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
2022-06-21 10:21:54	ga_ls8c_ard_3-2-1_100083_2022-06-21_final
2022-06-25 09:58:00	ga_ls8c_ard_3-2-1_096085_2022-06-25_final
2022-07-03 09:07:23	ga_ls8c_ard_3-2-1_088082_2022-07-02_final
2022-07-07 10:21:32	ga_ls8c_ard_3-2-1_100082_2022-07-07_final
2022-07-08 11:01:36	ga_ls8c_ard_3-2-1_107074_2022-07-08_final
2022-07-09 10:07:35	ga_ls8c_ard_3-2-1_098078_2022-07-09_final
2022-07-15 11:07:22	ga_ls8c_ard_3-2-1_108073_2022-07-15_final
2022-07-23 10:17:14	ga_ls8c_ard_3-2-1_100071_2022-07-23_final
2022-07-25 10:04:30	ga_ls8c_ard_3-2-1_098070_2022-07-25_final
2022-07-31 11:07:34	ga_ls8c_ard_3-2-1_108073_2022-07-31_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-08-06 10:29:44	ga_ls8c_ard_3-2-1_102071_2022-08-06_final
2022-08-06 10:30:32	ga_ls8c_ard_3-2-1_102073_2022-08-06_final
2022-08-09 11:01:51	ga_ls8c_ard_3-2-1_107074_2022-08-09_final
2022-08-11 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-08-11_final
2022-08-13 10:38:21	ga_ls8c_ard_3-2-1_103077_2022-08-13_final
2022-08-16 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-08-16_final
2022-08-19 10:04:29	ga_ls8c_ard_3-2-1_097085_2022-08-19_final
2022-08-20 09:07:16	ga_ls8c_ard_3-2-1_088081_2022-08-19_final
2022-08-23 09:40:34	ga_ls8c_ard_3-2-1_093087_2022-08-23_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-08-29 10:35:11	ga_ls8c_ard_3-2-1_103069_2022-08-29_final
2022-09-04 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-09-04_final
2022-09-06 11:28:14	ga_ls8c_ard_3-2-1_111078_2022-09-06_final
2022-09-07 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-09-07_final
2022-09-07 10:33:26	ga_ls8c_ard_3-2-1_102080_2022-09-07_final
2022-09-08 11:17:30	ga_ls8c_ard_3-2-1_109082_2022-09-08_final
2022-09-09 10:22:17	ga_ls8c_ard_3-2-1_100083_2022-09-09_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-13 11:36:29	ga_ls8c_ard_3-2-1_112083_2022-09-13_final
2022-09-15 09:41:15	ga_ls8c_ard_3-2-1_094073_2022-09-15_final
2022-09-15 09:46:26	ga_ls8c_ard_3-2-1_094086_2022-09-15_final
2022-09-17 09:34:29	ga_ls8c_ard_3-2-1_092087_2022-09-17_final
2022-09-27 10:07:59	ga_ls8c_ard_3-2-1_098078_2022-09-27_final
2022-10-02 10:25:19	ga_ls8c_ard_3-2-1_101075_2022-10-02_final
2022-10-03 11:07:46	ga_ls8c_ard_3-2-1_108073_2022-10-03_final
2022-10-04 10:09:45	ga_ls8c_ard_3-2-1_099067_2022-10-04_final
2022-10-13 10:03:51	ga_ls8c_ard_3-2-1_098068_2022-10-13_final
2022-10-13 11:47:55	ga_ls8c_ard_3-2-1_114081_2022-10-13_final
2022-10-14 09:13:00	ga_ls8c_ard_3-2-1_089080_2022-10-13_final
2022-10-14 10:52:17	ga_ls8c_ard_3-2-1_105081_2022-10-14_final
2022-10-17 11:22:50	ga_ls8c_ard_3-2-1_110080_2022-10-17_final
2022-10-24 09:47:25	ga_ls8c_ard_3-2-1_095073_2022-10-24_final
2022-10-25 10:29:53	ga_ls8c_ard_3-2-1_102071_2022-10-25_final
2022-10-25 10:30:41	ga_ls8c_ard_3-2-1_102073_2022-10-25_final
2022-10-27 10:20:20	ga_ls8c_ard_3-2-1_100078_2022-10-27_final
2022-10-27 10:22:43	ga_ls8c_ard_3-2-1_100084_2022-10-27_final
2022-11-01 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-11-01_final
