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
2022-03-29 10:44:10	ga_ls8c_ard_3-2-1_104078_2022-03-29_final
2022-03-30 09:46:32	ga_ls8c_ard_3-2-1_095073_2022-03-30_final
2022-03-30 09:48:08	ga_ls8c_ard_3-2-1_095077_2022-03-30_final
2022-03-30 11:26:13	ga_ls8c_ard_3-2-1_111075_2022-03-30_final
2022-03-30 11:27:01	ga_ls8c_ard_3-2-1_111077_2022-03-30_final
2022-03-31 10:28:36	ga_ls8c_ard_3-2-1_102070_2022-03-31_final
2022-04-01 09:36:10	ga_ls8c_ard_3-2-1_093078_2022-04-01_final
2022-04-02 10:17:26	ga_ls8c_ard_3-2-1_100073_2022-04-02_final
2022-04-02 10:17:50	ga_ls8c_ard_3-2-1_100074_2022-04-02_final
2022-04-02 10:21:26	ga_ls8c_ard_3-2-1_100083_2022-04-02_final
2022-04-02 11:57:55	ga_ls8c_ard_3-2-1_116077_2022-04-02_final
2022-04-03 09:23:49	ga_ls8c_ard_3-2-1_091078_2022-04-02_final
2022-04-03 11:00:42	ga_ls8c_ard_3-2-1_107073_2022-04-03_final
2022-04-05 10:49:10	ga_ls8c_ard_3-2-1_105075_2022-04-05_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-07 10:38:25	ga_ls8c_ard_3-2-1_103079_2022-04-07_final
2022-04-08 09:43:12	ga_ls8c_ard_3-2-1_094080_2022-04-08_final
2022-04-08 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-08_final
2022-04-09 10:22:53	ga_ls8c_ard_3-2-1_101071_2022-04-09_final
2022-04-10 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-04-10_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-12 09:20:55	ga_ls8c_ard_3-2-1_090086_2022-04-11_final
2022-04-12 10:52:37	ga_ls8c_ard_3-2-1_106068_2022-04-12_final
2022-04-12 10:54:37	ga_ls8c_ard_3-2-1_106073_2022-04-12_final
2022-04-12 10:56:36	ga_ls8c_ard_3-2-1_106078_2022-04-12_final
2022-04-13 10:00:11	ga_ls8c_ard_3-2-1_097076_2022-04-13_final
2022-04-13 10:00:59	ga_ls8c_ard_3-2-1_097078_2022-04-13_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-13 11:38:41	ga_ls8c_ard_3-2-1_113075_2022-04-13_final
2022-04-14 10:40:40	ga_ls8c_ard_3-2-1_104069_2022-04-14_final
2022-04-14 10:42:40	ga_ls8c_ard_3-2-1_104074_2022-04-14_final
2022-04-14 10:43:04	ga_ls8c_ard_3-2-1_104075_2022-04-14_final
2022-04-14 10:45:51	ga_ls8c_ard_3-2-1_104082_2022-04-14_final
2022-04-15 09:46:39	ga_ls8c_ard_3-2-1_095073_2022-04-15_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-19 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-04-19_final
2022-04-21 09:15:56	ga_ls8c_ard_3-2-1_089089_2022-04-20_final
2022-04-21 10:46:50	ga_ls8c_ard_3-2-1_105069_2022-04-21_final
2022-04-21 10:49:13	ga_ls8c_ard_3-2-1_105075_2022-04-21_final
2022-04-22 11:33:16	ga_ls8c_ard_3-2-1_112077_2022-04-22_final
2022-04-22 11:33:40	ga_ls8c_ard_3-2-1_112078_2022-04-22_final
2022-04-22 11:35:40	ga_ls8c_ard_3-2-1_112083_2022-04-22_final
2022-04-23 10:37:39	ga_ls8c_ard_3-2-1_103077_2022-04-23_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-04-24 09:43:13	ga_ls8c_ard_3-2-1_094080_2022-04-24_final
2022-04-28 10:53:45	ga_ls8c_ard_3-2-1_106071_2022-04-28_final
2022-04-29 10:00:07	ga_ls8c_ard_3-2-1_097076_2022-04-29_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-04-30 10:40:12	ga_ls8c_ard_3-2-1_104068_2022-04-30_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-01 11:27:28	ga_ls8c_ard_3-2-1_111078_2022-05-01_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-03 11:14:20	ga_ls8c_ard_3-2-1_109076_2022-05-03_final
