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
2021-06-17 09:35:05	ga_ls8c_ard_3-2-0_093075_2021-06-17_final
2021-06-17 11:15:10	ga_ls8c_ard_3-2-0_109078_2021-06-17_final
2021-06-19 09:25:32	ga_ls8c_ard_3-2-0_091082_2021-06-18_final
2021-06-22 11:35:19	ga_ls8c_ard_3-2-0_112082_2021-06-22_final
2021-06-26 11:06:14	ga_ls8c_ard_3-2-0_108071_2021-06-26_final
2021-07-11 10:23:47	ga_ls8c_ard_3-2-0_101073_2021-07-11_final
2021-07-12 09:30:58	ga_ls8c_ard_3-2-0_092080_2021-07-12_final
2021-07-18 10:29:12	ga_ls8c_ard_3-2-0_102071_2021-07-18_final
2021-08-04 11:15:24	ga_ls8c_ard_3-2-0_109078_2021-08-04_final
2021-08-13 11:10:28	ga_ls8c_ard_3-2-0_108081_2021-08-13_final
2021-08-27 11:24:06	ga_ls8c_ard_3-2-0_110084_2021-08-27_final
2021-09-08 11:42:06	ga_ls8c_ard_3-2-0_114067_2021-09-08_final
2021-09-08 11:45:41	ga_ls8c_ard_3-2-0_114076_2021-09-08_final
2021-09-10 11:36:08	ga_ls8c_ard_3-2-0_112083_2021-09-10_final
2021-09-16 09:19:47	ga_ls8c_ard_3-2-0_090082_2021-09-15_final
2021-09-16 09:21:46	ga_ls8c_ard_3-2-0_090087_2021-09-15_final
2021-09-16 10:56:40	ga_ls8c_ard_3-2-0_106077_2021-09-16_final
2021-09-25 10:50:55	ga_ls8c_ard_3-2-0_105078_2021-09-25_final
2021-10-04 10:44:00	ga_ls8c_ard_3-2-0_104076_2021-10-04_final
2021-11-03 10:56:48	ga_ls8c_ard_3-2-0_106077_2021-11-03_final
2021-11-14 10:37:48	ga_ls8c_ard_3-2-0_103076_2021-11-14_final
2021-11-15 09:42:10	ga_ls8c_ard_3-2-0_094076_2021-11-15_final
2021-11-15 09:44:34	ga_ls8c_ard_3-2-0_094082_2021-11-15_final
2021-11-17 09:31:23	ga_ls8c_ard_3-2-0_092080_2021-11-17_final
2021-11-23 10:30:01	ga_ls8c_ard_3-2-0_102072_2021-11-23_final
2021-11-27 10:03:18	ga_ls8c_ard_3-2-0_098067_2021-11-27_final
2021-12-05 10:57:09	ga_ls8c_ard_3-2-1_106078_2021-12-05_final
2021-12-19 11:10:40	ga_ls8c_ard_3-2-1_108081_2021-12-19_final
2021-12-26 11:15:36	ga_ls8c_ard_3-2-1_109078_2021-12-26_final
2021-12-26 11:18:00	ga_ls8c_ard_3-2-1_109084_2021-12-26_final
2022-01-02 11:24:32	ga_ls8c_ard_3-2-1_110085_2022-01-02_final
2022-01-17 10:35:40	ga_ls8c_ard_3-2-1_103071_2022-01-17_final
2022-02-09 09:07:39	ga_ls8c_ard_3-2-1_088083_2022-02-08_final
2022-02-12 09:36:56	ga_ls8c_ard_3-2-1_093079_2022-02-12_final
2022-02-13 10:17:48	ga_ls8c_ard_3-2-1_100073_2022-02-13_final
2022-02-15 10:09:01	ga_ls8c_ard_3-2-1_098082_2022-02-15_final
2022-02-17 09:55:50	ga_ls8c_ard_3-2-1_096080_2022-02-17_final
2022-03-06 10:39:02	ga_ls8c_ard_3-2-1_103080_2022-03-06_final
2022-03-12 10:01:55	ga_ls8c_ard_3-2-1_097080_2022-03-12_final
2022-03-23 09:45:39	ga_ls8c_ard_3-2-1_094086_2022-03-23_final
2022-03-29 10:44:10	ga_ls8c_ard_3-2-1_104078_2022-03-29_final
2022-04-04 10:07:29	ga_ls8c_ard_3-2-1_098079_2022-04-04_final
2022-04-05 09:14:16	ga_ls8c_ard_3-2-1_089085_2022-04-04_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-05-07 09:13:58	ga_ls8c_ard_3-2-1_089084_2022-05-06_final
2022-05-08 11:33:20	ga_ls8c_ard_3-2-1_112077_2022-05-08_final
2022-05-10 11:21:00	ga_ls8c_ard_3-2-1_110077_2022-05-10_final
2022-05-14 10:57:30	ga_ls8c_ard_3-2-1_106080_2022-05-14_final
2022-05-21 11:00:55	ga_ls8c_ard_3-2-1_107073_2022-05-21_final
