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
2015-08-23 11:44:24	ga_ls8c_ard_3-0-0_114074_2015-08-23_final
2015-08-25 11:33:39	ga_ls8c_ard_3-0-0_112078_2015-08-25_final
2015-08-25 11:34:02	ga_ls8c_ard_3-0-0_112079_2015-08-25_final
2015-08-25 11:34:26	ga_ls8c_ard_3-0-0_112080_2015-08-25_final
2015-08-25 11:34:50	ga_ls8c_ard_3-0-0_112081_2015-08-25_final
2015-08-25 11:35:14	ga_ls8c_ard_3-0-0_112082_2015-08-25_final
2015-08-25 11:35:38	ga_ls8c_ard_3-0-0_112083_2015-08-25_final
2015-09-08 11:44:29	ga_ls8c_ard_3-0-0_114074_2015-09-08_final
2015-09-24 11:44:37	ga_ls8c_ard_3-0-0_114074_2015-09-24_final
2015-10-10 11:44:38	ga_ls8c_ard_3-0-0_114074_2015-10-10_final
2015-11-11 11:44:44	ga_ls8c_ard_3-0-0_114074_2015-11-11_final
2015-12-13 11:44:45	ga_ls8c_ard_3-0-0_114074_2015-12-13_final
2015-12-15 11:33:59	ga_ls8c_ard_3-0-0_112078_2015-12-15_final
2015-12-15 11:34:23	ga_ls8c_ard_3-0-0_112079_2015-12-15_final
2015-12-15 11:34:47	ga_ls8c_ard_3-0-0_112080_2015-12-15_final
2015-12-15 11:35:11	ga_ls8c_ard_3-0-0_112081_2015-12-15_final
2015-12-15 11:35:35	ga_ls8c_ard_3-0-0_112082_2015-12-15_final
2015-12-15 11:35:59	ga_ls8c_ard_3-0-0_112083_2015-12-15_final
2019-06-10 11:29:04	ga_ls8c_ard_3-0-0_111082_2019-06-10_final
2019-06-10 11:29:28	ga_ls8c_ard_3-0-0_111083_2019-06-10_final
2019-06-10 11:29:52	ga_ls8c_ard_3-0-0_111084_2019-06-10_final
2019-06-10 11:30:16	ga_ls8c_ard_3-0-0_111085_2019-06-10_final
2019-07-19 11:33:49	ga_ls8c_ard_3-1-0_112078_2019-07-19_final
2019-07-19 11:34:13	ga_ls8c_ard_3-1-0_112079_2019-07-19_final
2019-07-19 11:34:37	ga_ls8c_ard_3-1-0_112080_2019-07-19_final
2019-07-19 11:35:01	ga_ls8c_ard_3-1-0_112081_2019-07-19_final
2019-07-19 11:35:25	ga_ls8c_ard_3-1-0_112082_2019-07-19_final
2019-07-19 11:35:49	ga_ls8c_ard_3-1-0_112083_2019-07-19_final
2019-08-29 11:29:28	ga_ls8c_ard_3-1-0_111082_2019-08-29_final
2019-08-29 11:29:52	ga_ls8c_ard_3-1-0_111083_2019-08-29_final
2019-08-29 11:30:16	ga_ls8c_ard_3-1-0_111084_2019-08-29_final
2019-08-29 11:30:40	ga_ls8c_ard_3-1-0_111085_2019-08-29_final
2019-09-05 11:34:04	ga_ls8c_ard_3-1-0_112078_2019-09-05_final
2019-09-05 11:34:28	ga_ls8c_ard_3-1-0_112079_2019-09-05_final
2019-09-05 11:34:52	ga_ls8c_ard_3-1-0_112080_2019-09-05_final
2019-09-05 11:35:16	ga_ls8c_ard_3-1-0_112081_2019-09-05_final
2019-09-05 11:35:40	ga_ls8c_ard_3-1-0_112082_2019-09-05_final
2019-09-05 11:36:04	ga_ls8c_ard_3-1-0_112083_2019-09-05_final
2019-09-14 11:29:33	ga_ls8c_ard_3-1-0_111082_2019-09-14_final
2019-09-14 11:29:57	ga_ls8c_ard_3-1-0_111083_2019-09-14_final
2019-09-14 11:30:21	ga_ls8c_ard_3-1-0_111084_2019-09-14_final
2019-09-14 11:30:45	ga_ls8c_ard_3-1-0_111085_2019-09-14_final
2019-10-16 11:29:40	ga_ls8c_ard_3-1-0_111082_2019-10-16_final
2019-10-16 11:30:04	ga_ls8c_ard_3-1-0_111083_2019-10-16_final
2019-10-16 11:30:28	ga_ls8c_ard_3-1-0_111084_2019-10-16_final
2019-10-16 11:30:52	ga_ls8c_ard_3-1-0_111085_2019-10-16_final
2019-10-23 11:34:15	ga_ls8c_ard_3-1-0_112078_2019-10-23_final
2019-10-23 11:34:39	ga_ls8c_ard_3-1-0_112079_2019-10-23_final
2019-10-23 11:35:03	ga_ls8c_ard_3-1-0_112080_2019-10-23_final
2019-10-23 11:35:27	ga_ls8c_ard_3-1-0_112081_2019-10-23_final
