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
2017-03-27 09:25:29	ga_ls8c_ard_3-0-0_092067_2017-03-26_final
2017-03-27 09:25:52	ga_ls8c_ard_3-0-0_092068_2017-03-26_final
2017-03-27 09:27:04	ga_ls8c_ard_3-0-0_092071_2017-03-26_final
2017-03-29 09:16:18	ga_ls8c_ard_3-0-0_090075_2017-03-28_final
2017-03-29 09:16:42	ga_ls8c_ard_3-0-0_090076_2017-03-28_final
2017-03-29 09:17:06	ga_ls8c_ard_3-0-0_090077_2017-03-28_final
2017-03-29 09:17:30	ga_ls8c_ard_3-0-0_090078_2017-03-28_final
2017-03-29 09:17:53	ga_ls8c_ard_3-0-0_090079_2017-03-28_final
2017-03-29 09:18:17	ga_ls8c_ard_3-0-0_090080_2017-03-28_final
2017-04-07 09:11:39	ga_ls8c_ard_3-0-0_089079_2017-04-06_final
2017-04-07 09:12:03	ga_ls8c_ard_3-0-0_089080_2017-04-06_final
2017-04-12 09:26:57	ga_ls8c_ard_3-0-0_092071_2017-04-11_final
2017-04-14 09:16:10	ga_ls8c_ard_3-0-0_090075_2017-04-13_final
2017-04-14 09:16:34	ga_ls8c_ard_3-0-0_090076_2017-04-13_final
2017-04-14 09:16:58	ga_ls8c_ard_3-0-0_090077_2017-04-13_final
2017-04-14 09:17:22	ga_ls8c_ard_3-0-0_090078_2017-04-13_final
2017-04-14 09:17:46	ga_ls8c_ard_3-0-0_090079_2017-04-13_final
2017-04-14 09:18:10	ga_ls8c_ard_3-0-0_090080_2017-04-13_final
2017-04-23 09:11:29	ga_ls8c_ard_3-0-0_089079_2017-04-22_final
2017-04-23 09:11:53	ga_ls8c_ard_3-0-0_089080_2017-04-22_final
2017-04-23 09:12:17	ga_ls8c_ard_3-0-0_089081_2017-04-22_final
2017-04-23 09:12:41	ga_ls8c_ard_3-0-0_089082_2017-04-22_final
2017-04-23 09:13:05	ga_ls8c_ard_3-0-0_089083_2017-04-22_final
2017-04-23 09:13:29	ga_ls8c_ard_3-0-0_089084_2017-04-22_final
2017-04-28 09:26:46	ga_ls8c_ard_3-0-0_092071_2017-04-27_final
2017-04-30 09:15:59	ga_ls8c_ard_3-0-0_090075_2017-04-29_final
2017-04-30 09:16:23	ga_ls8c_ard_3-0-0_090076_2017-04-29_final
2017-04-30 09:16:47	ga_ls8c_ard_3-1-0_090077_2017-04-29_final
2017-04-30 09:17:11	ga_ls8c_ard_3-1-0_090078_2017-04-29_final
2017-04-30 09:17:35	ga_ls8c_ard_3-0-0_090079_2017-04-29_final
2017-04-30 09:17:59	ga_ls8c_ard_3-0-0_090080_2017-04-29_final
2017-05-18 09:07:00	ga_ls8c_ard_3-0-0_088083_2017-05-17_final
2017-05-18 09:07:24	ga_ls8c_ard_3-0-0_088084_2017-05-17_final
2017-06-10 09:11:47	ga_ls8c_ard_3-0-0_089079_2017-06-09_final
2017-06-10 09:12:11	ga_ls8c_ard_3-0-0_089080_2017-06-09_final
2017-06-10 09:12:35	ga_ls8c_ard_3-0-0_089081_2017-06-09_final
2017-06-10 09:12:59	ga_ls8c_ard_3-0-0_089082_2017-06-09_final
2017-06-10 09:13:23	ga_ls8c_ard_3-0-0_089083_2017-06-09_final
2017-06-10 09:13:47	ga_ls8c_ard_3-0-0_089084_2017-06-09_final
2017-06-26 09:11:52	ga_ls8c_ard_3-0-0_089079_2017-06-25_final
2017-06-26 09:12:16	ga_ls8c_ard_3-0-0_089080_2017-06-25_final
2017-06-26 09:12:40	ga_ls8c_ard_3-0-0_089081_2017-06-25_final
2017-06-26 09:13:04	ga_ls8c_ard_3-0-0_089082_2017-06-25_final
2017-06-26 09:13:28	ga_ls8c_ard_3-0-0_089083_2017-06-25_final
2017-06-26 09:13:52	ga_ls8c_ard_3-0-0_089084_2017-06-25_final
2017-07-01 09:25:39	ga_ls8c_ard_3-0-0_092067_2017-06-30_final
2017-07-01 09:26:03	ga_ls8c_ard_3-0-0_092068_2017-06-30_final
2018-05-26 09:20:33	ga_ls8c_ard_3-0-0_091072_2018-05-25_final
2018-05-26 09:20:57	ga_ls8c_ard_3-0-0_091073_2018-05-25_final
2018-05-26 09:21:21	ga_ls8c_ard_3-0-0_091074_2018-05-25_final
