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
2023-02-02 11:45:01	ga_ls8c_ard_3-2-1_114074_2023-02-02_final
2023-02-02 11:46:12	ga_ls8c_ard_3-2-1_114077_2023-02-02_final
2023-03-12 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-03-12_final
2023-03-12 11:05:32	ga_ls8c_ard_3-2-1_108069_2023-03-12_final
2023-03-14 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-03-14_final
2023-03-19 09:38:45	ga_ls8c_ard_3-2-1_093084_2023-03-19_final
2023-03-19 11:12:50	ga_ls8c_ard_3-2-1_109072_2023-03-19_final
2023-03-20 10:18:00	ga_ls8c_ard_3-2-1_100074_2023-03-20_final
2023-03-21 11:00:27	ga_ls8c_ard_3-2-1_107072_2023-03-21_final
2023-03-22 10:08:00	ga_ls8c_ard_3-2-1_098080_2023-03-22_final
2023-03-24 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-03-24_final
2023-03-25 10:36:29	ga_ls8c_ard_3-2-1_103074_2023-03-25_final
2023-03-27 10:25:42	ga_ls8c_ard_3-2-1_101078_2023-03-27_final
2023-03-30 10:54:11	ga_ls8c_ard_3-2-1_106072_2023-03-30_final
2023-04-03 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-04-03_final
2023-04-04 11:11:51	ga_ls8c_ard_3-2-1_109070_2023-04-04_final
2023-04-06 09:24:09	ga_ls8c_ard_3-2-1_091079_2023-04-05_final
2023-04-07 11:45:53	ga_ls8c_ard_3-2-1_114078_2023-04-07_final
2023-04-11 11:22:16	ga_ls8c_ard_3-2-1_110081_2023-04-11_final
2023-04-14 11:51:10	ga_ls8c_ard_3-2-1_115076_2023-04-14_final
2023-04-15 10:57:08	ga_ls8c_ard_3-2-1_106080_2023-04-15_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-05-07 10:20:41	ga_ls8c_ard_3-2-1_100082_2023-05-07_final
2023-05-08 11:03:32	ga_ls8c_ard_3-2-1_107081_2023-05-08_final
2023-05-17 09:17:09	ga_ls8c_ard_3-2-1_090078_2023-05-16_final
2023-05-18 09:57:13	ga_ls8c_ard_3-2-1_097070_2023-05-18_final
2023-05-22 09:34:08	ga_ls8c_ard_3-2-1_093074_2023-05-22_final
2023-05-26 09:10:38	ga_ls8c_ard_3-2-1_089077_2023-05-25_final
2023-05-26 10:46:43	ga_ls8c_ard_3-2-1_105070_2023-05-26_final
2023-06-03 09:58:53	ga_ls8c_ard_3-2-1_097074_2023-06-03_final
2023-06-06 10:31:02	ga_ls8c_ard_3-2-1_102077_2023-06-06_final
2023-06-07 11:16:18	ga_ls8c_ard_3-2-1_109082_2023-06-07_final
2023-06-15 10:24:08	ga_ls8c_ard_3-2-1_101075_2023-06-15_final
2023-06-16 09:30:31	ga_ls8c_ard_3-2-1_092080_2023-06-16_final
2023-06-16 09:32:07	ga_ls8c_ard_3-2-1_092084_2023-06-16_final
2023-06-19 09:59:02	ga_ls8c_ard_3-2-1_097074_2023-06-19_final
2023-06-19 10:00:38	ga_ls8c_ard_3-2-1_097078_2023-06-19_final
2023-06-19 10:02:37	ga_ls8c_ard_3-2-1_097083_2023-06-19_final
2023-06-21 09:48:40	ga_ls8c_ard_3-2-1_095079_2023-06-21_final
2023-06-23 09:33:31	ga_ls8c_ard_3-2-1_093072_2023-06-23_final
2023-06-23 11:11:36	ga_ls8c_ard_3-2-1_109070_2023-06-23_final
2023-06-23 11:16:23	ga_ls8c_ard_3-2-1_109082_2023-06-23_final
2023-06-25 09:23:59	ga_ls8c_ard_3-2-1_091079_2023-06-24_final
2023-06-25 09:24:23	ga_ls8c_ard_3-2-1_091080_2023-06-24_final
2023-06-30 09:40:13	ga_ls8c_ard_3-2-1_094073_2023-06-30_final
2023-07-05 10:03:36	ga_ls8c_ard_3-2-1_097085_2023-07-05_final
2023-07-07 09:50:04	ga_ls8c_ard_3-2-1_095082_2023-07-07_final
2023-07-11 11:00:40	ga_ls8c_ard_3-2-1_107073_2023-07-11_final
2023-07-16 11:23:12	ga_ls8c_ard_3-2-1_110083_2023-07-16_final
2023-07-19 11:51:18	ga_ls8c_ard_3-2-1_115076_2023-07-19_final
