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
2023-08-24 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-08-24_final
2023-08-29 10:06:32	ga_ls8c_ard_3-2-1_098076_2023-08-29_final
2023-08-29 10:08:08	ga_ls8c_ard_3-2-1_098080_2023-08-29_final
2023-08-29 10:10:08	ga_ls8c_ard_3-2-1_098085_2023-08-29_final
2023-08-29 11:46:37	ga_ls8c_ard_3-2-1_114079_2023-08-29_final
2023-08-30 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-08-30_final
2023-08-30 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-08-30_final
2023-08-31 09:52:59	ga_ls8c_ard_3-2-1_096073_2023-08-31_final
2023-09-01 10:37:50	ga_ls8c_ard_3-2-1_103077_2023-09-01_final
2023-09-03 10:26:16	ga_ls8c_ard_3-2-1_101079_2023-09-03_final
2023-09-06 09:19:27	ga_ls8c_ard_3-2-1_090082_2023-09-05_final
2023-09-06 09:20:15	ga_ls8c_ard_3-2-1_090084_2023-09-05_final
2023-09-08 10:40:48	ga_ls8c_ard_3-2-1_104069_2023-09-08_final
2023-09-08 10:42:48	ga_ls8c_ard_3-2-1_104074_2023-09-08_final
2023-09-08 10:43:12	ga_ls8c_ard_3-2-1_104075_2023-09-08_final
2023-09-09 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-09-09_final
2023-09-09 11:26:05	ga_ls8c_ard_3-2-1_111074_2023-09-09_final
2023-09-10 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-09-10_final
2023-09-10 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-09-10_final
2023-09-10 10:32:04	ga_ls8c_ard_3-2-1_102078_2023-09-10_final
2023-09-11 11:16:56	ga_ls8c_ard_3-2-1_109082_2023-09-11_final
2023-09-12 10:17:44	ga_ls8c_ard_3-2-1_100073_2023-09-12_final
2023-09-12 10:18:32	ga_ls8c_ard_3-2-1_100075_2023-09-12_final
2023-09-13 09:26:55	ga_ls8c_ard_3-2-1_091085_2023-09-12_final
2023-09-13 11:02:12	ga_ls8c_ard_3-2-1_107076_2023-09-13_final
2023-09-14 10:05:23	ga_ls8c_ard_3-2-1_098073_2023-09-14_final
2023-09-14 10:08:11	ga_ls8c_ard_3-2-1_098080_2023-09-14_final
2023-09-14 10:10:11	ga_ls8c_ard_3-2-1_098085_2023-09-14_final
2023-09-14 11:45:04	ga_ls8c_ard_3-2-1_114075_2023-09-14_final
2023-09-16 09:58:14	ga_ls8c_ard_3-2-1_096086_2023-09-16_final
2023-09-16 11:32:44	ga_ls8c_ard_3-2-1_112075_2023-09-16_final
2023-09-17 10:35:07	ga_ls8c_ard_3-2-1_103070_2023-09-17_final
2023-09-18 09:44:17	ga_ls8c_ard_3-2-1_094082_2023-09-18_final
2023-09-18 09:45:05	ga_ls8c_ard_3-2-1_094084_2023-09-18_final
2023-09-19 10:24:45	ga_ls8c_ard_3-2-1_101075_2023-09-19_final
2023-09-23 10:00:50	ga_ls8c_ard_3-2-1_097077_2023-09-23_final
2023-09-23 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-09-23_final
2023-09-23 11:39:43	ga_ls8c_ard_3-2-1_113077_2023-09-23_final
2023-09-23 11:40:31	ga_ls8c_ard_3-2-1_113079_2023-09-23_final
2023-09-25 09:46:30	ga_ls8c_ard_3-2-1_095072_2023-09-25_final
2023-09-25 09:49:17	ga_ls8c_ard_3-2-1_095079_2023-09-25_final
2023-09-25 11:26:35	ga_ls8c_ard_3-2-1_111075_2023-09-25_final
2023-09-25 11:29:22	ga_ls8c_ard_3-2-1_111082_2023-09-25_final
2023-09-26 10:28:34	ga_ls8c_ard_3-2-1_102069_2023-09-26_final
2023-09-26 10:30:34	ga_ls8c_ard_3-2-1_102074_2023-09-26_final
2023-09-26 10:32:10	ga_ls8c_ard_3-2-1_102078_2023-09-26_final
2023-09-27 11:17:02	ga_ls8c_ard_3-2-1_109082_2023-09-27_final
2023-09-28 10:20:13	ga_ls8c_ard_3-2-1_100079_2023-09-28_final
2023-09-28 10:21:25	ga_ls8c_ard_3-2-1_100082_2023-09-28_final
