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
2018-05-22 09:43:20	ga_ls8c_ard_3-0-0_095067_2018-05-22_final
2018-05-22 09:44:32	ga_ls8c_ard_3-0-0_095070_2018-05-22_final
2018-05-22 09:44:56	ga_ls8c_ard_3-0-0_095071_2018-05-22_final
2018-05-24 09:34:08	ga_ls8c_ard_3-1-0_093075_2018-05-24_final
2018-05-24 09:34:32	ga_ls8c_ard_3-0-0_093076_2018-05-24_final
2018-05-24 09:34:56	ga_ls8c_ard_3-0-0_093077_2018-05-24_final
2018-05-24 09:35:20	ga_ls8c_ard_3-0-0_093078_2018-05-24_final
2018-05-24 09:35:44	ga_ls8c_ard_3-0-0_093079_2018-05-24_final
2018-05-24 09:36:08	ga_ls8c_ard_3-0-0_093080_2018-05-24_final
2018-05-24 09:36:32	ga_ls8c_ard_3-0-0_093081_2018-05-24_final
2018-06-07 09:43:12	ga_ls8c_ard_3-0-0_095067_2018-06-07_final
2018-06-07 09:44:24	ga_ls8c_ard_3-0-0_095070_2018-06-07_final
2018-06-07 09:44:48	ga_ls8c_ard_3-0-0_095071_2018-06-07_final
2018-06-09 09:34:03	ga_ls8c_ard_3-1-0_093075_2018-06-09_final
2018-06-09 09:34:27	ga_ls8c_ard_3-0-0_093076_2018-06-09_final
2018-06-09 09:34:51	ga_ls8c_ard_3-0-0_093077_2018-06-09_final
2018-06-09 09:35:15	ga_ls8c_ard_3-0-0_093078_2018-06-09_final
2018-06-09 09:35:39	ga_ls8c_ard_3-0-0_093079_2018-06-09_final
2018-06-09 09:36:03	ga_ls8c_ard_3-0-0_093080_2018-06-09_final
2018-06-09 09:36:27	ga_ls8c_ard_3-0-0_093081_2018-06-09_final
2018-06-23 09:43:23	ga_ls8c_ard_3-0-0_095067_2018-06-23_final
2018-06-23 09:44:35	ga_ls8c_ard_3-0-0_095070_2018-06-23_final
2018-06-23 09:44:59	ga_ls8c_ard_3-0-0_095071_2018-06-23_final
2018-06-25 09:34:14	ga_ls8c_ard_3-1-0_093075_2018-06-25_final
2018-06-25 09:34:38	ga_ls8c_ard_3-0-0_093076_2018-06-25_final
2018-06-25 09:35:02	ga_ls8c_ard_3-0-0_093077_2018-06-25_final
2018-06-25 09:35:26	ga_ls8c_ard_3-0-0_093078_2018-06-25_final
2018-06-25 09:35:50	ga_ls8c_ard_3-0-0_093079_2018-06-25_final
2018-06-25 09:36:14	ga_ls8c_ard_3-0-0_093080_2018-06-25_final
2018-06-25 09:36:38	ga_ls8c_ard_3-0-0_093081_2018-06-25_final
2018-06-30 09:49:38	ga_ls8c_ard_3-0-0_096067_2018-06-30_final
2018-07-02 09:38:53	ga_ls8c_ard_3-0-0_094071_2018-07-02_final
2018-07-02 09:39:17	ga_ls8c_ard_3-0-0_094072_2018-07-02_final
2018-07-02 09:39:41	ga_ls8c_ard_3-0-0_094073_2018-07-02_final
2018-07-02 09:40:05	ga_ls8c_ard_3-0-0_094074_2018-07-02_final
2018-07-02 09:40:29	ga_ls8c_ard_3-0-0_094075_2018-07-02_final
2018-07-02 09:40:53	ga_ls8c_ard_3-0-0_094076_2018-07-02_final
2018-08-14 09:25:30	ga_ls8c_ard_3-0-0_091083_2018-08-13_final
2018-08-14 09:25:54	ga_ls8c_ard_3-0-0_091084_2018-08-13_final
2018-08-14 09:26:17	ga_ls8c_ard_3-0-0_091085_2018-08-13_final
2018-08-14 09:26:41	ga_ls8c_ard_3-0-0_091086_2018-08-13_final
2018-08-14 09:27:05	ga_ls8c_ard_3-0-0_091087_2018-08-13_final
2018-08-14 09:27:29	ga_ls8c_ard_3-0-0_091088_2018-08-13_final
2018-08-14 09:27:53	ga_ls8c_ard_3-0-0_091089_2018-08-13_final
2018-09-22 09:30:19	ga_ls8c_ard_3-0-0_092079_2018-09-22_final
2018-09-22 09:30:43	ga_ls8c_ard_3-0-0_092080_2018-09-22_final
2018-09-22 09:31:06	ga_ls8c_ard_3-0-0_092081_2018-09-22_final
