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
2022-11-06 09:18:56	ga_ls8c_ard_3-2-1_090079_2022-11-05_final
2022-11-06 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-11-05_final
2022-11-06 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-11-06_final
2022-11-07 10:00:59	ga_ls8c_ard_3-2-1_097076_2022-11-07_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-08 10:43:27	ga_ls8c_ard_3-2-1_104074_2022-11-08_final
2022-11-16 09:53:07	ga_ls8c_ard_3-2-1_096072_2022-11-16_final
2022-11-16 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-11-16_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-18 09:43:55	ga_ls8c_ard_3-2-1_094080_2022-11-18_final
2022-11-21 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-11-21_final
2022-11-22 09:18:50	ga_ls8c_ard_3-2-1_090079_2022-11-21_final
2022-11-22 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-11-21_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-22 09:20:26	ga_ls8c_ard_3-2-1_090083_2022-11-21_final
2022-11-22 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-11-21_final
2022-11-23 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-11-23_final
2022-11-23 11:40:59	ga_ls8c_ard_3-2-1_113079_2022-11-23_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-09 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-12-09_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-10 10:45:21	ga_ls8c_ard_3-2-1_104079_2022-12-10_final
2022-12-11 09:51:43	ga_ls8c_ard_3-2-1_095084_2022-12-11_final
2022-12-15 11:03:51	ga_ls8c_ard_3-2-1_107079_2022-12-15_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-16 11:45:30	ga_ls8c_ard_3-2-1_114075_2022-12-16_final
2022-12-17 10:47:28	ga_ls8c_ard_3-2-1_105069_2022-12-17_final
2022-12-20 09:41:50	ga_ls8c_ard_3-2-1_094075_2022-12-20_final
2022-12-25 10:03:09	ga_ls8c_ard_3-2-1_097082_2022-12-25_final
2022-12-28 10:31:16	ga_ls8c_ard_3-2-1_102075_2022-12-28_final
2022-12-28 10:34:04	ga_ls8c_ard_3-2-1_102082_2022-12-28_final
2022-12-30 10:22:06	ga_ls8c_ard_3-2-1_100083_2022-12-30_final
2023-01-01 11:47:02	ga_ls8c_ard_3-2-1_114079_2023-01-01_final
2023-01-02 09:11:44	ga_ls8c_ard_3-2-1_089077_2023-01-01_final
2023-01-06 10:24:41	ga_ls8c_ard_3-2-1_101074_2023-01-06_final
2023-01-06 10:25:05	ga_ls8c_ard_3-2-1_101075_2023-01-06_final
2023-01-06 10:25:29	ga_ls8c_ard_3-2-1_101076_2023-01-06_final
2023-01-09 09:20:17	ga_ls8c_ard_3-2-1_090083_2023-01-08_final
2023-01-09 09:20:41	ga_ls8c_ard_3-2-1_090084_2023-01-08_final
2023-01-09 10:57:34	ga_ls8c_ard_3-2-1_106079_2023-01-09_final
2023-01-10 10:00:21	ga_ls8c_ard_3-2-1_097075_2023-01-10_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-11 10:43:12	ga_ls8c_ard_3-2-1_104074_2023-01-11_final
2023-01-11 10:45:35	ga_ls8c_ard_3-2-1_104080_2023-01-11_final
2023-01-12 09:50:21	ga_ls8c_ard_3-2-1_095081_2023-01-12_final
2023-01-12 11:30:02	ga_ls8c_ard_3-2-1_111083_2023-01-12_final
2023-01-14 09:39:58	ga_ls8c_ard_3-2-1_093086_2023-01-14_final
2023-01-14 09:40:22	ga_ls8c_ard_3-2-1_093087_2023-01-14_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-16 11:04:03	ga_ls8c_ard_3-2-1_107080_2023-01-16_final
