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
2022-01-14 10:07:10	ga_ls8c_ard_3-2-1_098077_2022-01-14_final
2022-01-14 10:09:57	ga_ls8c_ard_3-2-1_098084_2022-01-14_final
2022-11-18 09:41:32	ga_ls8c_ard_3-2-1_094074_2022-11-18_final
2022-11-18 09:44:43	ga_ls8c_ard_3-2-1_094082_2022-11-18_final
2022-11-21 11:52:08	ga_ls8c_ard_3-2-1_115076_2022-11-21_final
2022-11-24 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-11-24_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-12-01 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-12-01_final
2022-12-06 09:30:01	ga_ls8c_ard_3-2-1_092076_2022-12-06_final
2022-12-11 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-12-11_final
2022-12-18 09:57:49	ga_ls8c_ard_3-2-1_096084_2022-12-18_final
2022-12-19 10:35:29	ga_ls8c_ard_3-2-1_103070_2022-12-19_final
2022-12-20 11:20:19	ga_ls8c_ard_3-2-1_110074_2022-12-20_final
2022-12-20 11:20:43	ga_ls8c_ard_3-2-1_110075_2022-12-20_final
2022-12-22 09:33:50	ga_ls8c_ard_3-2-1_092086_2022-12-22_final
2022-12-25 11:39:14	ga_ls8c_ard_3-2-1_113075_2022-12-25_final
2022-12-26 09:07:56	ga_ls8c_ard_3-2-1_088083_2022-12-25_final
2022-12-26 10:44:49	ga_ls8c_ard_3-2-1_104078_2022-12-26_final
2022-12-30 10:22:30	ga_ls8c_ard_3-2-1_100084_2022-12-30_final
2022-12-31 09:24:06	ga_ls8c_ard_3-2-1_091077_2022-12-30_final
2023-01-01 10:08:09	ga_ls8c_ard_3-2-1_098079_2023-01-01_final
2023-01-08 10:15:07	ga_ls8c_ard_3-2-1_099081_2023-01-08_final
2023-01-10 09:58:21	ga_ls8c_ard_3-2-1_097070_2023-01-10_final
2023-01-12 09:52:21	ga_ls8c_ard_3-2-1_095086_2023-01-12_final
2023-01-14 09:39:34	ga_ls8c_ard_3-2-1_093085_2023-01-14_final
2023-01-18 09:13:35	ga_ls8c_ard_3-2-1_089082_2023-01-17_final
2023-01-21 09:44:32	ga_ls8c_ard_3-2-1_094082_2023-01-21_final
2023-01-21 11:19:26	ga_ls8c_ard_3-2-1_110072_2023-01-21_final
2023-01-24 10:16:40	ga_ls8c_ard_3-2-1_099085_2023-01-24_final
2023-01-25 10:55:57	ga_ls8c_ard_3-2-1_106075_2023-01-25_final
2023-01-26 09:58:44	ga_ls8c_ard_3-2-1_097071_2023-01-26_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-01-29 10:30:27	ga_ls8c_ard_3-2-1_102073_2023-01-29_final
2023-02-04 09:58:09	ga_ls8c_ard_3-2-1_096085_2023-02-04_final
2023-02-11 10:03:52	ga_ls8c_ard_3-2-1_097084_2023-02-11_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-23 10:24:23	ga_ls8c_ard_3-2-1_101074_2023-02-23_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-03-09 10:34:37	ga_ls8c_ard_3-2-1_103069_2023-03-09_final
2023-03-09 10:35:01	ga_ls8c_ard_3-2-1_103070_2023-03-09_final
2023-03-13 10:14:17	ga_ls8c_ard_3-2-1_099080_2023-03-13_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-16 09:06:41	ga_ls8c_ard_3-2-1_088081_2023-03-15_final
2023-03-17 11:28:49	ga_ls8c_ard_3-2-1_111081_2023-03-17_final
2023-03-18 10:30:00	ga_ls8c_ard_3-2-1_102073_2023-03-18_final
2023-03-22 10:07:36	ga_ls8c_ard_3-2-1_098079_2023-03-22_final
2023-03-23 10:46:51	ga_ls8c_ard_3-2-1_105069_2023-03-23_final
2023-03-27 10:22:55	ga_ls8c_ard_3-2-1_101071_2023-03-27_final
2023-03-28 09:28:53	ga_ls8c_ard_3-2-1_092075_2023-03-27_final
2023-03-29 11:52:37	ga_ls8c_ard_3-2-1_115079_2023-03-29_final
