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
2022-10-04 10:12:32	ga_ls8c_ard_3-2-1_099074_2022-10-04_final
2022-10-05 10:57:47	ga_ls8c_ard_3-2-1_106079_2022-10-05_final
2022-10-07 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-07_final
2022-10-09 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-10-09_final
2022-10-11 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-10-11_final
2022-10-15 09:55:53	ga_ls8c_ard_3-2-1_096079_2022-10-15_final
2022-10-16 10:37:34	ga_ls8c_ard_3-2-1_103075_2022-10-16_final
2022-10-17 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-10-17_final
2022-10-23 10:43:49	ga_ls8c_ard_3-2-1_104075_2022-10-23_final
2022-10-27 11:58:49	ga_ls8c_ard_3-2-1_116077_2022-10-27_final
2022-10-28 11:04:23	ga_ls8c_ard_3-2-1_107080_2022-10-28_final
2022-10-30 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-10-30_final
2022-11-02 09:42:28	ga_ls8c_ard_3-2-1_094076_2022-11-02_final
2022-11-05 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-11-05_final
2022-11-07 11:40:40	ga_ls8c_ard_3-2-1_113078_2022-11-07_final
2022-11-08 10:42:39	ga_ls8c_ard_3-2-1_104072_2022-11-08_final
2022-11-09 09:48:37	ga_ls8c_ard_3-2-1_095076_2022-11-09_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-16 11:34:48	ga_ls8c_ard_3-2-1_112079_2022-11-16_final
2022-11-17 10:38:46	ga_ls8c_ard_3-2-1_103078_2022-11-17_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-11-28 10:21:27	ga_ls8c_ard_3-2-1_100081_2022-11-28_final
2022-12-02 09:56:44	ga_ls8c_ard_3-2-1_096081_2022-12-02_final
2022-12-02 11:33:38	ga_ls8c_ard_3-2-1_112076_2022-12-02_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-12 10:32:59	ga_ls8c_ard_3-2-1_102079_2022-12-12_final
2022-12-14 10:19:00	ga_ls8c_ard_3-2-1_100075_2022-12-14_final
2022-12-20 09:43:26	ga_ls8c_ard_3-2-1_094079_2022-12-20_final
2022-12-22 09:30:38	ga_ls8c_ard_3-2-1_092078_2022-12-22_final
2022-12-23 11:51:11	ga_ls8c_ard_3-2-1_115074_2022-12-23_final
2022-12-25 10:03:09	ga_ls8c_ard_3-2-1_097082_2022-12-25_final
2022-12-29 11:16:08	ga_ls8c_ard_3-2-1_109079_2022-12-29_final
2022-12-31 11:03:23	ga_ls8c_ard_3-2-1_107078_2022-12-31_final
2023-01-03 09:56:35	ga_ls8c_ard_3-2-1_096081_2023-01-03_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-03 11:33:29	ga_ls8c_ard_3-2-1_112076_2023-01-03_final
2023-01-07 11:11:08	ga_ls8c_ard_3-2-1_108082_2023-01-07_final
2023-01-14 09:37:10	ga_ls8c_ard_3-2-1_093079_2023-01-14_final
2023-01-15 10:20:25	ga_ls8c_ard_3-2-1_100079_2023-01-15_final
2023-01-18 10:50:52	ga_ls8c_ard_3-2-1_105078_2023-01-18_final
2023-01-18 10:51:16	ga_ls8c_ard_3-2-1_105079_2023-01-18_final
2023-01-20 10:38:09	ga_ls8c_ard_3-2-1_103077_2023-01-20_final
2023-01-23 09:31:00	ga_ls8c_ard_3-2-1_092079_2023-01-23_final
2023-01-23 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-01-23_final
2023-01-26 09:59:32	ga_ls8c_ard_3-2-1_097073_2023-01-26_final
2023-01-30 11:16:54	ga_ls8c_ard_3-2-1_109081_2023-01-30_final
2023-02-11 10:00:41	ga_ls8c_ard_3-2-1_097076_2023-02-11_final
2023-02-12 10:42:20	ga_ls8c_ard_3-2-1_104072_2023-02-12_final
2023-02-14 10:31:08	ga_ls8c_ard_3-2-1_102075_2023-02-14_final
2023-02-14 10:33:08	ga_ls8c_ard_3-2-1_102080_2023-02-14_final
