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
2019-04-11 09:25:34	ga_ls8c_ard_3-1-0_091083_2019-04-10_final
2019-06-26 09:47:29	ga_ls8c_ard_3-1-0_095075_2019-06-26_final
2019-06-26 09:49:53	ga_ls8c_ard_3-1-0_095081_2019-06-26_final
2019-06-26 09:50:40	ga_ls8c_ard_3-1-0_095083_2019-06-26_final
2019-07-12 09:48:44	ga_ls8c_ard_3-1-0_095078_2019-07-12_final
2019-07-12 09:49:32	ga_ls8c_ard_3-1-0_095080_2019-07-12_final
2019-07-28 09:50:25	ga_ls8c_ard_3-1-0_095082_2019-07-28_final
2019-08-01 09:26:07	ga_ls8c_ard_3-1-0_091083_2019-07-31_final
2019-08-13 09:51:19	ga_ls8c_ard_3-1-0_095084_2019-08-13_final
2019-08-17 09:22:13	ga_ls8c_ard_3-1-0_091073_2019-08-16_final
2019-08-29 09:47:23	ga_ls8c_ard_3-1-0_095074_2019-08-29_final
2019-08-29 09:48:59	ga_ls8c_ard_3-1-0_095078_2019-08-29_final
2019-09-14 09:49:28	ga_ls8c_ard_3-1-0_095079_2019-09-14_final
2019-09-14 09:52:15	ga_ls8c_ard_3-1-0_095086_2019-09-14_final
2019-09-30 09:47:09	ga_ls8c_ard_3-1-0_095073_2019-09-30_final
2019-09-30 09:49:09	ga_ls8c_ard_3-1-0_095078_2019-09-30_final
2019-10-16 09:47:36	ga_ls8c_ard_3-1-0_095074_2019-10-16_final
2019-10-16 09:49:11	ga_ls8c_ard_3-1-0_095078_2019-10-16_final
2019-10-20 09:24:04	ga_ls8c_ard_3-1-0_091077_2019-10-19_final
2019-10-20 09:24:52	ga_ls8c_ard_3-1-0_091079_2019-10-19_final
2019-11-01 09:49:59	ga_ls8c_ard_3-1-0_095080_2019-11-01_final
2019-11-05 09:24:03	ga_ls8c_ard_3-1-0_091077_2019-11-04_final
2019-11-05 09:26:27	ga_ls8c_ard_3-1-0_091083_2019-11-04_final
2019-11-17 09:47:56	ga_ls8c_ard_3-1-0_095075_2019-11-17_final
2019-11-17 09:49:32	ga_ls8c_ard_3-1-0_095079_2019-11-17_final
2019-11-17 09:49:56	ga_ls8c_ard_3-1-0_095080_2019-11-17_final
2019-12-23 09:23:57	ga_ls8c_ard_3-1-0_091077_2019-12-22_final
2020-01-04 09:47:48	ga_ls8c_ard_3-1-0_095075_2020-01-04_final
2020-01-04 09:49:48	ga_ls8c_ard_3-1-0_095080_2020-01-04_final
2020-01-04 09:51:24	ga_ls8c_ard_3-1-0_095084_2020-01-04_final
2020-01-20 09:47:21	ga_ls8c_ard_3-1-0_095074_2020-01-20_final
2020-01-20 09:47:45	ga_ls8c_ard_3-1-0_095075_2020-01-20_final
2020-01-20 09:50:57	ga_ls8c_ard_3-1-0_095083_2020-01-20_final
2020-01-24 09:26:36	ga_ls8c_ard_3-1-0_091084_2020-01-23_final
2020-02-05 09:51:15	ga_ls8c_ard_3-1-0_095084_2020-02-05_final
2020-02-21 09:47:13	ga_ls8c_ard_3-1-0_095074_2020-02-21_final
2020-03-08 09:46:19	ga_ls8c_ard_3-1-0_095072_2020-03-08_final
2020-03-08 09:50:42	ga_ls8c_ard_3-1-0_095083_2020-03-08_final
2020-03-12 09:23:34	ga_ls8c_ard_3-1-0_091077_2020-03-11_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-03-30 11:25:49	ga_ls8c_ard_3-2-1_111074_2022-03-30_final
2022-04-01 09:39:46	ga_ls8c_ard_3-2-1_093087_2022-04-01_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-06 09:55:09	ga_ls8c_ard_3-2-1_096079_2022-04-06_final
2022-04-08 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-08_final
2022-04-08 09:42:49	ga_ls8c_ard_3-2-1_094079_2022-04-08_final
2022-04-09 10:26:53	ga_ls8c_ard_3-2-1_101081_2022-04-09_final
2022-04-10 09:29:16	ga_ls8c_ard_3-2-1_092076_2022-04-09_final
