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
2022-08-21 09:52:56	ga_ls8c_ard_3-2-1_095087_2022-08-21_final
2022-08-25 09:25:49	ga_ls8c_ard_3-2-1_091081_2022-08-24_final
2022-09-06 11:29:50	ga_ls8c_ard_3-2-1_111082_2022-09-06_final
2022-09-08 11:17:30	ga_ls8c_ard_3-2-1_109082_2022-09-08_final
2022-09-17 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-09-17_final
2022-09-19 10:55:26	ga_ls8c_ard_3-2-1_106073_2022-09-19_final
2022-09-20 09:58:37	ga_ls8c_ard_3-2-1_097070_2022-09-20_final
2022-09-23 10:28:43	ga_ls8c_ard_3-2-1_102068_2022-09-23_final
2022-09-23 10:31:07	ga_ls8c_ard_3-2-1_102074_2022-09-23_final
2022-10-15 11:32:23	ga_ls8c_ard_3-2-1_112073_2022-10-15_final
2022-10-20 11:52:11	ga_ls8c_ard_3-2-1_115076_2022-10-20_final
2022-10-21 10:55:46	ga_ls8c_ard_3-2-1_106074_2022-10-21_final
2022-10-25 10:30:17	ga_ls8c_ard_3-2-1_102072_2022-10-25_final
2022-10-26 11:12:45	ga_ls8c_ard_3-2-1_109070_2022-10-26_final
2022-10-26 11:17:32	ga_ls8c_ard_3-2-1_109082_2022-10-26_final
2022-10-28 11:04:47	ga_ls8c_ard_3-2-1_107081_2022-10-28_final
2022-10-30 10:51:14	ga_ls8c_ard_3-2-1_105078_2022-10-30_final
2022-10-31 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-10-31_final
2022-11-10 10:34:16	ga_ls8c_ard_3-2-1_102082_2022-11-10_final
2022-11-11 11:17:07	ga_ls8c_ard_3-2-1_109081_2022-11-11_final
2022-11-12 10:20:41	ga_ls8c_ard_3-2-1_100079_2022-11-12_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-12-01 10:50:46	ga_ls8c_ard_3-2-1_105077_2022-12-01_final
2022-12-06 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-12-06_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-08 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-12-07_final
2022-12-10 10:44:57	ga_ls8c_ard_3-2-1_104078_2022-12-10_final
2022-12-15 09:25:22	ga_ls8c_ard_3-2-1_091080_2022-12-14_final
2022-12-17 10:53:03	ga_ls8c_ard_3-2-1_105083_2022-12-17_final
2022-12-22 11:11:31	ga_ls8c_ard_3-2-1_108083_2022-12-22_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-03 09:52:36	ga_ls8c_ard_3-2-1_096071_2023-01-03_final
2023-01-11 10:43:36	ga_ls8c_ard_3-2-1_104075_2023-01-11_final
2023-01-17 10:07:13	ga_ls8c_ard_3-2-1_098077_2023-01-17_final
2023-01-18 10:50:28	ga_ls8c_ard_3-2-1_105077_2023-01-18_final
2023-01-30 09:35:13	ga_ls8c_ard_3-2-1_093074_2023-01-30_final
2023-02-14 10:31:56	ga_ls8c_ard_3-2-1_102077_2023-02-14_final
2023-02-16 11:58:02	ga_ls8c_ard_3-2-1_116076_2023-02-16_final
2023-02-17 09:23:55	ga_ls8c_ard_3-2-1_091077_2023-02-16_final
2023-02-17 09:25:07	ga_ls8c_ard_3-2-1_091080_2023-02-16_final
2023-02-17 11:05:35	ga_ls8c_ard_3-2-1_107084_2023-02-17_final
2023-02-26 10:54:26	ga_ls8c_ard_3-2-1_106072_2023-02-26_final
2023-03-01 11:30:08	ga_ls8c_ard_3-2-1_111084_2023-03-01_final
2023-03-14 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-03-13_final
2023-03-21 11:00:03	ga_ls8c_ard_3-2-1_107071_2023-03-21_final
2023-03-30 10:53:47	ga_ls8c_ard_3-2-1_106071_2023-03-30_final
2023-03-30 10:54:35	ga_ls8c_ard_3-2-1_106073_2023-03-30_final
2023-04-04 11:15:27	ga_ls8c_ard_3-2-1_109079_2023-04-04_final
2023-04-06 11:01:51	ga_ls8c_ard_3-2-1_107076_2023-04-06_final
