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
2014-10-02 09:46:34	ga_ls8c_ard_3-0-0_095072_2014-10-02_final
2014-10-02 09:46:58	ga_ls8c_ard_3-0-0_095073_2014-10-02_final
2014-10-02 09:47:22	ga_ls8c_ard_3-0-0_095074_2014-10-02_final
2014-10-02 09:47:46	ga_ls8c_ard_3-0-0_095075_2014-10-02_final
2017-04-01 09:45:11	ga_ls8c_ard_3-0-0_095070_2017-04-01_final
2017-04-01 09:45:35	ga_ls8c_ard_3-0-0_095071_2017-04-01_final
2017-04-01 09:45:59	ga_ls8c_ard_3-0-0_095072_2017-04-01_final
2017-04-01 09:46:23	ga_ls8c_ard_3-0-0_095073_2017-04-01_final
2017-04-01 09:46:47	ga_ls8c_ard_3-0-0_095074_2017-04-01_final
2017-04-01 09:47:11	ga_ls8c_ard_3-0-0_095075_2017-04-01_final
2017-05-19 09:45:05	ga_ls8c_ard_3-0-0_095070_2017-05-19_final
2017-05-19 09:45:29	ga_ls8c_ard_3-0-0_095071_2017-05-19_final
2017-05-19 09:45:53	ga_ls8c_ard_3-0-0_095072_2017-05-19_final
2017-05-19 09:46:17	ga_ls8c_ard_3-0-0_095073_2017-05-19_final
2017-05-19 09:46:41	ga_ls8c_ard_3-0-0_095074_2017-05-19_final
2017-05-19 09:47:05	ga_ls8c_ard_3-0-0_095075_2017-05-19_final
2017-05-21 09:36:20	ga_ls8c_ard_3-0-0_093079_2017-05-21_final
2017-05-21 09:36:44	ga_ls8c_ard_3-0-0_093080_2017-05-21_final
2017-05-21 09:37:08	ga_ls8c_ard_3-0-0_093081_2017-05-21_final
2017-05-21 09:37:32	ga_ls8c_ard_3-0-0_093082_2017-05-21_final
2017-05-21 09:37:56	ga_ls8c_ard_3-0-0_093083_2017-05-21_final
2017-05-21 09:38:20	ga_ls8c_ard_3-0-0_093084_2017-05-21_final
2017-06-29 09:40:47	ga_ls8c_ard_3-0-0_094074_2017-06-29_final
2017-06-29 09:41:11	ga_ls8c_ard_3-0-0_094075_2017-06-29_final
2017-06-29 09:41:35	ga_ls8c_ard_3-0-0_094076_2017-06-29_final
2017-06-29 09:41:59	ga_ls8c_ard_3-0-0_094077_2017-06-29_final
2017-06-29 09:42:23	ga_ls8c_ard_3-0-0_094078_2017-06-29_final
2017-06-29 09:42:47	ga_ls8c_ard_3-0-0_094079_2017-06-29_final
2017-06-29 09:43:11	ga_ls8c_ard_3-0-0_094080_2017-06-29_final
2017-07-01 09:32:02	ga_ls8c_ard_3-0-0_092083_2017-07-01_final
2017-07-01 09:32:26	ga_ls8c_ard_3-0-0_092084_2017-07-01_final
2017-07-01 09:32:50	ga_ls8c_ard_3-0-0_092085_2017-07-01_final
2017-07-01 09:33:14	ga_ls8c_ard_3-0-0_092086_2017-07-01_final
2017-07-01 09:33:38	ga_ls8c_ard_3-0-0_092087_2017-07-01_final
2017-07-01 09:34:02	ga_ls8c_ard_3-0-0_092088_2017-07-01_final
2017-07-03 09:22:28	ga_ls8c_ard_3-0-0_090090_2017-07-02_final
2017-07-03 09:22:52	ga_ls8c_ard_3-0-0_090091_2017-07-02_final
2017-07-08 09:36:38	ga_ls8c_ard_3-0-0_093079_2017-07-08_final
2017-07-08 09:37:02	ga_ls8c_ard_3-0-0_093080_2017-07-08_final
2017-07-08 09:37:26	ga_ls8c_ard_3-0-0_093081_2017-07-08_final
2017-07-08 09:37:50	ga_ls8c_ard_3-0-0_093082_2017-07-08_final
2017-07-08 09:38:14	ga_ls8c_ard_3-0-0_093083_2017-07-08_final
2017-07-08 09:38:38	ga_ls8c_ard_3-0-0_093084_2017-07-08_final
2017-07-15 09:40:50	ga_ls8c_ard_3-0-0_094074_2017-07-15_final
2017-07-15 09:41:14	ga_ls8c_ard_3-0-0_094075_2017-07-15_final
2017-07-15 09:41:38	ga_ls8c_ard_3-0-0_094076_2017-07-15_final
2017-07-15 09:42:02	ga_ls8c_ard_3-0-0_094077_2017-07-15_final
2017-07-15 09:42:26	ga_ls8c_ard_3-0-0_094078_2017-07-15_final
2017-07-15 09:42:50	ga_ls8c_ard_3-0-0_094079_2017-07-15_final
