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
2022-02-05 09:34:23	ga_ls8c_ard_3-2-1_092088_2022-02-05_final
2022-02-08 09:58:53	ga_ls8c_ard_3-2-1_097072_2022-02-08_final
2022-02-08 11:38:34	ga_ls8c_ard_3-2-1_113074_2022-02-08_final
2022-02-13 10:19:47	ga_ls8c_ard_3-2-1_100078_2022-02-13_final
2022-02-16 10:46:41	ga_ls8c_ard_3-2-1_105068_2022-02-16_final
2022-02-21 09:34:17	ga_ls8c_ard_3-2-1_092088_2022-02-21_final
2022-02-22 11:51:38	ga_ls8c_ard_3-2-1_115076_2022-02-22_final
2022-02-24 09:58:24	ga_ls8c_ard_3-2-1_097071_2022-02-24_final
2022-02-24 11:38:28	ga_ls8c_ard_3-2-1_113074_2022-02-24_final
2022-03-09 11:05:56	ga_ls8c_ard_3-2-1_108070_2022-03-09_final
2022-03-11 10:55:33	ga_ls8c_ard_3-2-1_106075_2022-03-11_final
2022-03-12 09:58:20	ga_ls8c_ard_3-2-1_097071_2022-03-12_final
2022-03-16 09:35:10	ga_ls8c_ard_3-2-1_093075_2022-03-16_final
2022-03-16 11:14:03	ga_ls8c_ard_3-2-1_109075_2022-03-16_final
2022-03-19 10:09:37	ga_ls8c_ard_3-2-1_098084_2022-03-19_final
2022-03-21 09:51:39	ga_ls8c_ard_3-2-1_096070_2022-03-21_final
2022-03-21 11:32:08	ga_ls8c_ard_3-2-1_112074_2022-03-21_final
2022-04-01 09:34:11	ga_ls8c_ard_3-2-1_093073_2022-04-01_final
2022-04-01 11:11:28	ga_ls8c_ard_3-2-1_109069_2022-04-01_final
2022-04-10 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-04-10_final
2022-04-11 10:09:21	ga_ls8c_ard_3-2-1_099068_2022-04-11_final
2022-04-14 09:06:34	ga_ls8c_ard_3-2-1_088081_2022-04-13_final
2022-04-21 10:46:26	ga_ls8c_ard_3-2-1_105068_2022-04-21_final
2022-04-26 09:34:26	ga_ls8c_ard_3-2-1_092089_2022-04-26_final
2022-04-27 11:52:10	ga_ls8c_ard_3-2-1_115078_2022-04-27_final
2022-05-05 09:24:19	ga_ls8c_ard_3-2-1_091079_2022-05-04_final
2022-05-07 10:49:40	ga_ls8c_ard_3-2-1_105076_2022-05-07_final
2022-05-08 09:52:03	ga_ls8c_ard_3-2-1_096071_2022-05-08_final
2022-05-13 10:13:50	ga_ls8c_ard_3-2-1_099079_2022-05-13_final
2022-05-14 09:18:13	ga_ls8c_ard_3-2-1_090079_2022-05-13_final
2022-05-16 09:06:16	ga_ls8c_ard_3-2-1_088080_2022-05-15_final
2022-05-26 11:19:02	ga_ls8c_ard_3-2-1_110072_2022-05-26_final
2022-06-08 09:12:36	ga_ls8c_ard_3-2-1_089080_2022-06-07_final
2022-06-08 09:13:24	ga_ls8c_ard_3-2-1_089082_2022-06-07_final
2022-06-08 09:15:00	ga_ls8c_ard_3-2-1_089086_2022-06-07_final
2022-06-12 10:28:01	ga_ls8c_ard_3-2-1_101083_2022-06-12_final
2022-06-23 10:09:57	ga_ls8c_ard_3-2-1_098084_2022-06-23_final
2022-06-29 09:33:18	ga_ls8c_ard_3-2-1_092085_2022-06-29_final
2022-06-29 11:06:11	ga_ls8c_ard_3-2-1_108070_2022-06-29_final
2022-07-07 10:17:09	ga_ls8c_ard_3-2-1_100071_2022-07-07_final
2022-07-10 09:12:45	ga_ls8c_ard_3-2-1_089080_2022-07-09_final
2022-07-10 10:49:14	ga_ls8c_ard_3-2-1_105074_2022-07-10_final
2022-07-21 10:28:22	ga_ls8c_ard_3-2-1_102068_2022-07-21_final
2022-07-22 09:40:44	ga_ls8c_ard_3-2-1_093088_2022-07-22_final
2022-07-22 11:12:02	ga_ls8c_ard_3-2-1_109069_2022-07-22_final
2022-07-25 10:07:17	ga_ls8c_ard_3-2-1_098077_2022-07-25_final
2022-08-02 09:22:19	ga_ls8c_ard_3-2-1_090088_2022-08-01_final
2022-08-02 10:53:13	ga_ls8c_ard_3-2-1_106068_2022-08-02_final
2022-08-11 09:12:37	ga_ls8c_ard_3-2-1_089079_2022-08-10_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-29 10:39:58	ga_ls8c_ard_3-2-1_103081_2022-08-29_final
