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
2022-03-29 10:43:22	ga_ls8c_ard_3-2-1_104076_2022-03-29_final
2022-03-29 10:43:46	ga_ls8c_ard_3-2-1_104077_2022-03-29_final
2022-03-30 09:48:08	ga_ls8c_ard_3-2-1_095077_2022-03-30_final
2022-03-30 09:48:32	ga_ls8c_ard_3-2-1_095078_2022-03-30_final
2022-04-01 09:35:46	ga_ls8c_ard_3-2-1_093077_2022-04-01_final
2022-04-01 09:36:58	ga_ls8c_ard_3-2-1_093080_2022-04-01_final
2022-04-01 11:13:04	ga_ls8c_ard_3-2-1_109073_2022-04-01_final
2022-04-02 10:18:14	ga_ls8c_ard_3-2-1_100075_2022-04-02_final
2022-04-03 11:02:42	ga_ls8c_ard_3-2-1_107078_2022-04-03_final
2022-04-03 11:03:06	ga_ls8c_ard_3-2-1_107079_2022-04-03_final
2022-04-05 09:12:40	ga_ls8c_ard_3-2-1_089081_2022-04-04_final
2022-04-05 09:13:28	ga_ls8c_ard_3-2-1_089083_2022-04-04_final
2022-04-06 09:53:33	ga_ls8c_ard_3-2-1_096075_2022-04-06_final
2022-04-06 11:33:38	ga_ls8c_ard_3-2-1_112078_2022-04-06_final
2022-04-07 10:36:26	ga_ls8c_ard_3-2-1_103074_2022-04-07_final
2022-04-08 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-08_final
2022-04-10 09:29:16	ga_ls8c_ard_3-2-1_092076_2022-04-09_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-10 11:08:57	ga_ls8c_ard_3-2-1_108078_2022-04-10_final
2022-04-11 10:12:56	ga_ls8c_ard_3-2-1_099077_2022-04-11_final
2022-04-11 10:14:08	ga_ls8c_ard_3-2-1_099080_2022-04-11_final
2022-04-12 09:18:31	ga_ls8c_ard_3-2-1_090080_2022-04-11_final
2022-04-13 11:39:52	ga_ls8c_ard_3-2-1_113078_2022-04-13_final
2022-04-13 11:40:16	ga_ls8c_ard_3-2-1_113079_2022-04-13_final
2022-04-14 10:44:39	ga_ls8c_ard_3-2-1_104079_2022-04-14_final
2022-04-14 10:45:03	ga_ls8c_ard_3-2-1_104080_2022-04-14_final
2022-04-15 11:27:07	ga_ls8c_ard_3-2-1_111077_2022-04-15_final
2022-04-15 11:27:55	ga_ls8c_ard_3-2-1_111079_2022-04-15_final
2022-04-15 11:28:43	ga_ls8c_ard_3-2-1_111081_2022-04-15_final
2022-04-15 11:29:07	ga_ls8c_ard_3-2-1_111082_2022-04-15_final
2022-04-17 09:37:04	ga_ls8c_ard_3-2-1_093080_2022-04-17_final
2022-04-17 11:12:22	ga_ls8c_ard_3-2-1_109071_2022-04-17_final
2022-04-17 11:15:09	ga_ls8c_ard_3-2-1_109078_2022-04-17_final
2022-04-17 11:15:33	ga_ls8c_ard_3-2-1_109079_2022-04-17_final
2022-04-19 09:24:42	ga_ls8c_ard_3-2-1_091080_2022-04-18_final
2022-04-19 11:01:35	ga_ls8c_ard_3-2-1_107075_2022-04-19_final
2022-04-19 11:02:47	ga_ls8c_ard_3-2-1_107078_2022-04-19_final
2022-04-19 11:03:11	ga_ls8c_ard_3-2-1_107079_2022-04-19_final
2022-04-20 10:08:21	ga_ls8c_ard_3-2-1_098081_2022-04-20_final
2022-04-20 11:44:51	ga_ls8c_ard_3-2-1_114075_2022-04-20_final
2022-04-21 09:15:56	ga_ls8c_ard_3-2-1_089089_2022-04-20_final
2022-04-21 10:47:13	ga_ls8c_ard_3-2-1_105070_2022-04-21_final
2022-04-22 09:55:11	ga_ls8c_ard_3-2-1_096079_2022-04-22_final
2022-04-22 11:34:04	ga_ls8c_ard_3-2-1_112079_2022-04-22_final
2022-04-23 10:37:39	ga_ls8c_ard_3-2-1_103077_2022-04-23_final
2022-04-24 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-24_final
2022-04-24 11:22:54	ga_ls8c_ard_3-2-1_110082_2022-04-24_final
2022-04-25 10:26:04	ga_ls8c_ard_3-2-1_101079_2022-04-25_final
2022-04-26 09:31:38	ga_ls8c_ard_3-2-1_092082_2022-04-26_final