2023-02-17 11:04:00	ga_ls8c_ard_3-2-1_107080_2023-02-17_final
2023-02-22 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-02-22_final
2023-02-24 09:32:44	ga_ls8c_ard_3-2-1_092084_2023-02-24_final
2023-02-26 10:58:02	ga_ls8c_ard_3-2-1_106081_2023-02-26_final
2023-03-03 09:39:41	ga_ls8c_ard_3-2-1_093086_2023-03-03_final
2023-03-05 11:02:35	ga_ls8c_ard_3-2-1_107077_2023-03-05_final
2023-03-05 11:04:35	ga_ls8c_ard_3-2-1_107082_2023-03-05_final
2023-03-07 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-03-07_final
2023-03-08 11:35:02	ga_ls8c_ard_3-2-1_112081_2023-03-08_final
2023-03-09 10:38:13	ga_ls8c_ard_3-2-1_103078_2023-03-09_final
2023-03-10 11:21:05	ga_ls8c_ard_3-2-1_110077_2023-03-10_final
2023-03-10 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-03-10_final
2023-03-12 09:31:50	ga_ls8c_ard_3-2-1_092082_2023-03-12_final
2023-03-14 10:56:45	ga_ls8c_ard_3-2-1_106078_2023-03-14_final
2023-03-14 10:57:09	ga_ls8c_ard_3-2-1_106079_2023-03-14_final
2023-03-15 11:38:48	ga_ls8c_ard_3-2-1_113075_2023-03-15_final
2023-03-16 10:43:34	ga_ls8c_ard_3-2-1_104076_2023-03-16_final
2023-03-19 11:15:14	ga_ls8c_ard_3-2-1_109078_2023-03-19_final
2023-03-25 10:35:17	ga_ls8c_ard_3-2-1_103071_2023-03-25_final
2023-03-25 10:38:04	ga_ls8c_ard_3-2-1_103078_2023-03-25_final
2023-04-01 10:41:48	ga_ls8c_ard_3-2-1_104072_2023-04-01_final
2023-04-01 10:42:36	ga_ls8c_ard_3-2-1_104074_2023-04-01_final
2023-04-05 10:18:12	ga_ls8c_ard_3-2-1_100075_2023-04-05_final
2023-04-06 09:23:45	ga_ls8c_ard_3-2-1_091078_2023-04-05_final
2023-04-13 09:30:13	ga_ls8c_ard_3-2-1_092079_2023-04-13_final
2023-04-15 09:18:15	ga_ls8c_ard_3-2-1_090080_2023-04-14_final
2023-04-15 10:56:20	ga_ls8c_ard_3-2-1_106078_2023-04-15_final
2023-04-15 10:56:44	ga_ls8c_ard_3-2-1_106079_2023-04-15_final
2023-04-20 09:35:57	ga_ls8c_ard_3-2-1_093078_2023-04-20_final
2023-04-20 11:16:01	ga_ls8c_ard_3-2-1_109081_2023-04-20_final
2023-04-21 10:20:24	ga_ls8c_ard_3-2-1_100081_2023-04-21_final
2023-05-06 09:35:03	ga_ls8c_ard_3-2-1_093076_2023-05-06_final
2023-05-07 10:19:30	ga_ls8c_ard_3-2-1_100079_2023-05-07_final
2023-05-07 10:19:53	ga_ls8c_ard_3-2-1_100080_2023-05-07_final
2023-05-09 10:05:54	ga_ls8c_ard_3-2-1_098076_2023-05-09_final
2023-05-11 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-11_final
2023-05-12 10:35:32	ga_ls8c_ard_3-2-1_103073_2023-05-12_final
2023-05-12 10:36:44	ga_ls8c_ard_3-2-1_103076_2023-05-12_final
2023-05-13 11:21:35	ga_ls8c_ard_3-2-1_110080_2023-05-13_final
2023-05-19 10:42:29	ga_ls8c_ard_3-2-1_104075_2023-05-19_final
2023-05-20 11:28:33	ga_ls8c_ard_3-2-1_111082_2023-05-20_final
2023-05-22 09:37:43	ga_ls8c_ard_3-2-1_093083_2023-05-22_final
2023-05-23 10:20:12	ga_ls8c_ard_3-2-1_100081_2023-05-23_final
2023-05-24 09:24:58	ga_ls8c_ard_3-2-1_091082_2023-05-23_final
2023-05-24 11:00:16	ga_ls8c_ard_3-2-1_107073_2023-05-24_final
2023-05-28 10:33:58	ga_ls8c_ard_3-2-1_103069_2023-05-28_nrt
2023-05-30 10:22:48	ga_ls8c_ard_3-2-1_101072_2023-05-30_nrt
2023-05-31 09:30:22	ga_ls8c_ard_3-2-1_092080_2023-05-31_nrt
2023-06-01 10:11:38	ga_ls8c_ard_3-2-1_099075_2023-06-01_nrt

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