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
2022-03-28 10:01:43	ga_ls8c_ard_3-2-1_097080_2022-03-28_final
2022-04-05 09:14:40	ga_ls8c_ard_3-2-1_089086_2022-04-04_final
2022-04-07 10:37:37	ga_ls8c_ard_3-2-1_103077_2022-04-07_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-17 11:12:46	ga_ls8c_ard_3-2-1_109072_2022-04-17_final
2022-04-18 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-04-18_final
2022-04-18 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-04-18_final
2022-04-21 09:13:08	ga_ls8c_ard_3-2-1_089082_2022-04-20_final
2022-04-21 10:46:50	ga_ls8c_ard_3-2-1_105069_2022-04-21_final
2022-04-22 09:57:35	ga_ls8c_ard_3-2-1_096085_2022-04-22_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-10 09:45:18	ga_ls8c_ard_3-2-1_094085_2022-05-10_final
2022-05-13 10:11:26	ga_ls8c_ard_3-2-1_099073_2022-05-13_final
2022-05-19 11:12:28	ga_ls8c_ard_3-2-1_109071_2022-05-19_final
2022-05-20 10:18:51	ga_ls8c_ard_3-2-1_100076_2022-05-20_final
2022-05-22 11:46:34	ga_ls8c_ard_3-2-1_114079_2022-05-22_final
2022-05-26 11:21:02	ga_ls8c_ard_3-2-1_110077_2022-05-26_final
2022-05-28 11:08:40	ga_ls8c_ard_3-2-1_108077_2022-05-28_final
2022-05-28 11:11:28	ga_ls8c_ard_3-2-1_108084_2022-05-28_final
2022-05-29 11:52:45	ga_ls8c_ard_3-2-1_115079_2022-05-29_final
2022-05-30 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-05-30_final
2022-05-31 11:41:13	ga_ls8c_ard_3-2-1_113081_2022-05-31_final
2022-06-02 09:47:36	ga_ls8c_ard_3-2-1_095075_2022-06-02_final
2022-06-16 09:59:44	ga_ls8c_ard_3-2-1_097074_2022-06-16_final
2022-06-20 09:36:39	ga_ls8c_ard_3-2-1_093078_2022-06-20_final
2022-06-20 11:17:32	ga_ls8c_ard_3-2-1_109083_2022-06-20_final
2022-06-23 10:05:10	ga_ls8c_ard_3-2-1_098072_2022-06-23_final
2022-07-02 10:02:12	ga_ls8c_ard_3-2-1_097080_2022-07-02_final
2022-07-02 11:41:53	ga_ls8c_ard_3-2-1_113082_2022-07-02_final
2022-07-09 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-07-09_final
2022-07-11 11:36:05	ga_ls8c_ard_3-2-1_112083_2022-07-11_final
2022-07-15 11:10:33	ga_ls8c_ard_3-2-1_108081_2022-07-15_final
2022-07-17 09:20:56	ga_ls8c_ard_3-2-1_090085_2022-07-16_final
2022-07-17 10:55:25	ga_ls8c_ard_3-2-1_106074_2022-07-17_final
2022-07-18 10:03:48	ga_ls8c_ard_3-2-1_097084_2022-07-18_final
2022-07-22 11:12:26	ga_ls8c_ard_3-2-1_109070_2022-07-22_final
2022-07-25 11:44:59	ga_ls8c_ard_3-2-1_114074_2022-07-25_final
2022-07-25 11:46:10	ga_ls8c_ard_3-2-1_114077_2022-07-25_final
2022-07-26 09:13:40	ga_ls8c_ard_3-2-1_089082_2022-07-25_final
2022-07-26 09:14:28	ga_ls8c_ard_3-2-1_089084_2022-07-25_final
2022-07-28 10:36:38	ga_ls8c_ard_3-2-1_103073_2022-07-28_final
2022-07-31 11:11:57	ga_ls8c_ard_3-2-1_108084_2022-07-31_final
2022-08-06 10:29:20	ga_ls8c_ard_3-2-1_102070_2022-08-06_final
2022-08-07 11:12:36	ga_ls8c_ard_3-2-1_109070_2022-08-07_final
2022-08-08 10:17:47	ga_ls8c_ard_3-2-1_100072_2022-08-08_final
2022-08-11 10:53:06	ga_ls8c_ard_3-2-1_105083_2022-08-11_final
2022-08-16 09:31:59	ga_ls8c_ard_3-2-1_092081_2022-08-16_final
2022-08-17 10:15:39	ga_ls8c_ard_3-2-1_099082_2022-08-17_final
2022-08-18 10:55:43	ga_ls8c_ard_3-2-1_106074_2022-08-18_final
