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
2023-02-03 09:11:42	ga_ls8c_ard_3-2-1_089077_2023-02-02_final
2023-08-28 09:24:05	ga_ls8c_ard_3-2-1_091078_2023-08-27_final
2023-08-28 11:00:34	ga_ls8c_ard_3-2-1_107072_2023-08-28_final
2023-08-29 10:06:09	ga_ls8c_ard_3-2-1_098075_2023-08-29_final
2023-08-29 10:08:32	ga_ls8c_ard_3-2-1_098081_2023-08-29_final
2023-08-30 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-08-29_final
2023-08-30 10:48:36	ga_ls8c_ard_3-2-1_105073_2023-08-30_final
2023-08-31 09:56:10	ga_ls8c_ard_3-2-1_096081_2023-08-31_final
2023-09-01 10:39:50	ga_ls8c_ard_3-2-1_103082_2023-09-01_final
2023-09-02 09:44:36	ga_ls8c_ard_3-2-1_094083_2023-09-02_final
2023-09-04 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-09-04_final
2023-09-04 09:33:50	ga_ls8c_ard_3-2-1_092087_2023-09-04_final
2023-09-05 10:11:54	ga_ls8c_ard_3-2-1_099074_2023-09-05_final
2023-09-05 10:12:17	ga_ls8c_ard_3-2-1_099075_2023-09-05_final
2023-09-06 09:19:51	ga_ls8c_ard_3-2-1_090083_2023-09-05_final
2023-09-06 09:20:15	ga_ls8c_ard_3-2-1_090084_2023-09-05_final
2023-09-06 09:21:03	ga_ls8c_ard_3-2-1_090086_2023-09-05_final
2023-09-06 09:21:51	ga_ls8c_ard_3-2-1_090088_2023-09-05_final
2023-09-06 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-09-06_final
2023-09-06 10:53:57	ga_ls8c_ard_3-2-1_106071_2023-09-06_final
2023-09-06 10:55:09	ga_ls8c_ard_3-2-1_106074_2023-09-06_final
2023-09-06 10:58:20	ga_ls8c_ard_3-2-1_106082_2023-09-06_final
2023-09-08 10:41:36	ga_ls8c_ard_3-2-1_104071_2023-09-08_final
2023-09-09 09:47:12	ga_ls8c_ard_3-2-1_095074_2023-09-09_final
2023-09-09 09:47:59	ga_ls8c_ard_3-2-1_095076_2023-09-09_final
2023-09-10 10:31:16	ga_ls8c_ard_3-2-1_102076_2023-09-10_final
2023-09-11 09:36:03	ga_ls8c_ard_3-2-1_093077_2023-09-11_final
2023-09-11 11:16:56	ga_ls8c_ard_3-2-1_109082_2023-09-11_final
2023-09-13 09:26:07	ga_ls8c_ard_3-2-1_091083_2023-09-12_final
2023-09-13 11:01:24	ga_ls8c_ard_3-2-1_107074_2023-09-13_final
2023-09-13 11:01:48	ga_ls8c_ard_3-2-1_107075_2023-09-13_final
2023-09-14 10:05:47	ga_ls8c_ard_3-2-1_098074_2023-09-14_final
2023-09-14 10:08:35	ga_ls8c_ard_3-2-1_098081_2023-09-14_final
2023-09-14 11:44:41	ga_ls8c_ard_3-2-1_114074_2023-09-14_final
2023-09-15 10:46:16	ga_ls8c_ard_3-2-1_105067_2023-09-15_final
2023-09-15 10:48:16	ga_ls8c_ard_3-2-1_105072_2023-09-15_final
2023-09-16 09:57:02	ga_ls8c_ard_3-2-1_096083_2023-09-16_final
2023-09-17 10:35:07	ga_ls8c_ard_3-2-1_103070_2023-09-17_final
2023-09-22 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-09-21_final
2023-09-22 10:55:15	ga_ls8c_ard_3-2-1_106074_2023-09-22_final
2023-09-22 10:56:51	ga_ls8c_ard_3-2-1_106078_2023-09-22_final
2023-09-23 11:39:19	ga_ls8c_ard_3-2-1_113076_2023-09-23_final
2023-09-27 09:34:57	ga_ls8c_ard_3-2-1_093074_2023-09-27_final
2023-09-28 10:17:49	ga_ls8c_ard_3-2-1_100073_2023-09-28_final
2023-09-28 10:18:13	ga_ls8c_ard_3-2-1_100074_2023-09-28_final
2023-09-28 10:21:49	ga_ls8c_ard_3-2-1_100083_2023-09-28_final
2023-09-29 09:25:48	ga_ls8c_ard_3-2-1_091082_2023-09-28_final
2023-09-29 11:00:17	ga_ls8c_ard_3-2-1_107071_2023-09-29_final
2023-09-30 11:44:45	ga_ls8c_ard_3-2-1_114074_2023-09-30_final
2023-10-04 09:43:08	ga_ls8c_ard_3-2-1_094079_2023-10-04_final