2019-10-23 11:35:51	ga_ls8c_ard_3-1-0_112082_2019-10-23_final
2019-10-23 11:36:15	ga_ls8c_ard_3-1-0_112083_2019-10-23_final
2023-04-16 11:37:59	ga_ls8c_ard_3-2-1_113074_2023-04-16_final
2023-04-16 11:38:23	ga_ls8c_ard_3-2-1_113075_2023-04-16_final
2023-04-16 11:38:47	ga_ls8c_ard_3-2-1_113076_2023-04-16_final
2023-04-16 11:39:11	ga_ls8c_ard_3-2-1_113077_2023-04-16_final
2023-04-16 11:39:35	ga_ls8c_ard_3-2-1_113078_2023-04-16_final
2023-04-16 11:39:59	ga_ls8c_ard_3-2-1_113079_2023-04-16_final
2023-04-18 11:28:48	ga_ls8c_ard_3-2-1_111082_2023-04-18_final
2023-04-18 11:29:12	ga_ls8c_ard_3-2-1_111083_2023-04-18_final
2023-04-18 11:29:36	ga_ls8c_ard_3-2-1_111084_2023-04-18_final
2023-05-02 11:37:31	ga_ls8c_ard_3-2-1_113073_2023-05-02_final
2023-05-02 11:37:55	ga_ls8c_ard_3-2-1_113074_2023-05-02_final
2023-05-02 11:38:19	ga_ls8c_ard_3-2-1_113075_2023-05-02_final
2023-05-02 11:38:42	ga_ls8c_ard_3-2-1_113076_2023-05-02_final
2023-05-02 11:39:06	ga_ls8c_ard_3-2-1_113077_2023-05-02_final
2023-05-02 11:39:30	ga_ls8c_ard_3-2-1_113078_2023-05-02_final
2023-05-02 11:39:54	ga_ls8c_ard_3-2-1_113079_2023-05-02_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-18 11:37:18	ga_ls8c_ard_3-2-1_113073_2023-05-18_final
2023-05-18 11:37:42	ga_ls8c_ard_3-2-1_113074_2023-05-18_final
2023-05-18 11:38:06	ga_ls8c_ard_3-2-1_113075_2023-05-18_final
2023-05-18 11:38:30	ga_ls8c_ard_3-2-1_113076_2023-05-18_final
2023-05-18 11:38:54	ga_ls8c_ard_3-2-1_113077_2023-05-18_final
2023-05-18 11:39:18	ga_ls8c_ard_3-2-1_113078_2023-05-18_final
2023-05-18 11:39:42	ga_ls8c_ard_3-2-1_113079_2023-05-18_final
2023-05-20 11:28:33	ga_ls8c_ard_3-2-1_111082_2023-05-20_final
2023-05-20 11:28:57	ga_ls8c_ard_3-2-1_111083_2023-05-20_final
2023-05-20 11:29:21	ga_ls8c_ard_3-2-1_111084_2023-05-20_final
2023-05-25 11:43:56	ga_ls8c_ard_3-2-1_114074_2023-05-25_final
2023-05-27 11:33:10	ga_ls8c_ard_3-2-1_112078_2023-05-27_final
2023-05-27 11:33:34	ga_ls8c_ard_3-2-1_112079_2023-05-27_final
2023-05-27 11:33:58	ga_ls8c_ard_3-2-1_112080_2023-05-27_final
2023-05-27 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-27_final
2023-05-27 11:34:46	ga_ls8c_ard_3-2-1_112082_2023-05-27_final
2023-05-27 11:35:10	ga_ls8c_ard_3-2-1_112083_2023-05-27_final
2023-06-30 11:23:53	ga_ls8c_ard_3-2-1_110085_2023-06-30_final
2023-07-05 11:37:42	ga_ls8c_ard_3-2-1_113073_2023-07-05_final
2023-07-05 11:38:06	ga_ls8c_ard_3-2-1_113074_2023-07-05_final
2023-07-05 11:38:30	ga_ls8c_ard_3-2-1_113075_2023-07-05_final
2023-07-05 11:38:54	ga_ls8c_ard_3-2-1_113076_2023-07-05_final
2023-07-05 11:39:18	ga_ls8c_ard_3-2-1_113077_2023-07-05_final
2023-07-05 11:39:42	ga_ls8c_ard_3-2-1_113078_2023-07-05_final
2023-07-05 11:40:06	ga_ls8c_ard_3-2-1_113079_2023-07-05_final
2023-08-06 11:37:54	ga_ls8c_ard_3-2-1_113073_2023-08-06_final
2023-08-06 11:38:18	ga_ls8c_ard_3-2-1_113074_2023-08-06_final
2023-08-06 11:38:42	ga_ls8c_ard_3-2-1_113075_2023-08-06_final
2023-08-06 11:39:06	ga_ls8c_ard_3-2-1_113076_2023-08-06_final
2023-08-06 11:39:30	ga_ls8c_ard_3-2-1_113077_2023-08-06_final
2023-08-06 11:39:54	ga_ls8c_ard_3-2-1_113078_2023-08-06_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