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
2023-02-02 10:03:44	ga_ls8c_ard_3-2-1_098068_2023-02-02_final
2023-02-03 09:15:17	ga_ls8c_ard_3-2-1_089086_2023-02-02_final
2023-03-22 10:06:48	ga_ls8c_ard_3-2-1_098077_2023-03-22_final
2023-06-09 09:23:53	ga_ls8c_ard_3-2-1_091079_2023-06-08_final
2023-06-09 11:01:34	ga_ls8c_ard_3-2-1_107076_2023-06-09_final
2023-06-11 09:13:32	ga_ls8c_ard_3-2-1_089084_2023-06-10_final
2023-06-17 11:52:16	ga_ls8c_ard_3-2-1_115079_2023-06-17_final
2023-06-18 09:20:10	ga_ls8c_ard_3-2-1_090085_2023-06-17_final
2023-06-25 10:59:41	ga_ls8c_ard_3-2-1_107071_2023-06-25_final
2023-06-29 10:37:25	ga_ls8c_ard_3-2-1_103077_2023-06-29_final
2023-07-03 11:51:14	ga_ls8c_ard_3-2-1_115076_2023-07-03_final
2023-07-07 09:51:16	ga_ls8c_ard_3-2-1_095085_2023-07-07_final
2023-07-11 09:22:58	ga_ls8c_ard_3-2-1_091076_2023-07-10_final
2023-07-16 11:19:13	ga_ls8c_ard_3-2-1_110073_2023-07-16_final
2023-07-16 11:20:25	ga_ls8c_ard_3-2-1_110076_2023-07-16_final
2023-07-19 10:10:49	ga_ls8c_ard_3-2-1_099072_2023-07-19_final
2023-07-20 09:20:23	ga_ls8c_ard_3-2-1_090085_2023-07-19_final
2023-07-23 09:46:32	ga_ls8c_ard_3-2-1_095073_2023-07-23_final
2023-07-27 09:24:40	ga_ls8c_ard_3-2-1_091080_2023-07-26_final
2023-07-27 09:26:40	ga_ls8c_ard_3-2-1_091085_2023-07-26_final
2023-07-28 10:06:45	ga_ls8c_ard_3-2-1_098077_2023-07-28_final
2023-07-29 09:13:32	ga_ls8c_ard_3-2-1_089083_2023-07-28_final
2023-08-02 10:27:43	ga_ls8c_ard_3-2-1_101083_2023-08-02_final
2023-08-06 09:58:13	ga_ls8c_ard_3-2-1_097071_2023-08-06_final
2023-08-08 09:46:40	ga_ls8c_ard_3-2-1_095073_2023-08-08_final
2023-08-10 09:34:42	ga_ls8c_ard_3-2-1_093074_2023-08-10_final
2023-08-11 10:18:45	ga_ls8c_ard_3-2-1_100076_2023-08-11_final
2023-08-17 11:19:27	ga_ls8c_ard_3-2-1_110073_2023-08-17_final
2023-08-18 10:25:26	ga_ls8c_ard_3-2-1_101077_2023-08-18_final
2023-08-21 09:17:28	ga_ls8c_ard_3-2-1_090077_2023-08-20_final
2023-08-21 09:17:52	ga_ls8c_ard_3-2-1_090078_2023-08-20_final
2023-09-02 09:45:00	ga_ls8c_ard_3-2-1_094084_2023-09-02_final
2023-09-02 09:45:48	ga_ls8c_ard_3-2-1_094086_2023-09-02_final
2023-09-04 09:29:02	ga_ls8c_ard_3-2-1_092075_2023-09-03_final
2023-09-04 09:33:02	ga_ls8c_ard_3-2-1_092085_2023-09-04_final
2023-09-05 10:11:06	ga_ls8c_ard_3-2-1_099072_2023-09-05_final
2023-09-05 10:15:29	ga_ls8c_ard_3-2-1_099083_2023-09-05_final
2023-09-05 10:16:17	ga_ls8c_ard_3-2-1_099085_2023-09-05_final
2023-09-05 11:51:34	ga_ls8c_ard_3-2-1_115076_2023-09-05_final
2023-09-07 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-09-07_final
2023-09-09 09:46:48	ga_ls8c_ard_3-2-1_095073_2023-09-09_final
2023-09-11 09:39:39	ga_ls8c_ard_3-2-1_093086_2023-09-11_final
2023-09-13 09:24:55	ga_ls8c_ard_3-2-1_091080_2023-09-12_final
2023-09-13 10:59:49	ga_ls8c_ard_3-2-1_107070_2023-09-13_final
2023-09-13 11:02:12	ga_ls8c_ard_3-2-1_107076_2023-09-13_final
2023-09-14 10:07:47	ga_ls8c_ard_3-2-1_098079_2023-09-14_final
2023-09-15 10:52:15	ga_ls8c_ard_3-2-1_105082_2023-09-15_final
2023-09-18 09:41:05	ga_ls8c_ard_3-2-1_094074_2023-09-18_final
2023-09-18 11:20:22	ga_ls8c_ard_3-2-1_110075_2023-09-18_final
2023-09-19 10:25:57	ga_ls8c_ard_3-2-1_101078_2023-09-19_final
