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
2022-04-09 10:24:29	ga_ls8c_ard_3-2-1_101075_2022-04-09_final
2022-04-29 11:39:24	ga_ls8c_ard_3-2-1_113077_2022-04-29_final
2022-05-04 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-05-04_final
2022-05-05 09:23:55	ga_ls8c_ard_3-2-1_091078_2022-05-04_final
2022-05-06 10:05:35	ga_ls8c_ard_3-2-1_098074_2022-05-06_final
2022-05-06 11:45:40	ga_ls8c_ard_3-2-1_114077_2022-05-06_final
2022-05-07 10:51:39	ga_ls8c_ard_3-2-1_105081_2022-05-07_final
2022-05-09 10:38:07	ga_ls8c_ard_3-2-1_103078_2022-05-09_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-11 10:26:58	ga_ls8c_ard_3-2-1_101081_2022-05-11_final
2022-05-15 11:39:10	ga_ls8c_ard_3-2-1_113076_2022-05-15_final
2022-05-19 09:37:35	ga_ls8c_ard_3-2-1_093081_2022-05-19_final
2022-05-19 11:12:52	ga_ls8c_ard_3-2-1_109072_2022-05-19_final
2022-05-22 10:10:04	ga_ls8c_ard_3-2-1_098085_2022-05-22_final
2022-05-25 10:34:35	ga_ls8c_ard_3-2-1_103069_2022-05-25_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-05-31 10:02:20	ga_ls8c_ard_3-2-1_097081_2022-05-31_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-04 11:15:45	ga_ls8c_ard_3-2-1_109079_2022-06-04_final
2022-06-08 10:51:53	ga_ls8c_ard_3-2-1_105081_2022-06-08_final
2022-06-09 09:55:05	ga_ls8c_ard_3-2-1_096078_2022-06-09_final
2022-06-16 10:02:32	ga_ls8c_ard_3-2-1_097081_2022-06-16_final
2022-06-17 10:45:00	ga_ls8c_ard_3-2-1_104079_2022-06-17_final
2022-06-18 09:50:11	ga_ls8c_ard_3-2-1_095081_2022-06-18_final
2022-06-18 11:28:17	ga_ls8c_ard_3-2-1_111079_2022-06-18_final
2022-06-22 11:01:11	ga_ls8c_ard_3-2-1_107073_2022-06-22_final
2022-07-06 09:35:29	ga_ls8c_ard_3-2-1_093075_2022-07-06_final
2022-07-10 10:47:39	ga_ls8c_ard_3-2-1_105070_2022-07-10_final
2022-07-11 11:35:18	ga_ls8c_ard_3-2-1_112081_2022-07-11_final
2022-07-13 09:43:14	ga_ls8c_ard_3-2-1_094079_2022-07-13_final
2022-07-17 09:18:32	ga_ls8c_ard_3-2-1_090079_2022-07-16_final
2022-07-18 09:58:37	ga_ls8c_ard_3-2-1_097071_2022-07-18_final
2022-08-03 10:00:48	ga_ls8c_ard_3-2-1_097076_2022-08-03_final
2022-08-07 11:12:36	ga_ls8c_ard_3-2-1_109070_2022-08-07_final
2022-08-07 11:13:00	ga_ls8c_ard_3-2-1_109071_2022-08-07_final
2022-08-10 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-08-10_final
2022-08-11 10:47:55	ga_ls8c_ard_3-2-1_105070_2022-08-11_final
2022-08-18 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-08-18_final
2022-08-21 11:30:37	ga_ls8c_ard_3-2-1_111084_2022-08-21_final
2022-08-22 10:30:12	ga_ls8c_ard_3-2-1_102072_2022-08-22_final
2022-08-30 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-08-30_final
2022-09-01 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-09-01_final
2022-09-01 11:10:04	ga_ls8c_ard_3-2-1_108079_2022-09-01_final
2022-09-01 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-09-01_final
2022-09-05 10:43:22	ga_ls8c_ard_3-2-1_104074_2022-09-05_final
2022-09-05 10:44:10	ga_ls8c_ard_3-2-1_104076_2022-09-05_final
2022-09-08 11:16:42	ga_ls8c_ard_3-2-1_109080_2022-09-08_final
2022-09-09 10:19:05	ga_ls8c_ard_3-2-1_100075_2022-09-09_final
2022-09-10 11:03:33	ga_ls8c_ard_3-2-1_107078_2022-09-10_final
