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
2016-02-14 09:27:13	ga_ls8c_ard_3-1-0_091086_2016-02-13_final
2019-03-10 09:24:54	ga_ls8c_ard_3-1-0_091081_2019-03-09_final
2019-03-22 09:50:22	ga_ls8c_ard_3-1-0_095083_2019-03-22_final
2019-03-26 09:26:26	ga_ls8c_ard_3-1-0_091085_2019-03-25_final
2019-04-07 09:50:42	ga_ls8c_ard_3-1-0_095084_2019-04-07_final
2019-04-11 09:25:10	ga_ls8c_ard_3-1-0_091082_2019-04-10_final
2019-06-26 09:47:29	ga_ls8c_ard_3-1-0_095075_2019-06-26_final
2019-06-30 09:23:11	ga_ls8c_ard_3-1-0_091076_2019-06-29_final
2019-08-01 09:26:07	ga_ls8c_ard_3-1-0_091083_2019-07-31_final
2019-08-17 09:24:37	ga_ls8c_ard_3-1-0_091079_2019-08-16_final
2019-08-17 09:26:13	ga_ls8c_ard_3-1-0_091083_2019-08-16_final
2019-09-14 09:47:52	ga_ls8c_ard_3-1-0_095075_2019-09-14_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-18 09:27:10	ga_ls8c_ard_3-1-0_091085_2019-09-17_final
2019-10-04 09:26:02	ga_ls8c_ard_3-1-0_091082_2019-10-03_final
2019-10-04 09:26:26	ga_ls8c_ard_3-1-0_091083_2019-10-03_final
2019-11-01 09:48:23	ga_ls8c_ard_3-1-0_095076_2019-11-01_final
2019-11-01 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-11-01_final
2019-11-08 09:53:21	ga_ls8c_ard_3-1-0_096073_2019-11-08_final
2019-11-21 09:25:36	ga_ls8c_ard_3-1-0_091081_2019-11-20_final
2019-11-21 09:26:47	ga_ls8c_ard_3-1-0_091084_2019-11-20_final
2019-12-03 09:48:19	ga_ls8c_ard_3-1-0_095076_2019-12-03_final
2019-12-07 09:26:47	ga_ls8c_ard_3-1-0_091084_2019-12-06_final
2019-12-23 09:24:21	ga_ls8c_ard_3-1-0_091078_2019-12-22_final
2020-01-04 09:48:12	ga_ls8c_ard_3-1-0_095076_2020-01-04_final
2020-01-04 09:51:24	ga_ls8c_ard_3-1-0_095084_2020-01-04_final
2020-01-08 09:24:16	ga_ls8c_ard_3-1-0_091078_2020-01-07_final
2020-02-05 09:51:15	ga_ls8c_ard_3-1-0_095084_2020-02-05_final
2020-03-08 09:47:55	ga_ls8c_ard_3-1-0_095076_2020-03-08_final
2020-03-28 09:25:49	ga_ls8c_ard_3-1-0_091083_2020-03-27_final
2020-04-13 09:25:41	ga_ls8c_ard_3-1-0_091083_2020-04-12_final
2020-04-25 09:46:43	ga_ls8c_ard_3-1-0_095074_2020-04-25_final
2022-03-29 10:42:34	ga_ls8c_ard_3-2-1_104074_2022-03-29_final
2022-03-29 10:44:10	ga_ls8c_ard_3-2-1_104078_2022-03-29_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-03-30 11:27:01	ga_ls8c_ard_3-2-1_111077_2022-03-30_final
2022-04-01 09:36:10	ga_ls8c_ard_3-2-1_093078_2022-04-01_final
2022-04-01 11:15:03	ga_ls8c_ard_3-2-1_109078_2022-04-01_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-05 10:49:58	ga_ls8c_ard_3-2-1_105077_2022-04-05_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-06 11:34:02	ga_ls8c_ard_3-2-1_112079_2022-04-06_final
2022-04-07 10:35:14	ga_ls8c_ard_3-2-1_103071_2022-04-07_final
2022-04-10 09:32:28	ga_ls8c_ard_3-2-1_092084_2022-04-10_final
2022-04-10 11:06:33	ga_ls8c_ard_3-2-1_108072_2022-04-10_final
2022-04-11 10:12:08	ga_ls8c_ard_3-2-1_099075_2022-04-11_final
2022-04-13 10:00:11	ga_ls8c_ard_3-2-1_097076_2022-04-13_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-14 10:41:28	ga_ls8c_ard_3-2-1_104071_2022-04-14_final
2022-04-14 10:43:04	ga_ls8c_ard_3-2-1_104075_2022-04-14_final
