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
2018-02-17 09:31:51	ga_ls8c_ard_3-0-0_093067_2018-02-17_final
2018-02-21 09:12:17	ga_ls8c_ard_3-0-0_089080_2018-02-20_final
2018-02-21 09:12:41	ga_ls8c_ard_3-0-0_089081_2018-02-20_final
2018-02-21 09:13:05	ga_ls8c_ard_3-0-0_089082_2018-02-20_final
2018-02-21 09:13:29	ga_ls8c_ard_3-0-0_089083_2018-02-20_final
2018-02-21 09:13:53	ga_ls8c_ard_3-0-0_089084_2018-02-20_final
2018-02-21 09:14:17	ga_ls8c_ard_3-0-0_089085_2018-02-20_final
2018-02-26 09:25:36	ga_ls8c_ard_3-0-0_092067_2018-02-25_final
2018-02-26 09:26:00	ga_ls8c_ard_3-0-0_092068_2018-02-25_final
2018-02-26 09:27:12	ga_ls8c_ard_3-0-0_092071_2018-02-25_final
2018-02-26 09:27:36	ga_ls8c_ard_3-0-0_092072_2018-02-25_final
2018-02-28 09:16:25	ga_ls8c_ard_3-0-0_090075_2018-02-27_final
2018-02-28 09:16:49	ga_ls8c_ard_3-0-0_090076_2018-02-27_final
2018-02-28 09:17:13	ga_ls8c_ard_3-0-0_090077_2018-02-27_final
2018-02-28 09:17:37	ga_ls8c_ard_3-0-0_090078_2018-02-27_final
2018-02-28 09:18:00	ga_ls8c_ard_3-0-0_090079_2018-02-27_final
2018-02-28 09:18:24	ga_ls8c_ard_3-0-0_090080_2018-02-27_final
2018-02-28 09:18:48	ga_ls8c_ard_3-0-0_090081_2018-02-27_final
2018-03-02 09:07:38	ga_ls8c_ard_3-0-0_088084_2018-03-01_final
2018-03-05 09:31:43	ga_ls8c_ard_3-0-0_093067_2018-03-05_final
2018-04-03 09:07:22	ga_ls8c_ard_3-0-0_088084_2018-04-02_final
2018-04-06 09:31:27	ga_ls8c_ard_3-0-0_093067_2018-04-06_final
2018-04-17 09:16:00	ga_ls8c_ard_3-0-0_090075_2018-04-16_final
2018-04-17 09:16:24	ga_ls8c_ard_3-0-0_090076_2018-04-16_final
2018-04-17 09:16:47	ga_ls8c_ard_3-0-0_090077_2018-04-16_final
2018-04-17 09:17:11	ga_ls8c_ard_3-0-0_090078_2018-04-16_final
2018-04-17 09:17:35	ga_ls8c_ard_3-0-0_090079_2018-04-16_final
2018-04-17 09:17:59	ga_ls8c_ard_3-0-0_090080_2018-04-16_final
2018-04-17 09:18:23	ga_ls8c_ard_3-0-0_090081_2018-04-16_final
2018-04-19 09:07:12	ga_ls8c_ard_3-0-0_088084_2018-04-18_final
2018-04-22 09:31:18	ga_ls8c_ard_3-0-0_093067_2018-04-22_final
2018-05-03 09:15:51	ga_ls8c_ard_3-0-0_090075_2018-05-02_final
2018-05-03 09:16:15	ga_ls8c_ard_3-0-0_090076_2018-05-02_final
2018-05-03 09:16:39	ga_ls8c_ard_3-0-0_090077_2018-05-02_final
2018-05-03 09:17:03	ga_ls8c_ard_3-0-0_090078_2018-05-02_final
2018-05-03 09:17:27	ga_ls8c_ard_3-0-0_090079_2018-05-02_final
2018-05-03 09:17:51	ga_ls8c_ard_3-0-0_090080_2018-05-02_final
2018-05-03 09:18:14	ga_ls8c_ard_3-0-0_090081_2018-05-02_final
2018-05-05 09:07:04	ga_ls8c_ard_3-0-0_088084_2018-05-04_final
2018-05-08 09:31:09	ga_ls8c_ard_3-0-0_093067_2018-05-08_final
2018-05-19 09:15:40	ga_ls8c_ard_3-0-0_090075_2018-05-18_final
2018-05-19 09:16:04	ga_ls8c_ard_3-0-0_090076_2018-05-18_final
2018-05-19 09:16:28	ga_ls8c_ard_3-0-0_090077_2018-05-18_final
2018-05-19 09:16:52	ga_ls8c_ard_3-0-0_090078_2018-05-18_final
2018-05-19 09:17:16	ga_ls8c_ard_3-0-0_090079_2018-05-18_final
2018-05-19 09:17:40	ga_ls8c_ard_3-0-0_090080_2018-05-18_final
2018-05-19 09:18:04	ga_ls8c_ard_3-0-0_090081_2018-05-18_final
2018-05-21 09:06:52	ga_ls8c_ard_3-0-0_088084_2018-05-20_final
2018-05-24 09:30:57	ga_ls8c_ard_3-0-0_093067_2018-05-24_final
2018-06-04 09:15:29	ga_ls8c_ard_3-0-0_090075_2018-06-03_final
