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
2017-09-21 09:21:39	ga_ls8c_ard_3-0-0_090087_2017-09-20_final
2017-09-21 09:22:03	ga_ls8c_ard_3-0-0_090088_2017-09-20_final
2017-09-21 09:22:27	ga_ls8c_ard_3-0-0_090089_2017-09-20_final
2017-09-21 09:22:51	ga_ls8c_ard_3-0-0_090090_2017-09-20_final
2017-09-21 09:23:15	ga_ls8c_ard_3-0-0_090091_2017-09-20_final
2017-10-14 09:26:22	ga_ls8c_ard_3-0-0_091083_2017-10-13_final
2017-10-14 09:26:46	ga_ls8c_ard_3-0-0_091084_2017-10-13_final
2017-10-14 09:27:10	ga_ls8c_ard_3-0-0_091085_2017-10-13_final
2017-10-14 09:27:33	ga_ls8c_ard_3-0-0_091086_2017-10-13_final
2017-10-14 09:27:57	ga_ls8c_ard_3-0-0_091087_2017-10-13_final
2017-10-14 09:28:21	ga_ls8c_ard_3-0-0_091088_2017-10-13_final
2017-11-13 09:35:30	ga_ls8c_ard_3-0-0_093075_2017-11-13_final
2017-11-13 09:35:54	ga_ls8c_ard_3-0-0_093076_2017-11-13_final
2017-11-13 09:36:18	ga_ls8c_ard_3-0-0_093077_2017-11-13_final
2017-11-13 09:36:42	ga_ls8c_ard_3-0-0_093078_2017-11-13_final
2017-11-13 09:37:06	ga_ls8c_ard_3-0-0_093079_2017-11-13_final
2017-11-13 09:37:30	ga_ls8c_ard_3-0-0_093080_2017-11-13_final
2017-11-13 09:37:54	ga_ls8c_ard_3-0-0_093081_2017-11-13_final
2017-11-15 09:26:19	ga_ls8c_ard_3-0-0_091083_2017-11-14_final
2017-11-15 09:26:43	ga_ls8c_ard_3-0-0_091084_2017-11-14_final
2017-11-15 09:27:07	ga_ls8c_ard_3-0-0_091085_2017-11-14_final
2017-11-15 09:27:31	ga_ls8c_ard_3-0-0_091086_2017-11-14_final
2017-11-15 09:27:55	ga_ls8c_ard_3-0-0_091087_2017-11-14_final
2017-11-15 09:28:19	ga_ls8c_ard_3-0-0_091088_2017-11-14_final
2017-11-24 09:21:41	ga_ls8c_ard_3-0-0_090087_2017-11-23_final
2017-11-24 09:22:05	ga_ls8c_ard_3-0-0_090088_2017-11-23_final
2017-11-24 09:22:29	ga_ls8c_ard_3-0-0_090089_2017-11-23_final
2017-11-24 09:22:53	ga_ls8c_ard_3-0-0_090090_2017-11-23_final
2017-11-24 09:23:17	ga_ls8c_ard_3-0-0_090091_2017-11-23_final
2017-12-15 09:35:25	ga_ls8c_ard_3-0-0_093075_2017-12-15_final
2017-12-17 09:26:15	ga_ls8c_ard_3-0-0_091083_2017-12-16_final
2017-12-17 09:26:39	ga_ls8c_ard_3-0-0_091084_2017-12-16_final
2017-12-17 09:27:03	ga_ls8c_ard_3-0-0_091085_2017-12-16_final
2017-12-17 09:27:27	ga_ls8c_ard_3-0-0_091086_2017-12-16_final
2017-12-17 09:27:51	ga_ls8c_ard_3-0-0_091087_2017-12-16_final
2017-12-17 09:28:15	ga_ls8c_ard_3-0-0_091088_2017-12-16_final
2017-12-17 09:28:39	ga_ls8c_ard_3-0-0_091089_2017-12-16_final
2017-12-26 09:21:40	ga_ls8c_ard_3-0-0_090087_2017-12-25_final
2017-12-26 09:22:04	ga_ls8c_ard_3-0-0_090088_2017-12-25_final
2017-12-26 09:22:28	ga_ls8c_ard_3-0-0_090089_2017-12-25_final
2017-12-26 09:22:52	ga_ls8c_ard_3-0-0_090090_2017-12-25_final
2017-12-26 09:23:16	ga_ls8c_ard_3-0-0_090091_2017-12-25_final
2017-12-31 09:35:24	ga_ls8c_ard_3-0-0_093075_2017-12-31_final
2017-12-31 09:35:48	ga_ls8c_ard_3-0-0_093076_2017-12-31_final
2017-12-31 09:36:12	ga_ls8c_ard_3-0-0_093077_2017-12-31_final
2017-12-31 09:36:36	ga_ls8c_ard_3-0-0_093078_2017-12-31_final
2017-12-31 09:37:00	ga_ls8c_ard_3-0-0_093079_2017-12-31_final
2017-12-31 09:37:24	ga_ls8c_ard_3-0-0_093080_2017-12-31_final
2017-12-31 09:37:48	ga_ls8c_ard_3-0-0_093081_2017-12-31_final
2018-01-02 09:26:13	ga_ls8c_ard_3-0-0_091083_2018-01-01_final
