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
2023-09-02 09:41:25	ga_ls8c_ard_3-2-1_094075_2023-09-02_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-03 10:25:52	ga_ls8c_ard_3-2-1_101078_2023-09-03_final
2023-09-05 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-09-05_final
2023-09-06 10:57:56	ga_ls8c_ard_3-2-1_106081_2023-09-06_final
2023-09-07 09:58:44	ga_ls8c_ard_3-2-1_097072_2023-09-07_final
2023-09-07 11:40:48	ga_ls8c_ard_3-2-1_113080_2023-09-07_final
2023-09-09 09:50:47	ga_ls8c_ard_3-2-1_095083_2023-09-09_final
2023-09-11 09:37:39	ga_ls8c_ard_3-2-1_093081_2023-09-11_final
2023-09-11 11:16:32	ga_ls8c_ard_3-2-1_109081_2023-09-11_final
2023-09-13 09:26:55	ga_ls8c_ard_3-2-1_091085_2023-09-12_final
2023-09-13 09:28:07	ga_ls8c_ard_3-2-1_091088_2023-09-12_final
2023-09-20 09:31:55	ga_ls8c_ard_3-2-1_092082_2023-09-20_final
2023-09-20 11:09:37	ga_ls8c_ard_3-2-1_108079_2023-09-20_final
2023-09-20 11:10:25	ga_ls8c_ard_3-2-1_108081_2023-09-20_final
2023-09-21 10:16:23	ga_ls8c_ard_3-2-1_099085_2023-09-21_final
2023-09-22 09:17:58	ga_ls8c_ard_3-2-1_090078_2023-09-21_final
2023-09-22 10:56:27	ga_ls8c_ard_3-2-1_106077_2023-09-22_final
2023-09-23 09:59:14	ga_ls8c_ard_3-2-1_097073_2023-09-23_final
2023-09-23 10:01:37	ga_ls8c_ard_3-2-1_097079_2023-09-23_final
2023-09-23 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-09-23_final
2023-09-23 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-09-23_final
2023-09-23 11:40:55	ga_ls8c_ard_3-2-1_113080_2023-09-23_final
2023-09-26 10:32:58	ga_ls8c_ard_3-2-1_102080_2023-09-26_final
2023-09-27 09:38:09	ga_ls8c_ard_3-2-1_093082_2023-09-27_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-09-27 11:15:02	ga_ls8c_ard_3-2-1_109077_2023-09-27_final
2023-09-27 11:17:26	ga_ls8c_ard_3-2-1_109083_2023-09-27_final
2023-09-28 10:20:13	ga_ls8c_ard_3-2-1_100079_2023-09-28_final
2023-09-29 09:25:24	ga_ls8c_ard_3-2-1_091081_2023-09-28_final
2023-09-30 10:04:16	ga_ls8c_ard_3-2-1_098070_2023-09-30_final
2023-09-30 10:05:28	ga_ls8c_ard_3-2-1_098073_2023-09-30_final
2023-09-30 11:44:45	ga_ls8c_ard_3-2-1_114074_2023-09-30_final
2023-09-30 11:45:09	ga_ls8c_ard_3-2-1_114075_2023-09-30_final
2023-10-01 09:13:02	ga_ls8c_ard_3-2-1_089081_2023-09-30_final
2023-10-02 09:53:06	ga_ls8c_ard_3-2-1_096073_2023-10-02_final
2023-10-02 09:56:42	ga_ls8c_ard_3-2-1_096082_2023-10-02_final
2023-10-02 11:34:23	ga_ls8c_ard_3-2-1_112079_2023-10-02_final
2023-10-03 10:35:10	ga_ls8c_ard_3-2-1_103070_2023-10-03_final
2023-10-03 10:37:58	ga_ls8c_ard_3-2-1_103077_2023-10-03_final
2023-10-04 09:41:32	ga_ls8c_ard_3-2-1_094075_2023-10-04_final
2023-10-06 09:29:34	ga_ls8c_ard_3-2-1_092076_2023-10-05_final
2023-10-07 10:12:03	ga_ls8c_ard_3-2-1_099074_2023-10-07_final
2023-10-07 11:51:44	ga_ls8c_ard_3-2-1_115076_2023-10-07_final
2023-10-10 10:41:47	ga_ls8c_ard_3-2-1_104071_2023-10-10_final
2023-10-12 10:31:02	ga_ls8c_ard_3-2-1_102075_2023-10-12_final
2023-10-12 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-10-12_final
2023-10-13 09:38:12	ga_ls8c_ard_3-2-1_093082_2023-10-13_final
2023-10-13 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-10-13_final
2023-10-13 11:16:41	ga_ls8c_ard_3-2-1_109081_2023-10-13_final