2022-11-02 09:44:28	ga_ls8c_ard_3-2-1_094081_2022-11-02_final
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-06 09:20:08	ga_ls8c_ard_3-2-1_090082_2022-11-05_final
2022-11-06 10:53:49	ga_ls8c_ard_3-2-1_106069_2022-11-06_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-10 10:29:52	ga_ls8c_ard_3-2-1_102071_2022-11-10_final
2022-11-10 10:34:16	ga_ls8c_ard_3-2-1_102082_2022-11-10_final
2022-11-14 10:03:31	ga_ls8c_ard_3-2-1_098067_2022-11-14_final
2022-11-17 10:35:34	ga_ls8c_ard_3-2-1_103070_2022-11-17_final
2022-11-18 09:45:55	ga_ls8c_ard_3-2-1_094085_2022-11-18_final
2022-11-18 09:46:19	ga_ls8c_ard_3-2-1_094086_2022-11-18_final
2022-11-18 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-11-18_final
2022-11-20 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-11-20_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-25 11:25:26	ga_ls8c_ard_3-2-1_111071_2022-11-25_final
2022-12-08 09:22:50	ga_ls8c_ard_3-2-1_090089_2022-12-07_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-11 09:52:31	ga_ls8c_ard_3-2-1_095086_2022-12-11_final
2022-12-14 10:22:35	ga_ls8c_ard_3-2-1_100084_2022-12-14_final
2022-12-15 09:23:46	ga_ls8c_ard_3-2-1_091076_2022-12-14_final
2022-12-20 11:18:43	ga_ls8c_ard_3-2-1_110070_2022-12-20_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-21 10:26:17	ga_ls8c_ard_3-2-1_101078_2022-12-21_final
2022-12-21 10:28:16	ga_ls8c_ard_3-2-1_101083_2022-12-21_final
2022-12-25 11:42:26	ga_ls8c_ard_3-2-1_113083_2022-12-25_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-04 10:34:40	ga_ls8c_ard_3-2-1_103068_2023-01-04_final
2023-01-07 09:33:03	ga_ls8c_ard_3-2-1_092084_2023-01-07_final
2023-01-07 09:34:39	ga_ls8c_ard_3-2-1_092088_2023-01-07_final
2023-01-07 11:10:44	ga_ls8c_ard_3-2-1_108081_2023-01-07_final
2023-01-09 09:19:53	ga_ls8c_ard_3-2-1_090082_2023-01-08_final
2023-01-10 10:03:08	ga_ls8c_ard_3-2-1_097082_2023-01-10_final
2023-01-11 10:43:12	ga_ls8c_ard_3-2-1_104074_2023-01-11_final
2023-01-18 10:50:04	ga_ls8c_ard_3-2-1_105076_2023-01-18_final
2023-01-19 09:52:52	ga_ls8c_ard_3-2-1_096072_2023-01-19_final
2023-01-23 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-01-23_final
2023-01-24 10:13:52	ga_ls8c_ard_3-2-1_099078_2023-01-24_final
2023-01-25 10:56:45	ga_ls8c_ard_3-2-1_106077_2023-01-25_final
2023-01-31 10:18:53	ga_ls8c_ard_3-2-1_100075_2023-01-31_final
2023-02-06 11:18:41	ga_ls8c_ard_3-2-1_110070_2023-02-06_final
2023-02-08 11:07:30	ga_ls8c_ard_3-2-1_108073_2023-02-08_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-10 09:22:37	ga_ls8c_ard_3-2-1_090089_2023-02-09_final
2023-02-11 09:58:41	ga_ls8c_ard_3-2-1_097071_2023-02-11_final
2023-02-12 09:07:02	ga_ls8c_ard_3-2-1_088081_2023-02-11_final
2023-02-15 11:17:59	ga_ls8c_ard_3-2-1_109084_2023-02-15_final
2023-02-18 10:10:21	ga_ls8c_ard_3-2-1_098085_2023-02-18_final
2023-02-18 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-02-18_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_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