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
2018-09-27 09:44:07	ga_ls8c_ard_3-0-0_095067_2018-09-27_final
2018-09-29 09:34:10	ga_ls8c_ard_3-0-0_093073_2018-09-29_final
2018-09-29 09:34:34	ga_ls8c_ard_3-0-0_093074_2018-09-29_final
2018-09-29 09:34:58	ga_ls8c_ard_3-0-0_093075_2018-09-29_final
2018-09-29 09:35:21	ga_ls8c_ard_3-0-0_093076_2018-09-29_final
2018-09-29 09:35:45	ga_ls8c_ard_3-0-0_093077_2018-09-29_final
2018-09-29 09:36:09	ga_ls8c_ard_3-0-0_093078_2018-09-29_final
2018-09-29 09:36:33	ga_ls8c_ard_3-0-0_093079_2018-09-29_final
2018-10-06 09:39:36	ga_ls8c_ard_3-0-0_094071_2018-10-06_final
2018-10-06 09:40:00	ga_ls8c_ard_3-0-0_094072_2018-10-06_final
2018-10-06 09:40:24	ga_ls8c_ard_3-0-0_094073_2018-10-06_final
2018-10-06 09:40:48	ga_ls8c_ard_3-0-0_094074_2018-10-06_final
2018-10-15 09:34:17	ga_ls8c_ard_3-0-0_093073_2018-10-15_final
2018-10-15 09:34:41	ga_ls8c_ard_3-0-0_093074_2018-10-15_final
2018-10-15 09:35:05	ga_ls8c_ard_3-0-0_093075_2018-10-15_final
2018-10-15 09:35:29	ga_ls8c_ard_3-0-0_093076_2018-10-15_final
2018-10-15 09:35:53	ga_ls8c_ard_3-0-0_093077_2018-10-15_final
2018-10-15 09:36:16	ga_ls8c_ard_3-0-0_093078_2018-10-15_final
2018-11-07 09:39:45	ga_ls8c_ard_3-0-0_094071_2018-11-07_final
2018-11-07 09:40:09	ga_ls8c_ard_3-0-0_094072_2018-11-07_final
2018-11-07 09:40:33	ga_ls8c_ard_3-0-0_094073_2018-11-07_final
2018-11-07 09:40:57	ga_ls8c_ard_3-0-0_094074_2018-11-07_final
2018-11-23 09:39:45	ga_ls8c_ard_3-0-0_094071_2018-11-23_final
2018-11-23 09:40:09	ga_ls8c_ard_3-0-0_094072_2018-11-23_final
2018-11-23 09:40:33	ga_ls8c_ard_3-0-0_094073_2018-11-23_final
2018-11-23 09:40:57	ga_ls8c_ard_3-0-0_094074_2018-11-23_final
2018-11-30 09:44:20	ga_ls8c_ard_3-0-0_095067_2018-11-30_final
2018-12-02 09:34:21	ga_ls8c_ard_3-0-0_093073_2018-12-02_final
2018-12-02 09:34:45	ga_ls8c_ard_3-0-0_093074_2018-12-02_final
2018-12-02 09:35:09	ga_ls8c_ard_3-0-0_093075_2018-12-02_final
2018-12-02 09:35:33	ga_ls8c_ard_3-0-0_093076_2018-12-02_final
2018-12-02 09:35:57	ga_ls8c_ard_3-0-0_093077_2018-12-02_final
2018-12-02 09:36:21	ga_ls8c_ard_3-0-0_093078_2018-12-02_final
2018-12-02 09:36:45	ga_ls8c_ard_3-0-0_093079_2018-12-02_final
2018-12-16 09:44:17	ga_ls8c_ard_3-0-0_095067_2018-12-16_final
2018-12-18 09:34:19	ga_ls8c_ard_3-0-0_093073_2018-12-18_final
2018-12-18 09:34:43	ga_ls8c_ard_3-0-0_093074_2018-12-18_final
2018-12-18 09:35:07	ga_ls8c_ard_3-0-0_093075_2018-12-18_final
2018-12-18 09:35:31	ga_ls8c_ard_3-0-0_093076_2018-12-18_final
2018-12-18 09:35:55	ga_ls8c_ard_3-0-0_093077_2018-12-18_final
2018-12-18 09:36:19	ga_ls8c_ard_3-0-0_093078_2018-12-18_final
2018-12-18 09:36:42	ga_ls8c_ard_3-0-0_093079_2018-12-18_final
2019-01-10 09:39:41	ga_ls8c_ard_3-0-0_094071_2019-01-10_final
2019-01-10 09:40:05	ga_ls8c_ard_3-0-0_094072_2019-01-10_final
2019-01-10 09:40:29	ga_ls8c_ard_3-0-0_094073_2019-01-10_final
2019-01-10 09:40:52	ga_ls8c_ard_3-0-0_094074_2019-01-10_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
