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
2016-08-08 09:27:42	ga_ls8c_ard_3-0-0_091087_2016-08-07_final
2016-08-08 09:28:06	ga_ls8c_ard_3-0-0_091088_2016-08-07_final
2017-12-20 09:50:47	ga_ls8c_ard_3-0-0_096067_2017-12-20_final
2017-12-20 09:51:11	ga_ls8c_ard_3-0-0_096068_2017-12-20_final
2017-12-20 09:51:35	ga_ls8c_ard_3-0-0_096069_2017-12-20_final
2017-12-20 09:51:59	ga_ls8c_ard_3-0-0_096070_2017-12-20_final
2017-12-20 09:52:23	ga_ls8c_ard_3-0-0_096071_2017-12-20_final
2017-12-20 09:52:47	ga_ls8c_ard_3-0-0_096072_2017-12-20_final
2018-01-05 09:50:43	ga_ls8c_ard_3-0-0_096067_2018-01-05_final
2018-01-05 09:51:07	ga_ls8c_ard_3-0-0_096068_2018-01-05_final
2018-01-05 09:51:31	ga_ls8c_ard_3-0-0_096069_2018-01-05_final
2018-01-05 09:51:55	ga_ls8c_ard_3-0-0_096070_2018-01-05_final
2018-01-05 09:52:19	ga_ls8c_ard_3-0-0_096071_2018-01-05_final
2018-01-05 09:52:43	ga_ls8c_ard_3-0-0_096072_2018-01-05_final
2019-07-10 09:56:42	ga_ls8c_ard_3-1-0_097067_2019-07-10_final
2019-09-27 09:23:01	ga_ls8c_ard_3-1-0_090090_2019-09-26_final
2019-09-27 09:23:25	ga_ls8c_ard_3-1-0_090091_2019-09-26_final
2019-09-28 09:57:07	ga_ls8c_ard_3-1-0_097067_2019-09-28_final
2019-10-09 09:42:12	ga_ls8c_ard_3-1-0_094076_2019-10-09_final
2019-10-09 09:42:36	ga_ls8c_ard_3-1-0_094077_2019-10-09_final
2019-10-09 09:43:00	ga_ls8c_ard_3-1-0_094078_2019-10-09_final
2019-10-09 09:43:24	ga_ls8c_ard_3-1-0_094079_2019-10-09_final
2019-10-09 09:43:48	ga_ls8c_ard_3-1-0_094080_2019-10-09_final
2019-10-09 09:44:12	ga_ls8c_ard_3-1-0_094081_2019-10-09_final
2019-10-11 09:33:02	ga_ls8c_ard_3-1-0_092084_2019-10-11_final
2019-10-11 09:33:26	ga_ls8c_ard_3-1-0_092085_2019-10-11_final
2019-10-11 09:33:50	ga_ls8c_ard_3-1-0_092086_2019-10-11_final
2019-10-11 09:34:14	ga_ls8c_ard_3-1-0_092087_2019-10-11_final
2019-10-11 09:34:38	ga_ls8c_ard_3-1-0_092088_2019-10-11_final
2019-10-11 09:35:02	ga_ls8c_ard_3-1-0_092089_2019-10-11_final
2019-10-18 09:37:38	ga_ls8c_ard_3-1-0_093080_2019-10-18_final
2019-10-18 09:38:02	ga_ls8c_ard_3-1-0_093081_2019-10-18_final
2019-10-18 09:38:26	ga_ls8c_ard_3-1-0_093082_2019-10-18_final
2019-10-18 09:38:50	ga_ls8c_ard_3-1-0_093083_2019-10-18_final
2019-10-18 09:39:14	ga_ls8c_ard_3-1-0_093084_2019-10-18_final
2019-10-18 09:39:37	ga_ls8c_ard_3-1-0_093085_2019-10-18_final
2019-10-20 09:28:04	ga_ls8c_ard_3-1-0_091087_2019-10-19_final
2019-10-20 09:28:28	ga_ls8c_ard_3-1-0_091088_2019-10-19_final
2019-10-20 09:28:52	ga_ls8c_ard_3-1-0_091089_2019-10-19_final
2019-10-20 09:29:16	ga_ls8c_ard_3-1-0_091090_2019-10-19_final
2019-10-20 09:29:40	ga_ls8c_ard_3-1-0_091091_2019-10-19_final
2019-10-23 09:50:59	ga_ls8c_ard_3-1-0_096067_2019-10-23_final
2019-10-23 09:51:23	ga_ls8c_ard_3-1-0_096068_2019-10-23_final
2019-10-23 09:51:47	ga_ls8c_ard_3-1-0_096069_2019-10-23_final
2019-10-23 09:52:11	ga_ls8c_ard_3-1-0_096070_2019-10-23_final
2019-10-23 09:52:35	ga_ls8c_ard_3-1-0_096071_2019-10-23_final
2019-10-23 09:52:59	ga_ls8c_ard_3-1-0_096072_2019-10-23_final
2019-11-14 09:23:02	ga_ls8c_ard_3-1-0_090090_2019-11-13_final
2019-11-14 09:23:26	ga_ls8c_ard_3-1-0_090091_2019-11-13_final
2019-11-15 09:57:07	ga_ls8c_ard_3-1-0_097067_2019-11-15_final
