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
2022-09-28 10:52:50	ga_ls8c_ard_3-2-1_105082_2022-09-28_final
2022-10-05 10:58:59	ga_ls8c_ard_3-2-1_106082_2022-10-05_final
2022-10-08 11:27:04	ga_ls8c_ard_3-2-1_111075_2022-10-08_final
2022-10-08 11:30:39	ga_ls8c_ard_3-2-1_111084_2022-10-08_final
2022-10-10 09:36:59	ga_ls8c_ard_3-2-1_093078_2022-10-10_final
2022-10-11 10:18:14	ga_ls8c_ard_3-2-1_100073_2022-10-11_final
2022-10-13 10:05:50	ga_ls8c_ard_3-2-1_098073_2022-10-13_final
2022-10-17 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-10-17_final
2022-10-17 11:24:02	ga_ls8c_ard_3-2-1_110083_2022-10-17_final
2022-10-18 10:26:49	ga_ls8c_ard_3-2-1_101079_2022-10-18_final
2022-10-19 11:07:18	ga_ls8c_ard_3-2-1_108072_2022-10-19_final
2022-10-19 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-10-19_final
2022-10-21 10:58:09	ga_ls8c_ard_3-2-1_106080_2022-10-21_final
2022-10-23 10:43:25	ga_ls8c_ard_3-2-1_104074_2022-10-23_final
2022-10-24 09:46:37	ga_ls8c_ard_3-2-1_095071_2022-10-24_final
2022-10-27 10:20:43	ga_ls8c_ard_3-2-1_100079_2022-10-27_final
2022-11-01 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-11-01_final
2022-11-01 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-11-01_final
2022-11-02 11:22:57	ga_ls8c_ard_3-2-1_110080_2022-11-02_final
2022-11-03 10:24:32	ga_ls8c_ard_3-2-1_101073_2022-11-03_final
2022-11-03 10:27:43	ga_ls8c_ard_3-2-1_101081_2022-11-03_final
2022-11-04 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-11-04_final
2022-11-07 10:04:35	ga_ls8c_ard_3-2-1_097085_2022-11-07_final
2022-11-07 11:39:52	ga_ls8c_ard_3-2-1_113076_2022-11-07_final
2022-11-07 11:40:16	ga_ls8c_ard_3-2-1_113077_2022-11-07_final
2022-11-09 11:29:06	ga_ls8c_ard_3-2-1_111080_2022-11-09_final
2022-11-11 09:38:14	ga_ls8c_ard_3-2-1_093081_2022-11-11_final
2022-11-12 10:21:29	ga_ls8c_ard_3-2-1_100081_2022-11-12_final
2022-11-12 11:58:46	ga_ls8c_ard_3-2-1_116077_2022-11-12_final
2022-11-13 11:02:20	ga_ls8c_ard_3-2-1_107075_2022-11-13_final
2022-11-16 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-11-16_final
2022-11-18 09:41:56	ga_ls8c_ard_3-2-1_094075_2022-11-18_final
2022-11-19 10:25:12	ga_ls8c_ard_3-2-1_101075_2022-11-19_final
2022-11-20 09:31:11	ga_ls8c_ard_3-2-1_092079_2022-11-20_final
2022-11-20 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-11-20_final
2022-11-21 10:12:51	ga_ls8c_ard_3-2-1_099075_2022-11-21_final
2022-11-27 11:17:05	ga_ls8c_ard_3-2-1_109081_2022-11-27_final
2022-12-01 10:48:46	ga_ls8c_ard_3-2-1_105072_2022-12-01_final
2022-12-04 09:41:59	ga_ls8c_ard_3-2-1_094075_2022-12-04_final
2022-12-06 09:30:49	ga_ls8c_ard_3-2-1_092078_2022-12-06_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-07 10:12:52	ga_ls8c_ard_3-2-1_099075_2022-12-07_final
2022-12-07 10:15:16	ga_ls8c_ard_3-2-1_099081_2022-12-07_final
2022-12-12 10:32:35	ga_ls8c_ard_3-2-1_102078_2022-12-12_final
2022-12-12 10:32:59	ga_ls8c_ard_3-2-1_102079_2022-12-12_final
2022-12-13 09:37:45	ga_ls8c_ard_3-2-1_093080_2022-12-13_final
2022-12-13 11:15:50	ga_ls8c_ard_3-2-1_109078_2022-12-13_final
2022-12-15 09:24:58	ga_ls8c_ard_3-2-1_091079_2022-12-14_final
2022-12-16 10:06:37	ga_ls8c_ard_3-2-1_098075_2022-12-16_final
