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
2022-12-09 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-12-09_final
2022-12-09 11:38:11	ga_ls8c_ard_3-2-1_113072_2022-12-09_final
2022-12-09 11:39:23	ga_ls8c_ard_3-2-1_113075_2022-12-09_final
2022-12-12 10:34:10	ga_ls8c_ard_3-2-1_102082_2022-12-12_final
2022-12-16 10:08:13	ga_ls8c_ard_3-2-1_098079_2022-12-16_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-18 09:53:02	ga_ls8c_ard_3-2-1_096072_2022-12-18_final
2022-12-19 10:35:05	ga_ls8c_ard_3-2-1_103069_2022-12-19_final
2022-12-20 11:21:07	ga_ls8c_ard_3-2-1_110076_2022-12-20_final
2022-12-22 11:10:43	ga_ls8c_ard_3-2-1_108081_2022-12-22_final
2022-12-25 10:03:57	ga_ls8c_ard_3-2-1_097084_2022-12-25_final
2022-12-25 11:42:26	ga_ls8c_ard_3-2-1_113083_2022-12-25_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2022-12-29 09:36:51	ga_ls8c_ard_3-2-1_093078_2022-12-29_final
2022-12-29 11:17:20	ga_ls8c_ard_3-2-1_109082_2022-12-29_final
2023-01-01 10:08:33	ga_ls8c_ard_3-2-1_098080_2023-01-01_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-06 10:25:53	ga_ls8c_ard_3-2-1_101077_2023-01-06_final
2023-01-07 11:07:57	ga_ls8c_ard_3-2-1_108074_2023-01-07_final
2023-01-08 10:12:19	ga_ls8c_ard_3-2-1_099074_2023-01-08_final
2023-01-08 11:51:12	ga_ls8c_ard_3-2-1_115074_2023-01-08_final
2023-01-09 09:22:41	ga_ls8c_ard_3-2-1_090089_2023-01-08_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-12 11:24:03	ga_ls8c_ard_3-2-1_111068_2023-01-12_final
2023-01-14 11:15:39	ga_ls8c_ard_3-2-1_109078_2023-01-14_final
2023-01-21 09:45:20	ga_ls8c_ard_3-2-1_094084_2023-01-21_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-21 11:18:14	ga_ls8c_ard_3-2-1_110069_2023-01-21_final
2023-01-22 10:27:49	ga_ls8c_ard_3-2-1_101082_2023-01-22_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-26 10:01:32	ga_ls8c_ard_3-2-1_097078_2023-01-26_final
2023-01-26 11:39:13	ga_ls8c_ard_3-2-1_113075_2023-01-26_final
2023-01-30 11:15:18	ga_ls8c_ard_3-2-1_109077_2023-01-30_final
2023-02-01 09:28:27	ga_ls8c_ard_3-2-1_091088_2023-01-31_final
2023-02-06 09:46:35	ga_ls8c_ard_3-2-1_094087_2023-02-06_final
2023-02-06 11:21:04	ga_ls8c_ard_3-2-1_110076_2023-02-06_final
2023-02-07 10:24:39	ga_ls8c_ard_3-2-1_101074_2023-02-07_final
2023-02-08 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-02-08_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-11 09:59:29	ga_ls8c_ard_3-2-1_097073_2023-02-11_final
2023-02-14 10:33:56	ga_ls8c_ard_3-2-1_102082_2023-02-14_final
2023-02-16 10:21:57	ga_ls8c_ard_3-2-1_100083_2023-02-16_final
2023-02-17 09:28:42	ga_ls8c_ard_3-2-1_091089_2023-02-16_final
2023-02-17 11:05:35	ga_ls8c_ard_3-2-1_107084_2023-02-17_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-02-23 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-02-23_final
2023-02-23 10:27:35	ga_ls8c_ard_3-2-1_101082_2023-02-23_final
2023-02-25 10:15:34	ga_ls8c_ard_3-2-1_099083_2023-02-25_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-01 11:30:08	ga_ls8c_ard_3-2-1_111084_2023-03-01_final
