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
2022-11-05 11:52:39	ga_ls8c_ard_3-2-1_115077_2022-11-05_final
2022-11-06 09:20:56	ga_ls8c_ard_3-2-1_090084_2022-11-05_final
2022-11-06 10:57:49	ga_ls8c_ard_3-2-1_106079_2022-11-06_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-08 10:43:51	ga_ls8c_ard_3-2-1_104075_2022-11-08_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-16 09:56:43	ga_ls8c_ard_3-2-1_096081_2022-11-16_final
2022-11-23 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-11-23_final
2022-11-27 11:15:29	ga_ls8c_ard_3-2-1_109077_2022-11-27_final
2022-11-29 11:05:55	ga_ls8c_ard_3-2-1_107084_2022-11-29_final
2022-12-01 10:48:46	ga_ls8c_ard_3-2-1_105072_2022-12-01_final
2022-12-03 10:36:00	ga_ls8c_ard_3-2-1_103071_2022-12-03_final
2022-12-03 10:37:36	ga_ls8c_ard_3-2-1_103075_2022-12-03_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-05 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-12-05_final
2022-12-06 09:30:49	ga_ls8c_ard_3-2-1_092078_2022-12-06_final
2022-12-06 09:32:24	ga_ls8c_ard_3-2-1_092082_2022-12-06_final
2022-12-06 09:35:12	ga_ls8c_ard_3-2-1_092089_2022-12-06_final
2022-12-06 09:35:36	ga_ls8c_ard_3-2-1_092090_2022-12-06_final
2022-12-07 10:15:16	ga_ls8c_ard_3-2-1_099081_2022-12-07_final
2022-12-08 09:18:51	ga_ls8c_ard_3-2-1_090079_2022-12-07_final
2022-12-08 10:56:56	ga_ls8c_ard_3-2-1_106077_2022-12-08_final
2022-12-13 09:37:45	ga_ls8c_ard_3-2-1_093080_2022-12-13_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-14 10:20:36	ga_ls8c_ard_3-2-1_100079_2022-12-14_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-14 11:58:41	ga_ls8c_ard_3-2-1_116077_2022-12-14_final
2022-12-18 09:56:37	ga_ls8c_ard_3-2-1_096081_2022-12-18_final
2022-12-20 11:22:43	ga_ls8c_ard_3-2-1_110080_2022-12-20_final
2022-12-20 11:23:31	ga_ls8c_ard_3-2-1_110082_2022-12-20_final
2022-12-22 09:35:02	ga_ls8c_ard_3-2-1_092089_2022-12-22_final
2022-12-24 10:57:10	ga_ls8c_ard_3-2-1_106078_2022-12-24_final
2022-12-25 11:40:02	ga_ls8c_ard_3-2-1_113077_2022-12-25_final
2022-12-27 09:51:36	ga_ls8c_ard_3-2-1_095084_2022-12-27_final
2022-12-29 11:16:08	ga_ls8c_ard_3-2-1_109079_2022-12-29_final
2022-12-29 11:17:44	ga_ls8c_ard_3-2-1_109083_2022-12-29_final
2022-12-31 09:24:30	ga_ls8c_ard_3-2-1_091078_2022-12-30_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2022-12-31 09:29:17	ga_ls8c_ard_3-2-1_091090_2022-12-30_final
2023-01-01 10:06:57	ga_ls8c_ard_3-2-1_098076_2023-01-01_final
2023-01-01 11:47:02	ga_ls8c_ard_3-2-1_114079_2023-01-01_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-09 09:20:41	ga_ls8c_ard_3-2-1_090084_2023-01-08_final
2023-01-10 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-10_final
2023-01-12 09:51:09	ga_ls8c_ard_3-2-1_095083_2023-01-12_final
2023-01-13 10:32:24	ga_ls8c_ard_3-2-1_102078_2023-01-13_final
2023-01-14 09:38:46	ga_ls8c_ard_3-2-1_093083_2023-01-14_final
2023-01-14 09:39:58	ga_ls8c_ard_3-2-1_093086_2023-01-14_final
2023-01-16 11:03:40	ga_ls8c_ard_3-2-1_107079_2023-01-16_final
