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 11:29:25	ga_ls8c_ard_3-2-1_111081_2022-08-21_final
2022-08-22 10:30:12	ga_ls8c_ard_3-2-1_102072_2022-08-22_final
2022-08-23 11:12:40	ga_ls8c_ard_3-2-1_109070_2022-08-23_final
2022-08-25 11:01:30	ga_ls8c_ard_3-2-1_107073_2022-08-25_final
2022-08-26 10:06:41	ga_ls8c_ard_3-2-1_098075_2022-08-26_final
2022-09-11 10:06:21	ga_ls8c_ard_3-2-1_098074_2022-09-11_final
2022-09-14 10:37:40	ga_ls8c_ard_3-2-1_103075_2022-09-14_final
2022-09-15 11:21:44	ga_ls8c_ard_3-2-1_110077_2022-09-15_final
2022-09-19 09:19:20	ga_ls8c_ard_3-2-1_090080_2022-09-18_final
2022-09-21 10:44:16	ga_ls8c_ard_3-2-1_104076_2022-09-21_final
2022-09-22 11:25:32	ga_ls8c_ard_3-2-1_111071_2022-09-22_final
2022-09-23 10:32:43	ga_ls8c_ard_3-2-1_102078_2022-09-23_final
2022-09-27 10:07:11	ga_ls8c_ard_3-2-1_098076_2022-09-27_final
2022-09-29 11:36:06	ga_ls8c_ard_3-2-1_112082_2022-09-29_final
2022-09-30 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-09-30_final
2022-09-30 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-09-30_final
2022-10-03 09:30:29	ga_ls8c_ard_3-2-1_092077_2022-10-03_final
2022-10-08 09:48:35	ga_ls8c_ard_3-2-1_095076_2022-10-08_final
2022-10-08 11:27:04	ga_ls8c_ard_3-2-1_111075_2022-10-08_final
2022-10-09 10:34:13	ga_ls8c_ard_3-2-1_102082_2022-10-09_final
2022-10-11 10:19:02	ga_ls8c_ard_3-2-1_100075_2022-10-11_final
2022-10-16 10:39:10	ga_ls8c_ard_3-2-1_103079_2022-10-16_final
2022-10-18 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-10-18_final
2022-10-20 10:12:30	ga_ls8c_ard_3-2-1_099074_2022-10-20_final
2022-10-22 10:04:32	ga_ls8c_ard_3-2-1_097085_2022-10-22_final
2022-10-23 10:42:37	ga_ls8c_ard_3-2-1_104072_2022-10-23_final
2022-10-26 11:16:20	ga_ls8c_ard_3-2-1_109079_2022-10-26_final
2022-10-30 10:52:02	ga_ls8c_ard_3-2-1_105080_2022-10-30_final
2022-11-03 10:25:44	ga_ls8c_ard_3-2-1_101076_2022-11-03_final
2022-11-04 09:30:54	ga_ls8c_ard_3-2-1_092078_2022-11-04_final
2022-11-06 10:57:01	ga_ls8c_ard_3-2-1_106077_2022-11-06_final
2022-11-23 10:03:42	ga_ls8c_ard_3-2-1_097083_2022-11-23_final
2022-11-28 10:20:39	ga_ls8c_ard_3-2-1_100079_2022-11-28_final
2022-12-05 10:23:15	ga_ls8c_ard_3-2-1_101070_2022-12-05_final
2022-12-05 10:27:38	ga_ls8c_ard_3-2-1_101081_2022-12-05_final
2022-12-09 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-12-09_final
2022-12-09 11:40:11	ga_ls8c_ard_3-2-1_113077_2022-12-09_final
2022-12-11 11:29:48	ga_ls8c_ard_3-2-1_111082_2022-12-11_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-18 09:53:26	ga_ls8c_ard_3-2-1_096073_2022-12-18_final
2022-12-18 09:56:37	ga_ls8c_ard_3-2-1_096081_2022-12-18_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_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
2022-12-22 09:30:14	ga_ls8c_ard_3-2-1_092077_2022-12-22_final
2022-12-24 09:20:16	ga_ls8c_ard_3-2-1_090083_2022-12-23_final
2022-12-24 10:58:22	ga_ls8c_ard_3-2-1_106081_2022-12-24_final
2022-12-25 10:03:33	ga_ls8c_ard_3-2-1_097083_2022-12-25_final
