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
2022-05-18 10:32:24	ga_ls8c_ard_3-2-1_102079_2022-05-18_final
2022-05-18 10:32:48	ga_ls8c_ard_3-2-1_102080_2022-05-18_final
2022-05-29 11:50:45	ga_ls8c_ard_3-2-1_115074_2022-05-29_final
2022-05-30 09:18:39	ga_ls8c_ard_3-2-1_090080_2022-05-29_final
2022-06-29 09:29:42	ga_ls8c_ard_3-2-1_092076_2022-06-28_final
2022-07-01 09:18:32	ga_ls8c_ard_3-2-1_090079_2022-06-30_final
2022-07-01 09:18:56	ga_ls8c_ard_3-2-1_090080_2022-06-30_final
2022-07-01 09:19:20	ga_ls8c_ard_3-2-1_090081_2022-06-30_final
2022-07-01 09:20:08	ga_ls8c_ard_3-2-1_090083_2022-06-30_final
2022-07-29 11:22:42	ga_ls8c_ard_3-2-1_110080_2022-07-29_final
2022-07-30 10:28:17	ga_ls8c_ard_3-2-1_101083_2022-07-30_final
2022-07-31 09:32:16	ga_ls8c_ard_3-2-1_092082_2022-07-31_final
2022-07-31 09:32:40	ga_ls8c_ard_3-2-1_092083_2022-07-31_final
2022-07-31 09:35:28	ga_ls8c_ard_3-2-1_092090_2022-07-31_final
2022-08-11 09:15:25	ga_ls8c_ard_3-2-1_089086_2022-08-10_final
2022-08-30 09:42:21	ga_ls8c_ard_3-2-1_094076_2022-08-30_final
2022-08-30 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-08-30_final
2022-08-30 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-08-30_final
2022-09-02 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-09-02_final
2022-09-02 11:53:20	ga_ls8c_ard_3-2-1_115079_2022-09-02_final
2022-09-02 11:53:44	ga_ls8c_ard_3-2-1_115080_2022-09-02_final
2022-09-08 09:37:49	ga_ls8c_ard_3-2-1_093080_2022-09-08_final
2022-09-08 09:38:13	ga_ls8c_ard_3-2-1_093081_2022-09-08_final
2022-09-08 09:38:37	ga_ls8c_ard_3-2-1_093082_2022-09-08_final
2022-09-08 09:39:01	ga_ls8c_ard_3-2-1_093083_2022-09-08_final
2022-09-08 09:39:25	ga_ls8c_ard_3-2-1_093084_2022-09-08_final
2022-09-08 09:39:49	ga_ls8c_ard_3-2-1_093085_2022-09-08_final
2022-09-08 09:40:13	ga_ls8c_ard_3-2-1_093086_2022-09-08_final
2022-09-08 09:40:37	ga_ls8c_ard_3-2-1_093087_2022-09-08_final
2022-09-11 10:07:57	ga_ls8c_ard_3-2-1_098078_2022-09-11_final
2022-09-21 09:07:23	ga_ls8c_ard_3-2-1_088081_2022-09-20_final
2022-09-21 09:07:47	ga_ls8c_ard_3-2-1_088082_2022-09-20_final
2022-10-04 10:13:44	ga_ls8c_ard_3-2-1_099077_2022-10-04_final
2022-10-04 10:16:56	ga_ls8c_ard_3-2-1_099085_2022-10-04_final
2022-10-05 09:20:06	ga_ls8c_ard_3-2-1_090082_2022-10-04_final
2022-10-05 09:20:30	ga_ls8c_ard_3-2-1_090083_2022-10-04_final
2022-10-05 09:20:54	ga_ls8c_ard_3-2-1_090084_2022-10-04_final
2022-10-05 09:21:18	ga_ls8c_ard_3-2-1_090085_2022-10-04_final
2022-10-05 09:21:42	ga_ls8c_ard_3-2-1_090086_2022-10-04_final
2022-10-05 09:22:06	ga_ls8c_ard_3-2-1_090087_2022-10-04_final
2022-10-13 10:09:02	ga_ls8c_ard_3-2-1_098081_2022-10-13_final
2022-10-19 09:30:49	ga_ls8c_ard_3-2-1_092078_2022-10-19_final
2022-10-19 09:31:13	ga_ls8c_ard_3-2-1_092079_2022-10-19_final
2022-10-19 09:31:37	ga_ls8c_ard_3-2-1_092080_2022-10-19_final
2022-10-19 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-10-19_final
2022-10-23 09:07:20	ga_ls8c_ard_3-2-1_088081_2022-10-22_final
2022-10-24 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-10-24_final
2022-10-24 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-10-24_final
2022-11-28 10:17:52	ga_ls8c_ard_3-2-1_100072_2022-11-28_final