2023-10-09 10:00:54	ga_ls8c_ard_3-2-1_097077_2023-10-09_final
2023-10-09 11:41:47	ga_ls8c_ard_3-2-1_113082_2023-10-09_final
2023-10-12 10:30:14	ga_ls8c_ard_3-2-1_102073_2023-10-12_final
2023-10-13 09:35:48	ga_ls8c_ard_3-2-1_093076_2023-10-13_final
2023-10-13 11:17:05	ga_ls8c_ard_3-2-1_109082_2023-10-13_final
2023-10-15 09:23:27	ga_ls8c_ard_3-2-1_091076_2023-10-14_final
2023-10-16 11:47:11	ga_ls8c_ard_3-2-1_114080_2023-10-16_final
2023-10-17 10:47:10	ga_ls8c_ard_3-2-1_105069_2023-10-17_final
2023-10-19 10:35:35	ga_ls8c_ard_3-2-1_103071_2023-10-19_final
2023-10-19 10:37:35	ga_ls8c_ard_3-2-1_103076_2023-10-19_final
2023-10-19 10:39:59	ga_ls8c_ard_3-2-1_103082_2023-10-19_final
2023-10-20 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-10-20_final
2023-10-20 11:24:02	ga_ls8c_ard_3-2-1_110084_2023-10-20_final
2023-10-21 10:26:02	ga_ls8c_ard_3-2-1_101078_2023-10-21_final
2023-10-22 09:29:37	ga_ls8c_ard_3-2-1_092076_2023-10-21_final
2023-10-24 09:20:52	ga_ls8c_ard_3-2-1_090085_2023-10-23_final
2023-10-25 10:00:33	ga_ls8c_ard_3-2-1_097076_2023-10-25_final
2023-10-25 11:39:26	ga_ls8c_ard_3-2-1_113076_2023-10-25_final
2023-10-27 09:48:36	ga_ls8c_ard_3-2-1_095077_2023-10-27_final
2023-10-28 10:29:53	ga_ls8c_ard_3-2-1_102072_2023-10-28_final
2023-10-31 09:28:17	ga_ls8c_ard_3-2-1_091088_2023-10-30_final
2023-10-31 11:01:11	ga_ls8c_ard_3-2-1_107073_2023-10-31_final
2023-11-01 11:45:15	ga_ls8c_ard_3-2-1_114075_2023-11-01_final
2023-11-02 10:49:13	ga_ls8c_ard_3-2-1_105074_2023-11-02_final
2023-11-03 11:34:04	ga_ls8c_ard_3-2-1_112078_2023-11-03_final
2023-11-05 09:43:37	ga_ls8c_ard_3-2-1_094080_2023-11-05_final
2023-11-05 11:19:42	ga_ls8c_ard_3-2-1_110073_2023-11-05_final
2023-11-06 10:22:52	ga_ls8c_ard_3-2-1_101070_2023-11-06_final
2023-11-06 10:27:16	ga_ls8c_ard_3-2-1_101081_2023-11-06_final
2023-11-08 10:15:40	ga_ls8c_ard_3-2-1_099083_2023-11-08_final
2023-11-08 11:52:57	ga_ls8c_ard_3-2-1_115079_2023-11-08_final
2023-11-08 11:53:21	ga_ls8c_ard_3-2-1_115080_2023-11-08_final
2023-11-09 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-11-08_final
2023-11-09 09:20:25	ga_ls8c_ard_3-2-1_090084_2023-11-08_final
2023-11-10 10:01:41	ga_ls8c_ard_3-2-1_097079_2023-11-10_final
2023-11-10 11:40:58	ga_ls8c_ard_3-2-1_113080_2023-11-10_final
2023-11-11 10:44:33	ga_ls8c_ard_3-2-1_104078_2023-11-11_final
2023-11-12 09:46:33	ga_ls8c_ard_3-2-1_095072_2023-11-12_final
2023-11-12 09:47:45	ga_ls8c_ard_3-2-1_095075_2023-11-12_final
2023-11-12 11:25:02	ga_ls8c_ard_3-2-1_111071_2023-11-12_final
2023-11-13 10:30:14	ga_ls8c_ard_3-2-1_102073_2023-11-13_final
2023-11-14 09:35:01	ga_ls8c_ard_3-2-1_093074_2023-11-14_final
2023-11-14 11:17:06	ga_ls8c_ard_3-2-1_109082_2023-11-14_final
2023-11-16 11:01:10	ga_ls8c_ard_3-2-1_107073_2023-11-16_final
2023-11-17 10:05:09	ga_ls8c_ard_3-2-1_098072_2023-11-17_final
2023-11-17 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-11-17_final
2023-11-18 09:12:44	ga_ls8c_ard_3-2-1_089080_2023-11-17_final
2023-11-18 10:48:02	ga_ls8c_ard_3-2-1_105071_2023-11-18_final
2023-11-19 11:32:30	ga_ls8c_ard_3-2-1_112074_2023-11-19_final
2023-11-19 11:35:41	ga_ls8c_ard_3-2-1_112082_2023-11-19_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