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
2016-02-14 09:27:13	ga_ls8c_ard_3-1-0_091086_2016-02-13_final
2018-11-18 09:27:36	ga_ls8c_ard_3-1-0_091087_2018-11-17_final
2019-03-22 09:47:59	ga_ls8c_ard_3-1-0_095077_2019-03-22_final
2019-04-07 09:47:55	ga_ls8c_ard_3-1-0_095077_2019-04-07_final
2019-04-11 09:26:22	ga_ls8c_ard_3-1-0_091085_2019-04-10_final
2019-06-14 09:19:54	ga_ls8c_ard_3-1-0_091068_2019-06-13_final
2019-06-14 09:23:06	ga_ls8c_ard_3-1-0_091076_2019-06-13_final
2019-06-26 09:48:17	ga_ls8c_ard_3-1-0_095077_2019-06-26_final
2019-06-30 09:23:11	ga_ls8c_ard_3-1-0_091076_2019-06-29_final
2019-08-29 09:48:11	ga_ls8c_ard_3-1-0_095076_2019-08-29_final
2019-08-29 09:51:23	ga_ls8c_ard_3-1-0_095084_2019-08-29_final
2019-09-14 09:51:28	ga_ls8c_ard_3-1-0_095084_2019-09-14_final
2019-09-18 09:24:46	ga_ls8c_ard_3-1-0_091079_2019-09-17_final
2019-09-30 09:50:45	ga_ls8c_ard_3-1-0_095082_2019-09-30_final
2019-10-04 09:24:50	ga_ls8c_ard_3-1-0_091079_2019-10-03_final
2019-11-01 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-11-01_final
2019-11-01 09:51:59	ga_ls8c_ard_3-1-0_095085_2019-11-01_final
2019-11-17 09:50:44	ga_ls8c_ard_3-1-0_095082_2019-11-17_final
2019-12-03 09:45:55	ga_ls8c_ard_3-1-0_095070_2019-12-03_final
2019-12-03 09:47:31	ga_ls8c_ard_3-1-0_095074_2019-12-03_final
2020-01-20 09:50:09	ga_ls8c_ard_3-1-0_095081_2020-01-20_final
2020-02-25 09:24:28	ga_ls8c_ard_3-1-0_091079_2020-02-24_final
2020-02-25 09:28:51	ga_ls8c_ard_3-1-0_091090_2020-02-24_final
2020-03-24 09:49:22	ga_ls8c_ard_3-1-0_095080_2020-03-24_final
2020-03-28 09:25:25	ga_ls8c_ard_3-1-0_091082_2020-03-27_final
2020-04-25 09:45:08	ga_ls8c_ard_3-1-0_095070_2020-04-25_final
2020-04-25 09:46:43	ga_ls8c_ard_3-1-0_095074_2020-04-25_final
2020-04-25 09:47:55	ga_ls8c_ard_3-1-0_095077_2020-04-25_final
2022-03-29 10:43:46	ga_ls8c_ard_3-2-1_104077_2022-03-29_final
2022-03-30 11:26:13	ga_ls8c_ard_3-2-1_111075_2022-03-30_final
2022-03-31 10:28:36	ga_ls8c_ard_3-2-1_102070_2022-03-31_final
2022-03-31 10:31:00	ga_ls8c_ard_3-2-1_102076_2022-03-31_final
2022-04-02 10:17:26	ga_ls8c_ard_3-2-1_100073_2022-04-02_final
2022-04-02 11:57:31	ga_ls8c_ard_3-2-1_116076_2022-04-02_final
2022-04-03 09:23:01	ga_ls8c_ard_3-2-1_091076_2022-04-02_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-06 11:36:02	ga_ls8c_ard_3-2-1_112084_2022-04-06_final
2022-04-08 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-08_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-11 10:12:08	ga_ls8c_ard_3-2-1_099075_2022-04-11_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-12 10:54:13	ga_ls8c_ard_3-2-1_106072_2022-04-12_final
2022-04-12 10:56:36	ga_ls8c_ard_3-2-1_106078_2022-04-12_final
2022-04-13 11:38:41	ga_ls8c_ard_3-2-1_113075_2022-04-13_final
2022-04-14 10:40:40	ga_ls8c_ard_3-2-1_104069_2022-04-14_final
2022-04-15 11:29:55	ga_ls8c_ard_3-2-1_111084_2022-04-15_final
2022-04-20 10:05:58	ga_ls8c_ard_3-2-1_098075_2022-04-20_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-22 11:34:52	ga_ls8c_ard_3-2-1_112081_2022-04-22_final