2023-09-28 10:22:13	ga_ls8c_ard_3-2-1_100084_2023-09-28_final
2023-09-30 11:45:09	ga_ls8c_ard_3-2-1_114075_2023-09-30_final
2023-10-02 11:35:11	ga_ls8c_ard_3-2-1_112081_2023-10-02_final
2023-10-03 10:35:34	ga_ls8c_ard_3-2-1_103071_2023-10-03_final
2023-10-04 09:43:32	ga_ls8c_ard_3-2-1_094080_2023-10-04_final
2023-10-04 11:20:25	ga_ls8c_ard_3-2-1_110075_2023-10-04_final
2023-10-06 11:06:51	ga_ls8c_ard_3-2-1_108072_2023-10-06_final
2023-10-08 10:57:19	ga_ls8c_ard_3-2-1_106079_2023-10-08_final
2023-10-08 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-10-08_final
2023-10-09 09:59:19	ga_ls8c_ard_3-2-1_097073_2023-10-09_final
2023-10-09 10:00:30	ga_ls8c_ard_3-2-1_097076_2023-10-09_final
2023-10-10 10:43:23	ga_ls8c_ard_3-2-1_104075_2023-10-10_final
2023-10-11 11:26:39	ga_ls8c_ard_3-2-1_111075_2023-10-11_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-12 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-10-12_final
2023-10-12 10:31:26	ga_ls8c_ard_3-2-1_102076_2023-10-12_final
2023-10-14 11:58:21	ga_ls8c_ard_3-2-1_116077_2023-10-14_final
2023-10-15 09:24:38	ga_ls8c_ard_3-2-1_091079_2023-10-14_final
2023-10-15 11:04:43	ga_ls8c_ard_3-2-1_107082_2023-10-15_final
2023-10-16 10:05:54	ga_ls8c_ard_3-2-1_098074_2023-10-16_final
2023-10-17 10:50:21	ga_ls8c_ard_3-2-1_105077_2023-10-17_final
2023-10-20 09:44:45	ga_ls8c_ard_3-2-1_094083_2023-10-20_final
2023-10-20 09:45:09	ga_ls8c_ard_3-2-1_094084_2023-10-20_final
2023-10-20 11:24:26	ga_ls8c_ard_3-2-1_110085_2023-10-20_final
2023-10-21 10:24:50	ga_ls8c_ard_3-2-1_101075_2023-10-21_final
2023-10-21 10:26:26	ga_ls8c_ard_3-2-1_101079_2023-10-21_final
2023-10-22 11:07:42	ga_ls8c_ard_3-2-1_108074_2023-10-22_final
2023-10-22 11:11:18	ga_ls8c_ard_3-2-1_108083_2023-10-22_final
2023-10-24 10:57:46	ga_ls8c_ard_3-2-1_106080_2023-10-24_final
2023-10-25 10:00:57	ga_ls8c_ard_3-2-1_097077_2023-10-25_final
2023-10-25 10:03:21	ga_ls8c_ard_3-2-1_097083_2023-10-25_final
2023-10-25 11:39:02	ga_ls8c_ard_3-2-1_113075_2023-10-25_final
2023-10-25 11:40:38	ga_ls8c_ard_3-2-1_113079_2023-10-25_final
2023-10-25 11:41:50	ga_ls8c_ard_3-2-1_113082_2023-10-25_final
2023-10-26 10:41:26	ga_ls8c_ard_3-2-1_104070_2023-10-26_final
2023-10-28 10:31:28	ga_ls8c_ard_3-2-1_102076_2023-10-28_final
2023-10-28 10:33:04	ga_ls8c_ard_3-2-1_102080_2023-10-28_final
2023-10-31 09:25:30	ga_ls8c_ard_3-2-1_091081_2023-10-30_final
2023-10-31 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-10-31_final
2023-11-02 10:47:37	ga_ls8c_ard_3-2-1_105070_2023-11-02_final
2023-11-03 09:57:11	ga_ls8c_ard_3-2-1_096083_2023-11-03_final
2023-11-05 09:45:36	ga_ls8c_ard_3-2-1_094085_2023-11-05_final
2023-11-05 11:24:05	ga_ls8c_ard_3-2-1_110084_2023-11-05_final
2023-11-06 10:26:28	ga_ls8c_ard_3-2-1_101079_2023-11-06_final
2023-11-10 10:02:04	ga_ls8c_ard_3-2-1_097080_2023-11-10_final
2023-11-10 11:39:22	ga_ls8c_ard_3-2-1_113076_2023-11-10_final
2023-11-12 11:28:38	ga_ls8c_ard_3-2-1_111080_2023-11-12_final
2023-11-14 09:35:49	ga_ls8c_ard_3-2-1_093076_2023-11-14_final
2023-11-14 11:15:30	ga_ls8c_ard_3-2-1_109078_2023-11-14_final
2023-11-16 09:25:52	ga_ls8c_ard_3-2-1_091082_2023-11-15_final
2023-11-19 11:35:17	ga_ls8c_ard_3-2-1_112081_2023-11-19_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