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
2022-09-28 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-09-27_final
2022-09-30 10:36:05	ga_ls8c_ard_3-2-1_103071_2022-09-30_final
2022-10-01 09:41:39	ga_ls8c_ard_3-2-1_094074_2022-10-01_final
2022-10-05 10:58:35	ga_ls8c_ard_3-2-1_106081_2022-10-05_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-13 10:06:14	ga_ls8c_ard_3-2-1_098074_2022-10-13_final
2022-10-17 09:45:57	ga_ls8c_ard_3-2-1_094085_2022-10-17_final
2022-10-19 11:07:42	ga_ls8c_ard_3-2-1_108073_2022-10-19_final
2022-10-22 09:59:45	ga_ls8c_ard_3-2-1_097073_2022-10-22_final
2022-10-22 10:03:21	ga_ls8c_ard_3-2-1_097082_2022-10-22_final
2022-10-26 09:37:51	ga_ls8c_ard_3-2-1_093080_2022-10-26_final
2022-10-28 09:23:55	ga_ls8c_ard_3-2-1_091076_2022-10-27_final
2022-10-28 09:26:42	ga_ls8c_ard_3-2-1_091083_2022-10-27_final
2022-10-29 10:03:59	ga_ls8c_ard_3-2-1_098068_2022-10-29_final
2022-10-29 10:06:23	ga_ls8c_ard_3-2-1_098074_2022-10-29_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-11-02 09:41:40	ga_ls8c_ard_3-2-1_094074_2022-11-02_final
2022-11-04 11:06:59	ga_ls8c_ard_3-2-1_108071_2022-11-04_final
2022-11-06 09:21:44	ga_ls8c_ard_3-2-1_090086_2022-11-05_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-06 10:58:37	ga_ls8c_ard_3-2-1_106081_2022-11-06_final
2022-11-07 11:42:16	ga_ls8c_ard_3-2-1_113082_2022-11-07_final
2022-11-09 09:47:01	ga_ls8c_ard_3-2-1_095072_2022-11-09_final
2022-11-10 10:34:16	ga_ls8c_ard_3-2-1_102082_2022-11-10_final
2022-11-11 11:12:20	ga_ls8c_ard_3-2-1_109069_2022-11-11_final
2022-11-18 11:18:49	ga_ls8c_ard_3-2-1_110070_2022-11-18_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-22 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-11-21_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-23 11:41:47	ga_ls8c_ard_3-2-1_113081_2022-11-23_final
2022-11-23 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-11-23_final
2022-11-24 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-11-24_final
2022-11-25 09:50:57	ga_ls8c_ard_3-2-1_095082_2022-11-25_final
2022-11-27 09:35:48	ga_ls8c_ard_3-2-1_093075_2022-11-27_final
2022-11-27 09:38:12	ga_ls8c_ard_3-2-1_093081_2022-11-27_final
2022-11-29 11:05:55	ga_ls8c_ard_3-2-1_107084_2022-11-29_final
2022-11-30 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-30_final
2022-12-03 10:35:13	ga_ls8c_ard_3-2-1_103069_2022-12-03_final
2022-12-03 10:36:24	ga_ls8c_ard_3-2-1_103072_2022-12-03_final
2022-12-04 09:41:35	ga_ls8c_ard_3-2-1_094074_2022-12-04_final
2022-12-06 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-12-06_final
2022-12-06 09:32:48	ga_ls8c_ard_3-2-1_092083_2022-12-06_final
2022-12-07 10:14:04	ga_ls8c_ard_3-2-1_099078_2022-12-07_final
2022-12-08 10:56:56	ga_ls8c_ard_3-2-1_106077_2022-12-08_final
2022-12-09 10:03:18	ga_ls8c_ard_3-2-1_097082_2022-12-09_final
2022-12-13 09:38:56	ga_ls8c_ard_3-2-1_093083_2022-12-13_final
2022-12-13 09:40:56	ga_ls8c_ard_3-2-1_093088_2022-12-13_final
2022-12-18 09:57:01	ga_ls8c_ard_3-2-1_096082_2022-12-18_final
