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
2019-07-28 09:46:50	ga_ls8c_ard_3-1-0_095073_2019-07-28_final
2019-12-03 09:50:19	ga_ls8c_ard_3-1-0_095081_2019-12-03_final
2020-02-05 09:48:51	ga_ls8c_ard_3-1-0_095078_2020-02-05_final
2020-03-24 09:47:47	ga_ls8c_ard_3-1-0_095076_2020-03-24_final
2022-03-29 10:43:46	ga_ls8c_ard_3-2-1_104077_2022-03-29_final
2022-03-30 09:46:56	ga_ls8c_ard_3-2-1_095074_2022-03-30_final
2022-03-30 09:47:44	ga_ls8c_ard_3-2-1_095076_2022-03-30_final
2022-03-30 11:27:25	ga_ls8c_ard_3-2-1_111078_2022-03-30_final
2022-04-01 09:40:10	ga_ls8c_ard_3-2-1_093088_2022-04-01_final
2022-04-01 11:17:03	ga_ls8c_ard_3-2-1_109083_2022-04-01_final
2022-04-02 10:16:38	ga_ls8c_ard_3-2-1_100071_2022-04-02_final
2022-04-02 10:21:02	ga_ls8c_ard_3-2-1_100082_2022-04-02_final
2022-04-03 09:25:48	ga_ls8c_ard_3-2-1_091083_2022-04-02_final
2022-04-03 11:01:30	ga_ls8c_ard_3-2-1_107075_2022-04-03_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-04 10:05:53	ga_ls8c_ard_3-2-1_098075_2022-04-04_final
2022-04-05 10:47:58	ga_ls8c_ard_3-2-1_105072_2022-04-05_final
2022-04-05 10:48:22	ga_ls8c_ard_3-2-1_105073_2022-04-05_final
2022-04-06 11:34:50	ga_ls8c_ard_3-2-1_112081_2022-04-06_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-09 10:23:17	ga_ls8c_ard_3-2-1_101072_2022-04-09_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-10 09:29:40	ga_ls8c_ard_3-2-1_092077_2022-04-09_final
2022-04-11 10:10:57	ga_ls8c_ard_3-2-1_099072_2022-04-11_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-13 11:39:05	ga_ls8c_ard_3-2-1_113076_2022-04-13_final
2022-04-15 09:47:02	ga_ls8c_ard_3-2-1_095074_2022-04-15_final
2022-04-15 11:25:32	ga_ls8c_ard_3-2-1_111073_2022-04-15_final
2022-04-15 11:29:55	ga_ls8c_ard_3-2-1_111084_2022-04-15_final
2022-04-16 10:31:06	ga_ls8c_ard_3-2-1_102076_2022-04-16_final
2022-04-18 10:20:44	ga_ls8c_ard_3-2-1_100081_2022-04-18_final
2022-04-19 09:23:54	ga_ls8c_ard_3-2-1_091078_2022-04-18_final
2022-04-20 10:08:21	ga_ls8c_ard_3-2-1_098081_2022-04-20_final
2022-04-20 11:44:51	ga_ls8c_ard_3-2-1_114075_2022-04-20_final
2022-04-21 09:14:44	ga_ls8c_ard_3-2-1_089086_2022-04-20_final
2022-04-23 10:35:15	ga_ls8c_ard_3-2-1_103071_2022-04-23_final
2022-04-24 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-24_final
2022-04-24 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-24_final
2022-04-27 10:15:17	ga_ls8c_ard_3-2-1_099083_2022-04-27_final
2022-04-28 09:17:15	ga_ls8c_ard_3-2-1_090077_2022-04-27_final
2022-04-28 09:21:39	ga_ls8c_ard_3-2-1_090088_2022-04-27_final
2022-04-28 10:54:09	ga_ls8c_ard_3-2-1_106072_2022-04-28_final
2022-04-30 10:41:24	ga_ls8c_ard_3-2-1_104071_2022-04-30_final
2022-05-01 09:46:35	ga_ls8c_ard_3-2-1_095073_2022-05-01_final
2022-05-01 09:47:23	ga_ls8c_ard_3-2-1_095075_2022-05-01_final
2022-05-01 11:24:40	ga_ls8c_ard_3-2-1_111071_2022-05-01_final
2022-05-01 11:28:40	ga_ls8c_ard_3-2-1_111081_2022-05-01_final
2022-05-02 10:31:04	ga_ls8c_ard_3-2-1_102076_2022-05-02_final