2019-08-17 09:27:49	ga_ls8c_ard_3-1-0_091087_2019-08-16_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
2019-09-04 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
2019-09-09 09:30:05	ga_ls8c_ard_3-1-0_092077_2019-09-09_final
2019-09-09 09:30:29	ga_ls8c_ard_3-1-0_092078_2019-09-09_final
2019-09-09 09:30:53	ga_ls8c_ard_3-1-0_092079_2019-09-09_final
2019-09-09 09:31:17	ga_ls8c_ard_3-1-0_092080_2019-09-09_final
2019-09-09 09:31:41	ga_ls8c_ard_3-1-0_092081_2019-09-09_final
2019-09-09 09:32:05	ga_ls8c_ard_3-1-0_092082_2019-09-09_final
2019-09-09 09:32:29	ga_ls8c_ard_3-1-0_092083_2019-09-09_final
2019-09-11 09:20:56	ga_ls8c_ard_3-1-0_090085_2019-09-10_final
2019-09-11 09:21:20	ga_ls8c_ard_3-1-0_090086_2019-09-10_final
2019-09-11 09:21:44	ga_ls8c_ard_3-1-0_090087_2019-09-10_final
2019-09-11 09:22:08	ga_ls8c_ard_3-1-0_090088_2019-09-10_final
2019-09-11 09:22:32	ga_ls8c_ard_3-1-0_090089_2019-09-10_final
2019-09-11 09:22:56	ga_ls8c_ard_3-1-0_090090_2019-09-10_final
2021-10-14 09:40:15	ga_ls8c_ard_3-2-0_094071_2021-10-14_final
2021-10-14 09:40:38	ga_ls8c_ard_3-2-0_094072_2021-10-14_final
2021-10-14 09:41:02	ga_ls8c_ard_3-2-0_094073_2021-10-14_final
2021-10-14 09:41:26	ga_ls8c_ard_3-2-0_094074_2021-10-14_final
2021-10-16 09:30:17	ga_ls8c_ard_3-2-0_092077_2021-10-16_final
2021-10-16 09:30:41	ga_ls8c_ard_3-2-0_092078_2021-10-16_final
2021-10-16 09:31:05	ga_ls8c_ard_3-2-0_092079_2021-10-16_final
2021-10-16 09:31:29	ga_ls8c_ard_3-2-0_092080_2021-10-16_final
2021-10-16 09:31:53	ga_ls8c_ard_3-2-0_092081_2021-10-16_final
2021-10-16 09:32:17	ga_ls8c_ard_3-2-0_092082_2021-10-16_final
2021-10-16 09:32:41	ga_ls8c_ard_3-2-0_092083_2021-10-16_final
2021-10-18 09:21:07	ga_ls8c_ard_3-2-0_090085_2021-10-17_final
2021-10-18 09:21:31	ga_ls8c_ard_3-2-0_090086_2021-10-17_final
2021-10-18 09:21:55	ga_ls8c_ard_3-2-0_090087_2021-10-17_final
2021-10-18 09:22:19	ga_ls8c_ard_3-2-0_090088_2021-10-17_final
2021-10-18 09:22:43	ga_ls8c_ard_3-2-0_090089_2021-10-17_final
2021-10-18 09:23:07	ga_ls8c_ard_3-2-0_090090_2021-10-17_final
2021-10-21 09:44:50	ga_ls8c_ard_3-2-0_095067_2021-10-21_final
2021-10-23 09:34:53	ga_ls8c_ard_3-2-0_093073_2021-10-23_final
2021-10-23 09:35:16	ga_ls8c_ard_3-2-0_093074_2021-10-23_final
2021-10-23 09:35:40	ga_ls8c_ard_3-2-0_093075_2021-10-23_final
2021-10-23 09:36:04	ga_ls8c_ard_3-2-0_093076_2021-10-23_final
2021-10-23 09:36:28	ga_ls8c_ard_3-2-0_093077_2021-10-23_final
2021-10-23 09:36:52	ga_ls8c_ard_3-2-0_093078_2021-10-23_final
2021-10-25 09:25:42	ga_ls8c_ard_3-2-0_091081_2021-10-24_final
2021-10-25 09:26:06	ga_ls8c_ard_3-2-0_091082_2021-10-24_final
2021-10-25 09:26:30	ga_ls8c_ard_3-2-0_091083_2021-10-24_final
2021-10-25 09:26:54	ga_ls8c_ard_3-2-0_091084_2021-10-24_final
2021-10-25 09:27:18	ga_ls8c_ard_3-2-0_091085_2021-10-24_final
2021-10-25 09:27:42	ga_ls8c_ard_3-2-0_091086_2021-10-24_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