2022-11-28 10:18:16	ga_ls8c_ard_3-2-1_100073_2022-11-28_final
2022-11-29 09:24:14	ga_ls8c_ard_3-2-1_091077_2022-11-28_final
2022-11-30 10:03:55	ga_ls8c_ard_3-2-1_098068_2022-11-30_final
2022-11-30 10:04:19	ga_ls8c_ard_3-2-1_098069_2022-11-30_final
2022-11-30 10:04:43	ga_ls8c_ard_3-2-1_098070_2022-11-30_final
2022-12-01 09:13:05	ga_ls8c_ard_3-2-1_089080_2022-11-30_final
2022-12-01 09:13:29	ga_ls8c_ard_3-2-1_089081_2022-11-30_final
2022-12-01 09:13:53	ga_ls8c_ard_3-2-1_089082_2022-11-30_final
2022-12-01 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-30_final
2022-12-22 11:05:56	ga_ls8c_ard_3-2-1_108069_2022-12-22_final
2022-12-22 11:06:20	ga_ls8c_ard_3-2-1_108070_2022-12-22_final
2022-12-24 09:18:17	ga_ls8c_ard_3-2-1_090078_2022-12-23_final
2022-12-24 09:18:41	ga_ls8c_ard_3-2-1_090079_2022-12-23_final
2022-12-24 09:19:05	ga_ls8c_ard_3-2-1_090080_2022-12-23_final
2022-12-24 10:53:34	ga_ls8c_ard_3-2-1_106069_2022-12-24_final
2022-12-24 10:53:58	ga_ls8c_ard_3-2-1_106070_2022-12-24_final
2022-12-25 09:57:57	ga_ls8c_ard_3-2-1_097069_2022-12-25_final
2022-12-29 11:12:08	ga_ls8c_ard_3-2-1_109069_2022-12-29_final
2022-12-29 11:12:32	ga_ls8c_ard_3-2-1_109070_2022-12-29_final
2022-12-29 11:12:56	ga_ls8c_ard_3-2-1_109071_2022-12-29_final
2022-12-29 11:13:20	ga_ls8c_ard_3-2-1_109072_2022-12-29_final
2022-12-30 10:17:19	ga_ls8c_ard_3-2-1_100071_2022-12-30_final
2023-01-01 10:03:46	ga_ls8c_ard_3-2-1_098068_2023-01-01_final
2023-01-01 10:04:58	ga_ls8c_ard_3-2-1_098071_2023-01-01_final
2023-01-01 10:05:22	ga_ls8c_ard_3-2-1_098072_2023-01-01_final
2023-01-03 11:32:17	ga_ls8c_ard_3-2-1_112073_2023-01-03_final
2023-01-05 11:19:55	ga_ls8c_ard_3-2-1_110073_2023-01-05_final
2023-01-14 09:35:11	ga_ls8c_ard_3-2-1_093074_2023-01-14_final
2023-01-14 09:35:34	ga_ls8c_ard_3-2-1_093075_2023-01-14_final
2023-01-14 09:35:58	ga_ls8c_ard_3-2-1_093076_2023-01-14_final
2023-01-17 10:10:25	ga_ls8c_ard_3-2-1_098085_2023-01-17_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-02-10 10:53:07	ga_ls8c_ard_3-2-1_106068_2023-02-10_final
2023-02-11 09:57:53	ga_ls8c_ard_3-2-1_097069_2023-02-11_final
2023-02-13 11:23:59	ga_ls8c_ard_3-2-1_111068_2023-02-13_final
2023-02-13 11:24:23	ga_ls8c_ard_3-2-1_111069_2023-02-13_final
2023-02-13 11:24:47	ga_ls8c_ard_3-2-1_111070_2023-02-13_final
2023-02-14 10:28:45	ga_ls8c_ard_3-2-1_102069_2023-02-14_final
2023-02-16 10:17:09	ga_ls8c_ard_3-2-1_100071_2023-02-16_final
2023-02-24 11:05:37	ga_ls8c_ard_3-2-1_108069_2023-02-24_final
2023-02-26 10:53:39	ga_ls8c_ard_3-2-1_106070_2023-02-26_final
2023-02-27 09:58:49	ga_ls8c_ard_3-2-1_097072_2023-02-27_final
2023-03-02 10:30:31	ga_ls8c_ard_3-2-1_102074_2023-03-02_final
2023-03-02 10:30:55	ga_ls8c_ard_3-2-1_102075_2023-03-02_final
2023-03-07 10:46:13	ga_ls8c_ard_3-2-1_105067_2023-03-07_final
2023-03-07 10:47:01	ga_ls8c_ard_3-2-1_105069_2023-03-07_final
2023-03-28 09:31:40	ga_ls8c_ard_3-2-1_092082_2023-03-28_final
2023-03-30 10:57:47	ga_ls8c_ard_3-2-1_106081_2023-03-30_final
2023-04-11 11:17:52	ga_ls8c_ard_3-2-1_110070_2023-04-11_final
2023-04-11 11:18:16	ga_ls8c_ard_3-2-1_110071_2023-04-11_final
2023-04-11 11:19:04	ga_ls8c_ard_3-2-1_110073_2023-04-11_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