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
2016-02-12 09:35:13	ga_ls8c_ard_3-0-0_093075_2016-02-12_final
2016-02-12 09:35:37	ga_ls8c_ard_3-0-0_093076_2016-02-12_final
2016-02-12 09:36:00	ga_ls8c_ard_3-0-0_093077_2016-02-12_final
2016-02-12 09:36:24	ga_ls8c_ard_3-0-0_093078_2016-02-12_final
2016-02-12 09:36:48	ga_ls8c_ard_3-0-0_093079_2016-02-12_final
2016-02-12 09:37:12	ga_ls8c_ard_3-0-0_093080_2016-02-12_final
2016-02-12 09:37:36	ga_ls8c_ard_3-0-0_093081_2016-02-12_final
2016-03-29 09:44:06	ga_ls8c_ard_3-0-0_095067_2016-03-29_final
2016-03-29 09:45:17	ga_ls8c_ard_3-0-0_095070_2016-03-29_final
2016-03-29 09:45:41	ga_ls8c_ard_3-0-0_095071_2016-03-29_final
2016-03-29 09:46:05	ga_ls8c_ard_3-0-0_095072_2016-03-29_final
2016-03-31 09:34:54	ga_ls8c_ard_3-0-0_093075_2016-03-31_final
2016-03-31 09:35:18	ga_ls8c_ard_3-0-0_093076_2016-03-31_final
2016-03-31 09:35:42	ga_ls8c_ard_3-0-0_093077_2016-03-31_final
2016-03-31 09:36:06	ga_ls8c_ard_3-0-0_093078_2016-03-31_final
2016-03-31 09:36:30	ga_ls8c_ard_3-0-0_093079_2016-03-31_final
2016-03-31 09:36:54	ga_ls8c_ard_3-0-0_093080_2016-03-31_final
2016-03-31 09:37:18	ga_ls8c_ard_3-0-0_093081_2016-03-31_final
2016-04-11 09:21:06	ga_ls8c_ard_3-0-0_090087_2016-04-10_final
2016-04-11 09:21:30	ga_ls8c_ard_3-0-0_090088_2016-04-10_final
2016-04-11 09:21:54	ga_ls8c_ard_3-0-0_090089_2016-04-10_final
2016-04-11 09:22:18	ga_ls8c_ard_3-0-0_090090_2016-04-10_final
2016-04-11 09:22:42	ga_ls8c_ard_3-0-0_090091_2016-04-10_final
2016-04-14 09:44:00	ga_ls8c_ard_3-0-0_095067_2016-04-14_final
2016-04-14 09:45:12	ga_ls8c_ard_3-0-0_095070_2016-04-14_final
2016-04-14 09:45:36	ga_ls8c_ard_3-0-0_095071_2016-04-14_final
2016-04-14 09:46:00	ga_ls8c_ard_3-0-0_095072_2016-04-14_final
2019-08-19 09:16:40	ga_ls8c_ard_3-1-0_089090_2019-08-18_final
2019-08-20 09:50:45	ga_ls8c_ard_3-1-0_096067_2019-08-20_final
2019-10-20 09:26:28	ga_ls8c_ard_3-1-0_091083_2019-10-19_final
2019-10-20 09:26:52	ga_ls8c_ard_3-1-0_091084_2019-10-19_final
2019-10-20 09:27:16	ga_ls8c_ard_3-1-0_091085_2019-10-19_final
2019-10-20 09:27:40	ga_ls8c_ard_3-1-0_091086_2019-10-19_final
2019-10-20 09:28:04	ga_ls8c_ard_3-1-0_091087_2019-10-19_final
2019-10-20 09:28:28	ga_ls8c_ard_3-1-0_091088_2019-10-19_final
2019-10-20 09:28:52	ga_ls8c_ard_3-1-0_091089_2019-10-19_final
2019-10-22 09:16:54	ga_ls8c_ard_3-1-0_089090_2019-10-21_final
2019-10-23 09:50:59	ga_ls8c_ard_3-1-0_096067_2019-10-23_final
2019-11-01 09:44:48	ga_ls8c_ard_3-1-0_095067_2019-11-01_final
2019-11-01 09:46:00	ga_ls8c_ard_3-1-0_095070_2019-11-01_final
2019-11-01 09:46:24	ga_ls8c_ard_3-1-0_095071_2019-11-01_final
2019-11-01 09:46:48	ga_ls8c_ard_3-1-0_095072_2019-11-01_final
2021-09-26 09:50:55	ga_ls8c_ard_3-2-0_096067_2021-09-26_final
2021-09-28 09:40:10	ga_ls8c_ard_3-2-0_094071_2021-09-28_final
2021-09-28 09:40:34	ga_ls8c_ard_3-2-0_094072_2021-09-28_final
2021-09-28 09:40:57	ga_ls8c_ard_3-2-0_094073_2021-09-28_final
2021-09-28 09:41:21	ga_ls8c_ard_3-2-0_094074_2021-09-28_final
2021-09-28 09:41:45	ga_ls8c_ard_3-2-0_094075_2021-09-28_final
2021-09-28 09:42:09	ga_ls8c_ard_3-2-0_094076_2021-09-28_final
2021-09-30 09:31:24	ga_ls8c_ard_3-2-0_092080_2021-09-30_final
