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
2022-04-11 10:13:44	ga_ls8c_ard_3-2-1_099079_2022-04-11_final
2022-05-03 09:34:15	ga_ls8c_ard_3-2-1_093073_2022-05-03_final
2022-05-13 10:09:27	ga_ls8c_ard_3-2-1_099068_2022-05-13_final
2022-05-13 11:52:19	ga_ls8c_ard_3-2-1_115078_2022-05-13_final
2022-05-16 09:07:04	ga_ls8c_ard_3-2-1_088082_2022-05-15_final
2022-05-21 09:27:37	ga_ls8c_ard_3-2-1_091087_2022-05-20_final
2022-05-21 11:04:54	ga_ls8c_ard_3-2-1_107083_2022-05-21_final
2022-05-22 10:03:17	ga_ls8c_ard_3-2-1_098068_2022-05-22_final
2022-05-22 10:09:41	ga_ls8c_ard_3-2-1_098084_2022-05-22_final
2022-05-23 09:12:03	ga_ls8c_ard_3-2-1_089079_2022-05-22_final
2022-05-23 09:12:27	ga_ls8c_ard_3-2-1_089080_2022-05-22_final
2022-05-25 10:35:47	ga_ls8c_ard_3-2-1_103072_2022-05-25_final
2022-05-26 09:44:56	ga_ls8c_ard_3-2-1_094084_2022-05-26_final
2022-05-30 09:20:15	ga_ls8c_ard_3-2-1_090084_2022-05-29_final
2022-05-31 09:57:09	ga_ls8c_ard_3-2-1_097068_2022-05-31_final
2022-06-06 11:01:50	ga_ls8c_ard_3-2-1_107075_2022-06-06_final
2022-06-08 09:11:24	ga_ls8c_ard_3-2-1_089077_2022-06-07_final
2022-06-09 11:32:22	ga_ls8c_ard_3-2-1_112074_2022-06-09_final
2022-06-10 10:35:58	ga_ls8c_ard_3-2-1_103072_2022-06-10_final
2022-06-16 11:42:13	ga_ls8c_ard_3-2-1_113083_2022-06-16_final
2022-06-18 11:27:29	ga_ls8c_ard_3-2-1_111077_2022-06-18_final
2022-06-20 09:40:38	ga_ls8c_ard_3-2-1_093088_2022-06-20_final
2022-06-21 11:58:24	ga_ls8c_ard_3-2-1_116077_2022-06-21_final
2022-06-22 09:27:29	ga_ls8c_ard_3-2-1_091086_2022-06-21_final
2022-06-23 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-06-23_final
2022-06-29 09:29:18	ga_ls8c_ard_3-2-1_092075_2022-06-28_final
2022-06-30 10:10:34	ga_ls8c_ard_3-2-1_099070_2022-06-30_final
2022-06-30 10:16:09	ga_ls8c_ard_3-2-1_099084_2022-06-30_final
2022-07-01 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-07-01_final
2022-07-08 09:28:19	ga_ls8c_ard_3-2-1_091088_2022-07-07_final
2022-07-09 10:03:11	ga_ls8c_ard_3-2-1_098067_2022-07-09_final
2022-07-13 11:20:08	ga_ls8c_ard_3-2-1_110074_2022-07-13_final
2022-07-22 09:34:45	ga_ls8c_ard_3-2-1_093073_2022-07-22_final
2022-07-31 09:28:17	ga_ls8c_ard_3-2-1_092072_2022-07-30_final
2022-08-17 10:10:27	ga_ls8c_ard_3-2-1_099069_2022-08-17_final
2022-09-06 09:47:22	ga_ls8c_ard_3-2-1_095073_2022-09-06_final
2022-09-06 09:52:33	ga_ls8c_ard_3-2-1_095086_2022-09-06_final
2022-09-09 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-09-09_final
2022-09-12 10:50:01	ga_ls8c_ard_3-2-1_105075_2022-09-12_final
2022-09-18 10:16:09	ga_ls8c_ard_3-2-1_099083_2022-09-18_final
2022-09-20 10:01:48	ga_ls8c_ard_3-2-1_097078_2022-09-20_final
2022-09-22 11:24:21	ga_ls8c_ard_3-2-1_111068_2022-09-22_final
2022-09-24 09:40:41	ga_ls8c_ard_3-2-1_093087_2022-09-24_final
2022-09-26 09:29:07	ga_ls8c_ard_3-2-1_091089_2022-09-25_final
2022-09-27 10:10:47	ga_ls8c_ard_3-2-1_098085_2022-09-27_final
2022-10-01 11:22:56	ga_ls8c_ard_3-2-1_110080_2022-10-01_final
2022-10-03 09:28:29	ga_ls8c_ard_3-2-1_092072_2022-10-02_final
2022-10-03 11:08:10	ga_ls8c_ard_3-2-1_108074_2022-10-03_final
2022-10-04 10:10:33	ga_ls8c_ard_3-2-1_099069_2022-10-04_final
