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
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-07 11:41:28	ga_ls8c_ard_3-2-1_113080_2022-11-07_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-22 10:58:07	ga_ls8c_ard_3-2-1_106080_2022-11-22_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-24 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-11-24_final
2022-12-02 11:35:37	ga_ls8c_ard_3-2-1_112081_2022-12-02_final
2022-12-03 10:36:00	ga_ls8c_ard_3-2-1_103071_2022-12-03_final
2022-12-03 10:37:12	ga_ls8c_ard_3-2-1_103074_2022-12-03_final
2022-12-10 10:42:10	ga_ls8c_ard_3-2-1_104071_2022-12-10_final
2022-12-10 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-12-10_final
2022-12-11 09:50:55	ga_ls8c_ard_3-2-1_095082_2022-12-11_final
2022-12-11 09:51:19	ga_ls8c_ard_3-2-1_095083_2022-12-11_final
2022-12-12 10:31:23	ga_ls8c_ard_3-2-1_102075_2022-12-12_final
2022-12-12 10:32:59	ga_ls8c_ard_3-2-1_102079_2022-12-12_final
2022-12-13 11:15:50	ga_ls8c_ard_3-2-1_109078_2022-12-13_final
2022-12-14 10:21:48	ga_ls8c_ard_3-2-1_100082_2022-12-14_final
2022-12-15 11:03:03	ga_ls8c_ard_3-2-1_107077_2022-12-15_final
2022-12-19 10:37:04	ga_ls8c_ard_3-2-1_103074_2022-12-19_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-20 09:45:02	ga_ls8c_ard_3-2-1_094083_2022-12-20_final
2022-12-21 10:25:29	ga_ls8c_ard_3-2-1_101076_2022-12-21_final
2022-12-23 10:15:05	ga_ls8c_ard_3-2-1_099081_2022-12-23_final
2022-12-24 10:57:58	ga_ls8c_ard_3-2-1_106080_2022-12-24_final
2022-12-25 10:03:33	ga_ls8c_ard_3-2-1_097083_2022-12-25_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2022-12-27 09:52:24	ga_ls8c_ard_3-2-1_095086_2022-12-27_final
2022-12-28 10:32:52	ga_ls8c_ard_3-2-1_102079_2022-12-28_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2023-01-03 09:54:12	ga_ls8c_ard_3-2-1_096075_2023-01-03_final
2023-01-03 09:56:35	ga_ls8c_ard_3-2-1_096081_2023-01-03_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-05 09:46:13	ga_ls8c_ard_3-2-1_094086_2023-01-05_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-07 09:32:15	ga_ls8c_ard_3-2-1_092082_2023-01-07_final
2023-01-07 11:10:20	ga_ls8c_ard_3-2-1_108080_2023-01-07_final
2023-01-09 10:56:46	ga_ls8c_ard_3-2-1_106077_2023-01-09_final
2023-01-11 10:42:24	ga_ls8c_ard_3-2-1_104072_2023-01-11_final
2023-01-12 09:51:33	ga_ls8c_ard_3-2-1_095084_2023-01-12_final
2023-01-13 10:32:48	ga_ls8c_ard_3-2-1_102079_2023-01-13_final
2023-01-14 09:38:46	ga_ls8c_ard_3-2-1_093083_2023-01-14_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-14 09:39:58	ga_ls8c_ard_3-2-1_093086_2023-01-14_final
2023-01-14 11:16:03	ga_ls8c_ard_3-2-1_109079_2023-01-14_final
2023-01-16 11:02:52	ga_ls8c_ard_3-2-1_107077_2023-01-16_final
2023-01-18 10:51:16	ga_ls8c_ard_3-2-1_105079_2023-01-18_final
2023-01-19 11:35:45	ga_ls8c_ard_3-2-1_112082_2023-01-19_final
2023-01-20 10:36:33	ga_ls8c_ard_3-2-1_103073_2023-01-20_final
2023-01-21 09:43:20	ga_ls8c_ard_3-2-1_094079_2023-01-21_final
