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
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-27 11:32:38	ga_ls8c_ard_3-2-1_112074_2022-07-27_final
2022-08-01 10:09:33	ga_ls8c_ard_3-2-1_099067_2022-08-01_final
2022-08-02 09:22:19	ga_ls8c_ard_3-2-1_090088_2022-08-01_final
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-08-09 11:05:27	ga_ls8c_ard_3-2-1_107083_2022-08-09_final
2022-08-10 10:03:27	ga_ls8c_ard_3-2-1_098067_2022-08-10_final
2022-08-11 09:13:49	ga_ls8c_ard_3-2-1_089082_2022-08-10_final
2022-08-11 09:14:37	ga_ls8c_ard_3-2-1_089084_2022-08-10_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-21 09:52:56	ga_ls8c_ard_3-2-1_095087_2022-08-21_final
2022-08-21 11:24:14	ga_ls8c_ard_3-2-1_111068_2022-08-21_final
2022-08-25 09:29:00	ga_ls8c_ard_3-2-1_091089_2022-08-24_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-09-01 11:12:04	ga_ls8c_ard_3-2-1_108084_2022-09-01_final
2022-09-10 09:27:28	ga_ls8c_ard_3-2-1_091085_2022-09-09_final
2022-09-12 09:17:07	ga_ls8c_ard_3-2-1_089090_2022-09-11_final
2022-09-15 09:46:02	ga_ls8c_ard_3-2-1_094085_2022-09-15_final
2022-09-17 09:33:17	ga_ls8c_ard_3-2-1_092084_2022-09-17_final
2022-09-19 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-09-18_final
2022-09-19 09:22:32	ga_ls8c_ard_3-2-1_090088_2022-09-18_final
2022-09-19 09:22:56	ga_ls8c_ard_3-2-1_090089_2022-09-18_final
2022-09-20 11:39:06	ga_ls8c_ard_3-2-1_113074_2022-09-20_final
2022-09-22 11:29:56	ga_ls8c_ard_3-2-1_111082_2022-09-22_final
2022-09-23 10:30:43	ga_ls8c_ard_3-2-1_102073_2022-09-23_final
2022-09-27 10:04:00	ga_ls8c_ard_3-2-1_098068_2022-09-27_final
2022-09-28 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-09-28_final
2022-09-28 10:47:39	ga_ls8c_ard_3-2-1_105069_2022-09-28_final
2022-09-29 11:32:54	ga_ls8c_ard_3-2-1_112074_2022-09-29_final
2022-10-01 11:19:44	ga_ls8c_ard_3-2-1_110072_2022-10-01_final
2022-10-03 09:29:41	ga_ls8c_ard_3-2-1_092075_2022-10-02_final
2022-10-03 09:33:40	ga_ls8c_ard_3-2-1_092085_2022-10-03_final
2022-10-04 10:10:09	ga_ls8c_ard_3-2-1_099068_2022-10-04_final
2022-10-08 09:51:22	ga_ls8c_ard_3-2-1_095083_2022-10-08_final
2022-10-11 10:19:50	ga_ls8c_ard_3-2-1_100077_2022-10-11_final
2022-10-12 09:29:23	ga_ls8c_ard_3-2-1_091090_2022-10-11_final
2022-10-12 11:01:53	ga_ls8c_ard_3-2-1_107074_2022-10-12_final
2022-10-16 10:36:22	ga_ls8c_ard_3-2-1_103072_2022-10-16_final
2022-10-16 10:39:58	ga_ls8c_ard_3-2-1_103081_2022-10-16_final
2022-10-17 11:20:50	ga_ls8c_ard_3-2-1_110075_2022-10-17_final
2022-10-24 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-10-24_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-10-28 09:23:31	ga_ls8c_ard_3-2-1_091075_2022-10-27_final
2022-10-28 09:25:30	ga_ls8c_ard_3-2-1_091080_2022-10-27_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-10-30 10:47:15	ga_ls8c_ard_3-2-1_105068_2022-10-30_final
2022-10-31 09:57:13	ga_ls8c_ard_3-2-1_096082_2022-10-31_final
2022-11-02 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-11-02_final
2022-11-06 10:59:25	ga_ls8c_ard_3-2-1_106083_2022-11-06_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-13 09:23:27	ga_ls8c_ard_3-2-1_091075_2022-11-12_final
