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
2022-06-04 09:40:04	ga_ls8c_ard_3-2-1_093087_2022-06-04_final
2022-06-05 10:16:57	ga_ls8c_ard_3-2-1_100071_2022-06-05_final
2022-06-05 10:19:45	ga_ls8c_ard_3-2-1_100078_2022-06-05_final
2022-06-09 09:57:29	ga_ls8c_ard_3-2-1_096084_2022-06-09_final
2022-06-13 11:07:42	ga_ls8c_ard_3-2-1_108074_2022-06-13_final
2022-06-17 09:06:55	ga_ls8c_ard_3-2-1_088081_2022-06-16_final
2022-06-22 09:27:53	ga_ls8c_ard_3-2-1_091087_2022-06-21_final
2022-06-24 09:13:08	ga_ls8c_ard_3-2-1_089081_2022-06-23_final
2022-06-28 10:23:43	ga_ls8c_ard_3-2-1_101072_2022-06-28_final
2022-06-28 10:28:07	ga_ls8c_ard_3-2-1_101083_2022-06-28_final
2022-07-11 09:52:01	ga_ls8c_ard_3-2-1_096070_2022-07-11_final
2022-07-16 11:52:13	ga_ls8c_ard_3-2-1_115077_2022-07-16_final
2022-07-19 09:07:00	ga_ls8c_ard_3-2-1_088081_2022-07-18_final
2022-08-11 10:53:06	ga_ls8c_ard_3-2-1_105083_2022-08-11_final
2022-08-16 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-08-15_final
2022-08-19 11:42:34	ga_ls8c_ard_3-2-1_113083_2022-08-19_final
2022-09-21 10:43:04	ga_ls8c_ard_3-2-1_104073_2022-09-21_final
2022-09-22 09:46:39	ga_ls8c_ard_3-2-1_095071_2022-09-22_final
2022-09-22 11:30:20	ga_ls8c_ard_3-2-1_111083_2022-09-22_final
2022-09-24 09:41:05	ga_ls8c_ard_3-2-1_093088_2022-09-24_final
2022-09-26 09:23:08	ga_ls8c_ard_3-2-1_091074_2022-09-25_final
2022-09-26 09:25:31	ga_ls8c_ard_3-2-1_091080_2022-09-25_final
2022-10-07 09:07:19	ga_ls8c_ard_3-2-1_088081_2022-10-06_final
2022-10-12 09:25:23	ga_ls8c_ard_3-2-1_091080_2022-10-11_final
2022-10-14 10:49:06	ga_ls8c_ard_3-2-1_105073_2022-10-14_final
2022-10-23 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-23_final
2022-11-05 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-11-05_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-21 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-11-21_final
2022-11-24 09:07:41	ga_ls8c_ard_3-2-1_088082_2022-11-23_final
2022-11-25 11:24:39	ga_ls8c_ard_3-2-1_111069_2022-11-25_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-12-07 10:10:05	ga_ls8c_ard_3-2-1_099068_2022-12-07_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-13 11:12:38	ga_ls8c_ard_3-2-1_109070_2022-12-13_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-02 10:50:13	ga_ls8c_ard_3-2-1_105076_2023-01-02_final
2023-01-08 11:52:00	ga_ls8c_ard_3-2-1_115076_2023-01-08_final
2023-01-08 11:52:48	ga_ls8c_ard_3-2-1_115078_2023-01-08_final
2023-01-08 11:53:36	ga_ls8c_ard_3-2-1_115080_2023-01-08_final
2023-01-16 09:28:46	ga_ls8c_ard_3-2-1_091089_2023-01-15_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-17 11:45:42	ga_ls8c_ard_3-2-1_114076_2023-01-17_final
2023-01-24 10:11:53	ga_ls8c_ard_3-2-1_099073_2023-01-24_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-01-30 11:13:19	ga_ls8c_ard_3-2-1_109072_2023-01-30_final
2023-02-02 10:06:07	ga_ls8c_ard_3-2-1_098074_2023-02-02_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-17 09:22:19	ga_ls8c_ard_3-2-1_091073_2023-02-16_final