2022-12-28 10:34:04	ga_ls8c_ard_3-2-1_102082_2022-12-28_final
2022-12-30 11:58:36	ga_ls8c_ard_3-2-1_116077_2022-12-30_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-07 09:30:40	ga_ls8c_ard_3-2-1_092078_2023-01-07_final
2023-01-09 09:20:17	ga_ls8c_ard_3-2-1_090083_2023-01-08_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-12 09:51:57	ga_ls8c_ard_3-2-1_095085_2023-01-12_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-19 09:56:04	ga_ls8c_ard_3-2-1_096080_2023-01-19_final
2023-01-23 09:30:12	ga_ls8c_ard_3-2-1_092077_2023-01-23_final
2023-02-01 09:26:03	ga_ls8c_ard_3-2-1_091082_2023-01-31_final
2023-02-07 10:26:15	ga_ls8c_ard_3-2-1_101078_2023-02-07_final
2023-02-13 09:48:17	ga_ls8c_ard_3-2-1_095076_2023-02-13_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-20 11:32:50	ga_ls8c_ard_3-2-1_112075_2023-02-20_final
2023-02-20 11:34:02	ga_ls8c_ard_3-2-1_112078_2023-02-20_final
2023-02-21 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-02-21_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-02-26 09:18:45	ga_ls8c_ard_3-2-1_090080_2023-02-25_final
2023-02-27 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-02-27_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_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
2023-03-13 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-03-13_final
2023-03-14 10:58:45	ga_ls8c_ard_3-2-1_106083_2023-03-14_final
2023-03-16 10:41:59	ga_ls8c_ard_3-2-1_104072_2023-03-16_final
2023-03-24 09:57:36	ga_ls8c_ard_3-2-1_096085_2023-03-24_final
2023-03-26 09:45:38	ga_ls8c_ard_3-2-1_094086_2023-03-26_final
2023-03-31 10:02:57	ga_ls8c_ard_3-2-1_097083_2023-03-31_final
2023-04-16 10:02:18	ga_ls8c_ard_3-2-1_097082_2023-04-16_final
2023-04-19 10:29:11	ga_ls8c_ard_3-2-1_102072_2023-04-19_final
2023-04-19 10:31:10	ga_ls8c_ard_3-2-1_102077_2023-04-19_final
2023-04-21 11:58:06	ga_ls8c_ard_3-2-1_116078_2023-04-21_final
2023-04-25 09:56:29	ga_ls8c_ard_3-2-1_096083_2023-04-25_final
2023-04-25 11:34:34	ga_ls8c_ard_3-2-1_112081_2023-04-25_final
2023-04-27 09:43:19	ga_ls8c_ard_3-2-1_094081_2023-04-27_final
2023-04-27 11:20:36	ga_ls8c_ard_3-2-1_110077_2023-04-27_final
2023-04-29 11:10:14	ga_ls8c_ard_3-2-1_108082_2023-04-29_final
2023-05-02 10:01:49	ga_ls8c_ard_3-2-1_097081_2023-05-02_final
2023-05-10 10:50:20	ga_ls8c_ard_3-2-1_105079_2023-05-10_final
2023-05-12 10:37:08	ga_ls8c_ard_3-2-1_103077_2023-05-12_final
2023-05-15 09:31:56	ga_ls8c_ard_3-2-1_092084_2023-05-15_final
2023-05-15 11:07:37	ga_ls8c_ard_3-2-1_108076_2023-05-15_final
2023-05-17 10:57:38	ga_ls8c_ard_3-2-1_106082_2023-05-17_final
2023-05-18 11:39:42	ga_ls8c_ard_3-2-1_113079_2023-05-18_final
2023-05-24 10:59:52	ga_ls8c_ard_3-2-1_107072_2023-05-24_final
2023-05-25 11:45:32	ga_ls8c_ard_3-2-1_114078_2023-05-25_final
2023-05-27 11:34:22	ga_ls8c_ard_3-2-1_112081_2023-05-27_final
2023-05-30 10:26:23	ga_ls8c_ard_3-2-1_101081_2023-05-30_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