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
2022-08-22 10:30:36	ga_ls8c_ard_3-2-1_102073_2022-08-22_final
2022-09-26 09:22:44	ga_ls8c_ard_3-2-1_091073_2022-09-25_final
2022-10-04 11:53:25	ga_ls8c_ard_3-2-1_115079_2022-10-04_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-10 09:35:23	ga_ls8c_ard_3-2-1_093074_2022-10-10_final
2022-10-10 11:17:28	ga_ls8c_ard_3-2-1_109082_2022-10-10_final
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-28 11:01:12	ga_ls8c_ard_3-2-1_107072_2022-10-28_final
2022-10-29 10:04:23	ga_ls8c_ard_3-2-1_098069_2022-10-29_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-11-02 11:19:45	ga_ls8c_ard_3-2-1_110072_2022-11-02_final
2022-11-04 09:31:42	ga_ls8c_ard_3-2-1_092080_2022-11-04_final
2022-11-10 10:32:16	ga_ls8c_ard_3-2-1_102077_2022-11-10_final
2022-11-15 09:14:40	ga_ls8c_ard_3-2-1_089084_2022-11-14_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-11-18 09:45:07	ga_ls8c_ard_3-2-1_094083_2022-11-18_final
2022-11-26 10:29:25	ga_ls8c_ard_3-2-1_102070_2022-11-26_final
2022-11-26 10:30:13	ga_ls8c_ard_3-2-1_102072_2022-11-26_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-05 10:26:02	ga_ls8c_ard_3-2-1_101077_2022-12-05_final
2022-12-08 10:54:32	ga_ls8c_ard_3-2-1_106071_2022-12-08_final
2022-12-09 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-12-09_final
2022-12-14 10:18:12	ga_ls8c_ard_3-2-1_100073_2022-12-14_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-22 09:33:26	ga_ls8c_ard_3-2-1_092085_2022-12-22_final
2023-01-01 10:10:33	ga_ls8c_ard_3-2-1_098085_2023-01-01_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-08 11:51:36	ga_ls8c_ard_3-2-1_115075_2023-01-08_final
2023-01-09 09:21:53	ga_ls8c_ard_3-2-1_090087_2023-01-08_final
2023-01-09 09:23:05	ga_ls8c_ard_3-2-1_090090_2023-01-08_final
2023-01-11 10:43:12	ga_ls8c_ard_3-2-1_104074_2023-01-11_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-06 11:19:05	ga_ls8c_ard_3-2-1_110071_2023-02-06_final
2023-02-09 11:51:57	ga_ls8c_ard_3-2-1_115076_2023-02-09_final
2023-02-10 09:21:25	ga_ls8c_ard_3-2-1_090086_2023-02-09_final
2023-02-11 11:39:10	ga_ls8c_ard_3-2-1_113075_2023-02-11_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-19 11:13:38	ga_ls8c_ard_3-2-1_109074_2023-03-19_final
2023-03-21 09:28:45	ga_ls8c_ard_3-2-1_091090_2023-03-20_final
2023-03-25 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-03-25_final
2023-03-29 10:13:20	ga_ls8c_ard_3-2-1_099078_2023-03-29_final
2023-04-01 10:43:24	ga_ls8c_ard_3-2-1_104076_2023-04-01_final
2023-04-02 09:46:10	ga_ls8c_ard_3-2-1_095072_2023-04-02_final
2023-04-08 10:46:38	ga_ls8c_ard_3-2-1_105069_2023-04-08_final
2023-04-15 09:16:15	ga_ls8c_ard_3-2-1_090075_2023-04-14_final
2023-04-19 10:27:59	ga_ls8c_ard_3-2-1_102069_2023-04-19_final
2023-04-20 09:39:08	ga_ls8c_ard_3-2-1_093086_2023-04-20_final
2023-04-20 09:39:32	ga_ls8c_ard_3-2-1_093087_2023-04-20_final
2023-04-24 09:12:50	ga_ls8c_ard_3-2-1_089082_2023-04-23_final
2023-04-24 10:46:56	ga_ls8c_ard_3-2-1_105070_2023-04-24_final