2022-11-13 11:00:21	ga_ls8c_ard_3-2-1_107070_2022-11-13_final
2022-11-18 09:44:43	ga_ls8c_ard_3-2-1_094082_2022-11-18_final
2022-11-21 10:15:39	ga_ls8c_ard_3-2-1_099082_2022-11-21_final
2022-11-22 09:22:49	ga_ls8c_ard_3-2-1_090089_2022-11-21_final
2022-11-24 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-11-24_final
2022-11-26 10:29:01	ga_ls8c_ard_3-2-1_102069_2022-11-26_final
2022-11-28 10:20:16	ga_ls8c_ard_3-2-1_100078_2022-11-28_final
2022-11-29 11:02:43	ga_ls8c_ard_3-2-1_107076_2022-11-29_final
2022-12-01 09:15:04	ga_ls8c_ard_3-2-1_089085_2022-11-30_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-07 10:14:28	ga_ls8c_ard_3-2-1_099079_2022-12-07_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-08 09:18:03	ga_ls8c_ard_3-2-1_090077_2022-12-07_final
2022-12-08 10:54:56	ga_ls8c_ard_3-2-1_106072_2022-12-08_final
2022-12-09 09:58:06	ga_ls8c_ard_3-2-1_097069_2022-12-09_final
2022-12-11 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-12-11_final
2022-12-13 11:14:14	ga_ls8c_ard_3-2-1_109074_2022-12-13_final
2022-12-15 09:27:21	ga_ls8c_ard_3-2-1_091085_2022-12-14_final
2022-12-21 10:27:52	ga_ls8c_ard_3-2-1_101082_2022-12-21_final
2022-12-23 11:53:11	ga_ls8c_ard_3-2-1_115079_2022-12-23_final
2022-12-26 09:07:32	ga_ls8c_ard_3-2-1_088082_2022-12-25_final
2022-12-26 10:46:25	ga_ls8c_ard_3-2-1_104082_2022-12-26_final
2023-01-09 09:21:05	ga_ls8c_ard_3-2-1_090085_2023-01-08_final
2023-01-10 11:38:50	ga_ls8c_ard_3-2-1_113074_2023-01-10_final
2023-01-16 11:02:28	ga_ls8c_ard_3-2-1_107076_2023-01-16_final
2023-01-17 11:47:42	ga_ls8c_ard_3-2-1_114081_2023-01-17_final
2023-01-18 10:46:29	ga_ls8c_ard_3-2-1_105067_2023-01-18_final
2023-01-20 10:39:21	ga_ls8c_ard_3-2-1_103080_2023-01-20_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-01-22 10:28:13	ga_ls8c_ard_3-2-1_101083_2023-01-22_final
2023-01-25 09:21:27	ga_ls8c_ard_3-2-1_090086_2023-01-24_final
2023-01-29 10:30:27	ga_ls8c_ard_3-2-1_102073_2023-01-29_final
2023-02-05 10:36:13	ga_ls8c_ard_3-2-1_103072_2023-02-05_final
2023-02-06 11:20:16	ga_ls8c_ard_3-2-1_110074_2023-02-06_final
2023-02-10 09:22:13	ga_ls8c_ard_3-2-1_090088_2023-02-09_final
2023-02-11 11:38:46	ga_ls8c_ard_3-2-1_113074_2023-02-11_final
2023-02-12 09:06:38	ga_ls8c_ard_3-2-1_088080_2023-02-11_final
2023-02-17 09:22:19	ga_ls8c_ard_3-2-1_091073_2023-02-16_final
2023-02-17 11:02:24	ga_ls8c_ard_3-2-1_107076_2023-02-17_final
2023-02-18 11:47:38	ga_ls8c_ard_3-2-1_114081_2023-02-18_final
2023-02-22 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-02-22_final
2023-02-23 10:27:35	ga_ls8c_ard_3-2-1_101082_2023-02-23_final
2023-02-24 11:11:36	ga_ls8c_ard_3-2-1_108084_2023-02-24_final
2023-02-25 10:13:34	ga_ls8c_ard_3-2-1_099078_2023-02-25_final
2023-03-01 11:23:45	ga_ls8c_ard_3-2-1_111068_2023-03-01_final
2023-03-06 11:47:26	ga_ls8c_ard_3-2-1_114081_2023-03-06_final
2023-03-08 11:32:15	ga_ls8c_ard_3-2-1_112074_2023-03-08_final
2023-03-08 11:35:50	ga_ls8c_ard_3-2-1_112083_2023-03-08_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_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