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
2022-10-04 11:51:49	ga_ls8c_ard_3-2-1_115075_2022-10-04_final
2022-10-05 10:54:12	ga_ls8c_ard_3-2-1_106070_2022-10-05_final
2022-10-05 10:54:36	ga_ls8c_ard_3-2-1_106071_2022-10-05_final
2022-10-10 11:17:04	ga_ls8c_ard_3-2-1_109081_2022-10-10_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-13 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-10-13_final
2022-10-13 10:10:38	ga_ls8c_ard_3-2-1_098085_2022-10-13_final
2022-10-14 09:12:12	ga_ls8c_ard_3-2-1_089078_2022-10-13_final
2022-10-15 09:58:17	ga_ls8c_ard_3-2-1_096085_2022-10-15_final
2022-10-16 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-10-16_final
2022-10-18 10:23:38	ga_ls8c_ard_3-2-1_101071_2022-10-18_final
2022-10-21 09:22:52	ga_ls8c_ard_3-2-1_090089_2022-10-20_final
2022-10-21 09:23:16	ga_ls8c_ard_3-2-1_090090_2022-10-20_final
2022-10-22 09:58:09	ga_ls8c_ard_3-2-1_097069_2022-10-22_final
2022-10-22 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-22_final
2022-10-27 10:17:56	ga_ls8c_ard_3-2-1_100072_2022-10-27_final
2022-10-30 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-10-30_final
2022-11-04 11:06:35	ga_ls8c_ard_3-2-1_108070_2022-11-04_final
2022-11-06 09:22:55	ga_ls8c_ard_3-2-1_090089_2022-11-05_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-14 11:47:59	ga_ls8c_ard_3-2-1_114081_2022-11-14_final
2022-11-15 10:50:45	ga_ls8c_ard_3-2-1_105077_2022-11-15_final
2022-11-17 10:37:34	ga_ls8c_ard_3-2-1_103075_2022-11-17_final
2022-11-18 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-11-18_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-19 10:28:00	ga_ls8c_ard_3-2-1_101082_2022-11-19_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-11-25 09:51:45	ga_ls8c_ard_3-2-1_095084_2022-11-25_final
2022-11-26 10:29:25	ga_ls8c_ard_3-2-1_102070_2022-11-26_final
2022-11-29 09:25:26	ga_ls8c_ard_3-2-1_091080_2022-11-28_final
2022-11-30 10:05:30	ga_ls8c_ard_3-2-1_098072_2022-11-30_final
2022-12-02 11:36:01	ga_ls8c_ard_3-2-1_112082_2022-12-02_final
2022-12-04 11:19:16	ga_ls8c_ard_3-2-1_110071_2022-12-04_final
2022-12-06 11:10:30	ga_ls8c_ard_3-2-1_108080_2022-12-06_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-07 11:51:45	ga_ls8c_ard_3-2-1_115075_2022-12-07_final
2022-12-16 10:05:01	ga_ls8c_ard_3-2-1_098071_2022-12-16_final
2022-12-16 10:09:48	ga_ls8c_ard_3-2-1_098083_2022-12-16_final
2022-12-22 11:11:31	ga_ls8c_ard_3-2-1_108083_2022-12-22_final
2022-12-25 10:04:20	ga_ls8c_ard_3-2-1_097085_2022-12-25_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-02 10:47:26	ga_ls8c_ard_3-2-1_105069_2023-01-02_final
2023-01-06 10:24:18	ga_ls8c_ard_3-2-1_101073_2023-01-06_final
2023-01-06 10:25:53	ga_ls8c_ard_3-2-1_101077_2023-01-06_final
2023-01-08 10:15:55	ga_ls8c_ard_3-2-1_099083_2023-01-08_final
2023-01-08 11:52:48	ga_ls8c_ard_3-2-1_115078_2023-01-08_final
2023-01-09 10:54:47	ga_ls8c_ard_3-2-1_106072_2023-01-09_final
2023-01-16 09:22:47	ga_ls8c_ard_3-2-1_091074_2023-01-15_final