2023-09-22 09:20:45	ga_ls8c_ard_3-2-1_090085_2023-09-21_final
2023-09-22 10:53:39	ga_ls8c_ard_3-2-1_106070_2023-09-22_final
2023-09-27 09:38:57	ga_ls8c_ard_3-2-1_093084_2023-09-27_final
2023-09-29 09:23:48	ga_ls8c_ard_3-2-1_091077_2023-09-28_final
2023-09-30 10:05:04	ga_ls8c_ard_3-2-1_098072_2023-09-30_final
2023-09-30 10:07:04	ga_ls8c_ard_3-2-1_098077_2023-09-30_final
2023-09-30 10:07:52	ga_ls8c_ard_3-2-1_098079_2023-09-30_final
2023-09-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2023-09-30_final
2023-10-01 09:12:38	ga_ls8c_ard_3-2-1_089080_2023-09-30_final
2023-10-01 10:48:44	ga_ls8c_ard_3-2-1_105073_2023-10-01_final
2023-10-03 10:34:46	ga_ls8c_ard_3-2-1_103069_2023-10-03_final
2023-10-04 11:18:50	ga_ls8c_ard_3-2-1_110071_2023-10-04_final
2023-10-04 11:20:25	ga_ls8c_ard_3-2-1_110075_2023-10-04_final
2023-10-05 10:24:48	ga_ls8c_ard_3-2-1_101075_2023-10-05_final
2023-10-07 10:16:02	ga_ls8c_ard_3-2-1_099084_2023-10-07_final
2023-10-07 11:52:08	ga_ls8c_ard_3-2-1_115077_2023-10-07_final
2023-10-08 10:53:44	ga_ls8c_ard_3-2-1_106070_2023-10-08_final
2023-10-08 10:54:55	ga_ls8c_ard_3-2-1_106073_2023-10-08_final
2023-10-13 11:17:53	ga_ls8c_ard_3-2-1_109084_2023-10-13_final
2023-10-15 11:01:32	ga_ls8c_ard_3-2-1_107074_2023-10-15_final
2023-10-16 10:05:06	ga_ls8c_ard_3-2-1_098072_2023-10-16_final
2023-10-20 09:41:09	ga_ls8c_ard_3-2-1_094074_2023-10-20_final
2023-10-21 10:25:38	ga_ls8c_ard_3-2-1_101077_2023-10-21_final
2023-10-22 09:29:37	ga_ls8c_ard_3-2-1_092076_2023-10-21_final
2023-10-23 10:14:29	ga_ls8c_ard_3-2-1_099080_2023-10-23_final
2023-10-23 10:16:05	ga_ls8c_ard_3-2-1_099084_2023-10-23_final
2023-10-23 11:50:59	ga_ls8c_ard_3-2-1_115074_2023-10-23_final
2023-10-23 11:51:23	ga_ls8c_ard_3-2-1_115075_2023-10-23_final
2023-10-24 10:53:22	ga_ls8c_ard_3-2-1_106069_2023-10-24_final
2023-10-24 10:53:46	ga_ls8c_ard_3-2-1_106070_2023-10-24_final
2023-10-24 10:55:22	ga_ls8c_ard_3-2-1_106074_2023-10-24_final
2023-10-31 11:01:59	ga_ls8c_ard_3-2-1_107075_2023-10-31_final
2023-11-03 09:58:23	ga_ls8c_ard_3-2-1_096086_2023-11-03_final
2023-11-03 11:35:40	ga_ls8c_ard_3-2-1_112082_2023-11-03_final
2023-11-06 10:24:04	ga_ls8c_ard_3-2-1_101073_2023-11-06_final
2023-11-07 11:07:19	ga_ls8c_ard_3-2-1_108073_2023-11-07_final
2023-11-08 11:52:09	ga_ls8c_ard_3-2-1_115077_2023-11-08_final
2023-11-09 10:58:54	ga_ls8c_ard_3-2-1_106083_2023-11-09_final
2023-11-10 09:58:53	ga_ls8c_ard_3-2-1_097072_2023-11-10_final
2023-11-11 10:40:58	ga_ls8c_ard_3-2-1_104069_2023-11-11_final
2023-11-12 09:47:21	ga_ls8c_ard_3-2-1_095074_2023-11-12_final
2023-11-12 11:29:02	ga_ls8c_ard_3-2-1_111081_2023-11-12_final
2023-11-13 10:28:38	ga_ls8c_ard_3-2-1_102069_2023-11-13_final
2023-11-16 11:01:10	ga_ls8c_ard_3-2-1_107073_2023-11-16_final
2023-11-16 11:01:34	ga_ls8c_ard_3-2-1_107074_2023-11-16_final
2023-11-16 11:01:58	ga_ls8c_ard_3-2-1_107075_2023-11-16_final
2023-11-17 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-17_final
2023-11-18 09:12:44	ga_ls8c_ard_3-2-1_089080_2023-11-17_final
2023-11-18 09:15:08	ga_ls8c_ard_3-2-1_089086_2023-11-17_final
2023-11-21 11:24:08	ga_ls8c_ard_3-2-1_110084_2023-11-21_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