2023-10-14 10:20:16	ga_ls8c_ard_3-2-1_100079_2023-10-14_final
2023-10-15 09:25:02	ga_ls8c_ard_3-2-1_091080_2023-10-14_final
2023-10-16 10:03:54	ga_ls8c_ard_3-2-1_098069_2023-10-16_final
2023-10-16 10:05:30	ga_ls8c_ard_3-2-1_098073_2023-10-16_final
2023-10-16 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-10-16_final
2023-10-16 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-10-16_final
2023-10-17 10:50:21	ga_ls8c_ard_3-2-1_105077_2023-10-17_final
2023-10-20 11:23:38	ga_ls8c_ard_3-2-1_110083_2023-10-20_final
2023-10-21 10:24:50	ga_ls8c_ard_3-2-1_101075_2023-10-21_final
2023-10-22 09:31:13	ga_ls8c_ard_3-2-1_092080_2023-10-22_final
2023-10-22 11:05:43	ga_ls8c_ard_3-2-1_108069_2023-10-22_final
2023-10-24 10:58:58	ga_ls8c_ard_3-2-1_106083_2023-10-24_final
2023-10-25 11:41:50	ga_ls8c_ard_3-2-1_113082_2023-10-25_final
2023-10-27 09:51:24	ga_ls8c_ard_3-2-1_095084_2023-10-27_final
2023-10-27 11:27:05	ga_ls8c_ard_3-2-1_111076_2023-10-27_final
2023-10-29 09:39:51	ga_ls8c_ard_3-2-1_093086_2023-10-29_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-10-31 09:25:06	ga_ls8c_ard_3-2-1_091080_2023-10-30_final
2023-11-01 10:03:58	ga_ls8c_ard_3-2-1_098069_2023-11-01_final
2023-11-01 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-11-01_final
2023-11-01 10:05:34	ga_ls8c_ard_3-2-1_098073_2023-11-01_final
2023-11-03 09:53:11	ga_ls8c_ard_3-2-1_096073_2023-11-03_final
2023-11-03 09:53:35	ga_ls8c_ard_3-2-1_096074_2023-11-03_final
2023-11-03 11:35:16	ga_ls8c_ard_3-2-1_112081_2023-11-03_final
2023-11-04 10:37:39	ga_ls8c_ard_3-2-1_103076_2023-11-04_final
2023-11-06 10:25:40	ga_ls8c_ard_3-2-1_101077_2023-11-06_final
2023-11-07 11:05:43	ga_ls8c_ard_3-2-1_108069_2023-11-07_final
2023-11-07 11:09:42	ga_ls8c_ard_3-2-1_108079_2023-11-07_final
2023-11-07 11:10:06	ga_ls8c_ard_3-2-1_108080_2023-11-07_final
2023-11-09 10:58:06	ga_ls8c_ard_3-2-1_106081_2023-11-09_final
2023-11-10 10:02:04	ga_ls8c_ard_3-2-1_097080_2023-11-10_final
2023-11-10 10:02:52	ga_ls8c_ard_3-2-1_097082_2023-11-10_final
2023-11-11 10:43:45	ga_ls8c_ard_3-2-1_104076_2023-11-11_final
2023-11-11 10:45:21	ga_ls8c_ard_3-2-1_104080_2023-11-11_final
2023-11-13 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-11-13_final
2023-11-14 09:36:37	ga_ls8c_ard_3-2-1_093078_2023-11-14_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-15 10:18:42	ga_ls8c_ard_3-2-1_100075_2023-11-15_final
2023-11-15 10:21:29	ga_ls8c_ard_3-2-1_100082_2023-11-15_final
2023-11-16 09:27:28	ga_ls8c_ard_3-2-1_091086_2023-11-15_final
2023-11-17 10:04:21	ga_ls8c_ard_3-2-1_098070_2023-11-17_final
2023-11-17 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-11-17_final
2023-11-17 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-11-17_final
2023-11-19 09:52:25	ga_ls8c_ard_3-2-1_096071_2023-11-19_final
2023-11-20 10:37:41	ga_ls8c_ard_3-2-1_103076_2023-11-20_final
2023-11-22 10:23:44	ga_ls8c_ard_3-2-1_101072_2023-11-22_final
2023-11-22 10:24:56	ga_ls8c_ard_3-2-1_101075_2023-11-22_final
2023-11-22 10:27:19	ga_ls8c_ard_3-2-1_101081_2023-11-22_final
2023-11-23 11:10:11	ga_ls8c_ard_3-2-1_108080_2023-11-23_final
2023-11-23 11:10:35	ga_ls8c_ard_3-2-1_108081_2023-11-23_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