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
2023-08-21 09:21:52	ga_ls8c_ard_3-2-1_090088_2023-08-20_final
2023-08-21 10:52:46	ga_ls8c_ard_3-2-1_106068_2023-08-21_final
2023-08-21 10:58:21	ga_ls8c_ard_3-2-1_106082_2023-08-21_final
2023-08-22 11:41:13	ga_ls8c_ard_3-2-1_113081_2023-08-22_final
2023-08-23 10:42:49	ga_ls8c_ard_3-2-1_104074_2023-08-23_final
2023-08-23 10:43:13	ga_ls8c_ard_3-2-1_104075_2023-08-23_final
2023-08-24 11:26:05	ga_ls8c_ard_3-2-1_111074_2023-08-24_final
2023-08-24 11:28:52	ga_ls8c_ard_3-2-1_111081_2023-08-24_final
2023-08-24 11:29:16	ga_ls8c_ard_3-2-1_111082_2023-08-24_final
2023-08-28 09:28:28	ga_ls8c_ard_3-2-1_091089_2023-08-27_final
2023-08-29 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-08-29_final
2023-08-29 11:46:37	ga_ls8c_ard_3-2-1_114079_2023-08-29_final
2023-08-31 09:52:59	ga_ls8c_ard_3-2-1_096073_2023-08-31_final
2023-09-01 10:35:02	ga_ls8c_ard_3-2-1_103070_2023-09-01_final
2023-09-02 09:41:25	ga_ls8c_ard_3-2-1_094075_2023-09-02_final
2023-09-03 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-09-03_final
2023-09-04 09:29:50	ga_ls8c_ard_3-2-1_092077_2023-09-03_final
2023-09-04 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-09-04_final
2023-09-06 10:53:57	ga_ls8c_ard_3-2-1_106071_2023-09-06_final
2023-09-07 11:39:36	ga_ls8c_ard_3-2-1_113077_2023-09-07_final
2023-09-08 10:41:36	ga_ls8c_ard_3-2-1_104071_2023-09-08_final
2023-09-09 09:47:59	ga_ls8c_ard_3-2-1_095076_2023-09-09_final
2023-09-11 11:13:45	ga_ls8c_ard_3-2-1_109074_2023-09-11_final
2023-09-13 11:01:24	ga_ls8c_ard_3-2-1_107074_2023-09-13_final
2023-09-14 10:07:23	ga_ls8c_ard_3-2-1_098078_2023-09-14_final
2023-09-15 09:14:34	ga_ls8c_ard_3-2-1_089085_2023-09-14_final
2023-09-15 10:47:28	ga_ls8c_ard_3-2-1_105070_2023-09-15_final
2023-09-16 11:32:44	ga_ls8c_ard_3-2-1_112075_2023-09-16_final
2023-09-17 10:34:43	ga_ls8c_ard_3-2-1_103069_2023-09-17_final
2023-09-18 09:41:29	ga_ls8c_ard_3-2-1_094075_2023-09-18_final
2023-09-18 11:23:34	ga_ls8c_ard_3-2-1_110083_2023-09-18_final
2023-09-19 10:24:21	ga_ls8c_ard_3-2-1_101074_2023-09-19_final
2023-09-22 09:19:57	ga_ls8c_ard_3-2-1_090083_2023-09-21_final
2023-09-23 10:02:49	ga_ls8c_ard_3-2-1_097082_2023-09-23_final
2023-09-23 11:40:31	ga_ls8c_ard_3-2-1_113079_2023-09-23_final
2023-09-25 11:29:22	ga_ls8c_ard_3-2-1_111082_2023-09-25_final
2023-09-26 10:30:10	ga_ls8c_ard_3-2-1_102073_2023-09-26_final
2023-09-27 11:12:38	ga_ls8c_ard_3-2-1_109071_2023-09-27_final
2023-09-29 09:26:12	ga_ls8c_ard_3-2-1_091083_2023-09-28_final
2023-09-29 11:00:41	ga_ls8c_ard_3-2-1_107072_2023-09-29_final
2023-09-29 11:04:17	ga_ls8c_ard_3-2-1_107081_2023-09-29_final
2023-10-01 10:47:56	ga_ls8c_ard_3-2-1_105071_2023-10-01_final
2023-10-04 11:18:50	ga_ls8c_ard_3-2-1_110071_2023-10-04_final
2023-10-05 10:24:00	ga_ls8c_ard_3-2-1_101073_2023-10-05_final
2023-10-08 09:18:26	ga_ls8c_ard_3-2-1_090079_2023-10-07_final
2023-10-08 09:19:14	ga_ls8c_ard_3-2-1_090081_2023-10-07_final
2023-10-08 10:52:56	ga_ls8c_ard_3-2-1_106068_2023-10-08_final
2023-10-08 10:57:43	ga_ls8c_ard_3-2-1_106080_2023-10-08_final
2023-10-09 11:39:47	ga_ls8c_ard_3-2-1_113077_2023-10-09_final
2023-10-09 11:40:35	ga_ls8c_ard_3-2-1_113079_2023-10-09_final
