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
2022-01-14 10:06:46	ga_ls8c_ard_3-2-1_098076_2022-01-14_final
2023-01-17 11:47:42	ga_ls8c_ard_3-2-1_114081_2023-01-17_final
2023-01-19 09:57:40	ga_ls8c_ard_3-2-1_096084_2023-01-19_final
2023-01-21 09:45:20	ga_ls8c_ard_3-2-1_094084_2023-01-21_final
2023-01-21 11:21:02	ga_ls8c_ard_3-2-1_110076_2023-01-21_final
2023-01-23 09:33:24	ga_ls8c_ard_3-2-1_092085_2023-01-23_final
2023-01-30 11:15:18	ga_ls8c_ard_3-2-1_109077_2023-01-30_final
2023-02-03 09:15:17	ga_ls8c_ard_3-2-1_089086_2023-02-02_final
2023-02-13 09:52:17	ga_ls8c_ard_3-2-1_095086_2023-02-13_final
2023-02-17 11:02:00	ga_ls8c_ard_3-2-1_107075_2023-02-17_final
2023-02-23 10:23:59	ga_ls8c_ard_3-2-1_101073_2023-02-23_final
2023-02-23 10:25:35	ga_ls8c_ard_3-2-1_101077_2023-02-23_final
2023-03-07 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-03-06_final
2023-03-12 09:29:02	ga_ls8c_ard_3-2-1_092075_2023-03-11_final
2023-03-26 11:19:20	ga_ls8c_ard_3-2-1_110073_2023-03-26_final
2023-04-01 10:43:24	ga_ls8c_ard_3-2-1_104076_2023-04-01_final
2023-04-02 11:24:39	ga_ls8c_ard_3-2-1_111071_2023-04-02_final
2023-04-08 09:11:45	ga_ls8c_ard_3-2-1_089079_2023-04-07_final
2023-04-08 10:47:02	ga_ls8c_ard_3-2-1_105070_2023-04-08_final
2023-04-09 11:35:52	ga_ls8c_ard_3-2-1_112084_2023-04-09_final
2023-04-15 10:57:56	ga_ls8c_ard_3-2-1_106082_2023-04-15_final
2023-04-24 10:46:56	ga_ls8c_ard_3-2-1_105070_2023-04-24_final
2023-04-25 09:51:42	ga_ls8c_ard_3-2-1_096071_2023-04-25_final
2023-04-25 09:52:30	ga_ls8c_ard_3-2-1_096073_2023-04-25_final
2023-04-27 11:20:13	ga_ls8c_ard_3-2-1_110076_2023-04-27_final
2023-05-02 09:57:50	ga_ls8c_ard_3-2-1_097071_2023-05-02_final
2023-05-05 10:32:17	ga_ls8c_ard_3-2-1_102080_2023-05-05_final
2023-05-08 09:26:15	ga_ls8c_ard_3-2-1_091085_2023-05-07_final
2023-05-09 11:45:59	ga_ls8c_ard_3-2-1_114079_2023-05-09_final
2023-05-10 09:14:15	ga_ls8c_ard_3-2-1_089086_2023-05-09_final
2023-05-11 09:57:05	ga_ls8c_ard_3-2-1_096085_2023-05-11_final
2023-05-14 10:24:22	ga_ls8c_ard_3-2-1_101076_2023-05-14_final
2023-05-16 11:50:28	ga_ls8c_ard_3-2-1_115075_2023-05-16_final
2023-05-17 10:52:51	ga_ls8c_ard_3-2-1_106070_2023-05-17_final
2023-05-23 10:16:36	ga_ls8c_ard_3-2-1_100072_2023-05-23_final
2023-05-31 11:05:15	ga_ls8c_ard_3-2-1_108070_2023-05-31_final
2023-06-03 09:58:05	ga_ls8c_ard_3-2-1_097072_2023-06-03_final
2023-06-03 10:00:53	ga_ls8c_ard_3-2-1_097079_2023-06-03_final
2023-06-04 10:42:10	ga_ls8c_ard_3-2-1_104074_2023-06-04_final
2023-06-09 09:24:41	ga_ls8c_ard_3-2-1_091081_2023-06-08_final
2023-06-11 09:13:32	ga_ls8c_ard_3-2-1_089084_2023-06-10_final
2023-06-11 10:51:14	ga_ls8c_ard_3-2-1_105081_2023-06-11_final
2023-06-14 09:44:28	ga_ls8c_ard_3-2-1_094084_2023-06-14_final
2023-06-17 11:52:16	ga_ls8c_ard_3-2-1_115079_2023-06-17_final
2023-06-18 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-06-17_final
2023-06-18 10:54:15	ga_ls8c_ard_3-2-1_106073_2023-06-18_final
2023-06-19 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-06-19_final
2023-06-19 11:41:30	ga_ls8c_ard_3-2-1_113083_2023-06-19_final
2023-06-24 10:16:48	ga_ls8c_ard_3-2-1_100072_2023-06-24_final
