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
2022-07-27 09:55:45	ga_ls8c_ard_3-2-1_096079_2022-07-27_final
2022-08-03 10:00:48	ga_ls8c_ard_3-2-1_097076_2022-08-03_final
2022-09-04 10:03:17	ga_ls8c_ard_3-2-1_097082_2022-09-04_final
2022-09-06 09:50:09	ga_ls8c_ard_3-2-1_095080_2022-09-06_final
2022-09-13 09:57:36	ga_ls8c_ard_3-2-1_096083_2022-09-13_final
2022-09-26 09:25:08	ga_ls8c_ard_3-2-1_091079_2022-09-25_final
2022-09-26 09:25:55	ga_ls8c_ard_3-2-1_091081_2022-09-25_final
2022-09-26 11:01:37	ga_ls8c_ard_3-2-1_107073_2022-09-26_final
2022-10-08 11:27:04	ga_ls8c_ard_3-2-1_111075_2022-10-08_final
2022-10-15 09:53:29	ga_ls8c_ard_3-2-1_096073_2022-10-15_final
2022-10-19 11:06:07	ga_ls8c_ard_3-2-1_108069_2022-10-19_final
2022-10-19 11:11:18	ga_ls8c_ard_3-2-1_108082_2022-10-19_final
2022-10-29 10:05:59	ga_ls8c_ard_3-2-1_098073_2022-10-29_final
2022-10-30 10:49:15	ga_ls8c_ard_3-2-1_105073_2022-10-30_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-10-31 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-10-31_final
2022-11-01 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-11-01_final
2022-11-04 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-11-04_final
2022-11-05 11:53:50	ga_ls8c_ard_3-2-1_115080_2022-11-05_final
2022-11-06 10:57:01	ga_ls8c_ard_3-2-1_106077_2022-11-06_final
2022-11-13 11:03:56	ga_ls8c_ard_3-2-1_107079_2022-11-13_final
2022-11-16 09:55:07	ga_ls8c_ard_3-2-1_096077_2022-11-16_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-25 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-11-25_final
2022-11-29 09:26:14	ga_ls8c_ard_3-2-1_091082_2022-11-28_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-08 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-12-07_final
2022-12-12 10:32:11	ga_ls8c_ard_3-2-1_102077_2022-12-12_final
2022-12-18 09:57:25	ga_ls8c_ard_3-2-1_096083_2022-12-18_final
2022-12-19 10:35:53	ga_ls8c_ard_3-2-1_103071_2022-12-19_final
2022-12-28 10:30:04	ga_ls8c_ard_3-2-1_102072_2022-12-28_final
2022-12-28 10:31:16	ga_ls8c_ard_3-2-1_102075_2022-12-28_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2022-12-31 11:04:34	ga_ls8c_ard_3-2-1_107081_2022-12-31_final
2023-01-11 10:45:35	ga_ls8c_ard_3-2-1_104080_2023-01-11_final
2023-01-13 10:31:13	ga_ls8c_ard_3-2-1_102075_2023-01-13_final
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-01-24 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-01-24_final
2023-02-10 10:57:31	ga_ls8c_ard_3-2-1_106079_2023-02-10_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-16 10:21:09	ga_ls8c_ard_3-2-1_100081_2023-02-16_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-17 11:03:36	ga_ls8c_ard_3-2-1_107079_2023-02-17_final
2023-02-25 10:12:22	ga_ls8c_ard_3-2-1_099075_2023-02-25_final
2023-03-01 11:27:44	ga_ls8c_ard_3-2-1_111078_2023-03-01_final
2023-03-04 10:20:08	ga_ls8c_ard_3-2-1_100079_2023-03-04_final
2023-03-10 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-03-10_final
2023-03-12 11:06:43	ga_ls8c_ard_3-2-1_108072_2023-03-12_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-24 11:32:06	ga_ls8c_ard_3-2-1_112074_2023-03-24_final
