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
2022-06-02 09:46:25	ga_ls8c_ard_3-2-1_095072_2022-06-02_final
2022-06-04 11:13:22	ga_ls8c_ard_3-2-1_109073_2022-06-04_final
2022-06-21 10:18:19	ga_ls8c_ard_3-2-1_100074_2022-06-21_final
2022-06-23 10:07:10	ga_ls8c_ard_3-2-1_098077_2022-06-23_final
2022-06-23 11:47:15	ga_ls8c_ard_3-2-1_114080_2022-06-23_final
2022-06-24 09:12:21	ga_ls8c_ard_3-2-1_089079_2022-06-23_final
2022-06-24 09:14:44	ga_ls8c_ard_3-2-1_089085_2022-06-23_final
2022-07-10 10:47:15	ga_ls8c_ard_3-2-1_105069_2022-07-10_final
2022-07-15 09:29:16	ga_ls8c_ard_3-2-1_092075_2022-07-14_final
2022-07-15 11:06:10	ga_ls8c_ard_3-2-1_108070_2022-07-15_final
2022-07-16 10:11:21	ga_ls8c_ard_3-2-1_099072_2022-07-16_final
2022-07-17 10:53:49	ga_ls8c_ard_3-2-1_106070_2022-07-17_final
2022-07-18 09:59:49	ga_ls8c_ard_3-2-1_097074_2022-07-18_final
2022-07-20 11:25:34	ga_ls8c_ard_3-2-1_111072_2022-07-20_final
2022-07-27 11:35:50	ga_ls8c_ard_3-2-1_112082_2022-07-27_final
2022-07-29 11:21:30	ga_ls8c_ard_3-2-1_110077_2022-07-29_final
2022-07-31 09:31:28	ga_ls8c_ard_3-2-1_092080_2022-07-31_final
2022-08-02 09:22:43	ga_ls8c_ard_3-2-1_090089_2022-08-01_final
2022-08-04 10:46:28	ga_ls8c_ard_3-2-1_104082_2022-08-04_final
2022-08-05 09:51:39	ga_ls8c_ard_3-2-1_095084_2022-08-05_final
2022-08-11 10:50:42	ga_ls8c_ard_3-2-1_105077_2022-08-11_final
2022-08-14 11:24:25	ga_ls8c_ard_3-2-1_110084_2022-08-14_final
2022-08-20 09:07:16	ga_ls8c_ard_3-2-1_088081_2022-08-19_final
2022-08-24 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-08-24_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-08-25 11:01:30	ga_ls8c_ard_3-2-1_107073_2022-08-25_final
2022-08-27 09:13:51	ga_ls8c_ard_3-2-1_089082_2022-08-26_final
2022-09-02 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-09-02_final
2022-09-03 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-09-02_final
2022-09-03 10:54:07	ga_ls8c_ard_3-2-1_106070_2022-09-03_final
2022-09-10 11:00:46	ga_ls8c_ard_3-2-1_107071_2022-09-10_final
2022-09-11 10:05:33	ga_ls8c_ard_3-2-1_098072_2022-09-11_final
2022-09-11 10:06:45	ga_ls8c_ard_3-2-1_098075_2022-09-11_final
2022-09-17 11:07:47	ga_ls8c_ard_3-2-1_108073_2022-09-17_final
2022-09-18 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-09-18_final
2022-09-19 10:54:38	ga_ls8c_ard_3-2-1_106071_2022-09-19_final
2022-09-24 09:37:29	ga_ls8c_ard_3-2-1_093079_2022-09-24_final
2022-09-24 09:39:05	ga_ls8c_ard_3-2-1_093083_2022-09-24_final
2022-09-26 09:24:20	ga_ls8c_ard_3-2-1_091077_2022-09-25_final
2022-09-26 11:02:49	ga_ls8c_ard_3-2-1_107076_2022-09-26_final
2022-09-28 09:13:58	ga_ls8c_ard_3-2-1_089082_2022-09-27_final
2022-10-10 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-10-10_final
2022-10-11 10:17:50	ga_ls8c_ard_3-2-1_100072_2022-10-11_final
2022-10-13 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-10-13_final
2022-10-22 09:58:33	ga_ls8c_ard_3-2-1_097070_2022-10-22_final
2022-10-24 09:50:36	ga_ls8c_ard_3-2-1_095081_2022-10-24_final
2022-10-27 10:19:32	ga_ls8c_ard_3-2-1_100076_2022-10-27_final
2022-10-30 09:13:33	ga_ls8c_ard_3-2-1_089081_2022-10-29_final
