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
2023-02-01 11:02:33	ga_ls8c_ard_3-2-1_107076_2023-02-01_final
2023-07-11 11:04:15	ga_ls8c_ard_3-2-1_107082_2023-07-11_final
2023-07-12 10:04:39	ga_ls8c_ard_3-2-1_098072_2023-07-12_final
2023-07-16 11:24:00	ga_ls8c_ard_3-2-1_110085_2023-07-16_final
2023-07-17 10:23:35	ga_ls8c_ard_3-2-1_101073_2023-07-17_final
2023-07-21 11:40:56	ga_ls8c_ard_3-2-1_113081_2023-07-21_final
2023-07-23 09:46:32	ga_ls8c_ard_3-2-1_095073_2023-07-23_final
2023-07-23 09:50:08	ga_ls8c_ard_3-2-1_095082_2023-07-23_final
2023-07-27 09:25:28	ga_ls8c_ard_3-2-1_091082_2023-07-26_final
2023-07-27 11:01:57	ga_ls8c_ard_3-2-1_107076_2023-07-27_final
2023-07-27 11:03:57	ga_ls8c_ard_3-2-1_107081_2023-07-27_final
2023-07-27 11:04:21	ga_ls8c_ard_3-2-1_107082_2023-07-27_final
2023-07-28 10:05:57	ga_ls8c_ard_3-2-1_098075_2023-07-28_final
2023-07-29 10:51:37	ga_ls8c_ard_3-2-1_105081_2023-07-29_final
2023-07-30 09:52:24	ga_ls8c_ard_3-2-1_096072_2023-07-30_final
2023-07-30 09:56:24	ga_ls8c_ard_3-2-1_096082_2023-07-30_final
2023-08-01 09:40:52	ga_ls8c_ard_3-2-1_094074_2023-08-01_final
2023-08-03 09:32:30	ga_ls8c_ard_3-2-1_092084_2023-08-03_final
2023-08-05 10:57:50	ga_ls8c_ard_3-2-1_106081_2023-08-05_final
2023-08-06 09:57:02	ga_ls8c_ard_3-2-1_097068_2023-08-06_final
2023-08-06 09:58:37	ga_ls8c_ard_3-2-1_097072_2023-08-06_final
2023-08-06 09:59:25	ga_ls8c_ard_3-2-1_097074_2023-08-06_final
2023-08-07 10:41:29	ga_ls8c_ard_3-2-1_104071_2023-08-07_final
2023-08-08 09:50:15	ga_ls8c_ard_3-2-1_095082_2023-08-08_final
2023-08-09 10:29:55	ga_ls8c_ard_3-2-1_102073_2023-08-09_final
2023-08-10 09:38:17	ga_ls8c_ard_3-2-1_093083_2023-08-10_final
2023-08-12 11:02:02	ga_ls8c_ard_3-2-1_107076_2023-08-12_final
2023-08-13 10:04:50	ga_ls8c_ard_3-2-1_098072_2023-08-13_final
2023-08-13 10:05:38	ga_ls8c_ard_3-2-1_098074_2023-08-13_final
2023-08-15 09:52:30	ga_ls8c_ard_3-2-1_096072_2023-08-15_final
2023-08-15 09:56:29	ga_ls8c_ard_3-2-1_096082_2023-08-15_final
2023-08-16 10:34:35	ga_ls8c_ard_3-2-1_103069_2023-08-16_final
2023-08-17 09:43:45	ga_ls8c_ard_3-2-1_094081_2023-08-17_final
2023-08-17 09:46:09	ga_ls8c_ard_3-2-1_094087_2023-08-17_final
2023-08-19 11:07:06	ga_ls8c_ard_3-2-1_108073_2023-08-19_final
2023-08-26 09:34:50	ga_ls8c_ard_3-2-1_093074_2023-08-26_final
2023-08-27 10:18:06	ga_ls8c_ard_3-2-1_100074_2023-08-27_final
2023-08-27 10:19:42	ga_ls8c_ard_3-2-1_100078_2023-08-27_final
2023-08-28 09:23:17	ga_ls8c_ard_3-2-1_091076_2023-08-27_final
2023-08-29 10:09:20	ga_ls8c_ard_3-2-1_098083_2023-08-29_final
2023-08-30 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-08-29_final
2023-08-31 11:35:51	ga_ls8c_ard_3-2-1_112083_2023-08-31_final
2023-09-02 11:23:53	ga_ls8c_ard_3-2-1_110084_2023-09-02_final
2023-09-07 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-09-07_final
2023-09-08 10:41:36	ga_ls8c_ard_3-2-1_104071_2023-09-08_final
2023-09-08 10:42:00	ga_ls8c_ard_3-2-1_104072_2023-09-08_final
2023-09-09 09:47:36	ga_ls8c_ard_3-2-1_095075_2023-09-09_final
2023-09-11 11:17:44	ga_ls8c_ard_3-2-1_109084_2023-09-11_final
2023-09-13 11:04:36	ga_ls8c_ard_3-2-1_107082_2023-09-13_final
2023-09-15 09:16:10	ga_ls8c_ard_3-2-1_089089_2023-09-14_final