2023-01-21 09:43:44	ga_ls8c_ard_3-2-1_094080_2023-01-21_final
2023-01-23 09:31:00	ga_ls8c_ard_3-2-1_092079_2023-01-23_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-23 11:10:17	ga_ls8c_ard_3-2-1_108080_2023-01-23_final
2023-01-24 10:12:17	ga_ls8c_ard_3-2-1_099074_2023-01-24_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-25 10:58:20	ga_ls8c_ard_3-2-1_106081_2023-01-25_final
2023-01-26 10:00:20	ga_ls8c_ard_3-2-1_097075_2023-01-26_final
2023-01-26 10:03:07	ga_ls8c_ard_3-2-1_097082_2023-01-26_final
2023-01-26 11:42:00	ga_ls8c_ard_3-2-1_113082_2023-01-26_final
2023-01-30 11:18:06	ga_ls8c_ard_3-2-1_109084_2023-01-30_final
2023-01-31 10:20:29	ga_ls8c_ard_3-2-1_100079_2023-01-31_final
2023-01-31 10:21:17	ga_ls8c_ard_3-2-1_100081_2023-01-31_final
2023-02-05 10:38:37	ga_ls8c_ard_3-2-1_103078_2023-02-05_final
2023-02-06 09:46:11	ga_ls8c_ard_3-2-1_094086_2023-02-06_final
2023-02-07 10:26:15	ga_ls8c_ard_3-2-1_101078_2023-02-07_final
2023-02-08 11:10:42	ga_ls8c_ard_3-2-1_108081_2023-02-08_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-11 11:39:34	ga_ls8c_ard_3-2-1_113076_2023-02-11_final
2023-02-12 10:45:31	ga_ls8c_ard_3-2-1_104080_2023-02-12_final
2023-02-13 09:48:41	ga_ls8c_ard_3-2-1_095077_2023-02-13_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-15 09:39:06	ga_ls8c_ard_3-2-1_093084_2023-02-15_final
2023-02-15 09:40:18	ga_ls8c_ard_3-2-1_093087_2023-02-15_final
2023-02-16 10:21:33	ga_ls8c_ard_3-2-1_100082_2023-02-16_final
2023-02-16 11:58:26	ga_ls8c_ard_3-2-1_116077_2023-02-16_final
2023-02-17 11:00:00	ga_ls8c_ard_3-2-1_107070_2023-02-17_final
2023-02-20 11:34:02	ga_ls8c_ard_3-2-1_112078_2023-02-20_final
2023-02-20 11:35:38	ga_ls8c_ard_3-2-1_112082_2023-02-20_final
2023-02-21 10:38:47	ga_ls8c_ard_3-2-1_103079_2023-02-21_final
2023-02-24 09:31:08	ga_ls8c_ard_3-2-1_092080_2023-02-24_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-02-25 11:50:52	ga_ls8c_ard_3-2-1_115074_2023-02-25_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-02-27 10:02:25	ga_ls8c_ard_3-2-1_097081_2023-02-27_final
2023-02-27 11:40:06	ga_ls8c_ard_3-2-1_113078_2023-02-27_final
2023-02-28 10:44:05	ga_ls8c_ard_3-2-1_104077_2023-02-28_final
2023-02-28 10:44:53	ga_ls8c_ard_3-2-1_104079_2023-02-28_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-02 10:32:07	ga_ls8c_ard_3-2-1_102078_2023-03-02_final
2023-03-03 09:38:53	ga_ls8c_ard_3-2-1_093084_2023-03-03_final
2023-03-03 11:16:34	ga_ls8c_ard_3-2-1_109081_2023-03-03_final
2023-03-04 11:58:13	ga_ls8c_ard_3-2-1_116077_2023-03-04_final
2023-03-05 09:25:42	ga_ls8c_ard_3-2-1_091082_2023-03-04_final
2023-03-10 09:44:59	ga_ls8c_ard_3-2-1_094084_2023-03-10_final
2023-03-12 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-03-12_final
2023-03-12 11:10:19	ga_ls8c_ard_3-2-1_108081_2023-03-12_final
2023-03-12 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-03-12_final
2023-03-12 11:11:31	ga_ls8c_ard_3-2-1_108084_2023-03-12_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