2022-09-09 10:21:53	ga_ls8c_ard_3-2-1_100082_2022-09-09_final
2022-09-11 10:07:09	ga_ls8c_ard_3-2-1_098076_2022-09-11_final
2022-09-11 10:10:20	ga_ls8c_ard_3-2-1_098084_2022-09-11_final
2022-09-20 09:57:49	ga_ls8c_ard_3-2-1_097068_2022-09-20_final
2022-09-20 11:39:06	ga_ls8c_ard_3-2-1_113074_2022-09-20_final
2022-09-28 10:49:39	ga_ls8c_ard_3-2-1_105074_2022-09-28_final
2022-10-01 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-10-01_final
2022-10-03 09:33:17	ga_ls8c_ard_3-2-1_092084_2022-10-03_final
2022-10-19 09:32:49	ga_ls8c_ard_3-2-1_092083_2022-10-19_final
2022-10-20 10:11:18	ga_ls8c_ard_3-2-1_099071_2022-10-20_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-06 09:22:08	ga_ls8c_ard_3-2-1_090087_2022-11-05_final
2022-11-08 09:07:45	ga_ls8c_ard_3-2-1_088082_2022-11-07_final
2022-11-10 10:28:41	ga_ls8c_ard_3-2-1_102068_2022-11-10_final
2022-11-13 09:25:27	ga_ls8c_ard_3-2-1_091080_2022-11-12_final
2022-11-23 11:38:59	ga_ls8c_ard_3-2-1_113074_2022-11-23_final
2022-11-24 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-11-23_final
2022-11-24 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-11-24_final
2022-11-27 11:13:29	ga_ls8c_ard_3-2-1_109072_2022-11-27_final
2022-11-29 09:27:50	ga_ls8c_ard_3-2-1_091086_2022-11-28_final
2022-12-01 10:53:09	ga_ls8c_ard_3-2-1_105083_2022-12-01_final
2022-12-02 09:52:45	ga_ls8c_ard_3-2-1_096071_2022-12-02_final
2022-12-02 11:36:49	ga_ls8c_ard_3-2-1_112084_2022-12-02_final
2022-12-03 10:40:00	ga_ls8c_ard_3-2-1_103081_2022-12-03_final
2022-12-04 09:41:11	ga_ls8c_ard_3-2-1_094073_2022-12-04_final
2022-12-08 10:53:44	ga_ls8c_ard_3-2-1_106069_2022-12-08_final
2022-12-11 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-12-11_final
2022-12-11 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-12-11_final
2022-12-22 11:06:44	ga_ls8c_ard_3-2-1_108071_2022-12-22_final
2023-01-03 09:53:48	ga_ls8c_ard_3-2-1_096074_2023-01-03_final
2023-01-05 11:19:07	ga_ls8c_ard_3-2-1_110071_2023-01-05_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-18 09:13:11	ga_ls8c_ard_3-2-1_089081_2023-01-17_final
2023-01-19 11:36:33	ga_ls8c_ard_3-2-1_112084_2023-01-19_final
2023-01-21 09:40:33	ga_ls8c_ard_3-2-1_094072_2023-01-21_final
2023-01-21 09:40:57	ga_ls8c_ard_3-2-1_094073_2023-01-21_final
2023-01-24 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-01-24_final
2023-01-26 11:38:01	ga_ls8c_ard_3-2-1_113072_2023-01-26_final
2023-01-29 10:28:27	ga_ls8c_ard_3-2-1_102068_2023-01-29_final
2023-01-30 09:39:13	ga_ls8c_ard_3-2-1_093084_2023-01-30_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-01-31 10:18:05	ga_ls8c_ard_3-2-1_100073_2023-01-31_final
2023-02-05 10:36:13	ga_ls8c_ard_3-2-1_103072_2023-02-05_final
2023-02-11 11:38:46	ga_ls8c_ard_3-2-1_113074_2023-02-11_final
2023-02-19 09:13:31	ga_ls8c_ard_3-2-1_089082_2023-02-18_final
2023-02-19 10:49:36	ga_ls8c_ard_3-2-1_105075_2023-02-19_final
2023-02-24 11:10:01	ga_ls8c_ard_3-2-1_108080_2023-02-24_final
2023-02-28 10:40:29	ga_ls8c_ard_3-2-1_104068_2023-02-28_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