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
2018-03-23 09:27:59	ga_ls8c_ard_3-1-0_091089_2018-03-22_final
2019-03-12 10:52:12	ga_ls8c_ard_3-1-0_105083_2019-03-12_final
2019-03-26 09:23:38	ga_ls8c_ard_3-1-0_091078_2019-03-25_final
2019-04-18 11:05:47	ga_ls8c_ard_3-1-0_108071_2019-04-18_final
2019-06-17 09:57:12	ga_ls8c_ard_3-1-0_096084_2019-06-17_final
2019-06-21 11:10:12	ga_ls8c_ard_3-1-0_108081_2019-06-21_final
2019-07-16 09:25:13	ga_ls8c_ard_3-1-0_091081_2019-07-15_final
2019-07-23 11:07:08	ga_ls8c_ard_3-1-0_108073_2019-07-23_final
2019-08-01 09:26:31	ga_ls8c_ard_3-1-0_091084_2019-07-31_final
2019-08-04 09:52:15	ga_ls8c_ard_3-1-0_096071_2019-08-04_final
2019-08-17 09:27:01	ga_ls8c_ard_3-1-0_091085_2019-08-16_final
2019-08-20 09:57:56	ga_ls8c_ard_3-1-0_096085_2019-08-20_final
2019-09-09 11:10:34	ga_ls8c_ard_3-1-0_108081_2019-09-09_final
2019-09-18 09:23:34	ga_ls8c_ard_3-1-0_091076_2019-09-17_final
2019-09-30 09:46:45	ga_ls8c_ard_3-1-0_095072_2019-09-30_final
2019-09-30 09:47:09	ga_ls8c_ard_3-1-0_095073_2019-09-30_final
2019-10-11 11:11:31	ga_ls8c_ard_3-1-0_108083_2019-10-11_final
2019-10-23 09:52:11	ga_ls8c_ard_3-1-0_096070_2019-10-23_final
2019-11-01 09:50:47	ga_ls8c_ard_3-1-0_095082_2019-11-01_final
2019-11-01 09:51:11	ga_ls8c_ard_3-1-0_095083_2019-11-01_final
2019-11-05 09:24:03	ga_ls8c_ard_3-1-0_091077_2019-11-04_final
2019-11-05 09:25:39	ga_ls8c_ard_3-1-0_091081_2019-11-04_final
2019-11-05 09:28:27	ga_ls8c_ard_3-1-0_091088_2019-11-04_final
2019-11-17 09:50:44	ga_ls8c_ard_3-1-0_095082_2019-11-17_final
2019-11-21 09:27:59	ga_ls8c_ard_3-1-0_091087_2019-11-20_final
2019-11-21 09:28:23	ga_ls8c_ard_3-1-0_091088_2019-11-20_final
2019-11-24 09:57:41	ga_ls8c_ard_3-1-0_096084_2019-11-24_final
2019-12-03 09:50:43	ga_ls8c_ard_3-1-0_095082_2019-12-03_final
2019-12-09 10:48:31	ga_ls8c_ard_3-1-0_105072_2019-12-09_final
2019-12-09 10:51:42	ga_ls8c_ard_3-1-0_105080_2019-12-09_final
2020-01-10 10:48:00	ga_ls8c_ard_3-1-0_105071_2020-01-10_final
2020-01-11 09:55:34	ga_ls8c_ard_3-1-0_096079_2020-01-11_final
2020-01-11 09:57:34	ga_ls8c_ard_3-1-0_096084_2020-01-11_final
2020-01-24 09:25:24	ga_ls8c_ard_3-1-0_091081_2020-01-23_final
2020-01-26 10:48:20	ga_ls8c_ard_3-1-0_105072_2020-01-26_final
2020-01-27 09:57:53	ga_ls8c_ard_3-1-0_096085_2020-01-27_final
2020-02-16 11:05:59	ga_ls8c_ard_3-1-0_108070_2020-02-16_final
2020-02-16 11:09:58	ga_ls8c_ard_3-1-0_108080_2020-02-16_final
2020-02-25 09:26:04	ga_ls8c_ard_3-1-0_091083_2020-02-24_final
2020-02-28 09:51:45	ga_ls8c_ard_3-1-0_096070_2020-02-28_final
2020-04-04 11:10:48	ga_ls8c_ard_3-1-0_108083_2020-04-04_final
2020-04-16 09:57:22	ga_ls8c_ard_3-1-0_096085_2020-04-16_final
2022-03-29 10:44:34	ga_ls8c_ard_3-2-1_104079_2022-03-29_final
2022-04-02 10:21:50	ga_ls8c_ard_3-2-1_100084_2022-04-02_final
2022-04-04 10:09:53	ga_ls8c_ard_3-2-1_098085_2022-04-04_final
2022-04-06 11:36:02	ga_ls8c_ard_3-2-1_112084_2022-04-06_final
2022-04-08 09:46:00	ga_ls8c_ard_3-2-1_094087_2022-04-08_final
2022-04-10 09:31:40	ga_ls8c_ard_3-2-1_092082_2022-04-10_final