2022-04-10 11:06:57	ga_ls8c_ard_3-2-1_108073_2022-04-10_final
2022-04-13 09:56:36	ga_ls8c_ard_3-2-1_097067_2022-04-13_final
2022-04-15 09:49:02	ga_ls8c_ard_3-2-1_095079_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-17 09:38:16	ga_ls8c_ard_3-2-1_093083_2022-04-17_final
2022-04-17 09:38:40	ga_ls8c_ard_3-2-1_093084_2022-04-17_final
2022-04-18 10:19:56	ga_ls8c_ard_3-2-1_100079_2022-04-18_final
2022-04-23 10:36:27	ga_ls8c_ard_3-2-1_103074_2022-04-23_final
2022-04-23 10:39:14	ga_ls8c_ard_3-2-1_103081_2022-04-23_final
2022-04-24 11:20:30	ga_ls8c_ard_3-2-1_110076_2022-04-24_final
2022-04-24 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-24_final
2022-04-27 10:12:05	ga_ls8c_ard_3-2-1_099075_2022-04-27_final
2022-05-01 09:49:47	ga_ls8c_ard_3-2-1_095081_2022-05-01_final
2022-05-03 09:38:39	ga_ls8c_ard_3-2-1_093084_2022-05-03_final
2022-05-04 10:20:19	ga_ls8c_ard_3-2-1_100080_2022-05-04_final
2022-05-04 11:58:25	ga_ls8c_ard_3-2-1_116078_2022-05-04_final
2022-05-08 09:55:15	ga_ls8c_ard_3-2-1_096079_2022-05-08_final
2022-05-08 09:55:39	ga_ls8c_ard_3-2-1_096080_2022-05-08_final
2022-05-08 11:34:08	ga_ls8c_ard_3-2-1_112079_2022-05-08_final
2022-05-08 11:34:32	ga_ls8c_ard_3-2-1_112080_2022-05-08_final
2022-05-09 10:34:32	ga_ls8c_ard_3-2-1_103069_2022-05-09_final
2022-05-09 10:38:07	ga_ls8c_ard_3-2-1_103078_2022-05-09_final
2022-05-10 09:45:18	ga_ls8c_ard_3-2-1_094085_2022-05-10_final
2022-05-11 10:26:58	ga_ls8c_ard_3-2-1_101081_2022-05-11_final
2022-05-12 11:07:03	ga_ls8c_ard_3-2-1_108073_2022-05-12_final
2022-05-15 09:59:53	ga_ls8c_ard_3-2-1_097075_2022-05-15_final
2022-05-17 09:48:44	ga_ls8c_ard_3-2-1_095078_2022-05-17_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-21 09:22:02	ga_ls8c_ard_3-2-1_091073_2022-05-20_final
2022-05-21 09:28:25	ga_ls8c_ard_3-2-1_091089_2022-05-20_final
2022-05-24 09:54:31	ga_ls8c_ard_3-2-1_096077_2022-05-24_final
2022-05-24 09:56:31	ga_ls8c_ard_3-2-1_096082_2022-05-24_final
2022-05-25 10:34:35	ga_ls8c_ard_3-2-1_103069_2022-05-25_final
2022-05-25 10:38:10	ga_ls8c_ard_3-2-1_103078_2022-05-25_final
2022-05-26 09:42:09	ga_ls8c_ard_3-2-1_094077_2022-05-26_final
2022-05-30 10:55:09	ga_ls8c_ard_3-2-1_106074_2022-05-30_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-04 11:12:58	ga_ls8c_ard_3-2-1_109072_2022-06-04_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-04 11:15:45	ga_ls8c_ard_3-2-1_109079_2022-06-04_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-12 10:27:13	ga_ls8c_ard_3-2-1_101081_2022-06-12_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-15 10:56:09	ga_ls8c_ard_3-2-1_106076_2022-06-15_final
2022-06-15 10:57:21	ga_ls8c_ard_3-2-1_106079_2022-06-15_final
2022-06-15 10:58:09	ga_ls8c_ard_3-2-1_106081_2022-06-15_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-18 09:49:47	ga_ls8c_ard_3-2-1_095080_2022-06-18_final
2022-06-19 10:29:04	ga_ls8c_ard_3-2-1_102070_2022-06-19_final
2022-06-20 09:37:51	ga_ls8c_ard_3-2-1_093081_2022-06-20_final
2022-06-20 11:16:20	ga_ls8c_ard_3-2-1_109080_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