2023-01-17 11:46:54	ga_ls8c_ard_3-2-1_114079_2023-01-17_final
2023-01-21 09:46:08	ga_ls8c_ard_3-2-1_094086_2023-01-21_final
2023-01-21 11:22:37	ga_ls8c_ard_3-2-1_110080_2023-01-21_final
2023-01-22 10:25:25	ga_ls8c_ard_3-2-1_101076_2023-01-22_final
2023-01-22 10:27:25	ga_ls8c_ard_3-2-1_101081_2023-01-22_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-23 11:11:53	ga_ls8c_ard_3-2-1_108084_2023-01-23_final
2023-01-24 10:12:41	ga_ls8c_ard_3-2-1_099075_2023-01-24_final
2023-01-25 09:21:51	ga_ls8c_ard_3-2-1_090087_2023-01-24_final
2023-01-25 09:23:03	ga_ls8c_ard_3-2-1_090090_2023-01-24_final
2023-01-25 10:57:09	ga_ls8c_ard_3-2-1_106078_2023-01-25_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 09:40:49	ga_ls8c_ard_3-2-1_093088_2023-01-30_final
2023-01-30 11:15:42	ga_ls8c_ard_3-2-1_109078_2023-01-30_final
2023-01-31 10:21:17	ga_ls8c_ard_3-2-1_100081_2023-01-31_final
2023-02-01 09:24:28	ga_ls8c_ard_3-2-1_091078_2023-01-31_final
2023-02-06 09:44:11	ga_ls8c_ard_3-2-1_094081_2023-02-06_final
2023-02-06 11:22:40	ga_ls8c_ard_3-2-1_110080_2023-02-06_final
2023-02-10 09:23:01	ga_ls8c_ard_3-2-1_090090_2023-02-09_final
2023-02-12 10:44:19	ga_ls8c_ard_3-2-1_104077_2023-02-12_final
2023-02-13 09:51:05	ga_ls8c_ard_3-2-1_095083_2023-02-13_final
2023-02-13 09:51:53	ga_ls8c_ard_3-2-1_095085_2023-02-13_final
2023-02-15 09:39:06	ga_ls8c_ard_3-2-1_093084_2023-02-15_final
2023-02-15 09:39:54	ga_ls8c_ard_3-2-1_093086_2023-02-15_final
2023-02-16 10:18:45	ga_ls8c_ard_3-2-1_100075_2023-02-16_final
2023-02-16 10:20:21	ga_ls8c_ard_3-2-1_100079_2023-02-16_final
2023-02-17 09:24:43	ga_ls8c_ard_3-2-1_091079_2023-02-16_final
2023-02-17 09:27:30	ga_ls8c_ard_3-2-1_091086_2023-02-16_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-18 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-02-18_final
2023-02-18 11:46:50	ga_ls8c_ard_3-2-1_114079_2023-02-18_final
2023-02-19 10:52:47	ga_ls8c_ard_3-2-1_105083_2023-02-19_final
2023-02-21 10:34:48	ga_ls8c_ard_3-2-1_103069_2023-02-21_final
2023-02-21 10:38:23	ga_ls8c_ard_3-2-1_103078_2023-02-21_final
2023-02-21 10:39:11	ga_ls8c_ard_3-2-1_103080_2023-02-21_final
2023-02-22 09:43:57	ga_ls8c_ard_3-2-1_094081_2023-02-22_final
2023-02-23 10:25:11	ga_ls8c_ard_3-2-1_101076_2023-02-23_final
2023-02-24 09:32:20	ga_ls8c_ard_3-2-1_092083_2023-02-24_final
2023-02-24 09:33:31	ga_ls8c_ard_3-2-1_092086_2023-02-24_final
2023-02-25 10:11:58	ga_ls8c_ard_3-2-1_099074_2023-02-25_final
2023-02-26 09:20:21	ga_ls8c_ard_3-2-1_090084_2023-02-25_final
2023-03-01 09:47:39	ga_ls8c_ard_3-2-1_095075_2023-03-01_final
2023-03-01 09:51:39	ga_ls8c_ard_3-2-1_095085_2023-03-01_final
2023-03-03 09:39:41	ga_ls8c_ard_3-2-1_093086_2023-03-03_final
2023-03-05 09:25:18	ga_ls8c_ard_3-2-1_091081_2023-03-04_final
2023-03-08 09:54:58	ga_ls8c_ard_3-2-1_096078_2023-03-08_final
2023-03-10 09:43:48	ga_ls8c_ard_3-2-1_094081_2023-03-10_final
2023-03-13 11:51:59	ga_ls8c_ard_3-2-1_115077_2023-03-13_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