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
2022-02-16 10:49:04	ga_ls8c_ard_3-2-1_105074_2022-02-16_final
2022-03-18 09:28:46	ga_ls8c_ard_3-2-1_091090_2022-03-17_final
2022-04-05 10:46:46	ga_ls8c_ard_3-2-1_105069_2022-04-05_final
2022-04-10 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-04-10_final
2022-04-30 10:42:12	ga_ls8c_ard_3-2-1_104073_2022-04-30_final
2022-05-03 09:40:14	ga_ls8c_ard_3-2-1_093088_2022-05-03_final
2022-05-19 11:13:16	ga_ls8c_ard_3-2-1_109073_2022-05-19_final
2022-05-21 09:27:13	ga_ls8c_ard_3-2-1_091086_2022-05-20_final
2022-05-22 10:06:53	ga_ls8c_ard_3-2-1_098077_2022-05-22_final
2022-05-23 10:51:20	ga_ls8c_ard_3-2-1_105080_2022-05-23_final
2022-05-29 10:11:04	ga_ls8c_ard_3-2-1_099072_2022-05-29_final
2022-06-02 11:26:30	ga_ls8c_ard_3-2-1_111075_2022-06-02_final
2022-06-16 09:58:33	ga_ls8c_ard_3-2-1_097071_2022-06-16_final
2022-07-17 09:16:56	ga_ls8c_ard_3-2-1_090075_2022-07-16_final
2022-07-22 09:37:09	ga_ls8c_ard_3-2-1_093079_2022-07-22_final
2022-07-29 09:46:12	ga_ls8c_ard_3-2-1_094086_2022-07-29_final
2022-08-03 11:41:17	ga_ls8c_ard_3-2-1_113080_2022-08-03_final
2022-08-05 11:30:08	ga_ls8c_ard_3-2-1_111083_2022-08-05_final
2022-08-07 09:34:31	ga_ls8c_ard_3-2-1_093072_2022-08-07_final
2022-08-08 10:19:23	ga_ls8c_ard_3-2-1_100076_2022-08-08_final
2022-08-09 09:22:58	ga_ls8c_ard_3-2-1_091074_2022-08-08_final
2022-08-14 11:20:01	ga_ls8c_ard_3-2-1_110073_2022-08-14_final
2022-08-25 09:23:01	ga_ls8c_ard_3-2-1_091074_2022-08-24_final
2022-09-02 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-09-02_final
2022-09-04 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-09-04_final
2022-09-08 09:36:13	ga_ls8c_ard_3-2-1_093076_2022-09-08_final
2022-09-18 11:53:03	ga_ls8c_ard_3-2-1_115078_2022-09-18_final
2022-09-26 09:27:31	ga_ls8c_ard_3-2-1_091085_2022-09-25_final
2022-10-02 10:25:19	ga_ls8c_ard_3-2-1_101075_2022-10-02_final
2022-10-03 09:34:28	ga_ls8c_ard_3-2-1_092087_2022-10-03_final
2022-10-08 09:51:22	ga_ls8c_ard_3-2-1_095083_2022-10-08_final
2022-10-18 10:23:38	ga_ls8c_ard_3-2-1_101071_2022-10-18_final
2022-10-20 11:53:22	ga_ls8c_ard_3-2-1_115079_2022-10-20_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-11-02 09:41:40	ga_ls8c_ard_3-2-1_094074_2022-11-02_final
2022-11-02 11:23:45	ga_ls8c_ard_3-2-1_110082_2022-11-02_final
2022-11-16 11:36:47	ga_ls8c_ard_3-2-1_112084_2022-11-16_final
2022-11-18 09:40:20	ga_ls8c_ard_3-2-1_094071_2022-11-18_final
2022-12-17 10:50:40	ga_ls8c_ard_3-2-1_105077_2022-12-17_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-27 11:30:29	ga_ls8c_ard_3-2-1_111084_2022-12-27_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2023-01-02 10:48:37	ga_ls8c_ard_3-2-1_105072_2023-01-02_final
2023-01-10 09:58:21	ga_ls8c_ard_3-2-1_097070_2023-01-10_final
2023-01-18 10:49:17	ga_ls8c_ard_3-2-1_105074_2023-01-18_final
2023-01-24 10:14:40	ga_ls8c_ard_3-2-1_099080_2023-01-24_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-02-01 09:27:15	ga_ls8c_ard_3-2-1_091085_2023-01-31_final
2023-02-06 11:19:29	ga_ls8c_ard_3-2-1_110072_2023-02-06_final
2023-02-17 09:27:06	ga_ls8c_ard_3-2-1_091085_2023-02-16_final
