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
2022-07-03 10:43:04	ga_ls8c_ard_3-2-1_104074_2022-07-03_final
2022-07-10 10:48:03	ga_ls8c_ard_3-2-1_105071_2022-07-10_final
2022-07-13 11:22:55	ga_ls8c_ard_3-2-1_110081_2022-07-13_final
2022-07-14 10:25:18	ga_ls8c_ard_3-2-1_101076_2022-07-14_final
2022-07-15 09:30:04	ga_ls8c_ard_3-2-1_092077_2022-07-15_final
2022-07-15 11:06:58	ga_ls8c_ard_3-2-1_108072_2022-07-15_final
2022-07-25 11:47:46	ga_ls8c_ard_3-2-1_114081_2022-07-25_final
2022-07-26 10:48:10	ga_ls8c_ard_3-2-1_105071_2022-07-26_final
2022-07-26 10:48:34	ga_ls8c_ard_3-2-1_105072_2022-07-26_final
2022-07-26 10:51:22	ga_ls8c_ard_3-2-1_105079_2022-07-26_final
2022-07-28 10:35:50	ga_ls8c_ard_3-2-1_103071_2022-07-28_final
2022-07-31 11:09:09	ga_ls8c_ard_3-2-1_108077_2022-07-31_final
2022-08-03 11:39:41	ga_ls8c_ard_3-2-1_113076_2022-08-03_final
2022-08-04 10:41:41	ga_ls8c_ard_3-2-1_104070_2022-08-04_final
2022-08-05 11:28:56	ga_ls8c_ard_3-2-1_111080_2022-08-05_final
2022-08-05 11:29:44	ga_ls8c_ard_3-2-1_111082_2022-08-05_final
2022-08-09 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-08-08_final
2022-08-12 09:56:17	ga_ls8c_ard_3-2-1_096080_2022-08-12_final
2022-08-29 10:39:34	ga_ls8c_ard_3-2-1_103080_2022-08-29_final
2022-09-01 09:33:11	ga_ls8c_ard_3-2-1_092084_2022-09-01_final
2022-09-01 11:09:16	ga_ls8c_ard_3-2-1_108077_2022-09-01_final
2022-09-04 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-09-04_final
2022-09-05 10:43:46	ga_ls8c_ard_3-2-1_104075_2022-09-05_final
2022-09-08 11:12:43	ga_ls8c_ard_3-2-1_109070_2022-09-08_final
2022-09-10 09:24:40	ga_ls8c_ard_3-2-1_091078_2022-09-09_final
2022-09-11 11:46:50	ga_ls8c_ard_3-2-1_114078_2022-09-11_final
2022-09-11 11:48:02	ga_ls8c_ard_3-2-1_114081_2022-09-11_final
2022-09-23 10:30:19	ga_ls8c_ard_3-2-1_102072_2022-09-23_final
2022-09-26 09:24:44	ga_ls8c_ard_3-2-1_091078_2022-09-25_final
2022-09-26 11:03:13	ga_ls8c_ard_3-2-1_107077_2022-09-26_final
2022-09-29 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-09-29_final
2022-09-30 10:38:53	ga_ls8c_ard_3-2-1_103078_2022-09-30_final
2022-10-11 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-10-11_final
2022-10-17 09:41:57	ga_ls8c_ard_3-2-1_094075_2022-10-17_final
2022-10-24 09:49:48	ga_ls8c_ard_3-2-1_095079_2022-10-24_final
2022-10-24 11:29:53	ga_ls8c_ard_3-2-1_111082_2022-10-24_final
2022-10-26 11:17:08	ga_ls8c_ard_3-2-1_109081_2022-10-26_final
2022-10-30 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-10-30_final
2022-10-31 09:54:01	ga_ls8c_ard_3-2-1_096074_2022-10-31_final
2022-11-09 09:50:13	ga_ls8c_ard_3-2-1_095080_2022-11-09_final
2022-11-09 09:50:37	ga_ls8c_ard_3-2-1_095081_2022-11-09_final
2022-11-11 09:36:38	ga_ls8c_ard_3-2-1_093077_2022-11-11_final
2022-11-11 09:37:02	ga_ls8c_ard_3-2-1_093078_2022-11-11_final
2022-11-11 11:16:43	ga_ls8c_ard_3-2-1_109080_2022-11-11_final
2022-11-14 10:05:30	ga_ls8c_ard_3-2-1_098072_2022-11-14_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-20 09:35:34	ga_ls8c_ard_3-2-1_092090_2022-11-20_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2022-11-27 09:37:24	ga_ls8c_ard_3-2-1_093079_2022-11-27_final
