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
2013-12-06 09:29:17	ga_ls8c_ard_3-1-0_091087_2013-12-05_final
2019-03-17 11:05:56	ga_ls8c_ard_3-1-0_108071_2019-03-17_final
2019-03-26 09:22:51	ga_ls8c_ard_3-1-0_091076_2019-03-25_final
2019-03-26 09:24:50	ga_ls8c_ard_3-1-0_091081_2019-03-25_final
2019-03-26 09:28:02	ga_ls8c_ard_3-1-0_091089_2019-03-25_final
2019-03-29 09:54:56	ga_ls8c_ard_3-1-0_096079_2019-03-29_final
2019-04-14 09:52:03	ga_ls8c_ard_3-1-0_096072_2019-04-14_final
2019-06-17 09:57:36	ga_ls8c_ard_3-1-0_096085_2019-06-17_final
2019-06-21 11:10:12	ga_ls8c_ard_3-1-0_108081_2019-06-21_final
2019-07-07 11:06:16	ga_ls8c_ard_3-1-0_108071_2019-07-07_final
2019-07-16 09:26:49	ga_ls8c_ard_3-1-0_091085_2019-07-15_final
2019-07-19 09:57:43	ga_ls8c_ard_3-1-0_096085_2019-07-19_final
2019-08-04 09:52:15	ga_ls8c_ard_3-1-0_096071_2019-08-04_final
2019-08-13 09:46:32	ga_ls8c_ard_3-1-0_095072_2019-08-13_final
2019-08-20 09:57:56	ga_ls8c_ard_3-1-0_096085_2019-08-20_final
2019-08-29 09:46:36	ga_ls8c_ard_3-1-0_095072_2019-08-29_final
2019-09-18 09:23:58	ga_ls8c_ard_3-1-0_091077_2019-09-17_final
2019-10-20 09:23:40	ga_ls8c_ard_3-1-0_091076_2019-10-19_final
2019-11-07 10:48:59	ga_ls8c_ard_3-1-0_105073_2019-11-07_final
2019-11-08 09:58:09	ga_ls8c_ard_3-1-0_096085_2019-11-08_final
2019-11-17 09:50:44	ga_ls8c_ard_3-1-0_095082_2019-11-17_final
2019-11-23 10:52:55	ga_ls8c_ard_3-1-0_105083_2019-11-23_final
2019-12-03 09:47:31	ga_ls8c_ard_3-1-0_095074_2019-12-03_final
2019-12-03 09:50:43	ga_ls8c_ard_3-1-0_095082_2019-12-03_final
2019-12-07 09:28:47	ga_ls8c_ard_3-1-0_091089_2019-12-06_final
2019-12-09 10:48:31	ga_ls8c_ard_3-1-0_105072_2019-12-09_final
2019-12-09 10:52:30	ga_ls8c_ard_3-1-0_105082_2019-12-09_final
2019-12-23 09:25:56	ga_ls8c_ard_3-1-0_091082_2019-12-22_final
2020-01-26 10:50:19	ga_ls8c_ard_3-1-0_105077_2020-01-26_final
2020-01-27 09:57:05	ga_ls8c_ard_3-1-0_096083_2020-01-27_final
2020-01-31 11:06:50	ga_ls8c_ard_3-1-0_108072_2020-01-31_final
2020-02-05 09:52:03	ga_ls8c_ard_3-1-0_095086_2020-02-05_final
2020-02-12 09:53:02	ga_ls8c_ard_3-1-0_096073_2020-02-12_final
2020-03-12 09:26:45	ga_ls8c_ard_3-1-0_091085_2020-03-11_final
2020-03-28 09:26:36	ga_ls8c_ard_3-1-0_091085_2020-03-27_final
2020-03-28 09:28:12	ga_ls8c_ard_3-1-0_091089_2020-03-27_final
2020-03-30 10:48:19	ga_ls8c_ard_3-1-0_105073_2020-03-30_final
2020-04-13 09:22:54	ga_ls8c_ard_3-1-0_091076_2020-04-12_final
2020-04-13 09:23:17	ga_ls8c_ard_3-1-0_091077_2020-04-12_final
2020-04-16 09:52:35	ga_ls8c_ard_3-1-0_096073_2020-04-16_final
2020-05-02 09:57:14	ga_ls8c_ard_3-1-0_096085_2020-05-02_final
2022-03-30 11:25:49	ga_ls8c_ard_3-2-1_111074_2022-03-30_final
2022-03-31 10:28:36	ga_ls8c_ard_3-2-1_102070_2022-03-31_final
2022-04-01 11:17:27	ga_ls8c_ard_3-2-1_109084_2022-04-01_final
2022-04-02 10:21:50	ga_ls8c_ard_3-2-1_100084_2022-04-02_final
2022-04-03 09:23:25	ga_ls8c_ard_3-2-1_091077_2022-04-02_final
2022-04-05 09:16:16	ga_ls8c_ard_3-2-1_089090_2022-04-04_final
2022-04-06 11:35:38	ga_ls8c_ard_3-2-1_112083_2022-04-06_final
2022-04-13 10:03:23	ga_ls8c_ard_3-2-1_097084_2022-04-13_final
2022-04-13 10:03:47	ga_ls8c_ard_3-2-1_097085_2022-04-13_final