2018-05-26 09:21:45	ga_ls8c_ard_3-0-0_091075_2018-05-25_final
2018-05-26 09:22:09	ga_ls8c_ard_3-0-0_091076_2018-05-25_final
2018-06-11 09:20:31	ga_ls8c_ard_3-0-0_091072_2018-06-10_final
2018-06-11 09:20:55	ga_ls8c_ard_3-0-0_091073_2018-06-10_final
2018-06-11 09:21:19	ga_ls8c_ard_3-0-0_091074_2018-06-10_final
2018-06-11 09:21:43	ga_ls8c_ard_3-0-0_091075_2018-06-10_final
2018-06-18 09:24:47	ga_ls8c_ard_3-0-0_092067_2018-06-17_final
2018-06-18 09:25:11	ga_ls8c_ard_3-0-0_092068_2018-06-17_final
2018-06-27 09:20:42	ga_ls8c_ard_3-0-0_091072_2018-06-26_final
2018-06-27 09:21:06	ga_ls8c_ard_3-0-0_091073_2018-06-26_final
2018-06-27 09:21:30	ga_ls8c_ard_3-0-0_091074_2018-06-26_final
2018-06-27 09:21:54	ga_ls8c_ard_3-0-0_091075_2018-06-26_final
2018-07-04 09:24:57	ga_ls8c_ard_3-0-0_092067_2018-07-03_final
2018-07-04 09:25:21	ga_ls8c_ard_3-0-0_092068_2018-07-03_final
2018-07-13 09:20:50	ga_ls8c_ard_3-0-0_091072_2018-07-12_final
2018-07-13 09:21:14	ga_ls8c_ard_3-0-0_091073_2018-07-12_final
2018-07-13 09:21:38	ga_ls8c_ard_3-0-0_091074_2018-07-12_final
2018-07-13 09:22:02	ga_ls8c_ard_3-0-0_091075_2018-07-12_final
2018-07-29 09:20:57	ga_ls8c_ard_3-0-0_091072_2018-07-28_final
2018-07-29 09:21:21	ga_ls8c_ard_3-0-0_091073_2018-07-28_final
2018-07-29 09:21:45	ga_ls8c_ard_3-0-0_091074_2018-07-28_final
2018-07-29 09:22:09	ga_ls8c_ard_3-0-0_091075_2018-07-28_final
2018-07-29 09:22:33	ga_ls8c_ard_3-0-0_091076_2018-07-28_final
2018-08-21 09:25:21	ga_ls8c_ard_3-0-0_092067_2018-08-20_final
2018-08-21 09:25:45	ga_ls8c_ard_3-0-0_092068_2018-08-20_final
2018-08-30 09:21:13	ga_ls8c_ard_3-0-0_091072_2018-08-29_final
2018-08-30 09:21:37	ga_ls8c_ard_3-0-0_091073_2018-08-29_final
2018-08-30 09:22:01	ga_ls8c_ard_3-0-0_091074_2018-08-29_final
2018-08-30 09:22:25	ga_ls8c_ard_3-0-0_091075_2018-08-29_final
2018-09-06 09:27:03	ga_ls8c_ard_3-0-0_092071_2018-09-05_final
2018-09-08 09:16:17	ga_ls8c_ard_3-0-0_090075_2018-09-07_final
2018-09-08 09:16:41	ga_ls8c_ard_3-0-0_090076_2018-09-07_final
2018-09-08 09:17:05	ga_ls8c_ard_3-0-0_090077_2018-09-07_final
2018-09-08 09:17:29	ga_ls8c_ard_3-0-0_090078_2018-09-07_final
2018-09-08 09:17:53	ga_ls8c_ard_3-0-0_090079_2018-09-07_final
2018-09-08 09:18:17	ga_ls8c_ard_3-0-0_090080_2018-09-07_final
2018-09-10 09:07:08	ga_ls8c_ard_3-0-0_088083_2018-09-09_final
2018-09-10 09:07:32	ga_ls8c_ard_3-0-0_088084_2018-09-09_final
2019-04-11 09:21:10	ga_ls8c_ard_3-1-0_091072_2019-04-10_final
2019-04-11 09:21:34	ga_ls8c_ard_3-1-0_091073_2019-04-10_final
2019-04-11 09:21:58	ga_ls8c_ard_3-1-0_091074_2019-04-10_final
2019-04-11 09:22:22	ga_ls8c_ard_3-1-0_091075_2019-04-10_final
2019-04-11 09:22:46	ga_ls8c_ard_3-1-0_091076_2019-04-10_final
2019-04-22 09:06:57	ga_ls8c_ard_3-0-0_088083_2019-04-21_final
2019-04-22 09:07:21	ga_ls8c_ard_3-0-0_088084_2019-04-21_final
2019-05-04 09:25:19	ga_ls8c_ard_3-0-0_092067_2019-05-03_final
2019-05-04 09:25:43	ga_ls8c_ard_3-0-0_092068_2019-05-03_final
2019-05-04 09:26:54	ga_ls8c_ard_3-0-0_092071_2019-05-03_final
2019-10-11 09:26:15	ga_ls8c_ard_3-1-0_092067_2019-10-10_final
2019-10-11 09:26:39	ga_ls8c_ard_3-1-0_092068_2019-10-10_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