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
2022-07-03 10:41:52	ga_ls8c_ard_3-2-1_104071_2022-07-03_final
2022-07-09 11:46:28	ga_ls8c_ard_3-2-1_114078_2022-07-09_final
2022-07-10 09:14:45	ga_ls8c_ard_3-2-1_089085_2022-07-09_final
2022-07-11 09:57:12	ga_ls8c_ard_3-2-1_096083_2022-07-11_final
2022-07-13 09:43:38	ga_ls8c_ard_3-2-1_094080_2022-07-13_final
2022-07-17 09:18:32	ga_ls8c_ard_3-2-1_090079_2022-07-16_final
2022-07-17 10:54:37	ga_ls8c_ard_3-2-1_106072_2022-07-17_final
2022-07-18 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-07-18_final
2022-07-22 09:35:09	ga_ls8c_ard_3-2-1_093074_2022-07-22_final
2022-07-22 09:37:09	ga_ls8c_ard_3-2-1_093079_2022-07-22_final
2022-07-28 10:38:13	ga_ls8c_ard_3-2-1_103077_2022-07-28_final
2022-07-29 09:41:01	ga_ls8c_ard_3-2-1_094073_2022-07-29_final
2022-08-01 10:13:09	ga_ls8c_ard_3-2-1_099076_2022-08-01_final
2022-08-03 10:04:00	ga_ls8c_ard_3-2-1_097084_2022-08-03_final
2022-08-05 09:48:04	ga_ls8c_ard_3-2-1_095075_2022-08-05_final
2022-08-07 09:38:07	ga_ls8c_ard_3-2-1_093081_2022-08-07_final
2022-08-08 11:59:04	ga_ls8c_ard_3-2-1_116078_2022-08-08_final
2022-08-09 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-08-08_final
2022-08-11 09:15:01	ga_ls8c_ard_3-2-1_089085_2022-08-10_final
2022-08-14 09:43:56	ga_ls8c_ard_3-2-1_094080_2022-08-14_final
2022-08-14 11:19:14	ga_ls8c_ard_3-2-1_110071_2022-08-14_final
2022-08-14 11:24:01	ga_ls8c_ard_3-2-1_110083_2022-08-14_final
2022-08-17 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-08-17_final
2022-08-22 10:31:24	ga_ls8c_ard_3-2-1_102075_2022-08-22_final
2022-08-23 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-08-23_final
2022-08-23 11:13:28	ga_ls8c_ard_3-2-1_109072_2022-08-23_final
2022-08-24 11:59:07	ga_ls8c_ard_3-2-1_116078_2022-08-24_final
2022-09-01 09:30:47	ga_ls8c_ard_3-2-1_092078_2022-09-01_final
2022-09-04 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-09-04_final
2022-09-05 10:41:23	ga_ls8c_ard_3-2-1_104069_2022-09-05_final
2022-09-06 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-09-06_final
2022-09-07 10:33:26	ga_ls8c_ard_3-2-1_102080_2022-09-07_final
2022-09-08 11:12:43	ga_ls8c_ard_3-2-1_109070_2022-09-08_final
2022-09-10 09:25:04	ga_ls8c_ard_3-2-1_091079_2022-09-09_final
2022-09-13 09:58:23	ga_ls8c_ard_3-2-1_096085_2022-09-13_final
2022-09-20 09:59:25	ga_ls8c_ard_3-2-1_097072_2022-09-20_final
2022-09-25 11:59:14	ga_ls8c_ard_3-2-1_116078_2022-09-25_final
2022-09-26 11:04:24	ga_ls8c_ard_3-2-1_107080_2022-09-26_final
2022-09-27 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-09-27_final
2022-09-28 10:52:27	ga_ls8c_ard_3-2-1_105081_2022-09-28_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-10-01 09:44:03	ga_ls8c_ard_3-2-1_094080_2022-10-01_final
2022-10-07 10:42:13	ga_ls8c_ard_3-2-1_104071_2022-10-07_final
2022-10-10 09:37:23	ga_ls8c_ard_3-2-1_093079_2022-10-10_final
2022-10-10 11:13:29	ga_ls8c_ard_3-2-1_109072_2022-10-10_final
2022-10-12 09:25:00	ga_ls8c_ard_3-2-1_091079_2022-10-11_final