2023-02-17 09:28:42	ga_ls8c_ard_3-2-1_091089_2023-02-16_final
2023-02-18 11:44:50	ga_ls8c_ard_3-2-1_114074_2023-02-18_final
2023-02-20 11:36:26	ga_ls8c_ard_3-2-1_112084_2023-02-20_final
2023-02-24 11:08:01	ga_ls8c_ard_3-2-1_108075_2023-02-24_final
2023-02-27 11:41:42	ga_ls8c_ard_3-2-1_113082_2023-02-27_final
2023-03-18 10:28:48	ga_ls8c_ard_3-2-1_102070_2023-03-18_final
2023-03-21 09:25:57	ga_ls8c_ard_3-2-1_091083_2023-03-20_final
2023-03-22 10:04:48	ga_ls8c_ard_3-2-1_098072_2023-03-22_final
2023-03-23 09:16:21	ga_ls8c_ard_3-2-1_089090_2023-03-22_final
2023-03-26 09:45:14	ga_ls8c_ard_3-2-1_094085_2023-03-26_final
2023-04-08 09:16:08	ga_ls8c_ard_3-2-1_089090_2023-04-07_final
2023-04-11 09:39:23	ga_ls8c_ard_3-2-1_094071_2023-04-11_final
2023-04-21 10:18:01	ga_ls8c_ard_3-2-1_100075_2023-04-21_final
2023-04-29 09:32:57	ga_ls8c_ard_3-2-1_092086_2023-04-29_final
2023-05-13 09:45:30	ga_ls8c_ard_3-2-1_094087_2023-05-13_final
2023-05-13 11:18:24	ga_ls8c_ard_3-2-1_110072_2023-05-13_final
2023-05-17 10:52:27	ga_ls8c_ard_3-2-1_106069_2023-05-17_final
2023-05-18 11:40:30	ga_ls8c_ard_3-2-1_113081_2023-05-18_final
2023-05-22 09:32:56	ga_ls8c_ard_3-2-1_093071_2023-05-22_final
2023-05-26 10:51:30	ga_ls8c_ard_3-2-1_105082_2023-05-26_final
2023-05-27 09:56:17	ga_ls8c_ard_3-2-1_096083_2023-05-27_final
2023-05-29 09:45:31	ga_ls8c_ard_3-2-1_094087_2023-05-29_final
2023-06-07 11:17:06	ga_ls8c_ard_3-2-1_109084_2023-06-07_final
2023-06-09 09:21:53	ga_ls8c_ard_3-2-1_091074_2023-06-08_final
2023-06-10 11:46:26	ga_ls8c_ard_3-2-1_114080_2023-06-10_final
2023-06-14 11:22:57	ga_ls8c_ard_3-2-1_110083_2023-06-14_final
2023-07-05 11:41:17	ga_ls8c_ard_3-2-1_113082_2023-07-05_final
2023-07-09 11:12:13	ga_ls8c_ard_3-2-1_109071_2023-07-09_final
2023-07-24 10:27:49	ga_ls8c_ard_3-2-1_102068_2023-07-24_final
2023-08-10 11:13:35	ga_ls8c_ard_3-2-1_109074_2023-08-10_final
2023-08-21 09:22:40	ga_ls8c_ard_3-2-1_090090_2023-08-20_final
2023-09-02 09:45:24	ga_ls8c_ard_3-2-1_094085_2023-09-02_final
2023-09-05 10:09:06	ga_ls8c_ard_3-2-1_099067_2023-09-05_final
2023-09-06 10:53:09	ga_ls8c_ard_3-2-1_106069_2023-09-06_final
2023-09-09 09:51:35	ga_ls8c_ard_3-2-1_095085_2023-09-09_final
2023-09-13 09:27:43	ga_ls8c_ard_3-2-1_091087_2023-09-12_final
2023-09-14 10:04:12	ga_ls8c_ard_3-2-1_098070_2023-09-14_final
2023-09-14 10:04:36	ga_ls8c_ard_3-2-1_098071_2023-09-14_final
2023-09-21 10:15:11	ga_ls8c_ard_3-2-1_099082_2023-09-21_final
2023-09-21 10:15:59	ga_ls8c_ard_3-2-1_099084_2023-09-21_final
2023-09-27 09:40:08	ga_ls8c_ard_3-2-1_093087_2023-09-27_final
2023-10-11 09:46:10	ga_ls8c_ard_3-2-1_095071_2023-10-11_final
2023-10-17 09:16:40	ga_ls8c_ard_3-2-1_089090_2023-10-16_final
2023-10-23 10:09:42	ga_ls8c_ard_3-2-1_099068_2023-10-23_final
2023-10-25 10:03:45	ga_ls8c_ard_3-2-1_097084_2023-10-25_final
2023-10-27 11:26:18	ga_ls8c_ard_3-2-1_111074_2023-10-27_final
2023-11-02 10:46:49	ga_ls8c_ard_3-2-1_105068_2023-11-02_final
2023-11-03 09:58:23	ga_ls8c_ard_3-2-1_096086_2023-11-03_final
2023-11-16 09:23:29	ga_ls8c_ard_3-2-1_091076_2023-11-15_final
2023-11-16 09:28:40	ga_ls8c_ard_3-2-1_091089_2023-11-15_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