2023-03-31 10:03:20	ga_ls8c_ard_3-2-1_097084_2023-03-31_final
2023-03-31 11:40:14	ga_ls8c_ard_3-2-1_113079_2023-03-31_final
2023-04-02 09:46:10	ga_ls8c_ard_3-2-1_095072_2023-04-02_final
2023-04-02 11:25:03	ga_ls8c_ard_3-2-1_111072_2023-04-02_final
2023-04-06 11:01:03	ga_ls8c_ard_3-2-1_107074_2023-04-06_final
2023-04-07 10:03:48	ga_ls8c_ard_3-2-1_098070_2023-04-07_final
2023-04-08 10:48:38	ga_ls8c_ard_3-2-1_105074_2023-04-08_final
2023-04-12 10:27:26	ga_ls8c_ard_3-2-1_101083_2023-04-12_final
2023-04-18 09:51:31	ga_ls8c_ard_3-2-1_095086_2023-04-18_final
2023-04-26 10:35:21	ga_ls8c_ard_3-2-1_103072_2023-04-26_final
2023-04-27 11:23:00	ga_ls8c_ard_3-2-1_110083_2023-04-27_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-05-09 10:08:41	ga_ls8c_ard_3-2-1_098083_2023-05-09_final
2023-05-13 11:22:23	ga_ls8c_ard_3-2-1_110082_2023-05-13_final
2023-05-22 11:13:25	ga_ls8c_ard_3-2-1_109075_2023-05-22_final
2023-05-25 10:03:03	ga_ls8c_ard_3-2-1_098069_2023-05-25_final
2023-05-25 10:04:15	ga_ls8c_ard_3-2-1_098072_2023-05-25_final
2023-05-26 10:51:30	ga_ls8c_ard_3-2-1_105082_2023-05-26_final
2023-06-01 10:13:37	ga_ls8c_ard_3-2-1_099080_2023-06-01_final
2023-06-02 09:16:24	ga_ls8c_ard_3-2-1_090076_2023-06-01_final
2023-06-05 09:50:33	ga_ls8c_ard_3-2-1_095084_2023-06-05_final
2023-06-06 10:30:14	ga_ls8c_ard_3-2-1_102075_2023-06-06_final
2023-06-08 10:21:29	ga_ls8c_ard_3-2-1_100084_2023-06-08_final
2023-06-11 10:48:50	ga_ls8c_ard_3-2-1_105075_2023-06-11_final
2023-06-16 11:07:00	ga_ls8c_ard_3-2-1_108074_2023-06-16_final
2023-06-19 09:56:14	ga_ls8c_ard_3-2-1_097067_2023-06-19_final
2023-06-19 11:40:43	ga_ls8c_ard_3-2-1_113081_2023-06-19_final
2023-06-21 11:28:45	ga_ls8c_ard_3-2-1_111082_2023-06-21_final
2023-06-21 11:29:09	ga_ls8c_ard_3-2-1_111083_2023-06-21_final
2023-06-23 11:16:47	ga_ls8c_ard_3-2-1_109083_2023-06-23_final
2023-06-27 09:15:39	ga_ls8c_ard_3-2-1_089089_2023-06-26_final
2023-06-30 11:19:54	ga_ls8c_ard_3-2-1_110075_2023-06-30_final
2023-07-02 11:10:45	ga_ls8c_ard_3-2-1_108083_2023-07-02_final
2023-07-07 09:50:52	ga_ls8c_ard_3-2-1_095084_2023-07-07_final
2023-07-09 11:17:00	ga_ls8c_ard_3-2-1_109083_2023-07-09_final
2023-07-10 10:21:47	ga_ls8c_ard_3-2-1_100084_2023-07-10_final
2023-07-13 10:46:43	ga_ls8c_ard_3-2-1_105069_2023-07-13_final
2023-07-18 09:32:45	ga_ls8c_ard_3-2-1_092085_2023-07-18_final
2023-07-18 11:11:14	ga_ls8c_ard_3-2-1_108084_2023-07-18_final
2023-07-24 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-07-24_final
2023-07-28 10:03:33	ga_ls8c_ard_3-2-1_098069_2023-07-28_final
2023-07-29 10:49:13	ga_ls8c_ard_3-2-1_105075_2023-07-29_final
2023-07-30 11:35:17	ga_ls8c_ard_3-2-1_112082_2023-07-30_final
2023-08-05 10:53:03	ga_ls8c_ard_3-2-1_106069_2023-08-05_final
2023-08-05 10:53:27	ga_ls8c_ard_3-2-1_106070_2023-08-05_final
2023-08-14 09:13:13	ga_ls8c_ard_3-2-1_089082_2023-08-13_final
2023-08-14 09:16:24	ga_ls8c_ard_3-2-1_089090_2023-08-13_final
2023-08-20 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-08-20_final
2023-08-24 11:29:40	ga_ls8c_ard_3-2-1_111083_2023-08-24_final
2023-09-09 11:24:53	ga_ls8c_ard_3-2-1_111071_2023-09-09_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