2018-09-22 09:31:30	ga_ls8c_ard_3-0-0_092082_2018-09-22_final
2018-09-22 09:31:54	ga_ls8c_ard_3-0-0_092083_2018-09-22_final
2018-09-22 09:32:18	ga_ls8c_ard_3-0-0_092084_2018-09-22_final
2018-09-22 09:32:42	ga_ls8c_ard_3-0-0_092085_2018-09-22_final
2018-09-24 09:21:10	ga_ls8c_ard_3-0-0_090087_2018-09-23_final
2018-09-24 09:21:34	ga_ls8c_ard_3-0-0_090088_2018-09-23_final
2018-09-24 09:21:58	ga_ls8c_ard_3-0-0_090089_2018-09-23_final
2018-09-24 09:22:22	ga_ls8c_ard_3-0-0_090090_2018-09-23_final
2018-09-24 09:22:46	ga_ls8c_ard_3-0-0_090091_2018-09-23_final
2018-11-30 09:44:20	ga_ls8c_ard_3-0-0_095067_2018-11-30_final
2018-11-30 09:45:31	ga_ls8c_ard_3-0-0_095070_2018-11-30_final
2018-11-30 09:45:55	ga_ls8c_ard_3-0-0_095071_2018-11-30_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
2018-12-02 09:37:09	ga_ls8c_ard_3-0-0_093080_2018-12-02_final
2018-12-02 09:37:33	ga_ls8c_ard_3-0-0_093081_2018-12-02_final
2022-04-03 09:26:12	ga_ls8c_ard_3-2-1_091084_2022-04-02_final
2022-04-03 09:26:36	ga_ls8c_ard_3-2-1_091085_2022-04-02_final
2022-04-03 09:27:00	ga_ls8c_ard_3-2-1_091086_2022-04-02_final
2022-04-03 09:27:24	ga_ls8c_ard_3-2-1_091087_2022-04-02_final
2022-04-10 09:30:28	ga_ls8c_ard_3-2-1_092079_2022-04-10_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-10 09:31:40	ga_ls8c_ard_3-2-1_092082_2022-04-10_final
2022-04-10 09:32:04	ga_ls8c_ard_3-2-1_092083_2022-04-10_final
2022-04-10 09:32:28	ga_ls8c_ard_3-2-1_092084_2022-04-10_final
2022-04-10 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-04-10_final
2022-04-12 09:21:19	ga_ls8c_ard_3-2-1_090087_2022-04-11_final
2022-04-12 09:21:43	ga_ls8c_ard_3-2-1_090088_2022-04-11_final
2022-04-12 09:22:07	ga_ls8c_ard_3-2-1_090089_2022-04-11_final
2022-04-12 09:22:31	ga_ls8c_ard_3-2-1_090090_2022-04-11_final
2022-04-12 09:22:55	ga_ls8c_ard_3-2-1_090091_2022-04-11_final
2022-05-12 09:30:34	ga_ls8c_ard_3-2-1_092079_2022-05-12_final
2022-05-12 09:30:58	ga_ls8c_ard_3-2-1_092080_2022-05-12_final
2022-05-12 09:31:22	ga_ls8c_ard_3-2-1_092081_2022-05-12_final
2022-05-12 09:31:46	ga_ls8c_ard_3-2-1_092082_2022-05-12_final
2022-05-12 09:32:10	ga_ls8c_ard_3-2-1_092083_2022-05-12_final
2022-05-12 09:32:34	ga_ls8c_ard_3-2-1_092084_2022-05-12_final
2022-05-12 09:32:57	ga_ls8c_ard_3-2-1_092085_2022-05-12_final
2022-05-14 09:21:25	ga_ls8c_ard_3-2-1_090087_2022-05-13_final
2022-05-14 09:21:49	ga_ls8c_ard_3-2-1_090088_2022-05-13_final
2022-05-14 09:22:13	ga_ls8c_ard_3-2-1_090089_2022-05-13_final
2022-05-14 09:22:37	ga_ls8c_ard_3-2-1_090090_2022-05-13_final
2022-05-14 09:23:00	ga_ls8c_ard_3-2-1_090091_2022-05-13_final
2022-05-17 09:45:56	ga_ls8c_ard_3-2-1_095071_2022-05-17_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-05-21 09:26:25	ga_ls8c_ard_3-2-1_091084_2022-05-20_final
2022-05-21 09:26:49	ga_ls8c_ard_3-2-1_091085_2022-05-20_final
2022-05-21 09:27:13	ga_ls8c_ard_3-2-1_091086_2022-05-20_final
2022-05-21 09:27:37	ga_ls8c_ard_3-2-1_091087_2022-05-20_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