2022-11-28 10:21:03	ga_ls8c_ard_3-2-1_100080_2022-11-28_final
2022-12-02 09:55:32	ga_ls8c_ard_3-2-1_096078_2022-12-02_final
2022-12-03 10:36:00	ga_ls8c_ard_3-2-1_103071_2022-12-03_final
2022-12-10 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-12-10_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-13 09:37:21	ga_ls8c_ard_3-2-1_093079_2022-12-13_final
2022-12-20 09:45:02	ga_ls8c_ard_3-2-1_094083_2022-12-20_final
2022-12-21 10:25:29	ga_ls8c_ard_3-2-1_101076_2022-12-21_final
2022-12-24 09:20:16	ga_ls8c_ard_3-2-1_090083_2022-12-23_final
2022-12-24 10:56:46	ga_ls8c_ard_3-2-1_106077_2022-12-24_final
2022-12-24 10:57:34	ga_ls8c_ard_3-2-1_106079_2022-12-24_final
2022-12-27 11:29:41	ga_ls8c_ard_3-2-1_111082_2022-12-27_final
2022-12-28 10:31:16	ga_ls8c_ard_3-2-1_102075_2022-12-28_final
2022-12-29 09:37:15	ga_ls8c_ard_3-2-1_093079_2022-12-29_final
2022-12-29 11:16:08	ga_ls8c_ard_3-2-1_109079_2022-12-29_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-05 09:43:26	ga_ls8c_ard_3-2-1_094079_2023-01-05_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-11 10:45:35	ga_ls8c_ard_3-2-1_104080_2023-01-11_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-20 10:37:45	ga_ls8c_ard_3-2-1_103076_2023-01-20_final
2023-01-23 09:31:00	ga_ls8c_ard_3-2-1_092079_2023-01-23_final
2023-01-30 11:16:30	ga_ls8c_ard_3-2-1_109080_2023-01-30_final
2023-02-07 10:26:15	ga_ls8c_ard_3-2-1_101078_2023-02-07_final
2023-02-24 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-02-23_final
2023-02-26 10:57:14	ga_ls8c_ard_3-2-1_106079_2023-02-26_final
2023-03-01 11:26:32	ga_ls8c_ard_3-2-1_111075_2023-03-01_final
2023-03-03 11:14:58	ga_ls8c_ard_3-2-1_109077_2023-03-03_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-04 10:20:32	ga_ls8c_ard_3-2-1_100080_2023-03-04_final
2023-03-08 11:32:39	ga_ls8c_ard_3-2-1_112075_2023-03-08_final
2023-03-10 11:22:17	ga_ls8c_ard_3-2-1_110080_2023-03-10_final
2023-03-16 10:45:34	ga_ls8c_ard_3-2-1_104081_2023-03-16_final
2023-03-26 11:21:44	ga_ls8c_ard_3-2-1_110079_2023-03-26_final
2023-03-30 09:19:42	ga_ls8c_ard_3-2-1_090083_2023-03-29_final
2023-03-31 10:02:57	ga_ls8c_ard_3-2-1_097083_2023-03-31_final
2023-04-01 10:41:24	ga_ls8c_ard_3-2-1_104071_2023-04-01_final
2023-04-02 11:28:14	ga_ls8c_ard_3-2-1_111080_2023-04-02_final
2023-04-07 10:06:12	ga_ls8c_ard_3-2-1_098076_2023-04-07_final
2023-04-09 09:52:11	ga_ls8c_ard_3-2-1_096072_2023-04-09_final
2023-04-09 11:33:28	ga_ls8c_ard_3-2-1_112078_2023-04-09_final
2023-04-15 10:57:32	ga_ls8c_ard_3-2-1_106081_2023-04-15_final
2023-04-17 10:42:22	ga_ls8c_ard_3-2-1_104074_2023-04-17_final
2023-04-20 11:11:14	ga_ls8c_ard_3-2-1_109069_2023-04-20_final
2023-04-24 10:50:55	ga_ls8c_ard_3-2-1_105080_2023-04-24_final
2023-04-25 09:54:30	ga_ls8c_ard_3-2-1_096078_2023-04-25_final
2023-04-25 09:55:41	ga_ls8c_ard_3-2-1_096081_2023-04-25_final
2023-05-03 10:42:17	ga_ls8c_ard_3-2-1_104074_2023-05-03_final
2023-05-06 09:37:03	ga_ls8c_ard_3-2-1_093081_2023-05-06_final
2023-05-10 10:46:45	ga_ls8c_ard_3-2-1_105070_2023-05-10_final
2023-05-12 10:37:56	ga_ls8c_ard_3-2-1_103079_2023-05-12_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