2023-01-17 10:06:49	ga_ls8c_ard_3-2-1_098076_2023-01-17_final
2023-01-17 10:08:49	ga_ls8c_ard_3-2-1_098081_2023-01-17_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-21 09:45:20	ga_ls8c_ard_3-2-1_094084_2023-01-21_final
2023-01-21 11:22:37	ga_ls8c_ard_3-2-1_110080_2023-01-21_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-01-23 09:30:12	ga_ls8c_ard_3-2-1_092077_2023-01-23_final
2023-01-23 09:32:12	ga_ls8c_ard_3-2-1_092082_2023-01-23_final
2023-01-25 09:20:15	ga_ls8c_ard_3-2-1_090083_2023-01-24_final
2023-01-25 10:56:45	ga_ls8c_ard_3-2-1_106077_2023-01-25_final
2023-01-25 10:57:56	ga_ls8c_ard_3-2-1_106080_2023-01-25_final
2023-02-01 09:26:03	ga_ls8c_ard_3-2-1_091082_2023-01-31_final
2023-02-05 10:39:01	ga_ls8c_ard_3-2-1_103079_2023-02-05_final
2023-02-06 09:45:47	ga_ls8c_ard_3-2-1_094085_2023-02-06_final
2023-02-07 10:24:15	ga_ls8c_ard_3-2-1_101073_2023-02-07_final
2023-02-07 10:27:50	ga_ls8c_ard_3-2-1_101082_2023-02-07_final
2023-02-08 11:07:06	ga_ls8c_ard_3-2-1_108072_2023-02-08_final
2023-02-09 10:15:52	ga_ls8c_ard_3-2-1_099083_2023-02-09_final
2023-02-09 10:16:39	ga_ls8c_ard_3-2-1_099085_2023-02-09_final
2023-02-10 09:20:14	ga_ls8c_ard_3-2-1_090083_2023-02-09_final
2023-02-10 09:20:37	ga_ls8c_ard_3-2-1_090084_2023-02-09_final
2023-02-11 11:39:58	ga_ls8c_ard_3-2-1_113077_2023-02-11_final
2023-02-11 11:40:46	ga_ls8c_ard_3-2-1_113079_2023-02-11_final
2023-02-11 11:41:33	ga_ls8c_ard_3-2-1_113081_2023-02-11_final
2023-02-13 09:47:05	ga_ls8c_ard_3-2-1_095073_2023-02-13_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-15 11:15:35	ga_ls8c_ard_3-2-1_109078_2023-02-15_final
2023-02-16 10:19:09	ga_ls8c_ard_3-2-1_100076_2023-02-16_final
2023-02-17 11:04:47	ga_ls8c_ard_3-2-1_107082_2023-02-17_final
2023-02-18 10:08:45	ga_ls8c_ard_3-2-1_098081_2023-02-18_final
2023-02-18 11:45:14	ga_ls8c_ard_3-2-1_114075_2023-02-18_final
2023-02-20 09:57:09	ga_ls8c_ard_3-2-1_096083_2023-02-20_final
2023-02-22 09:41:33	ga_ls8c_ard_3-2-1_094075_2023-02-22_final
2023-02-22 09:44:44	ga_ls8c_ard_3-2-1_094083_2023-02-22_final
2023-02-26 10:56:50	ga_ls8c_ard_3-2-1_106078_2023-02-26_final
2023-02-27 10:00:01	ga_ls8c_ard_3-2-1_097075_2023-02-27_final
2023-02-27 11:39:18	ga_ls8c_ard_3-2-1_113076_2023-02-27_final
2023-02-27 11:40:30	ga_ls8c_ard_3-2-1_113079_2023-02-27_final
2023-03-01 09:51:15	ga_ls8c_ard_3-2-1_095084_2023-03-01_final
2023-03-02 10:32:54	ga_ls8c_ard_3-2-1_102080_2023-03-02_final
2023-03-05 09:24:30	ga_ls8c_ard_3-2-1_091079_2023-03-04_final
2023-03-06 10:08:33	ga_ls8c_ard_3-2-1_098081_2023-03-06_final
2023-03-08 09:56:33	ga_ls8c_ard_3-2-1_096082_2023-03-08_final
2023-03-10 11:20:17	ga_ls8c_ard_3-2-1_110075_2023-03-10_final
2023-03-10 11:22:41	ga_ls8c_ard_3-2-1_110081_2023-03-10_final
2023-03-11 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-03-11_final
2023-03-13 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-03-13_final
2023-03-14 09:20:40	ga_ls8c_ard_3-2-1_090085_2023-03-13_final
2023-03-14 10:54:45	ga_ls8c_ard_3-2-1_106073_2023-03-14_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