2023-07-23 11:28:37	ga_ls8c_ard_3-2-1_111081_2023-07-23_final
2023-07-30 09:56:00	ga_ls8c_ard_3-2-1_096081_2023-07-30_final
2023-08-10 09:37:53	ga_ls8c_ard_3-2-1_093082_2023-08-10_final
2023-08-10 09:38:41	ga_ls8c_ard_3-2-1_093084_2023-08-10_final
2023-08-28 09:25:17	ga_ls8c_ard_3-2-1_091081_2023-08-27_final
2023-08-31 09:56:58	ga_ls8c_ard_3-2-1_096083_2023-08-31_final
2023-08-31 11:35:51	ga_ls8c_ard_3-2-1_112083_2023-08-31_final
2023-09-02 09:46:12	ga_ls8c_ard_3-2-1_094087_2023-09-02_final
2023-09-02 11:17:54	ga_ls8c_ard_3-2-1_110069_2023-09-02_final
2023-09-07 09:59:07	ga_ls8c_ard_3-2-1_097073_2023-09-07_final
2023-09-07 10:01:07	ga_ls8c_ard_3-2-1_097078_2023-09-07_final
2023-09-07 11:40:48	ga_ls8c_ard_3-2-1_113080_2023-09-07_final
2023-09-09 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-09-09_final
2023-09-13 09:25:19	ga_ls8c_ard_3-2-1_091081_2023-09-12_final
2023-09-19 10:23:09	ga_ls8c_ard_3-2-1_101071_2023-09-19_final
2023-09-22 09:18:22	ga_ls8c_ard_3-2-1_090079_2023-09-21_final
2023-09-30 11:45:57	ga_ls8c_ard_3-2-1_114077_2023-09-30_final
2023-10-01 09:13:50	ga_ls8c_ard_3-2-1_089083_2023-09-30_final
2023-10-02 09:53:30	ga_ls8c_ard_3-2-1_096074_2023-10-02_final
2023-10-05 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-10-05_final
2023-10-07 10:15:38	ga_ls8c_ard_3-2-1_099083_2023-10-07_final
2023-10-11 09:47:46	ga_ls8c_ard_3-2-1_095075_2023-10-11_final
2023-10-12 10:30:38	ga_ls8c_ard_3-2-1_102074_2023-10-12_final
2023-10-16 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-10-16_final
2023-10-19 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-10-19_final
2023-10-23 10:11:42	ga_ls8c_ard_3-2-1_099073_2023-10-23_final
2023-10-23 11:52:11	ga_ls8c_ard_3-2-1_115077_2023-10-23_final
2023-10-25 11:41:26	ga_ls8c_ard_3-2-1_113081_2023-10-25_final
2023-10-28 10:30:41	ga_ls8c_ard_3-2-1_102074_2023-10-28_final
2023-10-28 10:33:04	ga_ls8c_ard_3-2-1_102080_2023-10-28_final
2023-10-29 09:39:51	ga_ls8c_ard_3-2-1_093086_2023-10-29_final
2023-10-31 11:03:59	ga_ls8c_ard_3-2-1_107080_2023-10-31_final
2023-10-31 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-10-31_final
2023-11-01 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-01_final
2023-11-04 10:35:15	ga_ls8c_ard_3-2-1_103070_2023-11-04_final
2023-11-06 10:25:16	ga_ls8c_ard_3-2-1_101076_2023-11-06_final
2023-11-08 10:12:52	ga_ls8c_ard_3-2-1_099076_2023-11-08_final
2023-11-08 10:16:28	ga_ls8c_ard_3-2-1_099085_2023-11-08_final
2023-11-10 10:01:17	ga_ls8c_ard_3-2-1_097078_2023-11-10_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-11 10:40:34	ga_ls8c_ard_3-2-1_104068_2023-11-11_final
2023-11-12 11:26:38	ga_ls8c_ard_3-2-1_111075_2023-11-12_final
2023-11-15 10:17:54	ga_ls8c_ard_3-2-1_100073_2023-11-15_final
2023-11-16 11:02:46	ga_ls8c_ard_3-2-1_107077_2023-11-16_final
2023-11-19 11:32:54	ga_ls8c_ard_3-2-1_112075_2023-11-19_final
2023-11-19 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-11-19_final
2023-11-22 10:24:56	ga_ls8c_ard_3-2-1_101075_2023-11-22_final
2023-11-26 10:02:12	ga_ls8c_ard_3-2-1_097080_2023-11-26_final
2023-11-30 11:17:32	ga_ls8c_ard_3-2-1_109083_2023-11-30_nrt
2023-12-05 11:35:35	ga_ls8c_ard_3-2-1_112082_2023-12-05_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