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
2022-10-22 09:59:45	ga_ls8c_ard_3-2-1_097073_2022-10-22_final
2022-10-22 11:41:26	ga_ls8c_ard_3-2-1_113080_2022-10-22_final
2022-10-23 10:45:49	ga_ls8c_ard_3-2-1_104080_2022-10-23_final
2022-10-29 10:04:23	ga_ls8c_ard_3-2-1_098069_2022-10-29_final
2022-10-31 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-10-31_final
2022-11-03 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-11-03_final
2022-11-05 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-11-05_final
2022-11-06 09:20:32	ga_ls8c_ard_3-2-1_090083_2022-11-05_final
2022-11-07 09:59:24	ga_ls8c_ard_3-2-1_097072_2022-11-07_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-09 11:30:42	ga_ls8c_ard_3-2-1_111084_2022-11-09_final
2022-11-14 10:08:42	ga_ls8c_ard_3-2-1_098080_2022-11-14_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-17 10:35:58	ga_ls8c_ard_3-2-1_103071_2022-11-17_final
2022-11-17 10:37:58	ga_ls8c_ard_3-2-1_103076_2022-11-17_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-19 10:24:24	ga_ls8c_ard_3-2-1_101073_2022-11-19_final
2022-11-25 11:27:50	ga_ls8c_ard_3-2-1_111077_2022-11-25_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-11-30 11:45:35	ga_ls8c_ard_3-2-1_114075_2022-11-30_final
2022-12-01 10:51:34	ga_ls8c_ard_3-2-1_105079_2022-12-01_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-02 09:57:32	ga_ls8c_ard_3-2-1_096083_2022-12-02_final
2022-12-02 11:33:38	ga_ls8c_ard_3-2-1_112076_2022-12-02_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-06 11:06:06	ga_ls8c_ard_3-2-1_108069_2022-12-06_final
2022-12-07 10:13:16	ga_ls8c_ard_3-2-1_099076_2022-12-07_final
2022-12-09 11:39:47	ga_ls8c_ard_3-2-1_113076_2022-12-09_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-11 09:50:55	ga_ls8c_ard_3-2-1_095082_2022-12-11_final
2022-12-11 09:51:19	ga_ls8c_ard_3-2-1_095083_2022-12-11_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-16 10:08:37	ga_ls8c_ard_3-2-1_098080_2022-12-16_final
2022-12-16 11:45:54	ga_ls8c_ard_3-2-1_114076_2022-12-16_final
2022-12-16 11:46:42	ga_ls8c_ard_3-2-1_114078_2022-12-16_final
2022-12-20 11:21:55	ga_ls8c_ard_3-2-1_110078_2022-12-20_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-23 11:52:23	ga_ls8c_ard_3-2-1_115077_2022-12-23_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-27 09:50:48	ga_ls8c_ard_3-2-1_095082_2022-12-27_final
2022-12-27 11:29:41	ga_ls8c_ard_3-2-1_111082_2022-12-27_final
2022-12-29 09:36:27	ga_ls8c_ard_3-2-1_093077_2022-12-29_final
2022-12-29 11:16:56	ga_ls8c_ard_3-2-1_109081_2022-12-29_final
2022-12-30 10:21:43	ga_ls8c_ard_3-2-1_100082_2022-12-30_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-03 11:35:05	ga_ls8c_ard_3-2-1_112080_2023-01-03_final
2023-01-04 10:35:52	ga_ls8c_ard_3-2-1_103071_2023-01-04_final
2023-01-07 11:10:20	ga_ls8c_ard_3-2-1_108080_2023-01-07_final
2023-01-08 10:11:55	ga_ls8c_ard_3-2-1_099073_2023-01-08_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-09 09:23:05	ga_ls8c_ard_3-2-1_090090_2023-01-08_final
2023-01-10 09:59:57	ga_ls8c_ard_3-2-1_097074_2023-01-10_final
2023-01-10 11:39:38	ga_ls8c_ard_3-2-1_113076_2023-01-10_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-14 11:13:16	ga_ls8c_ard_3-2-1_109072_2023-01-14_final
2023-01-15 10:18:01	ga_ls8c_ard_3-2-1_100073_2023-01-15_final
2023-01-15 10:21:13	ga_ls8c_ard_3-2-1_100081_2023-01-15_final
2023-01-16 09:25:11	ga_ls8c_ard_3-2-1_091080_2023-01-15_final
2023-01-16 11:02:04	ga_ls8c_ard_3-2-1_107075_2023-01-16_final
2023-01-17 10:08:01	ga_ls8c_ard_3-2-1_098079_2023-01-17_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-21 09:41:44	ga_ls8c_ard_3-2-1_094075_2023-01-21_final
2023-01-23 09:30:12	ga_ls8c_ard_3-2-1_092077_2023-01-23_final
2023-01-23 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-01-23_final
2023-01-23 11:10:17	ga_ls8c_ard_3-2-1_108080_2023-01-23_final
2023-01-23 11:11:29	ga_ls8c_ard_3-2-1_108083_2023-01-23_final
2023-01-24 11:51:10	ga_ls8c_ard_3-2-1_115074_2023-01-24_final
2023-01-26 11:41:37	ga_ls8c_ard_3-2-1_113081_2023-01-26_final
2023-02-01 09:24:52	ga_ls8c_ard_3-2-1_091079_2023-01-31_final
2023-02-05 10:38:13	ga_ls8c_ard_3-2-1_103077_2023-02-05_final
2023-02-06 11:23:28	ga_ls8c_ard_3-2-1_110082_2023-02-06_final
2023-02-08 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-02-08_final
2023-02-08 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-02-08_final
2023-02-08 11:10:42	ga_ls8c_ard_3-2-1_108081_2023-02-08_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-10 09:19:02	ga_ls8c_ard_3-2-1_090080_2023-02-09_final
2023-02-11 10:02:16	ga_ls8c_ard_3-2-1_097080_2023-02-11_final
2023-02-11 11:41:33	ga_ls8c_ard_3-2-1_113081_2023-02-11_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-12 10:42:44	ga_ls8c_ard_3-2-1_104073_2023-02-12_final
2023-02-17 09:26:42	ga_ls8c_ard_3-2-1_091084_2023-02-16_final
2023-02-22 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-02-22_final
2023-02-22 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-02-22_final
2023-02-24 09:33:08	ga_ls8c_ard_3-2-1_092085_2023-02-24_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-03-03 09:38:53	ga_ls8c_ard_3-2-1_093084_2023-03-03_final
2023-03-03 11:16:34	ga_ls8c_ard_3-2-1_109081_2023-03-03_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_final
2023-03-05 09:28:54	ga_ls8c_ard_3-2-1_091090_2023-03-04_final
2023-03-05 11:01:00	ga_ls8c_ard_3-2-1_107073_2023-03-05_final
2023-03-07 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-03-06_final
2023-03-07 09:14:55	ga_ls8c_ard_3-2-1_089086_2023-03-06_final
2023-03-07 10:47:24	ga_ls8c_ard_3-2-1_105070_2023-03-07_final
2023-03-08 11:31:51	ga_ls8c_ard_3-2-1_112073_2023-03-08_final
2023-03-08 11:32:39	ga_ls8c_ard_3-2-1_112075_2023-03-08_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