2022-08-19 10:01:41	ga_ls8c_ard_3-2-1_097078_2022-08-19_final
2022-08-21 09:51:44	ga_ls8c_ard_3-2-1_095084_2022-08-21_final
2022-08-21 11:29:49	ga_ls8c_ard_3-2-1_111082_2022-08-21_final
2022-08-23 09:37:46	ga_ls8c_ard_3-2-1_093080_2022-08-23_final
2022-08-26 11:46:22	ga_ls8c_ard_3-2-1_114077_2022-08-26_final
2022-08-26 11:47:10	ga_ls8c_ard_3-2-1_114079_2022-08-26_final
2022-08-29 10:36:47	ga_ls8c_ard_3-2-1_103073_2022-08-29_final
2022-09-03 10:59:18	ga_ls8c_ard_3-2-1_106083_2022-09-03_final
2022-09-06 11:29:02	ga_ls8c_ard_3-2-1_111080_2022-09-06_final
2022-09-10 09:24:16	ga_ls8c_ard_3-2-1_091077_2022-09-09_final
2022-09-14 10:38:28	ga_ls8c_ard_3-2-1_103077_2022-09-14_final
2022-09-19 09:18:09	ga_ls8c_ard_3-2-1_090077_2022-09-18_final
2022-10-01 11:21:20	ga_ls8c_ard_3-2-1_110076_2022-10-01_final
2022-10-01 11:24:08	ga_ls8c_ard_3-2-1_110083_2022-10-01_final
2022-10-03 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-10-03_final
2022-10-03 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-10-03_final
2022-10-04 11:52:13	ga_ls8c_ard_3-2-1_115076_2022-10-04_final
2022-10-06 09:59:46	ga_ls8c_ard_3-2-1_097073_2022-10-06_final
2022-10-07 10:41:25	ga_ls8c_ard_3-2-1_104069_2022-10-07_final
2022-10-13 11:46:19	ga_ls8c_ard_3-2-1_114077_2022-10-13_final
2022-10-14 09:14:12	ga_ls8c_ard_3-2-1_089083_2022-10-13_final
2022-10-14 10:53:05	ga_ls8c_ard_3-2-1_105083_2022-10-14_final
2022-10-26 11:13:33	ga_ls8c_ard_3-2-1_109072_2022-10-26_final
2022-10-28 11:04:00	ga_ls8c_ard_3-2-1_107079_2022-10-28_final
2022-11-16 09:57:07	ga_ls8c_ard_3-2-1_096082_2022-11-16_final
2022-11-18 11:24:00	ga_ls8c_ard_3-2-1_110083_2022-11-18_final
2022-11-20 11:11:16	ga_ls8c_ard_3-2-1_108082_2022-11-20_final
2022-11-22 10:57:43	ga_ls8c_ard_3-2-1_106079_2022-11-22_final
2022-11-23 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-11-23_final
2022-11-23 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-11-23_final
2022-11-24 10:41:23	ga_ls8c_ard_3-2-1_104069_2022-11-24_final
2022-11-25 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-11-25_final
2022-12-04 11:21:40	ga_ls8c_ard_3-2-1_110077_2022-12-04_final
2022-12-05 10:25:14	ga_ls8c_ard_3-2-1_101075_2022-12-05_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-20 11:23:31	ga_ls8c_ard_3-2-1_110082_2022-12-20_final
2022-12-22 11:11:07	ga_ls8c_ard_3-2-1_108082_2022-12-22_final
2022-12-23 11:52:23	ga_ls8c_ard_3-2-1_115077_2022-12-23_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-11 10:01:53	ga_ls8c_ard_3-2-1_097079_2023-02-11_final
2023-02-16 10:18:45	ga_ls8c_ard_3-2-1_100075_2023-02-16_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-18 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-02-18_final
2023-02-28 10:40:53	ga_ls8c_ard_3-2-1_104069_2023-02-28_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_final
2023-03-11 10:25:04	ga_ls8c_ard_3-2-1_101076_2023-03-11_final
2023-05-09 10:07:30	ga_ls8c_ard_3-2-1_098080_2023-05-09_final
2023-05-19 10:39:42	ga_ls8c_ard_3-2-1_104068_2023-05-19_final
2023-05-25 10:08:14	ga_ls8c_ard_3-2-1_098082_2023-05-25_nrt
2023-05-26 10:50:18	ga_ls8c_ard_3-2-1_105079_2023-05-26_nrt

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