2022-12-21 10:27:29	ga_ls8c_ard_3-2-1_101081_2022-12-21_final
2022-12-22 09:32:14	ga_ls8c_ard_3-2-1_092082_2022-12-22_final
2022-12-22 09:33:26	ga_ls8c_ard_3-2-1_092085_2022-12-22_final
2022-12-24 10:56:22	ga_ls8c_ard_3-2-1_106076_2022-12-24_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-28 10:29:16	ga_ls8c_ard_3-2-1_102070_2022-12-28_final
2022-12-31 11:04:58	ga_ls8c_ard_3-2-1_107082_2022-12-31_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2023-01-01 10:10:09	ga_ls8c_ard_3-2-1_098084_2023-01-01_final
2023-01-02 10:51:49	ga_ls8c_ard_3-2-1_105080_2023-01-02_final
2023-01-03 09:56:59	ga_ls8c_ard_3-2-1_096082_2023-01-03_final
2023-01-05 09:41:50	ga_ls8c_ard_3-2-1_094075_2023-01-05_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-05 09:45:25	ga_ls8c_ard_3-2-1_094084_2023-01-05_final
2023-01-05 11:23:55	ga_ls8c_ard_3-2-1_110083_2023-01-05_final
2023-01-08 10:15:31	ga_ls8c_ard_3-2-1_099082_2023-01-08_final
2023-01-09 09:22:17	ga_ls8c_ard_3-2-1_090088_2023-01-08_final
2023-01-20 10:38:09	ga_ls8c_ard_3-2-1_103077_2023-01-20_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-23 09:32:36	ga_ls8c_ard_3-2-1_092083_2023-01-23_final
2023-01-23 11:07:29	ga_ls8c_ard_3-2-1_108073_2023-01-23_final
2023-01-24 10:11:05	ga_ls8c_ard_3-2-1_099071_2023-01-24_final
2023-01-25 09:21:03	ga_ls8c_ard_3-2-1_090085_2023-01-24_final
2023-01-26 10:00:20	ga_ls8c_ard_3-2-1_097075_2023-01-26_final
2023-01-26 11:42:00	ga_ls8c_ard_3-2-1_113082_2023-01-26_final
2023-01-30 11:12:07	ga_ls8c_ard_3-2-1_109069_2023-01-30_final
2023-02-01 09:28:51	ga_ls8c_ard_3-2-1_091089_2023-01-31_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-08 09:31:25	ga_ls8c_ard_3-2-1_092080_2023-02-08_final
2023-02-08 09:31:49	ga_ls8c_ard_3-2-1_092081_2023-02-08_final
2023-02-10 09:21:01	ga_ls8c_ard_3-2-1_090085_2023-02-09_final
2023-02-11 10:03:04	ga_ls8c_ard_3-2-1_097082_2023-02-11_final
2023-02-11 11:39:10	ga_ls8c_ard_3-2-1_113075_2023-02-11_final
2023-02-11 11:41:57	ga_ls8c_ard_3-2-1_113082_2023-02-11_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-17 11:05:11	ga_ls8c_ard_3-2-1_107083_2023-02-17_final
2023-02-18 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-02-18_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-20 09:56:45	ga_ls8c_ard_3-2-1_096082_2023-02-20_final
2023-02-22 11:19:38	ga_ls8c_ard_3-2-1_110073_2023-02-22_final
2023-02-22 11:23:37	ga_ls8c_ard_3-2-1_110083_2023-02-22_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-02-26 10:57:38	ga_ls8c_ard_3-2-1_106080_2023-02-26_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-03-01 11:25:45	ga_ls8c_ard_3-2-1_111073_2023-03-01_final
2023-03-02 10:28:55	ga_ls8c_ard_3-2-1_102070_2023-03-02_final
2023-03-03 09:38:05	ga_ls8c_ard_3-2-1_093082_2023-03-03_final
2023-03-05 09:28:54	ga_ls8c_ard_3-2-1_091090_2023-03-04_final
2023-03-05 11:04:35	ga_ls8c_ard_3-2-1_107082_2023-03-05_final
2023-03-10 09:44:59	ga_ls8c_ard_3-2-1_094084_2023-03-10_final
2023-03-10 11:24:16	ga_ls8c_ard_3-2-1_110085_2023-03-10_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