2022-10-30 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-10-29_final
2022-11-03 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-11-03_final
2022-11-06 10:55:01	ga_ls8c_ard_3-2-1_106072_2022-11-06_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-09 09:47:49	ga_ls8c_ard_3-2-1_095074_2022-11-09_final
2022-11-14 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-14_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_final
2022-11-18 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-11-18_final
2022-11-20 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-11-19_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-12-01 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-30_final
2022-12-13 09:35:45	ga_ls8c_ard_3-2-1_093075_2022-12-13_final
2022-12-15 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-12-15_final
2022-12-17 10:47:52	ga_ls8c_ard_3-2-1_105070_2022-12-17_final
2022-12-20 09:45:50	ga_ls8c_ard_3-2-1_094085_2022-12-20_final
2022-12-20 11:19:07	ga_ls8c_ard_3-2-1_110071_2022-12-20_final
2022-12-25 09:59:09	ga_ls8c_ard_3-2-1_097072_2022-12-25_final
2023-01-05 09:45:25	ga_ls8c_ard_3-2-1_094084_2023-01-05_final
2023-01-07 09:31:28	ga_ls8c_ard_3-2-1_092080_2023-01-07_final
2023-01-10 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-10_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-01-30 09:40:49	ga_ls8c_ard_3-2-1_093088_2023-01-30_final
2023-02-01 09:26:51	ga_ls8c_ard_3-2-1_091084_2023-01-31_final
2023-02-05 10:35:25	ga_ls8c_ard_3-2-1_103070_2023-02-05_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-11 09:59:53	ga_ls8c_ard_3-2-1_097074_2023-02-11_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-22 11:20:50	ga_ls8c_ard_3-2-1_110076_2023-02-22_final
2023-03-07 09:11:43	ga_ls8c_ard_3-2-1_089078_2023-03-06_final
2023-03-11 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-03-11_final
2023-03-17 11:28:49	ga_ls8c_ard_3-2-1_111081_2023-03-17_final
2023-03-22 11:46:53	ga_ls8c_ard_3-2-1_114080_2023-03-22_final
2023-03-28 11:06:10	ga_ls8c_ard_3-2-1_108071_2023-03-28_final
2023-03-30 09:20:29	ga_ls8c_ard_3-2-1_090085_2023-03-29_final
2023-04-06 09:26:57	ga_ls8c_ard_3-2-1_091086_2023-04-05_final
2023-04-07 10:07:00	ga_ls8c_ard_3-2-1_098078_2023-04-07_final
2023-04-10 10:34:14	ga_ls8c_ard_3-2-1_103069_2023-04-10_final
2023-04-14 10:13:52	ga_ls8c_ard_3-2-1_099080_2023-04-14_final
2023-04-15 09:19:51	ga_ls8c_ard_3-2-1_090084_2023-04-14_final
2023-04-15 10:55:32	ga_ls8c_ard_3-2-1_106076_2023-04-15_final
2023-04-16 09:57:31	ga_ls8c_ard_3-2-1_097070_2023-04-16_final
2023-04-25 09:51:18	ga_ls8c_ard_3-2-1_096070_2023-04-25_final
2023-04-27 09:45:19	ga_ls8c_ard_3-2-1_094086_2023-04-27_final
2023-04-28 10:25:23	ga_ls8c_ard_3-2-1_101078_2023-04-28_final
2023-04-29 09:32:33	ga_ls8c_ard_3-2-1_092085_2023-04-29_final
2023-04-29 11:06:38	ga_ls8c_ard_3-2-1_108073_2023-04-29_final
2023-05-01 10:57:03	ga_ls8c_ard_3-2-1_106080_2023-05-01_final
2023-05-08 09:26:15	ga_ls8c_ard_3-2-1_091085_2023-05-07_final
2023-05-13 11:20:00	ga_ls8c_ard_3-2-1_110076_2023-05-13_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_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