2018-01-02 09:26:37	ga_ls8c_ard_3-0-0_091084_2018-01-01_final
2018-01-02 09:27:01	ga_ls8c_ard_3-0-0_091085_2018-01-01_final
2018-01-02 09:27:25	ga_ls8c_ard_3-0-0_091086_2018-01-01_final
2018-01-02 09:27:49	ga_ls8c_ard_3-0-0_091087_2018-01-01_final
2018-01-02 09:28:13	ga_ls8c_ard_3-0-0_091088_2018-01-01_final
2018-01-02 09:28:37	ga_ls8c_ard_3-0-0_091089_2018-01-01_final
2018-02-08 09:39:40	ga_ls8c_ard_3-0-0_094071_2018-02-08_final
2018-02-08 09:40:04	ga_ls8c_ard_3-0-0_094072_2018-02-08_final
2018-02-08 09:40:28	ga_ls8c_ard_3-0-0_094073_2018-02-08_final
2018-02-08 09:40:52	ga_ls8c_ard_3-0-0_094074_2018-02-08_final
2018-02-08 09:41:16	ga_ls8c_ard_3-0-0_094075_2018-02-08_final
2018-02-08 09:41:40	ga_ls8c_ard_3-0-0_094076_2018-02-08_final
2018-02-10 09:30:29	ga_ls8c_ard_3-0-0_092079_2018-02-10_final
2018-02-10 09:30:53	ga_ls8c_ard_3-0-0_092080_2018-02-10_final
2018-02-10 09:31:17	ga_ls8c_ard_3-0-0_092081_2018-02-10_final
2018-02-10 09:31:41	ga_ls8c_ard_3-0-0_092082_2018-02-10_final
2018-02-10 09:32:05	ga_ls8c_ard_3-0-0_092083_2018-02-10_final
2018-02-10 09:32:29	ga_ls8c_ard_3-0-0_092084_2018-02-10_final
2018-02-10 09:32:53	ga_ls8c_ard_3-0-0_092085_2018-02-10_final
2018-02-12 09:21:19	ga_ls8c_ard_3-0-0_090087_2018-02-11_final
2018-02-12 09:21:43	ga_ls8c_ard_3-0-0_090088_2018-02-11_final
2018-02-12 09:22:07	ga_ls8c_ard_3-0-0_090089_2018-02-11_final
2018-02-12 09:22:31	ga_ls8c_ard_3-0-0_090090_2018-02-11_final
2018-02-12 09:22:55	ga_ls8c_ard_3-0-0_090091_2018-02-11_final
2018-03-09 09:16:08	ga_ls8c_ard_3-0-0_089090_2018-03-08_final
2018-03-10 09:50:12	ga_ls8c_ard_3-0-0_096067_2018-03-10_final
2018-03-14 09:30:38	ga_ls8c_ard_3-0-0_092080_2018-03-14_final
2018-03-14 09:31:02	ga_ls8c_ard_3-0-0_092081_2018-03-14_final
2018-03-14 09:31:26	ga_ls8c_ard_3-0-0_092082_2018-03-14_final
2018-03-14 09:31:50	ga_ls8c_ard_3-0-0_092083_2018-03-14_final
2018-03-14 09:32:14	ga_ls8c_ard_3-0-0_092084_2018-03-14_final
2018-03-14 09:32:38	ga_ls8c_ard_3-0-0_092085_2018-03-14_final
2018-03-28 09:39:18	ga_ls8c_ard_3-0-0_094071_2018-03-28_final
2018-03-28 09:39:42	ga_ls8c_ard_3-0-0_094072_2018-03-28_final
2018-03-28 09:40:06	ga_ls8c_ard_3-0-0_094073_2018-03-28_final
2018-03-28 09:40:30	ga_ls8c_ard_3-0-0_094074_2018-03-28_final
2018-03-28 09:40:54	ga_ls8c_ard_3-0-0_094075_2018-03-28_final
2018-03-28 09:41:18	ga_ls8c_ard_3-0-0_094076_2018-03-28_final
2018-03-30 09:30:07	ga_ls8c_ard_3-0-0_092079_2018-03-30_final
2018-03-30 09:30:31	ga_ls8c_ard_3-0-0_092080_2018-03-30_final
2018-03-30 09:30:55	ga_ls8c_ard_3-0-0_092081_2018-03-30_final
2018-03-30 09:31:19	ga_ls8c_ard_3-0-0_092082_2018-03-30_final
2018-03-30 09:31:43	ga_ls8c_ard_3-0-0_092083_2018-03-30_final
2018-03-30 09:32:07	ga_ls8c_ard_3-0-0_092084_2018-03-30_final
2018-03-30 09:32:31	ga_ls8c_ard_3-0-0_092085_2018-03-30_final
2018-04-10 09:15:52	ga_ls8c_ard_3-0-0_089090_2018-04-09_final
2018-04-11 09:49:57	ga_ls8c_ard_3-0-0_096067_2018-04-11_final
2018-04-26 09:15:43	ga_ls8c_ard_3-0-0_089090_2018-04-25_final
2018-04-27 09:49:48	ga_ls8c_ard_3-0-0_096067_2018-04-27_final
2018-05-28 09:15:21	ga_ls8c_ard_3-0-0_089090_2018-05-27_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