2022-04-26 09:33:38	ga_ls8c_ard_3-2-1_092087_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
2022-04-27 10:13:41	ga_ls8c_ard_3-2-1_099079_2022-04-27_final
2022-04-29 09:57:43	ga_ls8c_ard_3-2-1_097070_2022-04-29_final
2022-04-29 11:39:00	ga_ls8c_ard_3-2-1_113076_2022-04-29_final
2022-04-30 10:43:23	ga_ls8c_ard_3-2-1_104076_2022-04-30_final
2022-05-01 09:48:11	ga_ls8c_ard_3-2-1_095077_2022-05-01_final
2022-05-01 11:27:52	ga_ls8c_ard_3-2-1_111079_2022-05-01_final
2022-05-01 11:28:16	ga_ls8c_ard_3-2-1_111080_2022-05-01_final
2022-05-03 11:15:32	ga_ls8c_ard_3-2-1_109079_2022-05-03_final
2022-05-04 10:18:44	ga_ls8c_ard_3-2-1_100076_2022-05-04_final
2022-05-05 09:25:31	ga_ls8c_ard_3-2-1_091082_2022-05-04_final
2022-05-05 09:26:19	ga_ls8c_ard_3-2-1_091084_2022-05-04_final
2022-05-05 11:02:48	ga_ls8c_ard_3-2-1_107078_2022-05-05_final
2022-05-06 10:08:23	ga_ls8c_ard_3-2-1_098081_2022-05-06_final
2022-05-06 11:45:16	ga_ls8c_ard_3-2-1_114076_2022-05-06_final
2022-05-07 09:12:46	ga_ls8c_ard_3-2-1_089081_2022-05-06_final
2022-05-07 10:47:16	ga_ls8c_ard_3-2-1_105070_2022-05-07_final
2022-05-08 09:58:02	ga_ls8c_ard_3-2-1_096086_2022-05-08_final
2022-05-09 10:36:55	ga_ls8c_ard_3-2-1_103075_2022-05-09_final
2022-05-11 10:24:59	ga_ls8c_ard_3-2-1_101076_2022-05-11_final
2022-05-12 11:10:15	ga_ls8c_ard_3-2-1_108081_2022-05-12_final
2022-05-15 10:02:17	ga_ls8c_ard_3-2-1_097081_2022-05-15_final
2022-05-16 10:45:09	ga_ls8c_ard_3-2-1_104080_2022-05-16_final
2022-05-16 10:45:33	ga_ls8c_ard_3-2-1_104081_2022-05-16_final
2022-05-17 09:51:08	ga_ls8c_ard_3-2-1_095084_2022-05-17_final
2022-05-19 09:39:58	ga_ls8c_ard_3-2-1_093087_2022-05-19_final
2022-05-19 11:14:28	ga_ls8c_ard_3-2-1_109076_2022-05-19_final
2022-05-19 11:14:52	ga_ls8c_ard_3-2-1_109077_2022-05-19_final
2022-05-20 10:18:51	ga_ls8c_ard_3-2-1_100076_2022-05-20_final
2022-05-20 11:58:08	ga_ls8c_ard_3-2-1_116077_2022-05-20_final
2022-05-24 09:52:07	ga_ls8c_ard_3-2-1_096071_2022-05-24_final
2022-05-24 09:53:43	ga_ls8c_ard_3-2-1_096075_2022-05-24_final
2022-05-24 11:36:12	ga_ls8c_ard_3-2-1_112084_2022-05-24_final
2022-05-26 09:42:09	ga_ls8c_ard_3-2-1_094077_2022-05-26_final
2022-05-26 09:42:33	ga_ls8c_ard_3-2-1_094078_2022-05-26_final
2022-05-30 10:53:09	ga_ls8c_ard_3-2-1_106069_2022-05-30_final
2022-05-31 10:03:56	ga_ls8c_ard_3-2-1_097085_2022-05-31_final
2022-05-31 11:40:49	ga_ls8c_ard_3-2-1_113080_2022-05-31_final
2022-06-02 11:24:06	ga_ls8c_ard_3-2-1_111069_2022-06-02_final
2022-06-02 11:26:06	ga_ls8c_ard_3-2-1_111074_2022-06-02_final
2022-06-04 09:36:04	ga_ls8c_ard_3-2-1_093077_2022-06-04_final
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-04 11:12:58	ga_ls8c_ard_3-2-1_109072_2022-06-04_final
2022-06-07 10:08:37	ga_ls8c_ard_3-2-1_098081_2022-06-07_final
2022-06-07 11:45:06	ga_ls8c_ard_3-2-1_114075_2022-06-07_final
2022-06-08 09:13:48	ga_ls8c_ard_3-2-1_089083_2022-06-07_final
2022-06-13 09:33:12	ga_ls8c_ard_3-2-1_092085_2022-06-13_final
2022-06-13 11:09:17	ga_ls8c_ard_3-2-1_108078_2022-06-13_final
2022-06-15 10:52:58	ga_ls8c_ard_3-2-1_106068_2022-06-15_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