2019-12-05 09:37:33	ga_ls8c_ard_3-1-0_093080_2019-12-05_final
2019-12-05 09:37:57	ga_ls8c_ard_3-1-0_093081_2019-12-05_final
2019-12-05 09:38:21	ga_ls8c_ard_3-1-0_093082_2019-12-05_final
2019-12-05 09:38:45	ga_ls8c_ard_3-1-0_093083_2019-12-05_final
2019-12-05 09:39:09	ga_ls8c_ard_3-1-0_093084_2019-12-05_final
2019-12-05 09:39:33	ga_ls8c_ard_3-1-0_093085_2019-12-05_final
2020-06-14 09:36:52	ga_ls8c_ard_3-1-0_093080_2020-06-14_final
2020-06-14 09:37:16	ga_ls8c_ard_3-1-0_093081_2020-06-14_final
2020-06-14 09:37:40	ga_ls8c_ard_3-1-0_093082_2020-06-14_final
2020-06-14 09:38:04	ga_ls8c_ard_3-1-0_093083_2020-06-14_final
2020-06-14 09:38:28	ga_ls8c_ard_3-1-0_093084_2020-06-14_final
2020-06-14 09:38:52	ga_ls8c_ard_3-1-0_093085_2020-06-14_final
2020-06-16 09:27:19	ga_ls8c_ard_3-1-0_091087_2020-06-15_final
2020-06-16 09:27:43	ga_ls8c_ard_3-1-0_091088_2020-06-15_final
2020-06-16 09:28:07	ga_ls8c_ard_3-1-0_091089_2020-06-15_final
2020-06-16 09:28:31	ga_ls8c_ard_3-1-0_091090_2020-06-15_final
2020-06-16 09:28:55	ga_ls8c_ard_3-1-0_091091_2020-06-15_final
2020-06-30 09:37:00	ga_ls8c_ard_3-1-0_093080_2020-06-30_final
2020-06-30 09:37:24	ga_ls8c_ard_3-1-0_093081_2020-06-30_final
2020-06-30 09:37:48	ga_ls8c_ard_3-1-0_093082_2020-06-30_final
2020-06-30 09:38:12	ga_ls8c_ard_3-1-0_093083_2020-06-30_final
2020-06-30 09:38:36	ga_ls8c_ard_3-1-0_093084_2020-06-30_final
2020-06-30 09:39:00	ga_ls8c_ard_3-1-0_093085_2020-06-30_final
2020-07-02 09:27:27	ga_ls8c_ard_3-1-0_091087_2020-07-01_final
2020-07-02 09:27:51	ga_ls8c_ard_3-1-0_091088_2020-07-01_final
2020-07-02 09:28:15	ga_ls8c_ard_3-1-0_091089_2020-07-01_final
2020-07-02 09:28:39	ga_ls8c_ard_3-1-0_091090_2020-07-01_final
2020-07-02 09:29:03	ga_ls8c_ard_3-1-0_091091_2020-07-01_final
2020-07-16 09:37:07	ga_ls8c_ard_3-1-0_093080_2020-07-16_final
2020-07-16 09:37:31	ga_ls8c_ard_3-1-0_093081_2020-07-16_final
2020-07-16 09:37:55	ga_ls8c_ard_3-1-0_093082_2020-07-16_final
2020-07-16 09:38:18	ga_ls8c_ard_3-1-0_093083_2020-07-16_final
2020-07-16 09:38:42	ga_ls8c_ard_3-1-0_093084_2020-07-16_final
2020-07-16 09:39:06	ga_ls8c_ard_3-1-0_093085_2020-07-16_final
2020-07-18 09:27:33	ga_ls8c_ard_3-1-0_091087_2020-07-17_final
2020-07-18 09:27:57	ga_ls8c_ard_3-1-0_091088_2020-07-17_final
2020-07-18 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-07-17_final
2020-07-18 09:28:45	ga_ls8c_ard_3-1-0_091090_2020-07-17_final
2020-07-18 09:29:09	ga_ls8c_ard_3-1-0_091091_2020-07-17_final
2020-08-15 09:46:01	ga_ls8c_ard_3-1-0_095071_2020-08-15_final
2020-08-15 09:46:25	ga_ls8c_ard_3-1-0_095072_2020-08-15_final
2020-08-15 09:46:49	ga_ls8c_ard_3-1-0_095073_2020-08-15_final
2020-08-15 09:47:13	ga_ls8c_ard_3-1-0_095074_2020-08-15_final
2020-08-15 09:47:36	ga_ls8c_ard_3-1-0_095075_2020-08-15_final
2020-08-15 09:48:00	ga_ls8c_ard_3-1-0_095076_2020-08-15_final
2020-08-15 09:48:24	ga_ls8c_ard_3-1-0_095077_2020-08-15_final
2020-09-04 09:27:51	ga_ls8c_ard_3-1-0_091087_2020-09-03_final
2020-09-04 09:28:15	ga_ls8c_ard_3-1-0_091088_2020-09-03_final
2020-09-04 09:28:39	ga_ls8c_ard_3-1-0_091089_2020-09-03_final
2020-09-04 09:29:03	ga_ls8c_ard_3-1-0_091090_2020-09-03_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