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
2019-03-10 09:23:18	ga_ls8c_ard_3-1-0_091077_2019-03-09_final
2019-03-10 09:26:30	ga_ls8c_ard_3-1-0_091085_2019-03-09_final
2019-03-17 11:10:44	ga_ls8c_ard_3-1-0_108083_2019-03-17_final
2019-04-07 09:46:43	ga_ls8c_ard_3-1-0_095074_2019-04-07_final
2019-06-26 09:52:16	ga_ls8c_ard_3-1-0_095087_2019-06-26_final
2019-06-26 11:29:10	ga_ls8c_ard_3-1-0_111082_2019-06-26_final
2019-07-16 09:25:37	ga_ls8c_ard_3-1-0_091082_2019-07-15_final
2019-08-01 09:23:44	ga_ls8c_ard_3-1-0_091077_2019-07-31_final
2019-08-01 09:25:20	ga_ls8c_ard_3-1-0_091081_2019-07-31_final
2019-08-03 10:47:04	ga_ls8c_ard_3-1-0_105069_2019-08-03_final
2019-09-15 10:30:44	ga_ls8c_ard_3-1-0_102074_2019-09-15_final
2019-09-21 09:52:06	ga_ls8c_ard_3-1-0_096070_2019-09-21_final
2019-09-25 11:07:52	ga_ls8c_ard_3-1-0_108074_2019-09-25_final
2019-10-04 09:27:14	ga_ls8c_ard_3-1-0_091085_2019-10-03_final
2019-10-04 09:28:50	ga_ls8c_ard_3-1-0_091089_2019-10-03_final
2019-10-16 09:47:12	ga_ls8c_ard_3-1-0_095073_2019-10-16_final
2019-10-16 11:24:05	ga_ls8c_ard_3-1-0_111068_2019-10-16_final
2019-10-20 09:27:16	ga_ls8c_ard_3-1-0_091085_2019-10-19_final
2019-10-22 10:47:24	ga_ls8c_ard_3-1-0_105069_2019-10-22_final
2019-10-22 10:47:48	ga_ls8c_ard_3-1-0_105070_2019-10-22_final
2019-10-23 09:52:35	ga_ls8c_ard_3-1-0_096071_2019-10-23_final
2019-10-27 11:10:44	ga_ls8c_ard_3-1-0_108081_2019-10-27_final
2019-11-01 09:50:47	ga_ls8c_ard_3-1-0_095082_2019-11-01_final
2019-11-01 11:23:41	ga_ls8c_ard_3-1-0_111067_2019-11-01_final
2019-11-01 11:28:52	ga_ls8c_ard_3-1-0_111080_2019-11-01_final
2019-11-05 09:26:51	ga_ls8c_ard_3-1-0_091084_2019-11-04_final
2019-11-05 09:28:03	ga_ls8c_ard_3-1-0_091087_2019-11-04_final
2019-11-12 11:09:54	ga_ls8c_ard_3-1-0_108079_2019-11-12_final
2019-11-17 09:47:08	ga_ls8c_ard_3-1-0_095073_2019-11-17_final
2019-11-24 09:53:42	ga_ls8c_ard_3-1-0_096074_2019-11-24_final
2019-12-03 09:50:43	ga_ls8c_ard_3-1-0_095082_2019-12-03_final
2019-12-07 09:28:23	ga_ls8c_ard_3-1-0_091088_2019-12-06_final
2019-12-09 10:48:31	ga_ls8c_ard_3-1-0_105072_2019-12-09_final
2019-12-30 11:07:47	ga_ls8c_ard_3-1-0_108074_2019-12-30_final
2020-01-08 09:25:28	ga_ls8c_ard_3-1-0_091081_2020-01-07_final
2020-01-20 11:26:38	ga_ls8c_ard_3-1-0_111075_2020-01-20_final
2020-01-26 10:47:56	ga_ls8c_ard_3-1-0_105071_2020-01-26_final
2020-01-26 10:52:19	ga_ls8c_ard_3-1-0_105082_2020-01-26_final
2020-01-27 09:57:53	ga_ls8c_ard_3-1-0_096085_2020-01-27_final
2020-02-05 09:48:04	ga_ls8c_ard_3-1-0_095076_2020-02-05_final
2020-02-21 09:50:00	ga_ls8c_ard_3-1-0_095081_2020-02-21_final
2020-02-21 09:52:00	ga_ls8c_ard_3-1-0_095086_2020-02-21_final
2020-02-21 11:28:29	ga_ls8c_ard_3-1-0_111080_2020-02-21_final
2020-02-22 10:30:04	ga_ls8c_ard_3-1-0_102073_2020-02-22_final
2020-02-27 10:50:11	ga_ls8c_ard_3-1-0_105077_2020-02-27_final
2020-03-12 09:24:45	ga_ls8c_ard_3-1-0_091080_2020-03-11_final
2020-03-12 09:26:21	ga_ls8c_ard_3-1-0_091084_2020-03-11_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-03-14 10:50:04	ga_ls8c_ard_3-1-0_105077_2020-03-14_final