2022-04-22 11:35:16	ga_ls8c_ard_3-2-1_112082_2022-04-22_final
2022-04-22 11:35:40	ga_ls8c_ard_3-2-1_112083_2022-04-22_final
2022-04-23 10:37:15	ga_ls8c_ard_3-2-1_103076_2022-04-23_final
2022-04-24 09:44:25	ga_ls8c_ard_3-2-1_094083_2022-04-24_final
2022-04-26 11:06:31	ga_ls8c_ard_3-2-1_108072_2022-04-26_final
2022-04-28 10:57:20	ga_ls8c_ard_3-2-1_106080_2022-04-28_final
2022-04-29 10:00:07	ga_ls8c_ard_3-2-1_097076_2022-04-29_final
2022-04-29 11:38:36	ga_ls8c_ard_3-2-1_113075_2022-04-29_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-05 09:23:55	ga_ls8c_ard_3-2-1_091078_2022-05-04_final
2022-05-07 10:47:16	ga_ls8c_ard_3-2-1_105070_2022-05-07_final
2022-05-07 10:48:28	ga_ls8c_ard_3-2-1_105073_2022-05-07_final
2022-05-08 11:34:56	ga_ls8c_ard_3-2-1_112081_2022-05-08_final
2022-05-09 10:35:20	ga_ls8c_ard_3-2-1_103071_2022-05-09_final
2022-05-10 11:22:11	ga_ls8c_ard_3-2-1_110080_2022-05-10_final
2022-05-10 11:22:35	ga_ls8c_ard_3-2-1_110081_2022-05-10_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-12 11:07:51	ga_ls8c_ard_3-2-1_108075_2022-05-12_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-15 09:59:29	ga_ls8c_ard_3-2-1_097074_2022-05-15_final
2022-05-15 10:00:17	ga_ls8c_ard_3-2-1_097076_2022-05-15_final
2022-05-15 10:01:53	ga_ls8c_ard_3-2-1_097080_2022-05-15_final
2022-05-15 10:02:41	ga_ls8c_ard_3-2-1_097082_2022-05-15_final
2022-05-16 10:41:34	ga_ls8c_ard_3-2-1_104071_2022-05-16_final
2022-05-17 09:50:44	ga_ls8c_ard_3-2-1_095083_2022-05-17_final
2022-05-18 10:33:36	ga_ls8c_ard_3-2-1_102082_2022-05-18_final
2022-05-20 10:21:38	ga_ls8c_ard_3-2-1_100083_2022-05-20_final
2022-05-21 09:28:25	ga_ls8c_ard_3-2-1_091089_2022-05-20_final
2022-05-24 11:32:36	ga_ls8c_ard_3-2-1_112075_2022-05-24_final
2022-05-24 11:33:48	ga_ls8c_ard_3-2-1_112078_2022-05-24_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_2022-05-24_final
2022-05-26 09:40:57	ga_ls8c_ard_3-2-1_094074_2022-05-26_final
2022-05-26 09:41:21	ga_ls8c_ard_3-2-1_094075_2022-05-26_final
2022-05-26 11:23:25	ga_ls8c_ard_3-2-1_110083_2022-05-26_final
2022-05-26 11:23:49	ga_ls8c_ard_3-2-1_110084_2022-05-26_final
2022-05-30 10:54:21	ga_ls8c_ard_3-2-1_106072_2022-05-30_final
2022-06-02 09:46:25	ga_ls8c_ard_3-2-1_095072_2022-06-02_final
2022-06-02 11:26:06	ga_ls8c_ard_3-2-1_111074_2022-06-02_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-06 09:24:08	ga_ls8c_ard_3-2-1_091078_2022-06-05_final
2022-06-16 11:39:25	ga_ls8c_ard_3-2-1_113076_2022-06-16_final
2022-06-16 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-06-16_final
2022-06-18 09:50:59	ga_ls8c_ard_3-2-1_095083_2022-06-18_final
2022-06-18 11:25:05	ga_ls8c_ard_3-2-1_111071_2022-06-18_final
2022-06-19 10:31:28	ga_ls8c_ard_3-2-1_102076_2022-06-19_final
2022-06-20 09:38:14	ga_ls8c_ard_3-2-1_093082_2022-06-20_final
2022-06-20 09:39:02	ga_ls8c_ard_3-2-1_093084_2022-06-20_final
2022-06-20 11:11:56	ga_ls8c_ard_3-2-1_109069_2022-06-20_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