2018-06-04 09:15:53	ga_ls8c_ard_3-0-0_090076_2018-06-03_final
2018-06-04 09:16:17	ga_ls8c_ard_3-0-0_090077_2018-06-03_final
2018-06-04 09:16:41	ga_ls8c_ard_3-0-0_090078_2018-06-03_final
2018-06-06 09:06:19	ga_ls8c_ard_3-0-0_088083_2018-06-05_final
2018-06-06 09:06:42	ga_ls8c_ard_3-0-0_088084_2018-06-05_final
2018-06-09 09:30:52	ga_ls8c_ard_3-0-0_093067_2018-06-09_final
2018-06-20 09:15:39	ga_ls8c_ard_3-0-0_090075_2018-06-19_final
2018-06-20 09:16:03	ga_ls8c_ard_3-0-0_090076_2018-06-19_final
2018-06-20 09:16:27	ga_ls8c_ard_3-0-0_090077_2018-06-19_final
2018-06-20 09:16:50	ga_ls8c_ard_3-0-0_090078_2018-06-19_final
2018-06-20 09:17:14	ga_ls8c_ard_3-0-0_090079_2018-06-19_final
2018-06-20 09:17:38	ga_ls8c_ard_3-0-0_090080_2018-06-19_final
2018-06-20 09:18:02	ga_ls8c_ard_3-0-0_090081_2018-06-19_final
2018-06-22 09:06:30	ga_ls8c_ard_3-0-0_088083_2018-06-21_final
2018-06-22 09:06:54	ga_ls8c_ard_3-1-0_088084_2018-06-21_final
2018-06-25 09:31:03	ga_ls8c_ard_3-0-0_093067_2018-06-25_final
2018-07-06 09:15:48	ga_ls8c_ard_3-0-0_090075_2018-07-05_final
2018-07-06 09:16:12	ga_ls8c_ard_3-0-0_090076_2018-07-05_final
2018-07-06 09:16:36	ga_ls8c_ard_3-0-0_090077_2018-07-05_final
2018-07-06 09:17:00	ga_ls8c_ard_3-0-0_090078_2018-07-05_final
2018-07-06 09:17:24	ga_ls8c_ard_3-0-0_090079_2018-07-05_final
2018-07-06 09:17:48	ga_ls8c_ard_3-0-0_090080_2018-07-05_final
2018-07-06 09:18:11	ga_ls8c_ard_3-0-0_090081_2018-07-05_final
2018-07-08 09:06:39	ga_ls8c_ard_3-0-0_088083_2018-07-07_final
2018-07-08 09:07:03	ga_ls8c_ard_3-0-0_088084_2018-07-07_final
2018-07-11 09:31:11	ga_ls8c_ard_3-0-0_093067_2018-07-11_final
2019-02-01 09:07:42	ga_ls8c_ard_3-0-0_088084_2019-01-31_final
2019-02-22 09:21:24	ga_ls8c_ard_3-0-0_091072_2019-02-21_final
2019-02-22 09:21:48	ga_ls8c_ard_3-0-0_091073_2019-02-21_final
2019-02-22 09:22:12	ga_ls8c_ard_3-0-0_091074_2019-02-21_final
2019-02-22 09:22:36	ga_ls8c_ard_3-0-0_091075_2019-02-21_final
2019-02-22 09:23:00	ga_ls8c_ard_3-0-0_091076_2019-02-21_final
2019-03-21 09:07:31	ga_ls8c_ard_3-1-0_088084_2019-03-20_final
2019-04-13 09:11:59	ga_ls8c_ard_3-1-0_089080_2019-04-12_final
2019-04-13 09:12:23	ga_ls8c_ard_3-1-0_089081_2019-04-12_final
2019-04-13 09:12:47	ga_ls8c_ard_3-1-0_089082_2019-04-12_final
2019-04-13 09:13:11	ga_ls8c_ard_3-1-0_089083_2019-04-12_final
2019-04-13 09:13:35	ga_ls8c_ard_3-1-0_089084_2019-04-12_final
2019-04-13 09:13:59	ga_ls8c_ard_3-1-0_089085_2019-04-12_final
2019-05-11 09:31:34	ga_ls8c_ard_3-0-0_093067_2019-05-11_final
2019-05-13 09:21:14	ga_ls8c_ard_3-0-0_091072_2019-05-12_final
2019-05-13 09:21:38	ga_ls8c_ard_3-0-0_091073_2019-05-12_final
2019-05-13 09:22:02	ga_ls8c_ard_3-0-0_091074_2019-05-12_final
2019-05-13 09:22:26	ga_ls8c_ard_3-0-0_091075_2019-05-12_final
2019-05-13 09:22:50	ga_ls8c_ard_3-0-0_091076_2019-05-12_final
2019-05-31 09:12:14	ga_ls8c_ard_3-0-0_089080_2019-05-30_final
2019-05-31 09:12:38	ga_ls8c_ard_3-0-0_089081_2019-05-30_final
2019-05-31 09:13:02	ga_ls8c_ard_3-0-0_089082_2019-05-30_final
2019-05-31 09:13:26	ga_ls8c_ard_3-0-0_089083_2019-05-30_final
2019-05-31 09:13:50	ga_ls8c_ard_3-0-0_089084_2019-05-30_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