2023-04-07 10:07:48	ga_ls8c_ard_3-2-1_098080_2023-04-07_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-05-02 11:41:30	ga_ls8c_ard_3-2-1_113083_2023-05-02_final
2023-05-10 10:51:08	ga_ls8c_ard_3-2-1_105081_2023-05-10_final
2023-05-13 09:40:19	ga_ls8c_ard_3-2-1_094074_2023-05-13_final
2023-05-26 09:12:37	ga_ls8c_ard_3-2-1_089082_2023-05-25_final
2023-05-29 11:22:25	ga_ls8c_ard_3-2-1_110082_2023-05-29_final
2023-06-01 10:08:50	ga_ls8c_ard_3-2-1_099068_2023-06-01_final
2023-06-10 10:07:33	ga_ls8c_ard_3-2-1_098080_2023-06-10_final
2023-06-11 10:51:38	ga_ls8c_ard_3-2-1_105082_2023-06-11_final
2023-06-18 09:17:22	ga_ls8c_ard_3-2-1_090078_2023-06-17_final
2023-06-23 11:12:48	ga_ls8c_ard_3-2-1_109073_2023-06-23_final
2023-06-27 10:47:45	ga_ls8c_ard_3-2-1_105072_2023-06-27_final
2023-06-28 09:51:21	ga_ls8c_ard_3-2-1_096070_2023-06-28_final
2023-06-30 11:20:18	ga_ls8c_ard_3-2-1_110076_2023-06-30_final
2023-07-06 10:45:41	ga_ls8c_ard_3-2-1_104082_2023-07-06_final
2023-07-08 10:28:33	ga_ls8c_ard_3-2-1_102070_2023-07-08_final
2023-07-10 10:17:00	ga_ls8c_ard_3-2-1_100072_2023-07-10_final
2023-07-11 09:24:58	ga_ls8c_ard_3-2-1_091081_2023-07-10_final
2023-07-16 09:40:44	ga_ls8c_ard_3-2-1_094074_2023-07-16_final
2023-07-16 09:45:07	ga_ls8c_ard_3-2-1_094085_2023-07-16_final
2023-07-16 11:22:48	ga_ls8c_ard_3-2-1_110082_2023-07-16_final
2023-07-26 10:19:53	ga_ls8c_ard_3-2-1_100079_2023-07-26_final
2023-07-27 09:26:40	ga_ls8c_ard_3-2-1_091085_2023-07-26_final
2023-07-29 09:12:20	ga_ls8c_ard_3-2-1_089080_2023-07-28_final
2023-08-02 10:27:43	ga_ls8c_ard_3-2-1_101083_2023-08-02_final
2023-08-07 10:42:41	ga_ls8c_ard_3-2-1_104074_2023-08-07_final
2023-08-08 09:51:27	ga_ls8c_ard_3-2-1_095085_2023-08-08_final
2023-08-17 09:40:58	ga_ls8c_ard_3-2-1_094074_2023-08-17_final
2023-08-17 11:18:15	ga_ls8c_ard_3-2-1_110070_2023-08-17_final
2023-08-17 11:18:39	ga_ls8c_ard_3-2-1_110071_2023-08-17_final
2023-08-19 11:06:18	ga_ls8c_ard_3-2-1_108071_2023-08-19_final
2023-08-24 09:51:11	ga_ls8c_ard_3-2-1_095084_2023-08-24_final
2023-08-25 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-08-25_final
2023-08-29 10:10:08	ga_ls8c_ard_3-2-1_098085_2023-08-29_final
2023-09-02 09:41:01	ga_ls8c_ard_3-2-1_094074_2023-09-02_final
2023-09-02 11:20:42	ga_ls8c_ard_3-2-1_110076_2023-09-02_final
2023-09-05 11:51:34	ga_ls8c_ard_3-2-1_115076_2023-09-05_final
2023-09-07 10:01:55	ga_ls8c_ard_3-2-1_097080_2023-09-07_final
2023-09-11 11:11:45	ga_ls8c_ard_3-2-1_109069_2023-09-11_final
2023-09-13 11:01:48	ga_ls8c_ard_3-2-1_107075_2023-09-13_final
2023-11-04 10:34:51	ga_ls8c_ard_3-2-1_103069_2023-11-04_final
2023-11-07 09:33:13	ga_ls8c_ard_3-2-1_092085_2023-11-07_final
2023-11-09 10:55:19	ga_ls8c_ard_3-2-1_106074_2023-11-09_final
2023-11-10 10:04:04	ga_ls8c_ard_3-2-1_097085_2023-11-10_final
2023-11-10 11:41:22	ga_ls8c_ard_3-2-1_113081_2023-11-10_final
2023-11-15 10:21:05	ga_ls8c_ard_3-2-1_100081_2023-11-15_final
2023-11-17 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-17_nrt
2023-11-22 10:25:20	ga_ls8c_ard_3-2-1_101076_2023-11-22_nrt
2023-11-26 11:41:29	ga_ls8c_ard_3-2-1_113081_2023-11-26_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