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
2017-04-17 09:43:51	ga_ls8c_ard_3-0-0_095067_2017-04-17_final
2017-04-19 09:33:28	ga_ls8c_ard_3-0-0_093072_2017-04-19_final
2017-04-19 09:33:51	ga_ls8c_ard_3-0-0_093073_2017-04-19_final
2017-04-19 09:34:15	ga_ls8c_ard_3-0-0_093074_2017-04-19_final
2017-04-19 09:34:39	ga_ls8c_ard_3-0-0_093075_2017-04-19_final
2017-04-19 09:35:03	ga_ls8c_ard_3-0-0_093076_2017-04-19_final
2017-04-19 09:35:27	ga_ls8c_ard_3-0-0_093077_2017-04-19_final
2017-04-19 09:35:51	ga_ls8c_ard_3-0-0_093078_2017-04-19_final
2017-05-03 09:43:41	ga_ls8c_ard_3-0-0_095067_2017-05-03_final
2017-05-05 09:33:21	ga_ls8c_ard_3-0-0_093072_2017-05-05_final
2017-05-05 09:33:44	ga_ls8c_ard_3-0-0_093073_2017-05-05_final
2017-05-05 09:34:08	ga_ls8c_ard_3-0-0_093074_2017-05-05_final
2017-05-05 09:34:32	ga_ls8c_ard_3-0-0_093075_2017-05-05_final
2017-05-05 09:34:56	ga_ls8c_ard_3-0-0_093076_2017-05-05_final
2017-05-05 09:35:20	ga_ls8c_ard_3-0-0_093077_2017-05-05_final
2017-05-05 09:35:44	ga_ls8c_ard_3-0-0_093078_2017-05-05_final
2017-05-12 09:39:13	ga_ls8c_ard_3-0-0_094071_2017-05-12_final
2017-05-12 09:39:37	ga_ls8c_ard_3-0-0_094072_2017-05-12_final
2017-05-12 09:40:01	ga_ls8c_ard_3-0-0_094073_2017-05-12_final
2017-05-19 09:43:53	ga_ls8c_ard_3-0-0_095067_2017-05-19_final
2017-05-21 09:33:32	ga_ls8c_ard_3-0-0_093072_2017-05-21_final
2017-05-21 09:33:56	ga_ls8c_ard_3-0-0_093073_2017-05-21_final
2017-05-21 09:34:20	ga_ls8c_ard_3-0-0_093074_2017-05-21_final
2017-05-21 09:34:44	ga_ls8c_ard_3-0-0_093075_2017-05-21_final
2017-05-21 09:35:08	ga_ls8c_ard_3-0-0_093076_2017-05-21_final
2017-05-21 09:35:32	ga_ls8c_ard_3-0-0_093077_2017-05-21_final
2017-05-21 09:35:56	ga_ls8c_ard_3-0-0_093078_2017-05-21_final
2017-05-28 09:37:48	ga_ls8c_ard_3-0-0_094067_2017-05-28_final
2017-05-28 09:39:24	ga_ls8c_ard_3-0-0_094071_2017-05-28_final
2017-05-28 09:39:47	ga_ls8c_ard_3-0-0_094072_2017-05-28_final
2017-05-28 09:40:11	ga_ls8c_ard_3-0-0_094073_2017-05-28_final
2017-06-13 09:37:55	ga_ls8c_ard_3-0-0_094067_2017-06-13_final
2017-06-13 09:39:31	ga_ls8c_ard_3-0-0_094071_2017-06-13_final
2017-06-13 09:39:55	ga_ls8c_ard_3-0-0_094072_2017-06-13_final
2017-06-13 09:40:19	ga_ls8c_ard_3-0-0_094073_2017-06-13_final
2017-06-24 09:25:01	ga_ls8c_ard_3-0-0_091081_2017-06-23_final
2017-06-24 09:25:25	ga_ls8c_ard_3-0-0_091082_2017-06-23_final
2019-06-19 09:38:05	ga_ls8c_ard_3-1-0_094067_2019-06-19_final
2019-06-19 09:39:40	ga_ls8c_ard_3-1-0_094071_2019-06-19_final
2019-06-19 09:40:04	ga_ls8c_ard_3-1-0_094072_2019-06-19_final
2019-06-19 09:40:28	ga_ls8c_ard_3-1-0_094073_2019-06-19_final
2019-06-21 09:29:43	ga_ls8c_ard_3-1-0_092077_2019-06-20_final
2019-06-21 09:30:07	ga_ls8c_ard_3-1-0_092078_2019-06-21_final
2019-06-21 09:30:31	ga_ls8c_ard_3-1-0_092079_2019-06-21_final
2019-06-21 09:30:55	ga_ls8c_ard_3-1-0_092080_2019-06-21_final
2019-06-21 09:31:19	ga_ls8c_ard_3-1-0_092081_2019-06-21_final
2019-06-21 09:31:43	ga_ls8c_ard_3-1-0_092082_2019-06-21_final
2019-06-30 09:25:10	ga_ls8c_ard_3-1-0_091081_2019-06-29_final
2019-06-30 09:25:34	ga_ls8c_ard_3-1-0_091082_2019-06-29_final
2019-06-30 09:25:58	ga_ls8c_ard_3-1-0_091083_2019-06-29_final