2023-09-16 09:52:15	ga_ls8c_ard_3-2-1_096071_2023-09-16_final
2023-09-16 11:36:19	ga_ls8c_ard_3-2-1_112084_2023-09-16_final
2023-09-17 10:34:43	ga_ls8c_ard_3-2-1_103069_2023-09-17_final
2023-09-18 09:46:17	ga_ls8c_ard_3-2-1_094087_2023-09-18_final
2023-09-19 10:23:57	ga_ls8c_ard_3-2-1_101073_2023-09-19_final
2023-09-23 09:59:38	ga_ls8c_ard_3-2-1_097074_2023-09-23_final
2023-09-23 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-09-23_final
2023-09-27 09:38:09	ga_ls8c_ard_3-2-1_093082_2023-09-27_final
2023-09-29 11:01:29	ga_ls8c_ard_3-2-1_107074_2023-09-29_final
2023-09-29 11:05:29	ga_ls8c_ard_3-2-1_107084_2023-09-29_final
2023-09-30 10:05:28	ga_ls8c_ard_3-2-1_098073_2023-09-30_final
2023-09-30 10:07:04	ga_ls8c_ard_3-2-1_098077_2023-09-30_final
2023-09-30 10:07:52	ga_ls8c_ard_3-2-1_098079_2023-09-30_final
2023-09-30 10:09:27	ga_ls8c_ard_3-2-1_098083_2023-09-30_final
2023-10-02 09:56:42	ga_ls8c_ard_3-2-1_096082_2023-10-02_final
2023-10-02 09:57:06	ga_ls8c_ard_3-2-1_096083_2023-10-02_final
2023-10-02 11:35:35	ga_ls8c_ard_3-2-1_112082_2023-10-02_final
2023-10-04 09:41:08	ga_ls8c_ard_3-2-1_094074_2023-10-04_final
2023-10-08 10:55:19	ga_ls8c_ard_3-2-1_106074_2023-10-08_final
2023-10-09 09:58:55	ga_ls8c_ard_3-2-1_097072_2023-10-09_final
2023-10-09 11:41:47	ga_ls8c_ard_3-2-1_113082_2023-10-09_final
2023-10-15 11:05:07	ga_ls8c_ard_3-2-1_107083_2023-10-15_final
2023-10-16 10:05:06	ga_ls8c_ard_3-2-1_098072_2023-10-16_final
2023-10-16 10:05:30	ga_ls8c_ard_3-2-1_098073_2023-10-16_final
2023-10-17 10:49:10	ga_ls8c_ard_3-2-1_105074_2023-10-17_final
2023-10-17 10:51:57	ga_ls8c_ard_3-2-1_105081_2023-10-17_final
2023-10-17 10:52:45	ga_ls8c_ard_3-2-1_105083_2023-10-17_final
2023-10-21 10:23:14	ga_ls8c_ard_3-2-1_101071_2023-10-21_final
2023-10-24 10:56:10	ga_ls8c_ard_3-2-1_106076_2023-10-24_final
2023-10-25 09:58:57	ga_ls8c_ard_3-2-1_097072_2023-10-25_final
2023-10-25 09:59:45	ga_ls8c_ard_3-2-1_097074_2023-10-25_final
2023-10-25 10:02:57	ga_ls8c_ard_3-2-1_097082_2023-10-25_final
2023-10-27 09:46:37	ga_ls8c_ard_3-2-1_095072_2023-10-27_final
2023-10-27 09:51:48	ga_ls8c_ard_3-2-1_095085_2023-10-27_final
2023-10-27 11:29:53	ga_ls8c_ard_3-2-1_111083_2023-10-27_final
2023-11-01 10:05:34	ga_ls8c_ard_3-2-1_098073_2023-11-01_final
2023-11-01 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-11-01_final
2023-11-01 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-01_final
2023-11-03 09:56:47	ga_ls8c_ard_3-2-1_096082_2023-11-03_final
2023-11-05 09:45:36	ga_ls8c_ard_3-2-1_094085_2023-11-05_final
2023-11-07 09:31:13	ga_ls8c_ard_3-2-1_092080_2023-11-07_final
2023-11-07 11:07:19	ga_ls8c_ard_3-2-1_108073_2023-11-07_final
2023-11-10 10:02:52	ga_ls8c_ard_3-2-1_097082_2023-11-10_final
2023-11-10 11:42:09	ga_ls8c_ard_3-2-1_113083_2023-11-10_final
2023-11-11 10:42:10	ga_ls8c_ard_3-2-1_104072_2023-11-11_final
2023-11-12 09:47:21	ga_ls8c_ard_3-2-1_095074_2023-11-12_final
2023-11-12 09:50:57	ga_ls8c_ard_3-2-1_095083_2023-11-12_final
2023-11-15 10:21:05	ga_ls8c_ard_3-2-1_100081_2023-11-15_final
2023-11-16 09:27:52	ga_ls8c_ard_3-2-1_091087_2023-11-15_final
2023-11-17 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-11-17_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