2023-07-05 10:03:12	ga_ls8c_ard_3-2-1_097084_2023-07-05_final
2023-07-08 10:28:09	ga_ls8c_ard_3-2-1_102069_2023-07-08_final
2023-07-11 11:03:27	ga_ls8c_ard_3-2-1_107080_2023-07-11_final
2023-07-14 11:35:34	ga_ls8c_ard_3-2-1_112083_2023-07-14_final
2023-07-20 09:17:12	ga_ls8c_ard_3-2-1_090077_2023-07-19_final
2023-07-20 09:17:35	ga_ls8c_ard_3-2-1_090078_2023-07-19_final
2023-07-20 09:20:23	ga_ls8c_ard_3-2-1_090085_2023-07-19_final
2023-07-25 11:14:41	ga_ls8c_ard_3-2-1_109077_2023-07-25_final
2023-07-26 10:21:28	ga_ls8c_ard_3-2-1_100083_2023-07-26_final
2023-07-28 10:06:45	ga_ls8c_ard_3-2-1_098077_2023-07-28_final
2023-07-29 09:12:44	ga_ls8c_ard_3-2-1_089081_2023-07-28_final
2023-08-02 10:25:44	ga_ls8c_ard_3-2-1_101078_2023-08-02_final
2023-08-14 09:16:24	ga_ls8c_ard_3-2-1_089090_2023-08-13_final
2023-08-15 09:51:42	ga_ls8c_ard_3-2-1_096070_2023-08-15_final
2023-08-21 10:57:33	ga_ls8c_ard_3-2-1_106080_2023-08-21_final
2023-08-22 09:59:33	ga_ls8c_ard_3-2-1_097074_2023-08-22_final
2023-08-24 11:30:04	ga_ls8c_ard_3-2-1_111084_2023-08-24_final
2023-08-25 10:28:28	ga_ls8c_ard_3-2-1_102069_2023-08-25_final
2023-08-30 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-08-29_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-05 10:11:30	ga_ls8c_ard_3-2-1_099073_2023-09-05_final
2023-09-08 10:46:00	ga_ls8c_ard_3-2-1_104082_2023-09-08_final
2023-09-11 09:39:39	ga_ls8c_ard_3-2-1_093086_2023-09-11_final
2023-09-15 09:11:22	ga_ls8c_ard_3-2-1_089077_2023-09-14_final
2023-09-15 09:16:34	ga_ls8c_ard_3-2-1_089090_2023-09-14_final
2023-09-15 10:51:51	ga_ls8c_ard_3-2-1_105081_2023-09-15_final
2023-09-16 11:36:19	ga_ls8c_ard_3-2-1_112084_2023-09-16_final
2023-09-18 11:20:22	ga_ls8c_ard_3-2-1_110075_2023-09-18_final
2023-09-18 11:20:46	ga_ls8c_ard_3-2-1_110076_2023-09-18_final
2023-09-24 10:40:55	ga_ls8c_ard_3-2-1_104069_2023-09-24_final
2023-09-25 09:47:18	ga_ls8c_ard_3-2-1_095074_2023-09-25_final
2023-09-27 09:39:44	ga_ls8c_ard_3-2-1_093086_2023-09-27_final
2023-10-01 10:52:43	ga_ls8c_ard_3-2-1_105083_2023-10-01_final
2023-10-04 11:20:49	ga_ls8c_ard_3-2-1_110076_2023-10-04_final
2023-10-06 11:09:39	ga_ls8c_ard_3-2-1_108079_2023-10-06_final
2023-10-17 10:51:57	ga_ls8c_ard_3-2-1_105081_2023-10-17_final
2023-10-25 10:04:09	ga_ls8c_ard_3-2-1_097085_2023-10-25_final
2023-10-27 09:52:36	ga_ls8c_ard_3-2-1_095087_2023-10-27_final
2023-11-05 11:18:54	ga_ls8c_ard_3-2-1_110071_2023-11-05_final
2023-11-05 11:21:18	ga_ls8c_ard_3-2-1_110077_2023-11-05_final
2023-11-19 09:57:12	ga_ls8c_ard_3-2-1_096083_2023-11-19_final
2023-11-19 09:57:36	ga_ls8c_ard_3-2-1_096084_2023-11-19_final
2023-11-20 10:39:16	ga_ls8c_ard_3-2-1_103080_2023-11-20_final
2023-11-23 09:32:30	ga_ls8c_ard_3-2-1_092083_2023-11-23_final
2023-11-27 10:45:28	ga_ls8c_ard_3-2-1_104080_2023-11-27_nrt
2023-11-29 10:29:29	ga_ls8c_ard_3-2-1_102071_2023-11-29_nrt
2023-11-29 10:29:53	ga_ls8c_ard_3-2-1_102072_2023-11-29_nrt
2023-11-29 10:31:05	ga_ls8c_ard_3-2-1_102075_2023-11-29_nrt
2023-11-30 09:39:03	ga_ls8c_ard_3-2-1_093084_2023-11-30_nrt
2023-12-02 09:24:16	ga_ls8c_ard_3-2-1_091078_2023-12-01_nrt
2023-12-03 10:05:30	ga_ls8c_ard_3-2-1_098073_2023-12-03_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