2023-04-28 10:24:35	ga_ls8c_ard_3-2-1_101076_2023-04-28_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-20 11:24:34	ga_ls8c_ard_3-2-1_111072_2023-05-20_final
2023-05-21 10:27:45	ga_ls8c_ard_3-2-1_102069_2023-05-21_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-29 09:45:07	ga_ls8c_ard_3-2-1_094086_2023-05-29_final
2023-05-29 11:19:37	ga_ls8c_ard_3-2-1_110075_2023-05-29_final
2023-05-30 10:22:00	ga_ls8c_ard_3-2-1_101070_2023-05-30_final
2023-06-03 09:57:17	ga_ls8c_ard_3-2-1_097070_2023-06-03_final
2023-06-03 11:40:10	ga_ls8c_ard_3-2-1_113080_2023-06-03_final
2023-06-03 11:41:22	ga_ls8c_ard_3-2-1_113083_2023-06-03_final
2023-06-09 09:21:29	ga_ls8c_ard_3-2-1_091073_2023-06-08_final
2023-06-11 10:45:38	ga_ls8c_ard_3-2-1_105067_2023-06-11_final
2023-06-13 10:34:30	ga_ls8c_ard_3-2-1_103070_2023-06-13_final
2023-06-14 09:40:04	ga_ls8c_ard_3-2-1_094073_2023-06-14_final
2023-06-23 11:17:11	ga_ls8c_ard_3-2-1_109084_2023-06-23_final
2023-06-25 11:00:53	ga_ls8c_ard_3-2-1_107074_2023-06-25_final
2023-07-04 10:54:26	ga_ls8c_ard_3-2-1_106073_2023-07-04_final
2023-07-09 09:34:08	ga_ls8c_ard_3-2-1_093073_2023-07-09_final
2023-07-11 11:04:39	ga_ls8c_ard_3-2-1_107083_2023-07-11_final
2023-07-12 10:09:02	ga_ls8c_ard_3-2-1_098083_2023-07-12_final
2023-07-20 09:20:23	ga_ls8c_ard_3-2-1_090085_2023-07-19_final
2023-07-23 11:25:01	ga_ls8c_ard_3-2-1_111072_2023-07-23_final
2023-07-28 10:09:08	ga_ls8c_ard_3-2-1_098083_2023-07-28_final
2023-07-29 09:11:32	ga_ls8c_ard_3-2-1_089078_2023-07-28_final
2023-08-04 11:52:16	ga_ls8c_ard_3-2-1_115078_2023-08-04_final
2023-08-05 09:17:21	ga_ls8c_ard_3-2-1_090077_2023-08-04_final
2023-08-05 09:20:57	ga_ls8c_ard_3-2-1_090086_2023-08-04_final
2023-08-10 09:39:05	ga_ls8c_ard_3-2-1_093085_2023-08-10_final
2023-08-14 09:16:24	ga_ls8c_ard_3-2-1_089090_2023-08-13_final
2023-08-14 10:49:42	ga_ls8c_ard_3-2-1_105076_2023-08-14_final
2023-08-14 10:52:06	ga_ls8c_ard_3-2-1_105082_2023-08-14_final
2023-08-15 09:58:05	ga_ls8c_ard_3-2-1_096086_2023-08-15_final
2023-08-15 11:35:46	ga_ls8c_ard_3-2-1_112083_2023-08-15_final
2023-08-21 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-08-20_final
2023-08-24 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-08-24_final
2023-08-28 09:28:52	ga_ls8c_ard_3-2-1_091090_2023-08-27_final
2023-08-30 09:13:19	ga_ls8c_ard_3-2-1_089082_2023-08-29_final
2023-09-02 11:18:18	ga_ls8c_ard_3-2-1_110070_2023-09-02_final
2023-09-06 10:55:57	ga_ls8c_ard_3-2-1_106076_2023-09-06_final
2023-09-15 09:13:22	ga_ls8c_ard_3-2-1_089082_2023-09-14_final
2023-10-08 10:55:19	ga_ls8c_ard_3-2-1_106074_2023-10-08_final
2023-10-24 10:54:10	ga_ls8c_ard_3-2-1_106071_2023-10-24_final
2023-10-27 09:47:01	ga_ls8c_ard_3-2-1_095073_2023-10-27_final
2023-10-31 09:26:17	ga_ls8c_ard_3-2-1_091083_2023-10-30_final
2023-11-09 09:21:13	ga_ls8c_ard_3-2-1_090086_2023-11-08_final
2023-11-16 09:26:16	ga_ls8c_ard_3-2-1_091083_2023-11-15_final
2023-11-18 09:12:44	ga_ls8c_ard_3-2-1_089080_2023-11-17_final
2023-11-21 11:19:21	ga_ls8c_ard_3-2-1_110072_2023-11-21_final
2023-11-21 11:21:21	ga_ls8c_ard_3-2-1_110077_2023-11-21_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