2022-10-06 09:57:46	ga_ls8c_ard_3-2-1_097068_2022-10-06_final
2022-10-07 09:07:43	ga_ls8c_ard_3-2-1_088082_2022-10-06_final
2022-10-09 10:29:26	ga_ls8c_ard_3-2-1_102070_2022-10-09_final
2022-10-13 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-10-13_final
2022-10-29 10:10:22	ga_ls8c_ard_3-2-1_098084_2022-10-29_final
2022-11-01 10:34:54	ga_ls8c_ard_3-2-1_103068_2022-11-01_final
2022-11-04 09:29:42	ga_ls8c_ard_3-2-1_092075_2022-11-03_final
2022-11-05 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-11-05_final
2022-11-05 11:51:51	ga_ls8c_ard_3-2-1_115075_2022-11-05_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-07 10:04:11	ga_ls8c_ard_3-2-1_097084_2022-11-07_final
2022-11-14 10:03:31	ga_ls8c_ard_3-2-1_098067_2022-11-14_final
2022-11-16 11:36:47	ga_ls8c_ard_3-2-1_112084_2022-11-16_final
2022-11-21 11:53:20	ga_ls8c_ard_3-2-1_115079_2022-11-21_final
2022-11-22 09:21:14	ga_ls8c_ard_3-2-1_090085_2022-11-21_final
2022-11-23 09:57:19	ga_ls8c_ard_3-2-1_097067_2022-11-23_final
2022-11-24 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-11-23_final
2022-11-27 11:13:29	ga_ls8c_ard_3-2-1_109072_2022-11-27_final
2022-11-29 11:00:44	ga_ls8c_ard_3-2-1_107071_2022-11-29_final
2022-11-30 11:45:11	ga_ls8c_ard_3-2-1_114074_2022-11-30_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-07 10:10:29	ga_ls8c_ard_3-2-1_099069_2022-12-07_final
2022-12-07 11:53:21	ga_ls8c_ard_3-2-1_115079_2022-12-07_final
2022-12-10 10:46:33	ga_ls8c_ard_3-2-1_104082_2022-12-10_final
2022-12-16 10:07:49	ga_ls8c_ard_3-2-1_098078_2022-12-16_final
2022-12-18 11:32:43	ga_ls8c_ard_3-2-1_112074_2022-12-18_final
2022-12-20 11:20:19	ga_ls8c_ard_3-2-1_110074_2022-12-20_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-21 10:24:17	ga_ls8c_ard_3-2-1_101073_2022-12-21_final
2022-12-22 11:06:44	ga_ls8c_ard_3-2-1_108071_2022-12-22_final
2022-12-22 11:07:55	ga_ls8c_ard_3-2-1_108074_2022-12-22_final
2022-12-24 09:22:16	ga_ls8c_ard_3-2-1_090088_2022-12-23_final
2022-12-26 09:07:08	ga_ls8c_ard_3-2-1_088081_2022-12-25_final
2022-12-30 10:20:07	ga_ls8c_ard_3-2-1_100078_2022-12-30_final
2023-01-03 11:36:40	ga_ls8c_ard_3-2-1_112084_2023-01-03_final
2023-01-12 09:52:45	ga_ls8c_ard_3-2-1_095087_2023-01-12_final
2023-01-18 10:47:17	ga_ls8c_ard_3-2-1_105069_2023-01-18_final
2023-01-21 11:19:50	ga_ls8c_ard_3-2-1_110073_2023-01-21_final
2023-01-25 09:17:04	ga_ls8c_ard_3-2-1_090075_2023-01-24_final
2023-01-25 09:22:15	ga_ls8c_ard_3-2-1_090088_2023-01-24_final
2023-01-25 10:54:45	ga_ls8c_ard_3-2-1_106072_2023-01-25_final
2023-01-31 10:22:29	ga_ls8c_ard_3-2-1_100084_2023-01-31_final
2023-02-09 10:13:28	ga_ls8c_ard_3-2-1_099077_2023-02-09_final
2023-02-09 10:14:16	ga_ls8c_ard_3-2-1_099079_2023-02-09_final
2023-02-09 11:51:33	ga_ls8c_ard_3-2-1_115075_2023-02-09_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-20 09:51:58	ga_ls8c_ard_3-2-1_096070_2023-02-20_final
2023-02-25 10:13:10	ga_ls8c_ard_3-2-1_099077_2023-02-25_final
2023-02-25 10:13:58	ga_ls8c_ard_3-2-1_099079_2023-02-25_final
2023-02-28 09:07:11	ga_ls8c_ard_3-2-1_088082_2023-02-27_final
2023-03-08 11:36:14	ga_ls8c_ard_3-2-1_112084_2023-03-08_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