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
2022-01-22 09:21:40	ga_ls8c_ard_3-2-1_090087_2022-01-21_final
2022-02-16 10:46:41	ga_ls8c_ard_3-2-1_105068_2022-02-16_final
2022-03-06 10:39:50	ga_ls8c_ard_3-2-1_103082_2022-03-06_final
2022-03-12 09:58:20	ga_ls8c_ard_3-2-1_097071_2022-03-12_final
2022-04-04 10:04:18	ga_ls8c_ard_3-2-1_098071_2022-04-04_final
2022-04-04 10:07:05	ga_ls8c_ard_3-2-1_098078_2022-04-04_final
2022-04-10 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-04-10_final
2022-04-12 09:20:07	ga_ls8c_ard_3-2-1_090084_2022-04-11_final
2022-04-17 11:12:22	ga_ls8c_ard_3-2-1_109071_2022-04-17_final
2022-04-19 09:26:18	ga_ls8c_ard_3-2-1_091084_2022-04-18_final
2022-04-21 09:11:08	ga_ls8c_ard_3-2-1_089077_2022-04-20_final
2022-04-21 09:16:19	ga_ls8c_ard_3-2-1_089090_2022-04-20_final
2022-04-21 10:52:01	ga_ls8c_ard_3-2-1_105082_2022-04-21_final
2022-04-27 10:09:18	ga_ls8c_ard_3-2-1_099068_2022-04-27_final
2022-05-08 09:52:03	ga_ls8c_ard_3-2-1_096071_2022-05-08_final
2022-05-12 11:10:39	ga_ls8c_ard_3-2-1_108082_2022-05-12_final
2022-05-15 09:57:30	ga_ls8c_ard_3-2-1_097069_2022-05-15_final
2022-05-15 11:41:34	ga_ls8c_ard_3-2-1_113082_2022-05-15_final
2022-05-28 09:33:46	ga_ls8c_ard_3-2-1_092087_2022-05-28_final
2022-06-06 11:01:50	ga_ls8c_ard_3-2-1_107075_2022-06-06_final
2022-06-08 09:15:00	ga_ls8c_ard_3-2-1_089086_2022-06-07_final
2022-06-11 11:19:14	ga_ls8c_ard_3-2-1_110072_2022-06-11_final
2022-06-13 11:11:17	ga_ls8c_ard_3-2-1_108083_2022-06-13_final
2022-06-18 11:25:05	ga_ls8c_ard_3-2-1_111071_2022-06-18_final
2022-06-25 09:58:24	ga_ls8c_ard_3-2-1_096086_2022-06-25_final
2022-06-25 11:32:30	ga_ls8c_ard_3-2-1_112074_2022-06-25_final
2022-06-29 09:29:18	ga_ls8c_ard_3-2-1_092075_2022-06-28_final
2022-06-29 11:07:47	ga_ls8c_ard_3-2-1_108074_2022-06-29_final
2022-07-02 11:42:17	ga_ls8c_ard_3-2-1_113083_2022-07-02_final
2022-07-04 11:25:56	ga_ls8c_ard_3-2-1_111073_2022-07-04_final
2022-07-07 11:58:02	ga_ls8c_ard_3-2-1_116076_2022-07-07_final
2022-07-12 10:36:04	ga_ls8c_ard_3-2-1_103072_2022-07-12_final
2022-07-25 10:04:30	ga_ls8c_ard_3-2-1_098070_2022-07-25_final
2022-07-28 10:36:14	ga_ls8c_ard_3-2-1_103072_2022-07-28_final
2022-08-02 09:22:19	ga_ls8c_ard_3-2-1_090088_2022-08-01_final
2022-08-02 10:56:25	ga_ls8c_ard_3-2-1_106076_2022-08-02_final
2022-08-21 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-08-21_final
2022-08-24 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-08-24_final
2022-09-01 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-09-01_final
2022-09-10 09:23:05	ga_ls8c_ard_3-2-1_091074_2022-09-09_final
2022-09-12 10:49:37	ga_ls8c_ard_3-2-1_105074_2022-09-12_final
2022-09-20 09:58:13	ga_ls8c_ard_3-2-1_097069_2022-09-20_final
2022-09-20 11:39:06	ga_ls8c_ard_3-2-1_113074_2022-09-20_final
2022-09-26 09:29:07	ga_ls8c_ard_3-2-1_091089_2022-09-25_final
2022-09-26 11:02:25	ga_ls8c_ard_3-2-1_107075_2022-09-26_final
2022-09-27 10:10:47	ga_ls8c_ard_3-2-1_098085_2022-09-27_final
2022-09-29 11:33:18	ga_ls8c_ard_3-2-1_112075_2022-09-29_final
2022-10-06 09:57:46	ga_ls8c_ard_3-2-1_097068_2022-10-06_final
2022-10-06 11:42:38	ga_ls8c_ard_3-2-1_113083_2022-10-06_final
2022-10-11 10:22:38	ga_ls8c_ard_3-2-1_100084_2022-10-11_final
