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
2022-05-16 10:40:22	ga_ls8c_ard_3-2-1_104068_2022-05-16_final
2022-06-12 10:23:14	ga_ls8c_ard_3-2-1_101071_2022-06-12_final
2022-06-18 11:25:05	ga_ls8c_ard_3-2-1_111071_2022-06-18_final
2022-06-20 09:40:14	ga_ls8c_ard_3-2-1_093087_2022-06-20_final
2022-06-21 10:21:54	ga_ls8c_ard_3-2-1_100083_2022-06-21_final
2022-06-22 09:22:18	ga_ls8c_ard_3-2-1_091073_2022-06-21_final
2022-06-30 11:53:27	ga_ls8c_ard_3-2-1_115080_2022-06-30_final
2022-07-06 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-07-06_final
2022-07-08 11:05:36	ga_ls8c_ard_3-2-1_107084_2022-07-08_final
2022-07-17 09:22:55	ga_ls8c_ard_3-2-1_090090_2022-07-16_final
2022-07-29 11:24:17	ga_ls8c_ard_3-2-1_110084_2022-07-29_final
2022-07-31 11:07:34	ga_ls8c_ard_3-2-1_108073_2022-07-31_final
2022-08-06 10:30:32	ga_ls8c_ard_3-2-1_102073_2022-08-06_final
2022-08-13 10:38:21	ga_ls8c_ard_3-2-1_103077_2022-08-13_final
2022-08-13 10:39:57	ga_ls8c_ard_3-2-1_103081_2022-08-13_final
2022-08-16 09:28:23	ga_ls8c_ard_3-2-1_092072_2022-08-15_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-22 10:30:36	ga_ls8c_ard_3-2-1_102073_2022-08-22_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-09-01 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-09-01_final
2022-09-06 09:52:57	ga_ls8c_ard_3-2-1_095087_2022-09-06_final
2022-09-10 09:23:29	ga_ls8c_ard_3-2-1_091075_2022-09-09_final
2022-09-12 09:13:32	ga_ls8c_ard_3-2-1_089081_2022-09-11_final
2022-09-17 11:08:11	ga_ls8c_ard_3-2-1_108074_2022-09-17_final
2022-09-18 10:14:34	ga_ls8c_ard_3-2-1_099079_2022-09-18_final
2022-09-20 11:39:06	ga_ls8c_ard_3-2-1_113074_2022-09-20_final
2022-09-22 09:47:03	ga_ls8c_ard_3-2-1_095072_2022-09-22_final
2022-09-26 09:22:44	ga_ls8c_ard_3-2-1_091073_2022-09-25_final
2022-10-01 09:41:39	ga_ls8c_ard_3-2-1_094074_2022-10-01_final
2022-10-03 09:34:28	ga_ls8c_ard_3-2-1_092087_2022-10-03_final
2022-10-08 09:52:58	ga_ls8c_ard_3-2-1_095087_2022-10-08_final
2022-10-18 10:23:38	ga_ls8c_ard_3-2-1_101071_2022-10-18_final
2022-10-29 11:47:39	ga_ls8c_ard_3-2-1_114080_2022-10-29_final
2022-10-30 09:16:45	ga_ls8c_ard_3-2-1_089089_2022-10-29_final
2022-11-04 09:28:30	ga_ls8c_ard_3-2-1_092072_2022-11-03_final
2022-11-10 10:30:40	ga_ls8c_ard_3-2-1_102073_2022-11-10_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-11-21 11:51:20	ga_ls8c_ard_3-2-1_115074_2022-11-21_final
2022-11-24 10:42:58	ga_ls8c_ard_3-2-1_104073_2022-11-24_final
2022-12-02 09:58:44	ga_ls8c_ard_3-2-1_096086_2022-12-02_final
2022-12-07 11:51:45	ga_ls8c_ard_3-2-1_115075_2022-12-07_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-26 10:42:25	ga_ls8c_ard_3-2-1_104072_2022-12-26_final
2023-01-02 09:12:32	ga_ls8c_ard_3-2-1_089079_2023-01-01_final
2023-01-06 10:28:17	ga_ls8c_ard_3-2-1_101083_2023-01-06_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-18 09:14:47	ga_ls8c_ard_3-2-1_089085_2023-01-17_final
2023-01-20 10:35:21	ga_ls8c_ard_3-2-1_103070_2023-01-20_final
2023-01-25 09:17:52	ga_ls8c_ard_3-2-1_090077_2023-01-24_final
2023-01-31 10:18:53	ga_ls8c_ard_3-2-1_100075_2023-01-31_final