2023-01-18 09:16:23	ga_ls8c_ard_3-2-1_089089_2023-01-17_final
2023-01-29 10:28:51	ga_ls8c_ard_3-2-1_102069_2023-01-29_final
2023-01-31 10:18:05	ga_ls8c_ard_3-2-1_100073_2023-01-31_final
2023-01-31 10:22:05	ga_ls8c_ard_3-2-1_100083_2023-01-31_final
2023-02-09 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-02-09_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-16 10:18:21	ga_ls8c_ard_3-2-1_100074_2023-02-16_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-18 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-02-18_final
2023-02-23 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-02-23_final
2023-02-28 09:06:24	ga_ls8c_ard_3-2-1_088080_2023-02-27_final
2023-02-28 10:40:29	ga_ls8c_ard_3-2-1_104068_2023-02-28_final
2023-02-28 10:43:17	ga_ls8c_ard_3-2-1_104075_2023-02-28_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-05 11:04:59	ga_ls8c_ard_3-2-1_107083_2023-03-05_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_2023-03-08_final
2023-03-08 11:36:14	ga_ls8c_ard_3-2-1_112084_2023-03-08_final
2023-03-14 10:55:09	ga_ls8c_ard_3-2-1_106074_2023-03-14_final
2023-03-15 09:58:44	ga_ls8c_ard_3-2-1_097072_2023-03-15_final
2023-03-15 10:03:55	ga_ls8c_ard_3-2-1_097085_2023-03-15_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-17 09:45:57	ga_ls8c_ard_3-2-1_095071_2023-03-17_final
2023-03-18 10:30:00	ga_ls8c_ard_3-2-1_102073_2023-03-18_final
2023-03-20 10:19:36	ga_ls8c_ard_3-2-1_100078_2023-03-20_final
2023-03-28 09:32:28	ga_ls8c_ard_3-2-1_092084_2023-03-28_final
2023-03-28 11:09:21	ga_ls8c_ard_3-2-1_108079_2023-03-28_final
2023-04-01 09:06:31	ga_ls8c_ard_3-2-1_088081_2023-03-31_final
2023-04-06 09:21:46	ga_ls8c_ard_3-2-1_091073_2023-04-05_final
2023-04-06 11:04:38	ga_ls8c_ard_3-2-1_107083_2023-04-06_final
2023-04-07 10:03:24	ga_ls8c_ard_3-2-1_098069_2023-04-07_final
2023-04-07 10:09:47	ga_ls8c_ard_3-2-1_098085_2023-04-07_final
2023-04-11 11:23:27	ga_ls8c_ard_3-2-1_110084_2023-04-11_final
2023-04-15 10:57:56	ga_ls8c_ard_3-2-1_106082_2023-04-15_final
2023-04-18 11:24:25	ga_ls8c_ard_3-2-1_111071_2023-04-18_final
2023-04-18 11:29:36	ga_ls8c_ard_3-2-1_111084_2023-04-18_final
2023-04-24 10:51:43	ga_ls8c_ard_3-2-1_105082_2023-04-24_final
2023-04-30 10:15:00	ga_ls8c_ard_3-2-1_099083_2023-04-30_final
2023-05-02 10:00:37	ga_ls8c_ard_3-2-1_097078_2023-05-02_final
2023-05-04 09:50:38	ga_ls8c_ard_3-2-1_095084_2023-05-04_final
2023-05-08 09:22:39	ga_ls8c_ard_3-2-1_091076_2023-05-07_final
2023-05-09 10:07:06	ga_ls8c_ard_3-2-1_098079_2023-05-09_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-10 09:15:51	ga_ls8c_ard_3-2-1_089090_2023-05-09_final
2023-05-10 10:45:57	ga_ls8c_ard_3-2-1_105068_2023-05-10_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-14 10:26:46	ga_ls8c_ard_3-2-1_101082_2023-05-14_final
2023-05-16 10:14:47	ga_ls8c_ard_3-2-1_099083_2023-05-16_final
2023-05-17 09:21:09	ga_ls8c_ard_3-2-1_090088_2023-05-16_final
2023-05-20 09:49:40	ga_ls8c_ard_3-2-1_095082_2023-05-20_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