2023-02-18 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-02-18_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-03-07 10:48:12	ga_ls8c_ard_3-2-1_105072_2023-03-07_final
2023-03-07 10:48:36	ga_ls8c_ard_3-2-1_105073_2023-03-07_final
2023-03-14 09:17:04	ga_ls8c_ard_3-2-1_090076_2023-03-13_final
2023-03-15 09:58:44	ga_ls8c_ard_3-2-1_097072_2023-03-15_final
2023-04-09 09:51:24	ga_ls8c_ard_3-2-1_096070_2023-04-09_final
2023-04-14 10:13:28	ga_ls8c_ard_3-2-1_099079_2023-04-14_final
2023-04-24 09:12:02	ga_ls8c_ard_3-2-1_089080_2023-04-23_final
2023-04-24 10:51:19	ga_ls8c_ard_3-2-1_105081_2023-04-24_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-10 09:11:03	ga_ls8c_ard_3-2-1_089078_2023-05-09_final
2023-05-10 09:11:51	ga_ls8c_ard_3-2-1_089080_2023-05-09_final
2023-05-10 09:15:27	ga_ls8c_ard_3-2-1_089089_2023-05-09_final
2023-05-11 09:51:06	ga_ls8c_ard_3-2-1_096070_2023-05-11_final
2023-05-19 09:06:24	ga_ls8c_ard_3-2-1_088082_2023-05-18_final
2023-05-26 09:13:01	ga_ls8c_ard_3-2-1_089083_2023-05-25_final
2023-06-20 10:41:54	ga_ls8c_ard_3-2-1_104073_2023-06-20_final
2023-06-27 09:12:04	ga_ls8c_ard_3-2-1_089080_2023-06-26_final
2023-07-11 11:01:27	ga_ls8c_ard_3-2-1_107075_2023-07-11_final
2023-07-13 09:12:13	ga_ls8c_ard_3-2-1_089080_2023-07-12_final
2023-07-14 11:35:58	ga_ls8c_ard_3-2-1_112084_2023-07-14_final
2023-07-18 11:05:39	ga_ls8c_ard_3-2-1_108070_2023-07-18_final
2023-07-28 10:03:09	ga_ls8c_ard_3-2-1_098068_2023-07-28_final
2023-07-29 09:12:20	ga_ls8c_ard_3-2-1_089080_2023-07-28_final
2023-08-04 11:52:16	ga_ls8c_ard_3-2-1_115078_2023-08-04_final
2023-08-12 09:27:08	ga_ls8c_ard_3-2-1_091086_2023-08-11_final
2023-08-17 09:44:33	ga_ls8c_ard_3-2-1_094083_2023-08-17_final
2023-08-19 09:28:37	ga_ls8c_ard_3-2-1_092074_2023-08-18_final
2023-08-20 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-08-20_final
2023-08-30 09:12:31	ga_ls8c_ard_3-2-1_089080_2023-08-29_final
2023-08-31 09:57:22	ga_ls8c_ard_3-2-1_096084_2023-08-31_final
2023-08-31 11:31:52	ga_ls8c_ard_3-2-1_112073_2023-08-31_final
2023-09-21 10:15:35	ga_ls8c_ard_3-2-1_099083_2023-09-21_final
2023-09-21 11:52:28	ga_ls8c_ard_3-2-1_115078_2023-09-21_final
2023-09-29 09:26:36	ga_ls8c_ard_3-2-1_091084_2023-09-28_final
2023-10-01 09:16:38	ga_ls8c_ard_3-2-1_089090_2023-09-30_final
2023-10-08 09:17:38	ga_ls8c_ard_3-2-1_090077_2023-10-07_final
2023-10-16 10:04:42	ga_ls8c_ard_3-2-1_098071_2023-10-16_final
2023-10-30 10:19:07	ga_ls8c_ard_3-2-1_100076_2023-10-30_final
2023-10-30 10:19:55	ga_ls8c_ard_3-2-1_100078_2023-10-30_final
2023-10-31 09:26:41	ga_ls8c_ard_3-2-1_091084_2023-10-30_final
2023-11-01 10:04:46	ga_ls8c_ard_3-2-1_098071_2023-11-01_final
2023-11-01 11:46:26	ga_ls8c_ard_3-2-1_114078_2023-11-01_final
2023-11-02 09:12:20	ga_ls8c_ard_3-2-1_089079_2023-11-01_final
2023-11-03 09:52:24	ga_ls8c_ard_3-2-1_096071_2023-11-03_final
2023-11-08 11:51:45	ga_ls8c_ard_3-2-1_115076_2023-11-08_final
2023-11-17 11:45:38	ga_ls8c_ard_3-2-1_114076_2023-11-17_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