2023-10-10 10:43:47	ga_ls8c_ard_3-2-1_104076_2023-10-10_final
2023-10-11 09:46:58	ga_ls8c_ard_3-2-1_095073_2023-10-11_final
2023-10-11 11:25:27	ga_ls8c_ard_3-2-1_111072_2023-10-11_final
2023-10-11 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-10-11_final
2023-10-12 10:29:26	ga_ls8c_ard_3-2-1_102071_2023-10-12_final
2023-10-12 10:30:14	ga_ls8c_ard_3-2-1_102073_2023-10-12_final
2023-10-14 10:18:16	ga_ls8c_ard_3-2-1_100074_2023-10-14_final
2023-10-16 11:45:11	ga_ls8c_ard_3-2-1_114075_2023-10-16_final
2023-10-16 11:45:35	ga_ls8c_ard_3-2-1_114076_2023-10-16_final
2023-10-17 09:13:04	ga_ls8c_ard_3-2-1_089081_2023-10-16_final
2023-10-17 10:47:34	ga_ls8c_ard_3-2-1_105070_2023-10-17_final
2023-10-20 09:44:45	ga_ls8c_ard_3-2-1_094083_2023-10-20_final
2023-10-21 10:24:26	ga_ls8c_ard_3-2-1_101074_2023-10-21_final
2023-10-22 11:08:30	ga_ls8c_ard_3-2-1_108076_2023-10-22_final
2023-10-24 09:19:41	ga_ls8c_ard_3-2-1_090082_2023-10-23_final
2023-10-25 11:39:50	ga_ls8c_ard_3-2-1_113077_2023-10-25_final
2023-10-27 09:47:48	ga_ls8c_ard_3-2-1_095075_2023-10-27_final
2023-10-27 11:29:53	ga_ls8c_ard_3-2-1_111083_2023-10-27_final
2023-10-29 11:11:57	ga_ls8c_ard_3-2-1_109069_2023-10-29_final
2023-10-30 10:19:07	ga_ls8c_ard_3-2-1_100076_2023-10-30_final
2023-10-30 10:21:31	ga_ls8c_ard_3-2-1_100082_2023-10-30_final
2023-10-31 11:01:59	ga_ls8c_ard_3-2-1_107075_2023-10-31_final
2023-10-31 11:03:35	ga_ls8c_ard_3-2-1_107079_2023-10-31_final
2023-11-01 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-11-01_final
2023-11-04 10:35:15	ga_ls8c_ard_3-2-1_103070_2023-11-04_final
2023-11-04 10:35:39	ga_ls8c_ard_3-2-1_103071_2023-11-04_final
2023-11-05 11:23:41	ga_ls8c_ard_3-2-1_110083_2023-11-05_final
2023-11-07 09:29:14	ga_ls8c_ard_3-2-1_092075_2023-11-06_final
2023-11-07 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-11-07_final
2023-11-07 11:08:31	ga_ls8c_ard_3-2-1_108076_2023-11-07_final
2023-11-08 10:13:16	ga_ls8c_ard_3-2-1_099077_2023-11-08_final
2023-11-10 10:00:29	ga_ls8c_ard_3-2-1_097076_2023-11-10_final
2023-11-10 11:39:46	ga_ls8c_ard_3-2-1_113077_2023-11-10_final
2023-11-11 10:43:22	ga_ls8c_ard_3-2-1_104075_2023-11-11_final
2023-11-12 09:51:45	ga_ls8c_ard_3-2-1_095085_2023-11-12_final
2023-11-12 11:25:26	ga_ls8c_ard_3-2-1_111072_2023-11-12_final
2023-11-12 11:29:50	ga_ls8c_ard_3-2-1_111083_2023-11-12_final
2023-11-13 10:29:50	ga_ls8c_ard_3-2-1_102072_2023-11-13_final
2023-11-13 10:31:50	ga_ls8c_ard_3-2-1_102077_2023-11-13_final
2023-11-14 11:16:42	ga_ls8c_ard_3-2-1_109081_2023-11-14_final
2023-11-14 11:17:06	ga_ls8c_ard_3-2-1_109082_2023-11-14_final
2023-11-15 10:19:29	ga_ls8c_ard_3-2-1_100077_2023-11-15_final
2023-11-16 09:26:16	ga_ls8c_ard_3-2-1_091083_2023-11-15_final
2023-11-17 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-11-17_final
2023-11-17 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-11-17_final
2023-11-18 10:47:38	ga_ls8c_ard_3-2-1_105070_2023-11-18_final
2023-11-20 10:40:04	ga_ls8c_ard_3-2-1_103082_2023-11-20_final
2023-11-22 10:24:56	ga_ls8c_ard_3-2-1_101075_2023-11-22_final
2023-11-23 09:29:19	ga_ls8c_ard_3-2-1_092075_2023-11-22_final
2023-11-23 09:30:54	ga_ls8c_ard_3-2-1_092079_2023-11-23_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