2022-05-29 10:11:28	ga_ls8c_ard_3-2-1_099073_2022-05-29_final
2022-05-31 10:00:20	ga_ls8c_ard_3-2-1_097076_2022-05-31_final
2022-06-01 10:41:37	ga_ls8c_ard_3-2-1_104071_2022-06-01_final
2022-06-04 11:16:57	ga_ls8c_ard_3-2-1_109082_2022-06-04_final
2022-06-05 11:58:38	ga_ls8c_ard_3-2-1_116078_2022-06-05_final
2022-06-20 09:37:27	ga_ls8c_ard_3-2-1_093080_2022-06-20_final
2022-06-20 11:13:08	ga_ls8c_ard_3-2-1_109072_2022-06-20_final
2022-06-26 10:38:04	ga_ls8c_ard_3-2-1_103077_2022-06-26_final
2022-06-27 09:43:15	ga_ls8c_ard_3-2-1_094079_2022-06-27_final
2022-07-02 11:40:41	ga_ls8c_ard_3-2-1_113079_2022-07-02_final
2022-07-02 11:41:53	ga_ls8c_ard_3-2-1_113082_2022-07-02_final
2022-07-24 09:25:37	ga_ls8c_ard_3-2-1_091081_2022-07-23_final
2022-08-03 11:39:41	ga_ls8c_ard_3-2-1_113076_2022-08-03_final
2022-08-04 10:45:40	ga_ls8c_ard_3-2-1_104080_2022-08-04_final
2022-08-24 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-08-24_final
2022-09-05 10:41:47	ga_ls8c_ard_3-2-1_104070_2022-09-05_final
2022-09-09 10:22:41	ga_ls8c_ard_3-2-1_100084_2022-09-09_final
2022-10-01 09:43:15	ga_ls8c_ard_3-2-1_094078_2022-10-01_final
2022-10-03 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-10-03_final
2022-10-07 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-07_final
2022-10-09 10:30:14	ga_ls8c_ard_3-2-1_102072_2022-10-09_final
2022-10-24 11:28:41	ga_ls8c_ard_3-2-1_111079_2022-10-24_final
2022-10-28 11:04:23	ga_ls8c_ard_3-2-1_107080_2022-10-28_final
2022-11-01 10:38:05	ga_ls8c_ard_3-2-1_103076_2022-11-01_final
2022-11-05 10:12:34	ga_ls8c_ard_3-2-1_099074_2022-11-05_final
2022-11-10 10:31:28	ga_ls8c_ard_3-2-1_102075_2022-11-10_final
2022-11-16 09:52:19	ga_ls8c_ard_3-2-1_096070_2022-11-16_final
2022-11-19 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-11-19_final
2022-11-29 11:04:19	ga_ls8c_ard_3-2-1_107080_2022-11-29_final
2022-12-04 09:43:35	ga_ls8c_ard_3-2-1_094079_2022-12-04_final
2022-12-07 10:15:40	ga_ls8c_ard_3-2-1_099082_2022-12-07_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-25 09:58:45	ga_ls8c_ard_3-2-1_097071_2022-12-25_final
2022-12-27 11:27:41	ga_ls8c_ard_3-2-1_111077_2022-12-27_final
2023-01-09 09:20:41	ga_ls8c_ard_3-2-1_090084_2023-01-08_final
2023-01-10 11:42:01	ga_ls8c_ard_3-2-1_113082_2023-01-10_final
2023-01-14 09:37:10	ga_ls8c_ard_3-2-1_093079_2023-01-14_final
2023-01-24 10:12:41	ga_ls8c_ard_3-2-1_099075_2023-01-24_final
2023-01-30 11:15:42	ga_ls8c_ard_3-2-1_109078_2023-01-30_final
2023-02-21 10:37:36	ga_ls8c_ard_3-2-1_103076_2023-02-21_final
2023-02-26 09:18:21	ga_ls8c_ard_3-2-1_090079_2023-02-25_final
2023-03-05 11:03:47	ga_ls8c_ard_3-2-1_107080_2023-03-05_final
2023-03-11 10:23:28	ga_ls8c_ard_3-2-1_101072_2023-03-11_final
2023-03-15 09:59:08	ga_ls8c_ard_3-2-1_097073_2023-03-15_final
2023-03-22 10:05:36	ga_ls8c_ard_3-2-1_098074_2023-03-22_final
2023-04-04 09:37:21	ga_ls8c_ard_3-2-1_093081_2023-04-04_final
2023-04-24 09:14:26	ga_ls8c_ard_3-2-1_089086_2023-04-23_final
2023-05-04 11:29:31	ga_ls8c_ard_3-2-1_111084_2023-05-04_final
2023-05-06 11:12:20	ga_ls8c_ard_3-2-1_109072_2023-05-06_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