_3-0-0_092074_2019-02-28_final
2019-03-01 09:28:45	ga_ls8c_ard_3-0-0_092075_2019-02-28_final
2019-03-01 09:29:08	ga_ls8c_ard_3-0-0_092076_2019-02-28_final
2019-03-01 09:29:32	ga_ls8c_ard_3-0-0_092077_2019-02-28_final
2019-03-01 09:29:56	ga_ls8c_ard_3-0-0_092078_2019-02-28_final
2019-03-01 09:30:20	ga_ls8c_ard_3-0-0_092079_2019-03-01_final
2019-03-03 09:19:10	ga_ls8c_ard_3-0-0_090082_2019-03-02_final
2019-03-03 09:19:34	ga_ls8c_ard_3-0-0_090083_2019-03-02_final
2019-03-03 09:19:58	ga_ls8c_ard_3-0-0_090084_2019-03-02_final
2019-03-03 09:20:22	ga_ls8c_ard_3-0-0_090085_2019-03-02_final
2019-03-03 09:20:46	ga_ls8c_ard_3-0-0_090086_2019-03-02_final
2019-03-03 09:21:10	ga_ls8c_ard_3-0-0_090087_2019-03-02_final
2019-03-12 09:14:07	ga_ls8c_ard_3-1-0_089085_2019-03-11_final
2019-03-12 09:14:31	ga_ls8c_ard_3-1-0_089086_2019-03-11_final
2019-03-12 09:14:55	ga_ls8c_ard_3-1-0_089087_2019-03-11_final
2019-03-12 09:15:19	ga_ls8c_ard_3-1-0_089088_2019-03-11_final
2019-03-12 09:15:43	ga_ls8c_ard_3-1-0_089089_2019-03-11_final
2019-03-12 09:16:07	ga_ls8c_ard_3-1-0_089090_2019-03-11_final
2019-03-26 09:23:15	ga_ls8c_ard_3-1-0_091077_2019-03-25_final
2019-03-26 09:23:38	ga_ls8c_ard_3-1-0_091078_2019-03-25_final
2019-03-26 09:24:02	ga_ls8c_ard_3-1-0_091079_2019-03-25_final
2019-03-26 09:24:26	ga_ls8c_ard_3-1-0_091080_2019-03-25_final
2019-03-26 09:24:50	ga_ls8c_ard_3-1-0_091081_2019-03-25_final
2019-03-26 09:25:14	ga_ls8c_ard_3-1-0_091082_2019-03-25_final
2019-03-26 09:25:38	ga_ls8c_ard_3-1-0_091083_2019-03-25_final
2019-03-28 09:14:04	ga_ls8c_ard_3-1-0_089085_2019-03-27_final
2019-03-28 09:14:28	ga_ls8c_ard_3-1-0_089086_2019-03-27_final
2019-03-28 09:14:52	ga_ls8c_ard_3-1-0_089087_2019-03-27_final
2019-03-28 09:15:16	ga_ls8c_ard_3-1-0_089088_2019-03-27_final
2019-03-28 09:15:40	ga_ls8c_ard_3-1-0_089089_2019-03-27_final
2019-03-28 09:16:04	ga_ls8c_ard_3-1-0_089090_2019-03-27_final
2019-04-11 09:23:10	ga_ls8c_ard_3-1-0_091077_2019-04-10_final
2019-04-11 09:23:34	ga_ls8c_ard_3-1-0_091078_2019-04-10_final
2019-04-11 09:23:58	ga_ls8c_ard_3-1-0_091079_2019-04-10_final
2019-04-11 09:24:22	ga_ls8c_ard_3-1-0_091080_2019-04-10_final
2019-04-11 09:24:46	ga_ls8c_ard_3-1-0_091081_2019-04-10_final
2019-04-11 09:25:10	ga_ls8c_ard_3-1-0_091082_2019-04-10_final
2019-04-11 09:25:34	ga_ls8c_ard_3-1-0_091083_2019-04-10_final
2019-05-29 09:23:23	ga_ls8c_ard_3-0-0_091077_2019-05-28_final
2019-05-29 09:23:47	ga_ls8c_ard_3-0-0_091078_2019-05-28_final
2019-05-29 09:24:11	ga_ls8c_ard_3-0-0_091079_2019-05-28_final
2019-05-29 09:24:35	ga_ls8c_ard_3-0-0_091080_2019-05-28_final
2019-05-29 09:24:59	ga_ls8c_ard_3-0-0_091081_2019-05-28_final
2019-05-29 09:25:22	ga_ls8c_ard_3-0-0_091082_2019-05-28_final
2019-05-29 09:25:46	ga_ls8c_ard_3-0-0_091083_2019-05-28_final
2019-06-05 09:28:01	ga_ls8c_ard_3-0-0_092073_2019-06-04_final
2019-06-05 09:28:25	ga_ls8c_ard_3-0-0_092074_2019-06-04_final
2019-06-05 09:28:49	ga_ls8c_ard_3-0-0_092075_2019-06-04_final
2019-06-05 09:29:13	ga_ls8c_ard_3-0-0_092076_2019-06-04_final
2019-06-05 09:29:37	ga_ls8c_ard_3-1-0_092077_2019-06-04_final
2019-06-05 09:30:01	ga_ls8c_ard_3-0-0_092078_2019-06-05_final
2019-06-07 09:18:52	ga_ls8c_ard_3-0-0_090081_2019-06-06_final
2019-06-07 09:19:16	ga_ls8c_ard_3-0-0_090082_2019-06-06_final
2019-06-07 09:19:40	ga_ls8c_ard_3-0-0_090083_2019-06-06_final
2019-06-07 09:20:04	ga_ls8c_ard_3-0-0_090084_2019-06-06_final
2019-06-07 09:20:28	ga_ls8c_ard_3-0-0_090085_2019-06-06_final
2019-06-07 09:20:52	ga_ls8c_ard_3-0-0_090086_2019-06-06_final
2019-06-07 09:21:16	ga_ls8c_ard_3-0-0_090087_2019-06-06_final
2019-07-21 09:38:12	ga_ls8c_ard_3-1-0_094067_2019-07-21_final
2019-09-07 09:38:27	ga_ls8c_ard_3-1-0_094067_2019-09-07_final
2019-10-09 09:38:36	ga_ls8c_ard_3-1-0_094067_2019-10-09_final
2019-10-11 09:28:39	ga_ls8c_ard_3-1-0_092073_2019-10-10_final
2019-10-11 09:29:03	ga_ls8c_ard_3-1-0_092074_2019-10-10_final
2019-10-11 09:29:27	ga_ls8c_ard_3-1-0_092075_2019-10-10_final
2019-10-11 09:29:50	ga_ls8c_ard_3-1-0_092076_2019-10-10_final
2019-10-11 09:30:14	ga_ls8c_ard_3-1-0_092077_2019-10-11_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