2022-05-05 11:01:36	ga_ls8c_ard_3-2-1_107075_2022-05-05_final
2022-05-06 10:05:59	ga_ls8c_ard_3-2-1_098075_2022-05-06_final
2022-05-06 11:46:52	ga_ls8c_ard_3-2-1_114080_2022-05-06_final
2022-05-08 11:32:56	ga_ls8c_ard_3-2-1_112076_2022-05-08_final
2022-05-08 11:35:20	ga_ls8c_ard_3-2-1_112082_2022-05-08_final
2022-05-09 10:34:56	ga_ls8c_ard_3-2-1_103070_2022-05-09_final
2022-05-09 10:36:55	ga_ls8c_ard_3-2-1_103075_2022-05-09_final
2022-05-09 10:38:31	ga_ls8c_ard_3-2-1_103079_2022-05-09_final
2022-05-10 11:22:11	ga_ls8c_ard_3-2-1_110080_2022-05-10_final
2022-05-11 10:23:23	ga_ls8c_ard_3-2-1_101072_2022-05-11_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-11 10:24:59	ga_ls8c_ard_3-2-1_101076_2022-05-11_final
2022-05-12 11:06:39	ga_ls8c_ard_3-2-1_108072_2022-05-12_final
2022-05-13 10:12:14	ga_ls8c_ard_3-2-1_099075_2022-05-13_final
2022-05-13 10:14:38	ga_ls8c_ard_3-2-1_099081_2022-05-13_final
2022-05-14 09:20:37	ga_ls8c_ard_3-2-1_090085_2022-05-13_final
2022-05-14 10:52:43	ga_ls8c_ard_3-2-1_106068_2022-05-14_final
2022-05-14 10:53:54	ga_ls8c_ard_3-2-1_106071_2022-05-14_final
2022-05-14 10:54:42	ga_ls8c_ard_3-2-1_106073_2022-05-14_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-05-17 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-05-17_final
2022-05-18 10:29:12	ga_ls8c_ard_3-2-1_102071_2022-05-18_final
2022-05-18 10:33:36	ga_ls8c_ard_3-2-1_102082_2022-05-18_final
2022-05-19 09:36:47	ga_ls8c_ard_3-2-1_093079_2022-05-19_final
2022-05-19 09:37:59	ga_ls8c_ard_3-2-1_093082_2022-05-19_final
2022-05-20 10:21:38	ga_ls8c_ard_3-2-1_100083_2022-05-20_final
2022-05-24 09:52:31	ga_ls8c_ard_3-2-1_096072_2022-05-24_final
2022-05-24 09:55:43	ga_ls8c_ard_3-2-1_096080_2022-05-24_final
2022-05-24 11:32:36	ga_ls8c_ard_3-2-1_112075_2022-05-24_final
2022-05-24 11:33:24	ga_ls8c_ard_3-2-1_112077_2022-05-24_final
2022-05-25 10:35:23	ga_ls8c_ard_3-2-1_103071_2022-05-25_final
2022-05-25 10:36:11	ga_ls8c_ard_3-2-1_103073_2022-05-25_final
2022-05-25 10:38:34	ga_ls8c_ard_3-2-1_103079_2022-05-25_final
2022-05-26 09:41:45	ga_ls8c_ard_3-2-1_094076_2022-05-26_final
2022-05-26 09:43:45	ga_ls8c_ard_3-2-1_094081_2022-05-26_final
2022-05-30 10:53:57	ga_ls8c_ard_3-2-1_106071_2022-05-30_final
2022-05-31 11:40:25	ga_ls8c_ard_3-2-1_113079_2022-05-31_final
2022-06-02 09:48:00	ga_ls8c_ard_3-2-1_095076_2022-06-02_final
2022-06-02 09:48:24	ga_ls8c_ard_3-2-1_095077_2022-06-02_final
2022-06-02 09:51:36	ga_ls8c_ard_3-2-1_095085_2022-06-02_final
2022-06-02 11:25:18	ga_ls8c_ard_3-2-1_111072_2022-06-02_final
2022-06-02 11:27:41	ga_ls8c_ard_3-2-1_111078_2022-06-02_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-03 10:28:53	ga_ls8c_ard_3-2-1_102070_2022-06-03_final
2022-06-04 09:38:28	ga_ls8c_ard_3-2-1_093083_2022-06-04_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-06 11:03:49	ga_ls8c_ard_3-2-1_107080_2022-06-06_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