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
2017-04-21 09:25:04	ga_ls8c_ard_3-0-0_091082_2017-04-20_final
2017-04-21 09:25:28	ga_ls8c_ard_3-0-0_091083_2017-04-20_final
2017-04-21 09:25:52	ga_ls8c_ard_3-0-0_091084_2017-04-20_final
2017-04-21 09:26:16	ga_ls8c_ard_3-0-0_091085_2017-04-20_final
2017-04-21 09:26:40	ga_ls8c_ard_3-0-0_091086_2017-04-20_final
2017-04-21 09:27:04	ga_ls8c_ard_3-0-0_091087_2017-04-20_final
2017-05-30 09:29:51	ga_ls8c_ard_3-0-0_092078_2017-05-29_final
2017-05-30 09:30:14	ga_ls8c_ard_3-0-0_092079_2017-05-30_final
2017-05-30 09:30:38	ga_ls8c_ard_3-0-0_092080_2017-05-30_final
2017-05-30 09:31:02	ga_ls8c_ard_3-0-0_092081_2017-05-30_final
2017-05-30 09:31:26	ga_ls8c_ard_3-0-0_092082_2017-05-30_final
2017-05-30 09:31:50	ga_ls8c_ard_3-0-0_092083_2017-05-30_final
2017-06-01 09:20:18	ga_ls8c_ard_3-0-0_090085_2017-05-31_final
2017-06-01 09:20:42	ga_ls8c_ard_3-0-0_090086_2017-05-31_final
2017-06-01 09:21:06	ga_ls8c_ard_3-0-0_090087_2017-05-31_final
2017-06-01 09:21:29	ga_ls8c_ard_3-0-0_090088_2017-05-31_final
2017-06-01 09:21:53	ga_ls8c_ard_3-0-0_090089_2017-05-31_final
2017-06-01 09:22:17	ga_ls8c_ard_3-0-0_090090_2017-05-31_final
2017-06-01 09:22:41	ga_ls8c_ard_3-0-0_090091_2017-05-31_final
2017-06-06 09:34:05	ga_ls8c_ard_3-0-0_093073_2017-06-06_final
2017-06-06 09:34:29	ga_ls8c_ard_3-0-0_093074_2017-06-06_final
2017-06-06 09:34:53	ga_ls8c_ard_3-0-0_093075_2017-06-06_final
2017-06-06 09:35:17	ga_ls8c_ard_3-0-0_093076_2017-06-06_final
2017-06-06 09:35:41	ga_ls8c_ard_3-0-0_093077_2017-06-06_final
2017-06-06 09:36:05	ga_ls8c_ard_3-0-0_093078_2017-06-06_final
2017-06-06 09:36:29	ga_ls8c_ard_3-0-0_093079_2017-06-06_final
2017-06-08 09:25:20	ga_ls8c_ard_3-0-0_091082_2017-06-07_final
2017-06-08 09:25:44	ga_ls8c_ard_3-0-0_091083_2017-06-07_final
2017-06-08 09:26:08	ga_ls8c_ard_3-0-0_091084_2017-06-07_final
2017-06-08 09:26:32	ga_ls8c_ard_3-0-0_091085_2017-06-07_final
2017-06-08 09:26:56	ga_ls8c_ard_3-0-0_091086_2017-06-07_final
2017-06-08 09:27:20	ga_ls8c_ard_3-0-0_091087_2017-06-07_final
2017-06-17 09:20:24	ga_ls8c_ard_3-0-0_090085_2017-06-16_final
2017-06-17 09:20:48	ga_ls8c_ard_3-0-0_090086_2017-06-16_final
2017-06-17 09:21:12	ga_ls8c_ard_3-0-0_090087_2017-06-16_final
2017-06-17 09:21:36	ga_ls8c_ard_3-0-0_090088_2017-06-16_final
2017-06-17 09:22:00	ga_ls8c_ard_3-0-0_090089_2017-06-16_final
2017-07-17 09:30:06	ga_ls8c_ard_3-0-0_092078_2017-07-17_final
2017-07-17 09:30:30	ga_ls8c_ard_3-0-0_092079_2017-07-17_final
2017-07-17 09:30:54	ga_ls8c_ard_3-0-0_092080_2017-07-17_final
2017-07-17 09:31:18	ga_ls8c_ard_3-0-0_092081_2017-07-17_final
2017-07-17 09:31:42	ga_ls8c_ard_3-0-0_092082_2017-07-17_final
2017-07-17 09:32:06	ga_ls8c_ard_3-0-0_092083_2017-07-17_final
2017-07-19 09:20:57	ga_ls8c_ard_3-0-0_090086_2017-07-18_final
2017-07-19 09:21:21	ga_ls8c_ard_3-0-0_090087_2017-07-18_final
2017-07-19 09:21:45	ga_ls8c_ard_3-0-0_090088_2017-07-18_final
2017-07-19 09:22:09	ga_ls8c_ard_3-0-0_090089_2017-07-18_final
2017-07-19 09:22:33	ga_ls8c_ard_3-0-0_090090_2017-07-18_final
2017-07-19 09:22:57	ga_ls8c_ard_3-0-0_090091_2017-07-18_final
2017-07-28 09:16:02	ga_ls8c_ard_3-0-0_089089_2017-07-27_final