2022-10-13 10:04:15	ga_ls8c_ard_3-2-1_098069_2022-10-13_final
2022-10-13 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-10-13_final
2022-10-15 11:32:23	ga_ls8c_ard_3-2-1_112073_2022-10-15_final
2022-10-18 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-10-18_final
2022-10-26 09:34:16	ga_ls8c_ard_3-2-1_093071_2022-10-26_final
2022-10-30 10:50:03	ga_ls8c_ard_3-2-1_105075_2022-10-30_final
2022-10-30 10:53:14	ga_ls8c_ard_3-2-1_105083_2022-10-30_final
2022-11-01 10:36:29	ga_ls8c_ard_3-2-1_103072_2022-11-01_final
2022-11-02 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-11-02_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-14 10:04:19	ga_ls8c_ard_3-2-1_098069_2022-11-14_final
2022-11-22 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-11-21_final
2022-11-24 10:46:34	ga_ls8c_ard_3-2-1_104082_2022-11-24_final
2022-12-08 09:18:03	ga_ls8c_ard_3-2-1_090077_2022-12-07_final
2022-12-11 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-12-11_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2022-12-22 09:33:50	ga_ls8c_ard_3-2-1_092086_2022-12-22_final
2022-12-27 11:25:17	ga_ls8c_ard_3-2-1_111071_2022-12-27_final
2022-12-30 10:19:19	ga_ls8c_ard_3-2-1_100076_2022-12-30_final
2023-01-01 10:07:45	ga_ls8c_ard_3-2-1_098078_2023-01-01_final
2023-01-02 09:14:56	ga_ls8c_ard_3-2-1_089085_2023-01-01_final
2023-01-09 10:53:35	ga_ls8c_ard_3-2-1_106069_2023-01-09_final
2023-01-16 11:00:04	ga_ls8c_ard_3-2-1_107070_2023-01-16_final
2023-01-26 09:57:08	ga_ls8c_ard_3-2-1_097067_2023-01-26_final
2023-02-01 09:28:27	ga_ls8c_ard_3-2-1_091088_2023-01-31_final
2023-02-05 10:36:13	ga_ls8c_ard_3-2-1_103072_2023-02-05_final
2023-02-09 10:11:52	ga_ls8c_ard_3-2-1_099073_2023-02-09_final
2023-02-11 11:38:46	ga_ls8c_ard_3-2-1_113074_2023-02-11_final
2023-02-19 09:14:42	ga_ls8c_ard_3-2-1_089085_2023-02-18_final
2023-02-19 10:47:36	ga_ls8c_ard_3-2-1_105070_2023-02-19_final
2023-02-22 11:20:26	ga_ls8c_ard_3-2-1_110075_2023-02-22_final
2023-02-26 09:17:33	ga_ls8c_ard_3-2-1_090077_2023-02-25_final
2023-03-05 11:04:59	ga_ls8c_ard_3-2-1_107083_2023-03-05_final
2023-03-12 09:33:50	ga_ls8c_ard_3-2-1_092087_2023-03-12_final
2023-03-17 09:46:45	ga_ls8c_ard_3-2-1_095073_2023-03-17_final
2023-03-20 10:18:48	ga_ls8c_ard_3-2-1_100076_2023-03-20_final
2023-03-22 10:03:37	ga_ls8c_ard_3-2-1_098069_2023-03-22_final
2023-03-23 09:16:21	ga_ls8c_ard_3-2-1_089090_2023-03-22_final
2023-03-30 10:55:47	ga_ls8c_ard_3-2-1_106076_2023-03-30_final
2023-03-31 09:58:57	ga_ls8c_ard_3-2-1_097073_2023-03-31_final
2023-03-31 11:39:50	ga_ls8c_ard_3-2-1_113078_2023-03-31_final
2023-04-01 09:06:54	ga_ls8c_ard_3-2-1_088082_2023-03-31_final
2023-04-04 11:11:27	ga_ls8c_ard_3-2-1_109069_2023-04-04_final
2023-04-04 11:16:14	ga_ls8c_ard_3-2-1_109081_2023-04-04_final
2023-04-09 09:51:24	ga_ls8c_ard_3-2-1_096070_2023-04-09_final
2023-04-09 11:35:28	ga_ls8c_ard_3-2-1_112083_2023-04-09_final
2023-04-14 10:15:28	ga_ls8c_ard_3-2-1_099084_2023-04-14_final
2023-04-17 10:45:33	ga_ls8c_ard_3-2-1_104082_2023-04-17_final
2023-05-03 09:06:35	ga_ls8c_ard_3-2-1_088082_2023-05-02_final
2023-05-05 10:28:18	ga_ls8c_ard_3-2-1_102070_2023-05-05_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