2023-02-06 11:24:40	ga_ls8c_ard_3-2-1_110085_2023-02-06_final
2023-02-07 10:24:15	ga_ls8c_ard_3-2-1_101073_2023-02-07_final
2023-02-09 11:52:45	ga_ls8c_ard_3-2-1_115078_2023-02-09_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-12 10:42:20	ga_ls8c_ard_3-2-1_104072_2023-02-12_final
2023-02-18 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-02-18_final
2023-02-20 09:57:33	ga_ls8c_ard_3-2-1_096084_2023-02-20_final
2023-02-20 11:31:38	ga_ls8c_ard_3-2-1_112072_2023-02-20_final
2023-02-26 10:58:50	ga_ls8c_ard_3-2-1_106083_2023-02-26_final
2023-02-27 11:38:30	ga_ls8c_ard_3-2-1_113074_2023-02-27_final
2023-03-03 09:33:41	ga_ls8c_ard_3-2-1_093071_2023-03-03_final
2023-03-08 09:52:34	ga_ls8c_ard_3-2-1_096072_2023-03-08_final
2023-03-13 10:13:53	ga_ls8c_ard_3-2-1_099079_2023-03-13_final
2023-03-14 09:21:04	ga_ls8c_ard_3-2-1_090086_2023-03-13_final
2023-03-15 11:42:00	ga_ls8c_ard_3-2-1_113083_2023-03-15_final
2023-03-20 10:18:48	ga_ls8c_ard_3-2-1_100076_2023-03-20_final
2023-03-20 11:58:29	ga_ls8c_ard_3-2-1_116078_2023-03-20_final
2023-03-21 09:25:09	ga_ls8c_ard_3-2-1_091081_2023-03-20_final
2023-03-22 11:44:53	ga_ls8c_ard_3-2-1_114075_2023-03-22_final
2023-03-23 09:11:58	ga_ls8c_ard_3-2-1_089079_2023-03-22_final
2023-03-23 10:48:51	ga_ls8c_ard_3-2-1_105074_2023-03-23_final
2023-03-28 11:09:21	ga_ls8c_ard_3-2-1_108079_2023-03-28_final
2023-04-18 11:24:49	ga_ls8c_ard_3-2-1_111072_2023-04-18_final
2023-04-30 11:52:41	ga_ls8c_ard_3-2-1_115080_2023-04-30_final
2023-05-04 11:24:44	ga_ls8c_ard_3-2-1_111072_2023-05-04_final
2023-05-17 09:21:09	ga_ls8c_ard_3-2-1_090088_2023-05-16_final
2023-05-22 09:38:55	ga_ls8c_ard_3-2-1_093086_2023-05-22_final
2023-05-26 10:45:31	ga_ls8c_ard_3-2-1_105067_2023-05-26_final
2023-06-10 10:06:45	ga_ls8c_ard_3-2-1_098078_2023-06-10_final
2023-06-11 10:45:38	ga_ls8c_ard_3-2-1_105067_2023-06-11_final
2023-06-16 09:32:55	ga_ls8c_ard_3-2-1_092086_2023-06-16_final
2023-06-16 11:06:36	ga_ls8c_ard_3-2-1_108073_2023-06-16_final
2023-06-17 10:09:24	ga_ls8c_ard_3-2-1_099069_2023-06-17_final
2023-06-17 10:14:59	ga_ls8c_ard_3-2-1_099083_2023-06-17_final
2023-06-18 09:16:58	ga_ls8c_ard_3-2-1_090077_2023-06-17_final
2023-06-18 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-06-18_final
2023-06-20 09:06:12	ga_ls8c_ard_3-2-1_088081_2023-06-19_final
2023-06-23 09:33:07	ga_ls8c_ard_3-2-1_093071_2023-06-23_final
2023-06-23 11:17:11	ga_ls8c_ard_3-2-1_109084_2023-06-23_final
2023-06-24 10:20:47	ga_ls8c_ard_3-2-1_100082_2023-06-24_final
2023-07-05 11:41:17	ga_ls8c_ard_3-2-1_113082_2023-07-05_final
2023-07-10 10:21:23	ga_ls8c_ard_3-2-1_100083_2023-07-10_final
2023-07-19 10:09:38	ga_ls8c_ard_3-2-1_099069_2023-07-19_final
2023-07-19 11:50:54	ga_ls8c_ard_3-2-1_115075_2023-07-19_final
2023-07-23 09:50:56	ga_ls8c_ard_3-2-1_095084_2023-07-23_final
2023-07-24 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-07-24_final
2023-08-04 10:09:47	ga_ls8c_ard_3-2-1_099069_2023-08-04_final
2023-08-13 10:02:50	ga_ls8c_ard_3-2-1_098067_2023-08-13_final
2023-09-04 11:07:31	ga_ls8c_ard_3-2-1_108074_2023-09-04_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