2022-04-11 10:10:57	ga_ls8c_ard_3-2-1_099072_2022-04-11_final
2022-04-12 09:22:07	ga_ls8c_ard_3-2-1_090089_2022-04-11_final
2022-04-12 10:54:37	ga_ls8c_ard_3-2-1_106073_2022-04-12_final
2022-04-12 10:57:24	ga_ls8c_ard_3-2-1_106080_2022-04-12_final
2022-04-15 11:23:32	ga_ls8c_ard_3-2-1_111068_2022-04-15_final
2022-04-15 11:29:31	ga_ls8c_ard_3-2-1_111083_2022-04-15_final
2022-04-15 11:29:55	ga_ls8c_ard_3-2-1_111084_2022-04-15_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-18 11:57:37	ga_ls8c_ard_3-2-1_116076_2022-04-18_final
2022-04-19 11:03:59	ga_ls8c_ard_3-2-1_107081_2022-04-19_final
2022-04-21 09:14:20	ga_ls8c_ard_3-2-1_089085_2022-04-20_final
2022-04-21 10:52:01	ga_ls8c_ard_3-2-1_105082_2022-04-21_final
2022-04-22 11:36:04	ga_ls8c_ard_3-2-1_112084_2022-04-22_final
2022-04-24 11:18:54	ga_ls8c_ard_3-2-1_110072_2022-04-24_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-26 11:06:55	ga_ls8c_ard_3-2-1_108073_2022-04-26_final
2022-04-28 10:52:57	ga_ls8c_ard_3-2-1_106069_2022-04-28_final
2022-04-28 10:58:08	ga_ls8c_ard_3-2-1_106082_2022-04-28_final
2022-04-30 10:41:00	ga_ls8c_ard_3-2-1_104070_2022-04-30_final
2022-04-30 10:42:12	ga_ls8c_ard_3-2-1_104073_2022-04-30_final
2022-05-05 09:26:42	ga_ls8c_ard_3-2-1_091085_2022-05-04_final
2022-05-08 11:35:20	ga_ls8c_ard_3-2-1_112082_2022-05-08_final
2022-05-13 10:14:14	ga_ls8c_ard_3-2-1_099080_2022-05-13_final
2022-05-14 10:56:18	ga_ls8c_ard_3-2-1_106077_2022-05-14_final
2022-05-17 09:46:20	ga_ls8c_ard_3-2-1_095072_2022-05-17_final
2022-05-17 09:47:56	ga_ls8c_ard_3-2-1_095076_2022-05-17_final
2022-05-18 10:30:24	ga_ls8c_ard_3-2-1_102074_2022-05-18_final
2022-05-19 09:39:34	ga_ls8c_ard_3-2-1_093086_2022-05-19_final
2022-05-20 10:20:50	ga_ls8c_ard_3-2-1_100081_2022-05-20_final
2022-05-20 10:21:38	ga_ls8c_ard_3-2-1_100083_2022-05-20_final
2022-05-20 11:58:32	ga_ls8c_ard_3-2-1_116078_2022-05-20_final
2022-05-21 09:26:25	ga_ls8c_ard_3-2-1_091084_2022-05-20_final
2022-05-24 09:51:43	ga_ls8c_ard_3-2-1_096070_2022-05-24_final
2022-05-24 11:35:48	ga_ls8c_ard_3-2-1_112083_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
2022-05-26 11:23:02	ga_ls8c_ard_3-2-1_110082_2022-05-26_final
2022-06-01 09:06:20	ga_ls8c_ard_3-2-1_088080_2022-05-31_final
2022-06-02 09:47:12	ga_ls8c_ard_3-2-1_095074_2022-06-02_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-06 09:24:56	ga_ls8c_ard_3-2-1_091080_2022-06-05_final
2022-06-07 10:07:25	ga_ls8c_ard_3-2-1_098078_2022-06-07_final
2022-06-08 09:16:12	ga_ls8c_ard_3-2-1_089089_2022-06-07_final
2022-06-08 10:52:17	ga_ls8c_ard_3-2-1_105082_2022-06-08_final
2022-06-13 11:06:30	ga_ls8c_ard_3-2-1_108071_2022-06-13_final
2022-06-15 10:53:46	ga_ls8c_ard_3-2-1_106070_2022-06-15_final
2022-06-15 10:54:57	ga_ls8c_ard_3-2-1_106073_2022-06-15_final
2022-06-17 10:42:37	ga_ls8c_ard_3-2-1_104073_2022-06-17_final
2022-06-18 09:51:47	ga_ls8c_ard_3-2-1_095085_2022-06-18_final
2022-06-18 11:26:41	ga_ls8c_ard_3-2-1_111075_2022-06-18_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