2023-03-26 09:45:38	ga_ls8c_ard_3-2-1_094086_2023-03-26_final
2023-05-06 11:14:20	ga_ls8c_ard_3-2-1_109077_2023-05-06_final
2023-05-10 10:51:56	ga_ls8c_ard_3-2-1_105083_2023-05-10_final
2023-05-15 09:31:56	ga_ls8c_ard_3-2-1_092084_2023-05-15_final
2023-05-16 10:11:35	ga_ls8c_ard_3-2-1_099075_2023-05-16_final
2023-05-20 09:48:28	ga_ls8c_ard_3-2-1_095079_2023-05-20_final
2023-05-21 10:31:45	ga_ls8c_ard_3-2-1_102079_2023-05-21_final
2023-05-22 11:15:01	ga_ls8c_ard_3-2-1_109079_2023-05-22_final
2023-05-26 10:49:31	ga_ls8c_ard_3-2-1_105077_2023-05-26_final
2023-05-27 11:31:11	ga_ls8c_ard_3-2-1_112073_2023-05-27_final
2023-05-31 09:30:46	ga_ls8c_ard_3-2-1_092081_2023-05-31_final
2023-06-11 10:47:38	ga_ls8c_ard_3-2-1_105072_2023-06-11_final
2023-06-12 09:56:01	ga_ls8c_ard_3-2-1_096082_2023-06-12_final
2023-06-16 09:31:19	ga_ls8c_ard_3-2-1_092082_2023-06-16_final
2023-06-18 10:55:51	ga_ls8c_ard_3-2-1_106077_2023-06-18_final
2023-06-23 11:14:48	ga_ls8c_ard_3-2-1_109078_2023-06-23_final
2023-06-30 09:43:24	ga_ls8c_ard_3-2-1_094081_2023-06-30_final
2023-07-06 10:40:29	ga_ls8c_ard_3-2-1_104069_2023-07-06_final
2023-07-07 09:46:28	ga_ls8c_ard_3-2-1_095073_2023-07-07_final
2023-07-09 11:15:24	ga_ls8c_ard_3-2-1_109079_2023-07-09_final
2023-07-11 11:02:39	ga_ls8c_ard_3-2-1_107078_2023-07-11_final
2023-07-19 10:12:01	ga_ls8c_ard_3-2-1_099075_2023-07-19_final
2023-07-20 10:56:28	ga_ls8c_ard_3-2-1_106078_2023-07-20_final
2023-07-22 10:40:33	ga_ls8c_ard_3-2-1_104069_2023-07-22_final
2023-08-02 10:24:32	ga_ls8c_ard_3-2-1_101075_2023-08-02_final
2023-08-05 10:56:38	ga_ls8c_ard_3-2-1_106078_2023-08-05_final
2023-08-07 10:40:41	ga_ls8c_ard_3-2-1_104069_2023-08-07_final
2023-08-20 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-08-20_final
2023-08-21 10:56:21	ga_ls8c_ard_3-2-1_106077_2023-08-21_final
2023-08-21 10:56:45	ga_ls8c_ard_3-2-1_106078_2023-08-21_final
2023-09-02 09:41:49	ga_ls8c_ard_3-2-1_094076_2023-09-02_final
2023-09-07 10:00:19	ga_ls8c_ard_3-2-1_097076_2023-09-07_final
2023-09-16 09:53:27	ga_ls8c_ard_3-2-1_096074_2023-09-16_final
2023-09-20 11:08:25	ga_ls8c_ard_3-2-1_108076_2023-09-20_final
2023-09-22 10:56:51	ga_ls8c_ard_3-2-1_106078_2023-09-22_final
2023-09-27 09:37:45	ga_ls8c_ard_3-2-1_093081_2023-09-27_final
2023-10-03 10:35:34	ga_ls8c_ard_3-2-1_103071_2023-10-03_final
2023-10-07 10:15:14	ga_ls8c_ard_3-2-1_099082_2023-10-07_final
2023-10-08 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-10-07_final
2023-10-25 11:40:14	ga_ls8c_ard_3-2-1_113078_2023-10-25_final
2023-10-27 09:51:24	ga_ls8c_ard_3-2-1_095084_2023-10-27_final
2023-10-28 10:29:53	ga_ls8c_ard_3-2-1_102072_2023-10-28_final
2023-10-30 10:20:19	ga_ls8c_ard_3-2-1_100079_2023-10-30_final
2023-10-31 11:02:47	ga_ls8c_ard_3-2-1_107077_2023-10-31_final
2023-11-02 10:47:37	ga_ls8c_ard_3-2-1_105070_2023-11-02_final
2023-11-04 10:39:14	ga_ls8c_ard_3-2-1_103080_2023-11-04_final
2023-11-09 10:56:31	ga_ls8c_ard_3-2-1_106077_2023-11-09_final
2023-11-09 10:58:30	ga_ls8c_ard_3-2-1_106082_2023-11-09_final
2023-11-25 10:56:38	ga_ls8c_ard_3-2-1_106077_2023-11-25_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