2022-05-03 09:35:03	ga_ls8c_ard_3-2-1_093075_2022-05-03_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-05 09:23:07	ga_ls8c_ard_3-2-1_091076_2022-05-04_final
2022-05-05 09:27:06	ga_ls8c_ard_3-2-1_091086_2022-05-04_final
2022-05-06 10:04:48	ga_ls8c_ard_3-2-1_098072_2022-05-06_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-08 09:53:39	ga_ls8c_ard_3-2-1_096075_2022-05-08_final
2022-05-08 09:56:51	ga_ls8c_ard_3-2-1_096083_2022-05-08_final
2022-05-10 09:44:30	ga_ls8c_ard_3-2-1_094083_2022-05-10_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-05-10 11:22:59	ga_ls8c_ard_3-2-1_110082_2022-05-10_final
2022-05-12 11:07:27	ga_ls8c_ard_3-2-1_108074_2022-05-12_final
2022-05-15 10:01:29	ga_ls8c_ard_3-2-1_097079_2022-05-15_final
2022-05-15 11:38:46	ga_ls8c_ard_3-2-1_113075_2022-05-15_final
2022-05-15 11:39:10	ga_ls8c_ard_3-2-1_113076_2022-05-15_final
2022-05-15 11:39:58	ga_ls8c_ard_3-2-1_113078_2022-05-15_final
2022-05-16 10:42:45	ga_ls8c_ard_3-2-1_104074_2022-05-16_final
2022-05-18 10:28:48	ga_ls8c_ard_3-2-1_102070_2022-05-18_final
2022-05-19 09:39:58	ga_ls8c_ard_3-2-1_093087_2022-05-19_final
2022-05-19 11:17:40	ga_ls8c_ard_3-2-1_109084_2022-05-19_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-20 10:18:27	ga_ls8c_ard_3-2-1_100075_2022-05-20_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-05-26 09:41:21	ga_ls8c_ard_3-2-1_094075_2022-05-26_final
2022-05-26 11:18:14	ga_ls8c_ard_3-2-1_110070_2022-05-26_final
2022-05-31 09:59:32	ga_ls8c_ard_3-2-1_097074_2022-05-31_final
2022-06-01 10:46:00	ga_ls8c_ard_3-2-1_104082_2022-06-01_final
2022-06-02 09:46:25	ga_ls8c_ard_3-2-1_095072_2022-06-02_final
2022-06-02 09:46:49	ga_ls8c_ard_3-2-1_095073_2022-06-02_final
2022-06-03 10:29:41	ga_ls8c_ard_3-2-1_102072_2022-06-03_final
2022-06-04 09:37:40	ga_ls8c_ard_3-2-1_093081_2022-06-04_final
2022-06-05 10:17:45	ga_ls8c_ard_3-2-1_100073_2022-06-05_final
2022-06-06 09:24:08	ga_ls8c_ard_3-2-1_091078_2022-06-05_final
2022-06-07 11:44:42	ga_ls8c_ard_3-2-1_114074_2022-06-07_final
2022-06-08 09:14:36	ga_ls8c_ard_3-2-1_089085_2022-06-07_final
2022-06-08 10:47:30	ga_ls8c_ard_3-2-1_105070_2022-06-08_final
2022-06-08 10:52:17	ga_ls8c_ard_3-2-1_105082_2022-06-08_final
2022-06-13 11:08:06	ga_ls8c_ard_3-2-1_108075_2022-06-13_final
2022-06-15 10:54:57	ga_ls8c_ard_3-2-1_106073_2022-06-15_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_final
2022-06-16 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-06-16_final
2022-06-18 09:47:48	ga_ls8c_ard_3-2-1_095075_2022-06-18_final
2022-06-18 09:51:23	ga_ls8c_ard_3-2-1_095084_2022-06-18_final
2022-06-18 11:25:05	ga_ls8c_ard_3-2-1_111071_2022-06-18_final
2022-06-19 10:29:52	ga_ls8c_ard_3-2-1_102072_2022-06-19_final
2022-06-19 10:31:28	ga_ls8c_ard_3-2-1_102076_2022-06-19_final
2022-06-20 09:34:15	ga_ls8c_ard_3-2-1_093072_2022-06-20_final
2022-06-20 09:35:27	ga_ls8c_ard_3-2-1_093075_2022-06-20_final
2022-06-20 09:38:38	ga_ls8c_ard_3-2-1_093083_2022-06-20_final
2022-06-20 11:17:55	ga_ls8c_ard_3-2-1_109084_2022-06-20_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