2021-09-30 09:31:48	ga_ls8c_ard_3-2-0_092081_2021-09-30_final
2021-09-30 09:32:12	ga_ls8c_ard_3-2-0_092082_2021-09-30_final
2021-09-30 09:32:36	ga_ls8c_ard_3-2-0_092083_2021-09-30_final
2021-09-30 09:33:00	ga_ls8c_ard_3-2-0_092084_2021-09-30_final
2021-09-30 09:33:24	ga_ls8c_ard_3-2-0_092085_2021-09-30_final
2021-10-09 09:26:28	ga_ls8c_ard_3-2-0_091083_2021-10-08_final
2021-10-09 09:26:52	ga_ls8c_ard_3-2-0_091084_2021-10-08_final
2021-10-09 09:27:16	ga_ls8c_ard_3-2-0_091085_2021-10-08_final
2021-10-09 09:27:40	ga_ls8c_ard_3-2-0_091086_2021-10-08_final
2021-10-09 09:28:04	ga_ls8c_ard_3-2-0_091087_2021-10-08_final
2021-10-09 09:28:28	ga_ls8c_ard_3-2-0_091088_2021-10-08_final
2021-10-09 09:28:52	ga_ls8c_ard_3-2-0_091089_2021-10-08_final
2021-10-11 09:16:55	ga_ls8c_ard_3-2-0_089090_2021-10-10_final
2021-10-14 09:40:15	ga_ls8c_ard_3-2-0_094071_2021-10-14_final
2021-10-14 09:40:38	ga_ls8c_ard_3-2-0_094072_2021-10-14_final
2021-10-14 09:41:02	ga_ls8c_ard_3-2-0_094073_2021-10-14_final
2021-10-14 09:41:26	ga_ls8c_ard_3-2-0_094074_2021-10-14_final
2021-10-14 09:41:50	ga_ls8c_ard_3-2-0_094075_2021-10-14_final
2021-10-14 09:42:14	ga_ls8c_ard_3-2-0_094076_2021-10-14_final
2023-10-11 09:46:10	ga_ls8c_ard_3-2-1_095071_2023-10-11_final
2023-10-11 09:46:34	ga_ls8c_ard_3-2-1_095072_2023-10-11_final
2023-10-13 09:35:24	ga_ls8c_ard_3-2-1_093075_2023-10-13_final
2023-10-13 09:35:48	ga_ls8c_ard_3-2-1_093076_2023-10-13_final
2023-10-13 09:36:12	ga_ls8c_ard_3-2-1_093077_2023-10-13_final
2023-10-13 09:36:36	ga_ls8c_ard_3-2-1_093078_2023-10-13_final
2023-10-13 09:37:00	ga_ls8c_ard_3-2-1_093079_2023-10-13_final
2023-10-13 09:37:24	ga_ls8c_ard_3-2-1_093080_2023-10-13_final
2023-10-13 09:37:48	ga_ls8c_ard_3-2-1_093081_2023-10-13_final
2023-10-15 09:26:14	ga_ls8c_ard_3-2-1_091083_2023-10-14_final
2023-10-15 09:26:14	ga_ls8c_ard_3-2-1_091083_2023-10-14_nrt
2023-10-15 09:26:38	ga_ls8c_ard_3-2-1_091084_2023-10-14_final
2023-10-15 09:26:38	ga_ls8c_ard_3-2-1_091084_2023-10-14_nrt
2023-10-15 09:27:02	ga_ls8c_ard_3-2-1_091085_2023-10-14_final
2023-10-15 09:27:02	ga_ls8c_ard_3-2-1_091085_2023-10-14_nrt
2023-10-15 09:27:26	ga_ls8c_ard_3-2-1_091086_2023-10-14_final
2023-10-15 09:27:26	ga_ls8c_ard_3-2-1_091086_2023-10-14_nrt
2023-10-15 09:27:50	ga_ls8c_ard_3-2-1_091087_2023-10-14_final
2023-10-15 09:27:50	ga_ls8c_ard_3-2-1_091087_2023-10-14_nrt
2023-10-15 09:28:14	ga_ls8c_ard_3-2-1_091088_2023-10-14_final
2023-10-15 09:28:14	ga_ls8c_ard_3-2-1_091088_2023-10-14_nrt
2023-10-15 09:28:38	ga_ls8c_ard_3-2-1_091089_2023-10-14_final
2023-10-15 09:28:38	ga_ls8c_ard_3-2-1_091089_2023-10-14_nrt
2023-10-22 09:32:01	ga_ls8c_ard_3-2-1_092082_2023-10-22_final
2023-10-22 09:32:25	ga_ls8c_ard_3-2-1_092083_2023-10-22_final
2023-10-22 09:32:49	ga_ls8c_ard_3-2-1_092084_2023-10-22_final
2023-10-22 09:33:13	ga_ls8c_ard_3-2-1_092085_2023-10-22_final
2023-10-24 09:21:40	ga_ls8c_ard_3-2-1_090087_2023-10-23_final
2023-10-24 09:22:04	ga_ls8c_ard_3-2-1_090088_2023-10-23_final
2023-10-24 09:22:28	ga_ls8c_ard_3-2-1_090089_2023-10-23_final
2023-10-24 09:22:52	ga_ls8c_ard_3-2-1_090090_2023-10-23_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years