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
2023-02-01 11:02:09	ga_ls8c_ard_3-2-1_107075_2023-02-01_final
2023-02-02 10:03:44	ga_ls8c_ard_3-2-1_098068_2023-02-02_final
2023-02-26 09:19:33	ga_ls8c_ard_3-2-1_090082_2023-02-25_final
2023-03-15 11:40:00	ga_ls8c_ard_3-2-1_113078_2023-03-15_final
2023-03-18 10:31:35	ga_ls8c_ard_3-2-1_102077_2023-03-18_final
2023-03-20 11:58:05	ga_ls8c_ard_3-2-1_116077_2023-03-20_final
2023-05-02 09:58:38	ga_ls8c_ard_3-2-1_097073_2023-05-02_final
2023-05-02 10:01:25	ga_ls8c_ard_3-2-1_097080_2023-05-02_final
2023-05-02 11:40:18	ga_ls8c_ard_3-2-1_113080_2023-05-02_final
2023-05-02 11:41:06	ga_ls8c_ard_3-2-1_113082_2023-05-02_final
2023-05-03 10:42:40	ga_ls8c_ard_3-2-1_104075_2023-05-03_final
2023-05-08 09:26:15	ga_ls8c_ard_3-2-1_091085_2023-05-07_final
2023-05-16 10:09:12	ga_ls8c_ard_3-2-1_099069_2023-05-16_final
2023-05-16 11:50:28	ga_ls8c_ard_3-2-1_115075_2023-05-16_final
2023-05-22 09:34:32	ga_ls8c_ard_3-2-1_093075_2023-05-22_final
2023-05-22 11:11:49	ga_ls8c_ard_3-2-1_109071_2023-05-22_final
2023-05-23 10:20:36	ga_ls8c_ard_3-2-1_100082_2023-05-23_final
2023-05-25 10:03:51	ga_ls8c_ard_3-2-1_098071_2023-05-25_final
2023-05-26 10:48:43	ga_ls8c_ard_3-2-1_105075_2023-05-26_final
2023-05-30 10:26:47	ga_ls8c_ard_3-2-1_101082_2023-05-30_final
2023-06-01 10:10:50	ga_ls8c_ard_3-2-1_099073_2023-06-01_final
2023-06-07 11:12:19	ga_ls8c_ard_3-2-1_109072_2023-06-07_final
2023-06-10 10:03:58	ga_ls8c_ard_3-2-1_098071_2023-06-10_final
2023-06-11 09:10:45	ga_ls8c_ard_3-2-1_089077_2023-06-10_final
2023-06-15 10:22:57	ga_ls8c_ard_3-2-1_101072_2023-06-15_final
2023-06-16 11:07:00	ga_ls8c_ard_3-2-1_108074_2023-06-16_final
2023-06-19 11:38:43	ga_ls8c_ard_3-2-1_113076_2023-06-19_final
2023-06-25 09:26:47	ga_ls8c_ard_3-2-1_091086_2023-06-24_final
2023-06-26 11:44:57	ga_ls8c_ard_3-2-1_114076_2023-06-26_final
2023-07-09 09:34:31	ga_ls8c_ard_3-2-1_093074_2023-07-09_final
2023-07-11 09:28:10	ga_ls8c_ard_3-2-1_091089_2023-07-10_final
2023-07-12 11:46:19	ga_ls8c_ard_3-2-1_114079_2023-07-12_final
2023-07-12 11:46:43	ga_ls8c_ard_3-2-1_114080_2023-07-12_final
2023-07-16 09:43:07	ga_ls8c_ard_3-2-1_094080_2023-07-16_final
2023-07-16 11:19:13	ga_ls8c_ard_3-2-1_110073_2023-07-16_final
2023-07-19 10:10:49	ga_ls8c_ard_3-2-1_099072_2023-07-19_final
2023-07-20 09:19:59	ga_ls8c_ard_3-2-1_090084_2023-07-19_final
2023-07-21 09:56:52	ga_ls8c_ard_3-2-1_097068_2023-07-21_final
2023-07-21 09:59:16	ga_ls8c_ard_3-2-1_097074_2023-07-21_final
2023-07-26 10:21:04	ga_ls8c_ard_3-2-1_100082_2023-07-26_final
2023-07-27 09:25:04	ga_ls8c_ard_3-2-1_091081_2023-07-26_final
2023-07-28 10:05:57	ga_ls8c_ard_3-2-1_098075_2023-07-28_final
2023-07-29 09:14:19	ga_ls8c_ard_3-2-1_089085_2023-07-28_final
2023-08-01 11:18:33	ga_ls8c_ard_3-2-1_110071_2023-08-01_final
2023-08-05 09:17:21	ga_ls8c_ard_3-2-1_090077_2023-08-04_final
2023-08-08 09:47:28	ga_ls8c_ard_3-2-1_095075_2023-08-08_final
2023-08-08 11:25:57	ga_ls8c_ard_3-2-1_111074_2023-08-08_final
2023-08-10 09:39:29	ga_ls8c_ard_3-2-1_093086_2023-08-10_final
2023-08-10 11:17:34	ga_ls8c_ard_3-2-1_109084_2023-08-10_final
2023-08-12 11:01:38	ga_ls8c_ard_3-2-1_107075_2023-08-12_final