2017-07-15 09:43:14	ga_ls8c_ard_3-0-0_094080_2017-07-15_final
2022-10-17 09:41:33	ga_ls8c_ard_3-2-1_094074_2022-10-17_final
2022-10-17 09:41:57	ga_ls8c_ard_3-2-1_094075_2022-10-17_final
2022-10-17 09:42:21	ga_ls8c_ard_3-2-1_094076_2022-10-17_final
2022-10-17 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-10-17_final
2022-10-17 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-10-17_final
2022-10-17 09:43:33	ga_ls8c_ard_3-2-1_094079_2022-10-17_final
2022-10-17 09:43:57	ga_ls8c_ard_3-2-1_094080_2022-10-17_final
2022-10-19 09:32:49	ga_ls8c_ard_3-2-1_092083_2022-10-19_final
2022-10-19 09:33:13	ga_ls8c_ard_3-2-1_092084_2022-10-19_final
2022-10-19 09:33:37	ga_ls8c_ard_3-2-1_092085_2022-10-19_final
2022-10-19 09:34:01	ga_ls8c_ard_3-2-1_092086_2022-10-19_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-10-24 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-10-24_final
2022-10-24 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-10-24_final
2022-10-24 09:47:48	ga_ls8c_ard_3-2-1_095074_2022-10-24_final
2022-10-24 09:48:12	ga_ls8c_ard_3-2-1_095075_2022-10-24_final
2022-10-26 09:37:27	ga_ls8c_ard_3-2-1_093079_2022-10-26_final
2022-10-26 09:37:51	ga_ls8c_ard_3-2-1_093080_2022-10-26_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-10-26 09:38:39	ga_ls8c_ard_3-2-1_093082_2022-10-26_final
2022-10-26 09:39:03	ga_ls8c_ard_3-2-1_093083_2022-10-26_final
2022-10-26 09:39:27	ga_ls8c_ard_3-2-1_093084_2022-10-26_final
2022-10-28 09:27:54	ga_ls8c_ard_3-2-1_091086_2022-10-27_final
2022-10-28 09:28:18	ga_ls8c_ard_3-2-1_091087_2022-10-27_final
2022-10-28 09:28:42	ga_ls8c_ard_3-2-1_091088_2022-10-27_final
2022-10-28 09:29:06	ga_ls8c_ard_3-2-1_091089_2022-10-27_final
2022-10-28 09:29:30	ga_ls8c_ard_3-2-1_091090_2022-10-27_final
2022-11-02 09:41:40	ga_ls8c_ard_3-2-1_094074_2022-11-02_final
2022-11-02 09:42:04	ga_ls8c_ard_3-2-1_094075_2022-11-02_final
2022-11-02 09:42:28	ga_ls8c_ard_3-2-1_094076_2022-11-02_final
2022-11-02 09:42:52	ga_ls8c_ard_3-2-1_094077_2022-11-02_final
2022-11-02 09:43:16	ga_ls8c_ard_3-2-1_094078_2022-11-02_final
2022-11-02 09:43:40	ga_ls8c_ard_3-2-1_094079_2022-11-02_final
2022-11-02 09:44:04	ga_ls8c_ard_3-2-1_094080_2022-11-02_final
2022-11-04 09:32:54	ga_ls8c_ard_3-2-1_092083_2022-11-04_final
2022-11-04 09:33:18	ga_ls8c_ard_3-2-1_092084_2022-11-04_final
2022-11-04 09:33:42	ga_ls8c_ard_3-2-1_092085_2022-11-04_final
2022-11-04 09:34:06	ga_ls8c_ard_3-2-1_092086_2022-11-04_final
2022-11-04 09:34:30	ga_ls8c_ard_3-2-1_092087_2022-11-04_final
2022-11-04 09:34:54	ga_ls8c_ard_3-2-1_092088_2022-11-04_final
2022-11-11 09:37:26	ga_ls8c_ard_3-2-1_093079_2022-11-11_final
2022-11-11 09:37:50	ga_ls8c_ard_3-2-1_093080_2022-11-11_final
2022-11-11 09:38:14	ga_ls8c_ard_3-2-1_093081_2022-11-11_final
2022-11-11 09:38:38	ga_ls8c_ard_3-2-1_093082_2022-11-11_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-11 09:39:26	ga_ls8c_ard_3-2-1_093084_2022-11-11_final
2023-10-13 09:38:12	ga_ls8c_ard_3-2-1_093082_2023-10-13_final
2023-10-13 09:38:36	ga_ls8c_ard_3-2-1_093083_2023-10-13_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