2022-12-17 10:49:04	ga_ls8c_ard_3-2-1_105073_2022-12-17_final
2022-12-18 11:35:54	ga_ls8c_ard_3-2-1_112082_2022-12-18_final
2022-12-20 11:23:07	ga_ls8c_ard_3-2-1_110081_2022-12-20_final
2022-12-21 10:25:29	ga_ls8c_ard_3-2-1_101076_2022-12-21_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2022-12-27 11:28:05	ga_ls8c_ard_3-2-1_111078_2022-12-27_final
2022-12-29 11:16:56	ga_ls8c_ard_3-2-1_109081_2022-12-29_final
2022-12-29 11:17:44	ga_ls8c_ard_3-2-1_109083_2022-12-29_final
2022-12-30 11:58:36	ga_ls8c_ard_3-2-1_116077_2022-12-30_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2022-12-31 11:03:23	ga_ls8c_ard_3-2-1_107078_2022-12-31_final
2023-01-05 11:22:43	ga_ls8c_ard_3-2-1_110080_2023-01-05_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-09 10:59:10	ga_ls8c_ard_3-2-1_106083_2023-01-09_final
2023-01-10 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-10_final
2023-01-10 11:42:01	ga_ls8c_ard_3-2-1_113082_2023-01-10_final
2023-01-11 10:42:24	ga_ls8c_ard_3-2-1_104072_2023-01-11_final
2023-01-12 11:27:15	ga_ls8c_ard_3-2-1_111076_2023-01-12_final
2023-01-12 11:27:39	ga_ls8c_ard_3-2-1_111077_2023-01-12_final
2023-01-12 11:30:02	ga_ls8c_ard_3-2-1_111083_2023-01-12_final
2023-01-13 10:34:00	ga_ls8c_ard_3-2-1_102082_2023-01-13_final
2023-01-14 09:38:46	ga_ls8c_ard_3-2-1_093083_2023-01-14_final
2023-01-15 11:58:30	ga_ls8c_ard_3-2-1_116077_2023-01-15_final
2023-01-16 09:24:47	ga_ls8c_ard_3-2-1_091079_2023-01-15_final
2023-01-19 11:35:45	ga_ls8c_ard_3-2-1_112082_2023-01-19_final
2023-01-20 10:34:57	ga_ls8c_ard_3-2-1_103069_2023-01-20_final
2023-01-21 11:23:01	ga_ls8c_ard_3-2-1_110081_2023-01-21_final
2023-01-22 10:26:37	ga_ls8c_ard_3-2-1_101079_2023-01-22_final
2023-01-24 10:12:41	ga_ls8c_ard_3-2-1_099075_2023-01-24_final
2023-01-26 11:40:01	ga_ls8c_ard_3-2-1_113077_2023-01-26_final
2023-01-31 10:21:41	ga_ls8c_ard_3-2-1_100082_2023-01-31_final
2023-01-31 11:58:58	ga_ls8c_ard_3-2-1_116078_2023-01-31_final
2023-02-01 09:26:03	ga_ls8c_ard_3-2-1_091082_2023-01-31_final
2023-02-05 10:36:37	ga_ls8c_ard_3-2-1_103073_2023-02-05_final
2023-02-06 11:23:04	ga_ls8c_ard_3-2-1_110081_2023-02-06_final
2023-02-08 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-02-08_final
2023-02-11 10:01:05	ga_ls8c_ard_3-2-1_097077_2023-02-11_final
2023-02-13 09:47:53	ga_ls8c_ard_3-2-1_095075_2023-02-13_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-20 09:57:09	ga_ls8c_ard_3-2-1_096083_2023-02-20_final
2023-02-22 09:42:21	ga_ls8c_ard_3-2-1_094077_2023-02-22_final
2023-02-26 10:57:14	ga_ls8c_ard_3-2-1_106079_2023-02-26_final
2023-02-27 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-02-27_final
2023-02-27 11:39:18	ga_ls8c_ard_3-2-1_113076_2023-02-27_final
2023-02-28 10:43:41	ga_ls8c_ard_3-2-1_104076_2023-02-28_final
2023-03-01 09:47:39	ga_ls8c_ard_3-2-1_095075_2023-03-01_final
2023-03-01 11:28:32	ga_ls8c_ard_3-2-1_111080_2023-03-01_final
2023-03-03 09:38:53	ga_ls8c_ard_3-2-1_093084_2023-03-03_final
2023-03-05 11:04:35	ga_ls8c_ard_3-2-1_107082_2023-03-05_final
2023-03-12 09:32:38	ga_ls8c_ard_3-2-1_092084_2023-03-12_final
2023-03-16 10:42:47	ga_ls8c_ard_3-2-1_104074_2023-03-16_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