2019-06-30 09:26:22	ga_ls8c_ard_3-1-0_091084_2019-06-29_final
2019-06-30 09:26:46	ga_ls8c_ard_3-1-0_091085_2019-06-29_final
2019-06-30 09:27:10	ga_ls8c_ard_3-1-0_091086_2019-06-29_final
2019-07-02 09:15:37	ga_ls8c_ard_3-1-0_089088_2019-07-01_final
2019-07-02 09:16:01	ga_ls8c_ard_3-1-0_089089_2019-07-01_final
2019-07-02 09:16:25	ga_ls8c_ard_3-1-0_089090_2019-07-01_final
2019-08-06 09:39:54	ga_ls8c_ard_3-1-0_094071_2019-08-06_final
2019-08-06 09:40:18	ga_ls8c_ard_3-1-0_094072_2019-08-06_final
2019-08-06 09:40:42	ga_ls8c_ard_3-1-0_094073_2019-08-06_final
2019-08-08 09:29:57	ga_ls8c_ard_3-1-0_092077_2019-08-07_final
2019-08-08 09:30:21	ga_ls8c_ard_3-1-0_092078_2019-08-08_final
2019-08-08 09:30:45	ga_ls8c_ard_3-1-0_092079_2019-08-08_final
2019-08-08 09:31:09	ga_ls8c_ard_3-1-0_092080_2019-08-08_final
2019-08-08 09:31:33	ga_ls8c_ard_3-1-0_092081_2019-08-08_final
2019-08-08 09:31:57	ga_ls8c_ard_3-1-0_092082_2019-08-08_final
2019-08-17 09:25:25	ga_ls8c_ard_3-1-0_091081_2019-08-16_final
2019-08-17 09:25:49	ga_ls8c_ard_3-1-0_091082_2019-08-16_final
2019-08-17 09:26:13	ga_ls8c_ard_3-1-0_091083_2019-08-16_final
2019-08-17 09:26:37	ga_ls8c_ard_3-1-0_091084_2019-08-16_final
2019-08-17 09:27:01	ga_ls8c_ard_3-1-0_091085_2019-08-16_final
2019-08-17 09:27:25	ga_ls8c_ard_3-1-0_091086_2019-08-16_final
2019-08-19 09:15:52	ga_ls8c_ard_3-1-0_089088_2019-08-18_final
2019-08-19 09:16:16	ga_ls8c_ard_3-1-0_089089_2019-08-18_final
2019-08-19 09:16:40	ga_ls8c_ard_3-1-0_089090_2019-08-18_final
2019-09-02 09:25:29	ga_ls8c_ard_3-1-0_091081_2019-09-01_final
2019-09-02 09:25:52	ga_ls8c_ard_3-1-0_091082_2019-09-01_final
2019-09-02 09:26:16	ga_ls8c_ard_3-1-0_091083_2019-09-01_final
2019-09-02 09:26:40	ga_ls8c_ard_3-1-0_091084_2019-09-01_final
2019-09-02 09:27:04	ga_ls8c_ard_3-1-0_091085_2019-09-01_final
2019-09-02 09:27:28	ga_ls8c_ard_3-1-0_091086_2019-09-01_final
2019-09-04 09:15:55	ga_ls8c_ard_3-1-0_089088_2019-09-03_final
2019-09-04 09:16:19	ga_ls8c_ard_3-1-0_089089_2019-09-03_final
2019-09-04 09:16:43	ga_ls8c_ard_3-1-0_089090_2019-09-03_final
2019-10-04 09:25:38	ga_ls8c_ard_3-1-0_091081_2019-10-03_final
2019-10-04 09:26:02	ga_ls8c_ard_3-1-0_091082_2019-10-03_final
2019-10-04 09:26:26	ga_ls8c_ard_3-1-0_091083_2019-10-03_final
2019-10-04 09:26:50	ga_ls8c_ard_3-1-0_091084_2019-10-03_final
2019-10-04 09:27:14	ga_ls8c_ard_3-1-0_091085_2019-10-03_final
2019-10-04 09:27:38	ga_ls8c_ard_3-1-0_091086_2019-10-03_final
2019-10-06 09:16:05	ga_ls8c_ard_3-1-0_089088_2019-10-05_final
2019-10-06 09:16:29	ga_ls8c_ard_3-1-0_089089_2019-10-05_final
2019-10-06 09:16:53	ga_ls8c_ard_3-1-0_089090_2019-10-05_final
2019-10-20 09:25:40	ga_ls8c_ard_3-1-0_091081_2019-10-19_final
2019-10-20 09:26:04	ga_ls8c_ard_3-1-0_091082_2019-10-19_final
2019-10-20 09:26:28	ga_ls8c_ard_3-1-0_091083_2019-10-19_final
2019-10-20 09:26:52	ga_ls8c_ard_3-1-0_091084_2019-10-19_final
2019-10-20 09:27:16	ga_ls8c_ard_3-1-0_091085_2019-10-19_final
2019-10-20 09:27:40	ga_ls8c_ard_3-1-0_091086_2019-10-19_final
2019-10-22 09:16:06	ga_ls8c_ard_3-1-0_089088_2019-10-21_final
2019-10-22 09:16:30	ga_ls8c_ard_3-1-0_089089_2019-10-21_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