2023-03-02 10:28:31	ga_ls8c_ard_3-2-1_102069_2023-03-02_final
2023-03-03 11:14:34	ga_ls8c_ard_3-2-1_109076_2023-03-03_final
2023-03-04 11:57:49	ga_ls8c_ard_3-2-1_116076_2023-03-04_final
2023-03-06 10:06:57	ga_ls8c_ard_3-2-1_098077_2023-03-06_final
2023-03-07 09:16:06	ga_ls8c_ard_3-2-1_089089_2023-03-06_final
2023-03-07 10:49:00	ga_ls8c_ard_3-2-1_105074_2023-03-07_final
2023-03-07 10:49:24	ga_ls8c_ard_3-2-1_105075_2023-03-07_final
2023-03-14 10:54:45	ga_ls8c_ard_3-2-1_106073_2023-03-14_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-17 11:29:13	ga_ls8c_ard_3-2-1_111082_2023-03-17_final
2023-03-21 09:27:09	ga_ls8c_ard_3-2-1_091086_2023-03-20_final
2023-03-21 09:28:45	ga_ls8c_ard_3-2-1_091090_2023-03-20_final
2023-03-25 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-03-25_final
2023-03-28 09:30:52	ga_ls8c_ard_3-2-1_092080_2023-03-28_final
2023-03-30 10:53:47	ga_ls8c_ard_3-2-1_106071_2023-03-30_final
2023-04-02 09:45:46	ga_ls8c_ard_3-2-1_095071_2023-04-02_final
2023-04-04 11:15:27	ga_ls8c_ard_3-2-1_109079_2023-04-04_final
2023-04-04 11:15:50	ga_ls8c_ard_3-2-1_109080_2023-04-04_final
2023-04-06 09:25:21	ga_ls8c_ard_3-2-1_091082_2023-04-05_final
2023-04-06 09:26:33	ga_ls8c_ard_3-2-1_091085_2023-04-05_final
2023-04-06 11:01:27	ga_ls8c_ard_3-2-1_107075_2023-04-06_final
2023-04-09 11:31:28	ga_ls8c_ard_3-2-1_112073_2023-04-09_final
2023-04-11 09:39:23	ga_ls8c_ard_3-2-1_094071_2023-04-11_final
2023-04-12 10:24:15	ga_ls8c_ard_3-2-1_101075_2023-04-12_final
2023-04-15 10:54:44	ga_ls8c_ard_3-2-1_106074_2023-04-15_final
2023-04-16 09:58:19	ga_ls8c_ard_3-2-1_097072_2023-04-16_final
2023-04-17 09:07:04	ga_ls8c_ard_3-2-1_088083_2023-04-16_final
2023-04-18 11:25:37	ga_ls8c_ard_3-2-1_111074_2023-04-18_final
2023-04-20 09:33:33	ga_ls8c_ard_3-2-1_093072_2023-04-20_final
2023-04-20 11:11:38	ga_ls8c_ard_3-2-1_109070_2023-04-20_final
2023-04-21 10:16:49	ga_ls8c_ard_3-2-1_100072_2023-04-21_final
2023-04-25 09:51:42	ga_ls8c_ard_3-2-1_096071_2023-04-25_final
2023-04-25 09:56:53	ga_ls8c_ard_3-2-1_096084_2023-04-25_final
2023-04-26 10:37:45	ga_ls8c_ard_3-2-1_103078_2023-04-26_final
2023-04-27 11:20:13	ga_ls8c_ard_3-2-1_110076_2023-04-27_final
2023-05-05 10:27:54	ga_ls8c_ard_3-2-1_102069_2023-05-05_final
2023-05-13 09:39:55	ga_ls8c_ard_3-2-1_094073_2023-05-13_final
2023-05-13 11:21:59	ga_ls8c_ard_3-2-1_110081_2023-05-13_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_2023-05-15_final
2023-05-16 11:50:28	ga_ls8c_ard_3-2-1_115075_2023-05-16_final
2023-05-16 11:52:04	ga_ls8c_ard_3-2-1_115079_2023-05-16_final
2023-05-17 10:52:51	ga_ls8c_ard_3-2-1_106070_2023-05-17_final
2023-05-18 09:58:01	ga_ls8c_ard_3-2-1_097072_2023-05-18_final
2023-05-19 09:06:00	ga_ls8c_ard_3-2-1_088081_2023-05-18_final
2023-05-20 09:50:28	ga_ls8c_ard_3-2-1_095084_2023-05-20_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-24 09:24:35	ga_ls8c_ard_3-2-1_091081_2023-05-23_final
2023-05-24 10:59:28	ga_ls8c_ard_3-2-1_107071_2023-05-24_final
2023-05-24 11:03:04	ga_ls8c_ard_3-2-1_107080_2023-05-24_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