2020-03-19 11:11:22	ga_ls8c_ard_3-1-0_108084_2020-03-19_final
2020-03-24 09:50:10	ga_ls8c_ard_3-1-0_095082_2020-03-24_final
2020-03-24 09:50:34	ga_ls8c_ard_3-1-0_095083_2020-03-24_final
2020-03-31 09:52:17	ga_ls8c_ard_3-1-0_096072_2020-03-31_final
2020-04-16 09:52:35	ga_ls8c_ard_3-1-0_096073_2020-04-16_final
2020-04-25 11:24:25	ga_ls8c_ard_3-1-0_111071_2020-04-25_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 09:33:47	ga_ls8c_ard_3-2-1_093072_2022-04-01_final
2022-04-03 11:01:30	ga_ls8c_ard_3-2-1_107075_2022-04-03_final
2022-04-03 11:05:05	ga_ls8c_ard_3-2-1_107084_2022-04-03_final
2022-04-04 10:06:41	ga_ls8c_ard_3-2-1_098077_2022-04-04_final
2022-04-04 10:09:05	ga_ls8c_ard_3-2-1_098083_2022-04-04_final
2022-04-06 09:51:57	ga_ls8c_ard_3-2-1_096071_2022-04-06_final
2022-04-08 11:19:42	ga_ls8c_ard_3-2-1_110074_2022-04-08_final
2022-04-10 11:10:57	ga_ls8c_ard_3-2-1_108083_2022-04-10_final
2022-04-14 10:40:16	ga_ls8c_ard_3-2-1_104068_2022-04-14_final
2022-04-14 10:41:04	ga_ls8c_ard_3-2-1_104070_2022-04-14_final
2022-04-17 11:11:34	ga_ls8c_ard_3-2-1_109069_2022-04-17_final
2022-04-18 10:20:44	ga_ls8c_ard_3-2-1_100081_2022-04-18_final
2022-04-20 11:44:27	ga_ls8c_ard_3-2-1_114074_2022-04-20_final
2022-04-21 09:13:32	ga_ls8c_ard_3-2-1_089083_2022-04-20_final
2022-04-21 09:13:56	ga_ls8c_ard_3-2-1_089084_2022-04-20_final
2022-04-26 09:32:50	ga_ls8c_ard_3-2-1_092085_2022-04-26_final
2022-04-30 09:06:06	ga_ls8c_ard_3-2-1_088080_2022-04-29_final
2022-05-01 09:49:23	ga_ls8c_ard_3-2-1_095080_2022-05-01_final
2022-05-03 11:17:32	ga_ls8c_ard_3-2-1_109084_2022-05-03_final
2022-05-04 10:21:31	ga_ls8c_ard_3-2-1_100083_2022-05-04_final
2022-05-06 10:04:24	ga_ls8c_ard_3-2-1_098071_2022-05-06_final
2022-05-06 10:06:47	ga_ls8c_ard_3-2-1_098077_2022-05-06_final
2022-05-06 10:07:59	ga_ls8c_ard_3-2-1_098080_2022-05-06_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-08 11:35:44	ga_ls8c_ard_3-2-1_112083_2022-05-08_final
2022-05-08 11:36:08	ga_ls8c_ard_3-2-1_112084_2022-05-08_final
2022-05-10 09:44:54	ga_ls8c_ard_3-2-1_094084_2022-05-10_final
2022-05-14 09:19:49	ga_ls8c_ard_3-2-1_090083_2022-05-13_final
2022-05-15 10:02:17	ga_ls8c_ard_3-2-1_097081_2022-05-15_final
2022-05-18 10:30:48	ga_ls8c_ard_3-2-1_102075_2022-05-18_final
2022-05-20 10:17:15	ga_ls8c_ard_3-2-1_100072_2022-05-20_final
2022-05-26 11:17:50	ga_ls8c_ard_3-2-1_110069_2022-05-26_final
2022-05-31 09:57:09	ga_ls8c_ard_3-2-1_097068_2022-05-31_final
2022-05-31 10:03:08	ga_ls8c_ard_3-2-1_097083_2022-05-31_final
2022-06-04 11:12:34	ga_ls8c_ard_3-2-1_109071_2022-06-04_final
2022-06-05 10:17:21	ga_ls8c_ard_3-2-1_100072_2022-06-05_final
2022-06-05 10:22:09	ga_ls8c_ard_3-2-1_100084_2022-06-05_final
2022-06-06 09:25:44	ga_ls8c_ard_3-2-1_091082_2022-06-05_final
2022-06-07 10:04:37	ga_ls8c_ard_3-2-1_098071_2022-06-07_final
2022-06-07 10:05:01	ga_ls8c_ard_3-2-1_098072_2022-06-07_final
2022-06-07 10:09:25	ga_ls8c_ard_3-2-1_098083_2022-06-07_final
2022-06-16 11:41:49	ga_ls8c_ard_3-2-1_113082_2022-06-16_final
2022-06-22 11:01:35	ga_ls8c_ard_3-2-1_107074_2022-06-22_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