2022-04-14 10:43:27	ga_ls8c_ard_3-2-1_104076_2022-04-14_final
2022-04-15 09:49:50	ga_ls8c_ard_3-2-1_095081_2022-04-15_final
2022-04-16 10:33:30	ga_ls8c_ard_3-2-1_102082_2022-04-16_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-18 10:20:20	ga_ls8c_ard_3-2-1_100080_2022-04-18_final
2022-04-19 11:00:48	ga_ls8c_ard_3-2-1_107073_2022-04-19_final
2022-04-22 09:55:59	ga_ls8c_ard_3-2-1_096081_2022-04-22_final
2022-04-23 10:34:51	ga_ls8c_ard_3-2-1_103070_2022-04-23_final
2022-04-24 09:44:25	ga_ls8c_ard_3-2-1_094083_2022-04-24_final
2022-04-24 09:45:12	ga_ls8c_ard_3-2-1_094085_2022-04-24_final
2022-04-24 11:20:30	ga_ls8c_ard_3-2-1_110076_2022-04-24_final
2022-04-26 11:10:07	ga_ls8c_ard_3-2-1_108081_2022-04-26_final
2022-04-29 10:00:31	ga_ls8c_ard_3-2-1_097077_2022-04-29_final
2022-04-30 10:40:36	ga_ls8c_ard_3-2-1_104069_2022-04-30_final
2022-04-30 10:42:36	ga_ls8c_ard_3-2-1_104074_2022-04-30_final
2022-04-30 10:42:59	ga_ls8c_ard_3-2-1_104075_2022-04-30_final
2022-04-30 10:45:23	ga_ls8c_ard_3-2-1_104081_2022-04-30_final
2022-05-01 09:49:47	ga_ls8c_ard_3-2-1_095081_2022-05-01_final
2022-05-02 10:32:15	ga_ls8c_ard_3-2-1_102079_2022-05-02_final
2022-05-03 09:38:15	ga_ls8c_ard_3-2-1_093083_2022-05-03_final
2022-05-04 10:21:55	ga_ls8c_ard_3-2-1_100084_2022-05-04_final
2022-05-05 11:03:12	ga_ls8c_ard_3-2-1_107079_2022-05-05_final
2022-05-08 09:52:27	ga_ls8c_ard_3-2-1_096072_2022-05-08_final
2022-05-09 10:36:07	ga_ls8c_ard_3-2-1_103073_2022-05-09_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-11 10:24:11	ga_ls8c_ard_3-2-1_101074_2022-05-11_final
2022-05-11 10:24:35	ga_ls8c_ard_3-2-1_101075_2022-05-11_final
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-16 10:45:33	ga_ls8c_ard_3-2-1_104081_2022-05-16_final
2022-05-17 09:49:32	ga_ls8c_ard_3-2-1_095080_2022-05-17_final
2022-05-17 09:49:56	ga_ls8c_ard_3-2-1_095081_2022-05-17_final
2022-05-18 10:29:36	ga_ls8c_ard_3-2-1_102072_2022-05-18_final
2022-05-18 10:31:12	ga_ls8c_ard_3-2-1_102076_2022-05-18_final
2022-05-18 10:33:36	ga_ls8c_ard_3-2-1_102082_2022-05-18_final
2022-05-19 09:37:35	ga_ls8c_ard_3-2-1_093081_2022-05-19_final
2022-05-19 11:12:52	ga_ls8c_ard_3-2-1_109072_2022-05-19_final
2022-05-24 11:33:48	ga_ls8c_ard_3-2-1_112078_2022-05-24_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-05-26 11:20:38	ga_ls8c_ard_3-2-1_110076_2022-05-26_final
2022-05-30 10:56:20	ga_ls8c_ard_3-2-1_106077_2022-05-30_final
2022-06-02 09:48:00	ga_ls8c_ard_3-2-1_095076_2022-06-02_final
2022-06-03 10:33:41	ga_ls8c_ard_3-2-1_102082_2022-06-03_final
2022-06-05 10:20:33	ga_ls8c_ard_3-2-1_100080_2022-06-05_final
2022-06-13 09:30:24	ga_ls8c_ard_3-2-1_092078_2022-06-13_final
2022-06-16 11:39:25	ga_ls8c_ard_3-2-1_113076_2022-06-16_final
2022-06-17 10:43:01	ga_ls8c_ard_3-2-1_104074_2022-06-17_final
2022-06-17 10:43:49	ga_ls8c_ard_3-2-1_104076_2022-06-17_final
2022-06-18 09:48:12	ga_ls8c_ard_3-2-1_095076_2022-06-18_final
2022-06-20 09:37:27	ga_ls8c_ard_3-2-1_093080_2022-06-20_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