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
2019-03-22 09:49:34	ga_ls8c_ard_3-1-0_095081_2019-03-22_final
2019-03-26 09:26:02	ga_ls8c_ard_3-1-0_091084_2019-03-25_final
2019-04-07 09:49:30	ga_ls8c_ard_3-1-0_095081_2019-04-07_final
2019-04-07 09:50:42	ga_ls8c_ard_3-1-0_095084_2019-04-07_final
2019-04-11 09:24:22	ga_ls8c_ard_3-1-0_091080_2019-04-10_final
2019-06-26 09:51:28	ga_ls8c_ard_3-1-0_095085_2019-06-26_final
2019-06-30 09:25:34	ga_ls8c_ard_3-1-0_091082_2019-06-29_final
2019-07-12 09:49:56	ga_ls8c_ard_3-1-0_095081_2019-07-12_final
2019-07-12 09:50:20	ga_ls8c_ard_3-1-0_095082_2019-07-12_final
2019-07-16 09:25:37	ga_ls8c_ard_3-1-0_091082_2019-07-15_final
2019-08-17 09:23:25	ga_ls8c_ard_3-1-0_091076_2019-08-16_final
2019-08-17 09:23:49	ga_ls8c_ard_3-1-0_091077_2019-08-16_final
2019-08-17 09:25:25	ga_ls8c_ard_3-1-0_091081_2019-08-16_final
2019-08-29 09:51:23	ga_ls8c_ard_3-1-0_095084_2019-08-29_final
2019-09-02 09:26:16	ga_ls8c_ard_3-1-0_091083_2019-09-01_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-18 09:22:46	ga_ls8c_ard_3-1-0_091074_2019-09-17_final
2019-09-30 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-09-30_final
2019-10-20 09:20:29	ga_ls8c_ard_3-1-0_091068_2019-10-19_final
2019-11-01 09:50:23	ga_ls8c_ard_3-1-0_095081_2019-11-01_final
2019-12-03 09:51:07	ga_ls8c_ard_3-1-0_095083_2019-12-03_final
2019-12-07 09:23:59	ga_ls8c_ard_3-1-0_091077_2019-12-06_final
2019-12-07 09:26:47	ga_ls8c_ard_3-1-0_091084_2019-12-06_final
2019-12-10 09:52:53	ga_ls8c_ard_3-1-0_096072_2019-12-10_final
2020-01-04 09:50:12	ga_ls8c_ard_3-1-0_095081_2020-01-04_final
2020-01-08 09:25:28	ga_ls8c_ard_3-1-0_091081_2020-01-07_final
2020-01-08 09:28:16	ga_ls8c_ard_3-1-0_091088_2020-01-07_final
2020-02-05 09:50:03	ga_ls8c_ard_3-1-0_095081_2020-02-05_final
2020-02-05 09:51:39	ga_ls8c_ard_3-1-0_095085_2020-02-05_final
2020-02-09 09:28:55	ga_ls8c_ard_3-1-0_091090_2020-02-08_final
2020-02-21 09:52:24	ga_ls8c_ard_3-1-0_095087_2020-02-21_final
2020-02-25 09:26:28	ga_ls8c_ard_3-1-0_091084_2020-02-24_final
2020-03-08 09:47:31	ga_ls8c_ard_3-1-0_095075_2020-03-08_final
2020-03-08 09:49:31	ga_ls8c_ard_3-1-0_095080_2020-03-08_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-04-09 09:47:14	ga_ls8c_ard_3-1-0_095075_2020-04-09_final
2020-04-29 09:24:22	ga_ls8c_ard_3-1-0_091080_2020-04-28_final
2020-05-02 09:56:02	ga_ls8c_ard_3-1-0_096082_2020-05-02_final
2022-04-01 09:36:58	ga_ls8c_ard_3-2-1_093080_2022-04-01_final
2022-04-02 10:17:26	ga_ls8c_ard_3-2-1_100073_2022-04-02_final
2022-04-03 11:02:18	ga_ls8c_ard_3-2-1_107077_2022-04-03_final
2022-04-03 11:03:30	ga_ls8c_ard_3-2-1_107080_2022-04-03_final
2022-04-04 10:06:41	ga_ls8c_ard_3-2-1_098077_2022-04-04_final
2022-04-04 11:45:10	ga_ls8c_ard_3-2-1_114076_2022-04-04_final
2022-04-07 10:36:02	ga_ls8c_ard_3-2-1_103073_2022-04-07_final
2022-04-08 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-08_final
2022-04-15 11:29:55	ga_ls8c_ard_3-2-1_111084_2022-04-15_final
2022-04-16 10:30:18	ga_ls8c_ard_3-2-1_102074_2022-04-16_final
2022-04-17 11:11:58	ga_ls8c_ard_3-2-1_109070_2022-04-17_final