2022-09-11 11:46:50	ga_ls8c_ard_3-2-1_114078_2022-09-11_final
2022-09-13 09:56:48	ga_ls8c_ard_3-2-1_096081_2022-09-13_final
2022-09-18 10:15:21	ga_ls8c_ard_3-2-1_099081_2022-09-18_final
2022-09-19 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-09-18_final
2022-09-21 10:43:28	ga_ls8c_ard_3-2-1_104074_2022-09-21_final
2022-09-21 10:44:16	ga_ls8c_ard_3-2-1_104076_2022-09-21_final
2022-09-22 11:25:32	ga_ls8c_ard_3-2-1_111071_2022-09-22_final
2022-09-24 11:16:46	ga_ls8c_ard_3-2-1_109080_2022-09-24_final
2022-09-28 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-09-28_final
2022-09-29 09:55:37	ga_ls8c_ard_3-2-1_096078_2022-09-29_final
2022-10-10 11:12:17	ga_ls8c_ard_3-2-1_109069_2022-10-10_final
2022-10-12 09:25:00	ga_ls8c_ard_3-2-1_091079_2022-10-11_final
2022-10-17 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-10-17_final
2022-10-20 10:16:53	ga_ls8c_ard_3-2-1_099085_2022-10-20_final
2022-10-22 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-22_final
2022-10-23 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-23_final
2022-11-01 10:40:29	ga_ls8c_ard_3-2-1_103082_2022-11-01_final
2022-11-02 11:22:57	ga_ls8c_ard_3-2-1_110080_2022-11-02_final
2022-11-04 11:10:11	ga_ls8c_ard_3-2-1_108079_2022-11-04_final
2022-11-07 11:39:52	ga_ls8c_ard_3-2-1_113076_2022-11-07_final
2022-11-18 11:22:49	ga_ls8c_ard_3-2-1_110080_2022-11-18_final
2022-11-21 10:12:27	ga_ls8c_ard_3-2-1_099074_2022-11-21_final
2022-11-27 11:16:41	ga_ls8c_ard_3-2-1_109080_2022-11-27_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-12-05 10:27:14	ga_ls8c_ard_3-2-1_101080_2022-12-05_final
2022-12-14 10:19:24	ga_ls8c_ard_3-2-1_100076_2022-12-14_final
2022-12-18 11:32:19	ga_ls8c_ard_3-2-1_112073_2022-12-18_final
2022-12-20 11:22:43	ga_ls8c_ard_3-2-1_110080_2022-12-20_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-26 10:41:37	ga_ls8c_ard_3-2-1_104070_2022-12-26_final
2022-12-29 11:15:44	ga_ls8c_ard_3-2-1_109078_2022-12-29_final
2023-01-03 11:33:53	ga_ls8c_ard_3-2-1_112077_2023-01-03_final
2023-01-03 11:34:41	ga_ls8c_ard_3-2-1_112079_2023-01-03_final
2023-01-05 11:22:43	ga_ls8c_ard_3-2-1_110080_2023-01-05_final
2023-01-08 11:53:36	ga_ls8c_ard_3-2-1_115080_2023-01-08_final
2023-01-13 10:32:48	ga_ls8c_ard_3-2-1_102079_2023-01-13_final
2023-01-14 11:15:15	ga_ls8c_ard_3-2-1_109077_2023-01-14_final
2023-01-15 11:58:54	ga_ls8c_ard_3-2-1_116078_2023-01-15_final
2023-01-17 10:09:13	ga_ls8c_ard_3-2-1_098082_2023-01-17_final
2023-01-20 10:36:33	ga_ls8c_ard_3-2-1_103073_2023-01-20_final
2023-01-20 10:37:45	ga_ls8c_ard_3-2-1_103076_2023-01-20_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-26 09:59:32	ga_ls8c_ard_3-2-1_097073_2023-01-26_final
2023-02-05 10:36:37	ga_ls8c_ard_3-2-1_103073_2023-02-05_final
2023-02-06 09:41:47	ga_ls8c_ard_3-2-1_094075_2023-02-06_final
2023-02-10 10:56:19	ga_ls8c_ard_3-2-1_106076_2023-02-10_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-23 10:27:11	ga_ls8c_ard_3-2-1_101081_2023-02-23_final
2023-02-24 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-02-23_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