2022-10-12 11:01:29	ga_ls8c_ard_3-2-1_107073_2022-10-12_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-23 10:41:50	ga_ls8c_ard_3-2-1_104070_2022-10-23_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-10-26 09:37:03	ga_ls8c_ard_3-2-1_093078_2022-10-26_final
2022-10-29 10:08:46	ga_ls8c_ard_3-2-1_098080_2022-10-29_final
2022-11-02 11:23:21	ga_ls8c_ard_3-2-1_110081_2022-11-02_final
2022-11-03 10:25:20	ga_ls8c_ard_3-2-1_101075_2022-11-03_final
2022-11-04 09:30:06	ga_ls8c_ard_3-2-1_092076_2022-11-04_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-07 11:39:29	ga_ls8c_ard_3-2-1_113075_2022-11-07_final
2022-11-14 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-14_final
2022-11-25 11:29:50	ga_ls8c_ard_3-2-1_111082_2022-11-25_final
2022-11-26 10:32:37	ga_ls8c_ard_3-2-1_102078_2022-11-26_final
2022-11-26 10:33:01	ga_ls8c_ard_3-2-1_102079_2022-11-26_final
2022-11-27 09:37:48	ga_ls8c_ard_3-2-1_093080_2022-11-27_final
2022-11-29 11:01:32	ga_ls8c_ard_3-2-1_107073_2022-11-29_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-11-30 10:07:06	ga_ls8c_ard_3-2-1_098076_2022-11-30_final
2022-12-01 10:48:46	ga_ls8c_ard_3-2-1_105072_2022-12-01_final
2022-12-04 09:45:10	ga_ls8c_ard_3-2-1_094083_2022-12-04_final
2022-12-09 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-12-09_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-16 11:47:06	ga_ls8c_ard_3-2-1_114079_2022-12-16_final
2022-12-18 09:53:50	ga_ls8c_ard_3-2-1_096074_2022-12-18_final
2022-12-21 10:25:05	ga_ls8c_ard_3-2-1_101075_2022-12-21_final
2022-12-27 11:30:05	ga_ls8c_ard_3-2-1_111083_2022-12-27_final
2022-12-29 09:38:03	ga_ls8c_ard_3-2-1_093081_2022-12-29_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-02-20 11:35:38	ga_ls8c_ard_3-2-1_112082_2023-02-20_final
2023-02-23 10:25:59	ga_ls8c_ard_3-2-1_101078_2023-02-23_final
2023-02-26 09:19:09	ga_ls8c_ard_3-2-1_090081_2023-02-25_final
2023-03-03 11:17:46	ga_ls8c_ard_3-2-1_109084_2023-03-03_final
2023-03-10 11:20:41	ga_ls8c_ard_3-2-1_110076_2023-03-10_final
2023-03-12 09:29:50	ga_ls8c_ard_3-2-1_092077_2023-03-11_final
2023-03-13 10:11:54	ga_ls8c_ard_3-2-1_099074_2023-03-13_final
2023-03-28 09:30:52	ga_ls8c_ard_3-2-1_092080_2023-03-28_final
2023-03-30 10:57:47	ga_ls8c_ard_3-2-1_106081_2023-03-30_final
2023-04-02 11:26:39	ga_ls8c_ard_3-2-1_111076_2023-04-02_final
2023-04-04 09:36:10	ga_ls8c_ard_3-2-1_093078_2023-04-04_final
2023-05-11 09:51:30	ga_ls8c_ard_3-2-1_096071_2023-05-11_final
2023-05-17 10:53:38	ga_ls8c_ard_3-2-1_106072_2023-05-17_final
2023-05-18 09:58:25	ga_ls8c_ard_3-2-1_097073_2023-05-18_final
2023-05-24 09:25:22	ga_ls8c_ard_3-2-1_091083_2023-05-23_final
2023-05-26 10:46:19	ga_ls8c_ard_3-2-1_105069_2023-05-26_final
2023-05-29 09:39:56	ga_ls8c_ard_3-2-1_094073_2023-05-29_final
2023-05-30 10:23:12	ga_ls8c_ard_3-2-1_101073_2023-05-30_final
2023-06-04 10:42:34	ga_ls8c_ard_3-2-1_104075_2023-06-04_final
2023-06-05 09:48:57	ga_ls8c_ard_3-2-1_095080_2023-06-05_final
2023-08-10 09:35:06	ga_ls8c_ard_3-2-1_093075_2023-08-10_final
2023-08-16 10:37:46	ga_ls8c_ard_3-2-1_103077_2023-08-16_final
2023-08-18 10:24:14	ga_ls8c_ard_3-2-1_101074_2023-08-18_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