2017-07-28 09:16:26	ga_ls8c_ard_3-0-0_089090_2017-07-27_final
2017-08-13 09:16:09	ga_ls8c_ard_3-0-0_089089_2017-08-12_final
2017-08-13 09:16:33	ga_ls8c_ard_3-0-0_089090_2017-08-12_final
2017-11-01 09:16:24	ga_ls8c_ard_3-0-0_089089_2017-10-31_final
2017-11-01 09:16:48	ga_ls8c_ard_3-0-0_089090_2017-10-31_final
2017-11-17 09:16:21	ga_ls8c_ard_3-0-0_089089_2017-11-16_final
2017-11-17 09:16:45	ga_ls8c_ard_3-0-0_089090_2017-11-16_final
2017-12-03 09:16:15	ga_ls8c_ard_3-0-0_089089_2017-12-02_final
2017-12-03 09:16:39	ga_ls8c_ard_3-0-0_089090_2017-12-02_final
2018-01-20 09:16:07	ga_ls8c_ard_3-0-0_089089_2018-01-19_final
2018-01-20 09:16:31	ga_ls8c_ard_3-0-0_089090_2018-01-19_final
2018-02-05 09:15:58	ga_ls8c_ard_3-0-0_089089_2018-02-04_final
2018-02-05 09:16:22	ga_ls8c_ard_3-0-0_089090_2018-02-04_final
2018-03-09 09:15:44	ga_ls8c_ard_3-0-0_089089_2018-03-08_final
2018-03-09 09:16:08	ga_ls8c_ard_3-0-0_089090_2018-03-08_final
2018-03-25 09:15:37	ga_ls8c_ard_3-0-0_089089_2018-03-24_final
2018-03-25 09:16:00	ga_ls8c_ard_3-0-0_089090_2018-03-24_final
2018-05-12 09:15:10	ga_ls8c_ard_3-0-0_089089_2018-05-11_final
2018-05-12 09:15:33	ga_ls8c_ard_3-0-0_089090_2018-05-11_final
2018-05-28 09:14:57	ga_ls8c_ard_3-0-0_089089_2018-05-27_final
2018-05-28 09:15:21	ga_ls8c_ard_3-0-0_089090_2018-05-27_final
2018-05-31 09:38:37	ga_ls8c_ard_3-0-0_094071_2018-05-31_final
2018-05-31 09:39:01	ga_ls8c_ard_3-0-0_094072_2018-05-31_final
2018-05-31 09:39:25	ga_ls8c_ard_3-0-0_094073_2018-05-31_final
2018-05-31 09:39:49	ga_ls8c_ard_3-0-0_094074_2018-05-31_final
2018-06-02 09:29:03	ga_ls8c_ard_3-0-0_092078_2018-06-01_final
2018-06-02 09:29:27	ga_ls8c_ard_3-0-0_092079_2018-06-01_final
2018-06-02 09:29:50	ga_ls8c_ard_3-0-0_092080_2018-06-01_final
2018-06-02 09:30:14	ga_ls8c_ard_3-0-0_092081_2018-06-02_final
2018-06-02 09:30:38	ga_ls8c_ard_3-0-0_092082_2018-06-02_final
2018-06-02 09:31:02	ga_ls8c_ard_3-0-0_092083_2018-06-02_final
2018-06-16 09:38:43	ga_ls8c_ard_3-0-0_094071_2018-06-16_final
2018-06-16 09:39:07	ga_ls8c_ard_3-0-0_094072_2018-06-16_final
2018-06-16 09:39:31	ga_ls8c_ard_3-0-0_094073_2018-06-16_final
2018-06-16 09:39:55	ga_ls8c_ard_3-0-0_094074_2018-06-16_final
2018-06-29 09:15:09	ga_ls8c_ard_3-0-0_089089_2018-06-28_final
2018-06-29 09:15:33	ga_ls8c_ard_3-0-0_089090_2018-06-28_final
2018-07-15 09:15:16	ga_ls8c_ard_3-0-0_089089_2018-07-14_final
2018-07-15 09:15:40	ga_ls8c_ard_3-0-0_089090_2018-07-14_final
2018-07-20 09:29:27	ga_ls8c_ard_3-0-0_092078_2018-07-19_final
2018-07-20 09:29:51	ga_ls8c_ard_3-0-0_092079_2018-07-19_final
2018-07-20 09:30:15	ga_ls8c_ard_3-0-0_092080_2018-07-20_final
2018-07-20 09:30:39	ga_ls8c_ard_3-0-0_092081_2018-07-20_final
2018-07-20 09:31:03	ga_ls8c_ard_3-0-0_092082_2018-07-20_final
2018-07-20 09:31:27	ga_ls8c_ard_3-0-0_092083_2018-07-20_final
2018-07-22 09:20:18	ga_ls8c_ard_3-0-0_090086_2018-07-21_final
2018-07-22 09:20:42	ga_ls8c_ard_3-0-0_090087_2018-07-21_final
2018-07-22 09:21:06	ga_ls8c_ard_3-0-0_090088_2018-07-21_final
2018-07-22 09:21:30	ga_ls8c_ard_3-0-0_090089_2018-07-21_final
2018-07-22 09:21:54	ga_ls8c_ard_3-0-0_090090_2018-07-21_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years