2022-04-18 10:17:32	ga_ls8c_ard_3-2-1_100073_2022-04-18_final
2022-04-19 09:25:54	ga_ls8c_ard_3-2-1_091083_2022-04-18_final
2022-04-19 11:03:59	ga_ls8c_ard_3-2-1_107081_2022-04-19_final
2022-04-20 11:47:15	ga_ls8c_ard_3-2-1_114081_2022-04-20_final
2022-04-21 09:13:32	ga_ls8c_ard_3-2-1_089083_2022-04-20_final
2022-04-23 10:34:27	ga_ls8c_ard_3-2-1_103069_2022-04-23_final
2022-04-24 11:20:54	ga_ls8c_ard_3-2-1_110077_2022-04-24_final
2022-04-26 09:34:50	ga_ls8c_ard_3-2-1_092090_2022-04-26_final
2022-04-26 11:10:31	ga_ls8c_ard_3-2-1_108082_2022-04-26_final
2022-04-27 10:11:18	ga_ls8c_ard_3-2-1_099073_2022-04-27_final
2022-04-29 11:40:36	ga_ls8c_ard_3-2-1_113080_2022-04-29_final
2022-04-29 11:41:00	ga_ls8c_ard_3-2-1_113081_2022-04-29_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-02 10:32:39	ga_ls8c_ard_3-2-1_102080_2022-05-02_final
2022-05-03 09:36:15	ga_ls8c_ard_3-2-1_093078_2022-05-03_final
2022-05-03 09:37:27	ga_ls8c_ard_3-2-1_093081_2022-05-03_final
2022-05-06 11:44:53	ga_ls8c_ard_3-2-1_114075_2022-05-06_final
2022-05-06 11:46:52	ga_ls8c_ard_3-2-1_114080_2022-05-06_final
2022-05-07 09:14:46	ga_ls8c_ard_3-2-1_089086_2022-05-06_final
2022-05-08 09:54:27	ga_ls8c_ard_3-2-1_096077_2022-05-08_final
2022-05-10 11:21:00	ga_ls8c_ard_3-2-1_110077_2022-05-10_final
2022-05-10 11:23:23	ga_ls8c_ard_3-2-1_110083_2022-05-10_final
2022-05-11 10:24:11	ga_ls8c_ard_3-2-1_101074_2022-05-11_final
2022-05-12 11:06:15	ga_ls8c_ard_3-2-1_108071_2022-05-12_final
2022-05-14 10:57:06	ga_ls8c_ard_3-2-1_106079_2022-05-14_final
2022-05-17 09:47:32	ga_ls8c_ard_3-2-1_095075_2022-05-17_final
2022-05-17 11:29:13	ga_ls8c_ard_3-2-1_111082_2022-05-17_final
2022-05-17 11:30:01	ga_ls8c_ard_3-2-1_111084_2022-05-17_final
2022-05-19 11:11:40	ga_ls8c_ard_3-2-1_109069_2022-05-19_final
2022-05-19 11:12:28	ga_ls8c_ard_3-2-1_109071_2022-05-19_final
2022-05-19 11:16:28	ga_ls8c_ard_3-2-1_109081_2022-05-19_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-20 10:18:03	ga_ls8c_ard_3-2-1_100074_2022-05-20_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-05-31 10:02:20	ga_ls8c_ard_3-2-1_097081_2022-05-31_final
2022-06-02 09:47:36	ga_ls8c_ard_3-2-1_095075_2022-06-02_final
2022-06-03 10:32:05	ga_ls8c_ard_3-2-1_102078_2022-06-03_final
2022-06-05 10:20:09	ga_ls8c_ard_3-2-1_100079_2022-06-05_final
2022-06-06 11:00:38	ga_ls8c_ard_3-2-1_107072_2022-06-06_final
2022-06-07 10:10:13	ga_ls8c_ard_3-2-1_098085_2022-06-07_final
2022-06-08 10:47:06	ga_ls8c_ard_3-2-1_105069_2022-06-08_final
2022-06-11 09:41:09	ga_ls8c_ard_3-2-1_094074_2022-06-11_final
2022-06-12 10:27:13	ga_ls8c_ard_3-2-1_101081_2022-06-12_final
2022-06-13 11:08:30	ga_ls8c_ard_3-2-1_108076_2022-06-13_final
2022-06-13 11:10:05	ga_ls8c_ard_3-2-1_108080_2022-06-13_final
2022-06-15 10:54:33	ga_ls8c_ard_3-2-1_106072_2022-06-15_final
2022-06-17 10:45:48	ga_ls8c_ard_3-2-1_104081_2022-06-17_final
2022-06-18 09:50:59	ga_ls8c_ard_3-2-1_095083_2022-06-18_final
2022-06-20 09:35:27	ga_ls8c_ard_3-2-1_093075_2022-06-20_final
2022-06-22 09:26:17	ga_ls8c_ard_3-2-1_091083_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