2022-04-15 11:25:56	ga_ls8c_ard_3-2-1_111074_2022-04-15_final
2022-04-15 11:29:31	ga_ls8c_ard_3-2-1_111083_2022-04-15_final
2022-04-17 09:35:04	ga_ls8c_ard_3-2-1_093075_2022-04-17_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-18 10:17:08	ga_ls8c_ard_3-2-1_100072_2022-04-18_final
2022-04-24 11:24:05	ga_ls8c_ard_3-2-1_110085_2022-04-24_final
2022-04-26 11:10:55	ga_ls8c_ard_3-2-1_108083_2022-04-26_final
2022-04-27 11:50:34	ga_ls8c_ard_3-2-1_115074_2022-04-27_final
2022-04-27 11:51:22	ga_ls8c_ard_3-2-1_115076_2022-04-27_final
2022-04-28 10:58:08	ga_ls8c_ard_3-2-1_106082_2022-04-28_final
2022-04-29 11:38:36	ga_ls8c_ard_3-2-1_113075_2022-04-29_final
2022-04-30 10:41:00	ga_ls8c_ard_3-2-1_104070_2022-04-30_final
2022-04-30 10:45:47	ga_ls8c_ard_3-2-1_104082_2022-04-30_final
2022-05-01 11:29:28	ga_ls8c_ard_3-2-1_111083_2022-05-01_final
2022-05-03 09:35:03	ga_ls8c_ard_3-2-1_093075_2022-05-03_final
2022-05-03 09:39:27	ga_ls8c_ard_3-2-1_093086_2022-05-03_final
2022-05-03 11:12:20	ga_ls8c_ard_3-2-1_109071_2022-05-03_final
2022-05-03 11:17:08	ga_ls8c_ard_3-2-1_109083_2022-05-03_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-05 11:01:12	ga_ls8c_ard_3-2-1_107074_2022-05-05_final
2022-05-06 10:07:35	ga_ls8c_ard_3-2-1_098079_2022-05-06_final
2022-05-07 09:13:10	ga_ls8c_ard_3-2-1_089082_2022-05-06_final
2022-05-14 09:19:49	ga_ls8c_ard_3-2-1_090083_2022-05-13_final
2022-05-14 10:53:31	ga_ls8c_ard_3-2-1_106070_2022-05-14_final
2022-05-15 09:59:29	ga_ls8c_ard_3-2-1_097074_2022-05-15_final
2022-05-15 10:01:53	ga_ls8c_ard_3-2-1_097080_2022-05-15_final
2022-05-19 09:35:35	ga_ls8c_ard_3-2-1_093076_2022-05-19_final
2022-05-21 09:26:01	ga_ls8c_ard_3-2-1_091083_2022-05-20_final
2022-05-24 11:35:00	ga_ls8c_ard_3-2-1_112081_2022-05-24_final
2022-05-26 09:40:57	ga_ls8c_ard_3-2-1_094074_2022-05-26_final
2022-05-26 11:22:14	ga_ls8c_ard_3-2-1_110080_2022-05-26_final
2022-05-30 10:53:33	ga_ls8c_ard_3-2-1_106070_2022-05-30_final
2022-05-30 10:53:57	ga_ls8c_ard_3-2-1_106071_2022-05-30_final
2022-05-31 10:03:32	ga_ls8c_ard_3-2-1_097084_2022-05-31_final
2022-06-01 10:40:25	ga_ls8c_ard_3-2-1_104068_2022-06-01_final
2022-06-02 09:49:36	ga_ls8c_ard_3-2-1_095080_2022-06-02_final
2022-06-03 10:32:29	ga_ls8c_ard_3-2-1_102079_2022-06-03_final
2022-06-03 10:33:41	ga_ls8c_ard_3-2-1_102082_2022-06-03_final
2022-06-04 09:37:40	ga_ls8c_ard_3-2-1_093081_2022-06-04_final
2022-06-04 11:12:34	ga_ls8c_ard_3-2-1_109071_2022-06-04_final
2022-06-06 09:24:32	ga_ls8c_ard_3-2-1_091079_2022-06-05_final
2022-06-07 10:05:01	ga_ls8c_ard_3-2-1_098072_2022-06-07_final
2022-06-15 10:53:22	ga_ls8c_ard_3-2-1_106069_2022-06-15_final
2022-06-15 10:54:57	ga_ls8c_ard_3-2-1_106073_2022-06-15_final
2022-06-15 10:55:21	ga_ls8c_ard_3-2-1_106074_2022-06-15_final
2022-06-15 10:58:33	ga_ls8c_ard_3-2-1_106082_2022-06-15_final
2022-06-16 11:41:25	ga_ls8c_ard_3-2-1_113081_2022-06-16_final
2022-06-18 09:47:24	ga_ls8c_ard_3-2-1_095074_2022-06-18_final
2022-06-19 10:28:40	ga_ls8c_ard_3-2-1_102069_2022-06-19_final
2022-06-21 10:21:54	ga_ls8c_ard_3-2-1_100083_2022-06-21_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