2023-08-13 11:44:31	ga_ls8c_ard_3-2-1_114074_2023-08-13_final
2023-08-16 10:37:46	ga_ls8c_ard_3-2-1_103077_2023-08-16_final
2023-08-25 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-08-25_final
2023-08-26 11:14:31	ga_ls8c_ard_3-2-1_109076_2023-08-26_final
2023-08-28 09:26:04	ga_ls8c_ard_3-2-1_091083_2023-08-27_final
2023-09-02 09:41:01	ga_ls8c_ard_3-2-1_094074_2023-09-02_final
2023-09-03 10:25:52	ga_ls8c_ard_3-2-1_101078_2023-09-03_final
2023-09-05 11:51:34	ga_ls8c_ard_3-2-1_115076_2023-09-05_final
2023-09-06 09:19:03	ga_ls8c_ard_3-2-1_090081_2023-09-05_final
2023-09-07 09:59:07	ga_ls8c_ard_3-2-1_097073_2023-09-07_final
2023-09-08 09:06:43	ga_ls8c_ard_3-2-1_088081_2023-09-07_final
2023-09-09 11:24:29	ga_ls8c_ard_3-2-1_111070_2023-09-09_final
2023-09-10 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-09-10_final
2023-09-10 10:29:40	ga_ls8c_ard_3-2-1_102072_2023-09-10_final
2023-09-12 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-09-12_final
2023-09-14 10:06:35	ga_ls8c_ard_3-2-1_098076_2023-09-14_final
2023-09-14 11:45:28	ga_ls8c_ard_3-2-1_114076_2023-09-14_final
2023-09-15 09:11:46	ga_ls8c_ard_3-2-1_089078_2023-09-14_final
2023-09-15 09:12:58	ga_ls8c_ard_3-2-1_089081_2023-09-14_final
2023-09-16 09:51:51	ga_ls8c_ard_3-2-1_096070_2023-09-16_final
2023-09-19 10:22:45	ga_ls8c_ard_3-2-1_101070_2023-09-19_final
2023-09-23 09:58:26	ga_ls8c_ard_3-2-1_097071_2023-09-23_final
2023-09-26 10:32:34	ga_ls8c_ard_3-2-1_102079_2023-09-26_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-09-27 11:13:02	ga_ls8c_ard_3-2-1_109072_2023-09-27_final
2023-09-30 11:45:57	ga_ls8c_ard_3-2-1_114077_2023-09-30_final
2023-10-05 10:25:36	ga_ls8c_ard_3-2-1_101077_2023-10-05_final
2023-10-07 10:12:51	ga_ls8c_ard_3-2-1_099076_2023-10-07_final
2023-10-09 10:00:30	ga_ls8c_ard_3-2-1_097076_2023-10-09_final
2023-10-13 11:13:06	ga_ls8c_ard_3-2-1_109072_2023-10-13_final
2023-10-16 10:08:18	ga_ls8c_ard_3-2-1_098080_2023-10-16_final
2023-10-17 10:52:21	ga_ls8c_ard_3-2-1_105082_2023-10-17_final
2023-10-20 11:22:50	ga_ls8c_ard_3-2-1_110081_2023-10-20_final
2023-10-20 11:24:02	ga_ls8c_ard_3-2-1_110084_2023-10-20_final
2023-10-21 10:25:38	ga_ls8c_ard_3-2-1_101077_2023-10-21_final
2023-10-22 09:32:49	ga_ls8c_ard_3-2-1_092084_2023-10-22_final
2023-10-29 09:33:52	ga_ls8c_ard_3-2-1_093071_2023-10-29_final
2023-10-29 09:39:51	ga_ls8c_ard_3-2-1_093086_2023-10-29_final
2023-10-29 11:12:45	ga_ls8c_ard_3-2-1_109071_2023-10-29_final
2023-11-01 10:05:10	ga_ls8c_ard_3-2-1_098072_2023-11-01_final
2023-11-01 11:45:15	ga_ls8c_ard_3-2-1_114075_2023-11-01_final
2023-11-01 11:46:02	ga_ls8c_ard_3-2-1_114077_2023-11-01_final
2023-11-08 10:09:17	ga_ls8c_ard_3-2-1_099067_2023-11-08_final
2023-11-08 10:15:40	ga_ls8c_ard_3-2-1_099083_2023-11-08_final
2023-11-11 09:06:28	ga_ls8c_ard_3-2-1_088080_2023-11-10_final
2023-11-12 11:29:26	ga_ls8c_ard_3-2-1_111082_2023-11-12_final
2023-11-14 09:34:13	ga_ls8c_ard_3-2-1_093072_2023-11-14_final
2023-11-14 09:34:37	ga_ls8c_ard_3-2-1_093073_2023-11-14_final
2023-11-14 11:12:18	ga_ls8c_ard_3-2-1_109070_2023-11-14_final
2023-11-14 11:13:30	ga_ls8c_ard_3-2-1_109073_2023-11-14_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