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
2021-11-11 10:04:08	ga_ls8c_ard_3-2-0_098069_2021-11-11_final
2021-11-19 10:56:19	ga_ls8c_ard_3-2-0_106076_2021-11-19_final
2021-11-23 10:28:25	ga_ls8c_ard_3-2-0_102068_2021-11-23_final
2021-11-28 09:16:28	ga_ls8c_ard_3-2-0_089089_2021-11-27_final
2021-12-01 11:20:16	ga_ls8c_ard_3-2-0_110074_2021-12-01_final
2021-12-01 11:21:04	ga_ls8c_ard_3-2-0_110076_2021-12-01_final
2021-12-04 11:52:46	ga_ls8c_ard_3-2-0_115078_2021-12-04_final
2021-12-09 10:30:25	ga_ls8c_ard_3-2-1_102073_2021-12-09_final
2021-12-12 11:05:42	ga_ls8c_ard_3-2-1_107084_2021-12-12_final
2021-12-17 11:19:03	ga_ls8c_ard_3-2-1_110071_2021-12-17_final
2021-12-21 10:53:31	ga_ls8c_ard_3-2-1_106069_2021-12-21_final
2022-01-04 11:06:36	ga_ls8c_ard_3-2-1_108071_2022-01-04_final
2022-01-13 09:25:06	ga_ls8c_ard_3-2-1_091080_2022-01-12_final
2022-01-14 11:45:39	ga_ls8c_ard_3-2-1_114076_2022-01-14_final
2022-02-01 09:57:31	ga_ls8c_ard_3-2-1_096084_2022-02-01_final
2022-02-04 10:24:01	ga_ls8c_ard_3-2-1_101073_2022-02-04_final
2022-02-05 11:07:17	ga_ls8c_ard_3-2-1_108073_2022-02-05_final
2022-02-08 10:03:40	ga_ls8c_ard_3-2-1_097084_2022-02-08_final
2022-02-10 11:26:36	ga_ls8c_ard_3-2-1_111075_2022-02-10_final
2022-02-11 10:29:22	ga_ls8c_ard_3-2-1_102071_2022-02-11_final
2022-03-11 09:21:28	ga_ls8c_ard_3-2-1_090087_2022-03-10_final
2022-04-10 11:07:21	ga_ls8c_ard_3-2-1_108074_2022-04-10_final
2022-04-20 10:03:10	ga_ls8c_ard_3-2-1_098068_2022-04-20_final
2022-05-04 10:17:08	ga_ls8c_ard_3-2-1_100072_2022-05-04_final
2022-05-09 10:35:44	ga_ls8c_ard_3-2-1_103072_2022-05-09_final
2022-05-10 11:23:47	ga_ls8c_ard_3-2-1_110084_2022-05-10_final
2022-05-13 11:52:43	ga_ls8c_ard_3-2-1_115079_2022-05-13_final
2022-05-28 09:27:47	ga_ls8c_ard_3-2-1_092072_2022-05-27_final
2022-05-31 09:57:33	ga_ls8c_ard_3-2-1_097069_2022-05-31_final
2022-06-17 09:07:19	ga_ls8c_ard_3-2-1_088082_2022-06-16_final
2022-06-22 11:01:59	ga_ls8c_ard_3-2-1_107075_2022-06-22_final
2022-07-10 09:12:21	ga_ls8c_ard_3-2-1_089079_2022-07-09_final
2022-07-11 11:32:30	ga_ls8c_ard_3-2-1_112074_2022-07-11_final
2022-07-13 11:24:07	ga_ls8c_ard_3-2-1_110084_2022-07-13_final
2022-07-23 11:58:07	ga_ls8c_ard_3-2-1_116076_2022-07-23_final
2022-08-16 11:06:28	ga_ls8c_ard_3-2-1_108070_2022-08-16_final
2022-08-25 09:22:13	ga_ls8c_ard_3-2-1_091072_2022-08-24_final
2022-08-26 10:03:29	ga_ls8c_ard_3-2-1_098067_2022-08-26_final
2022-08-27 09:11:51	ga_ls8c_ard_3-2-1_089077_2022-08-26_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-08-30 11:18:50	ga_ls8c_ard_3-2-1_110070_2022-08-30_final
2022-09-02 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-09-02_final
2022-09-03 09:20:49	ga_ls8c_ard_3-2-1_090084_2022-09-02_final
2022-09-03 10:53:43	ga_ls8c_ard_3-2-1_106069_2022-09-03_final
2022-09-26 09:23:56	ga_ls8c_ard_3-2-1_091076_2022-09-25_final
2022-09-29 09:52:26	ga_ls8c_ard_3-2-1_096070_2022-09-29_final
2022-10-08 09:51:46	ga_ls8c_ard_3-2-1_095084_2022-10-08_final
2022-10-11 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-10-11_final
2022-10-14 09:17:00	ga_ls8c_ard_3-2-1_089090_2022-10-13_final
2022-10-17 11:20:26	ga_ls8c_ard_3-2-1_110074_2022-10-17_final
2022-10-28 11:00:48	ga_ls8c_ard_3-2-1_107071_2022-10-28_final
2022-10-29 10:09:34	ga_ls8c_ard_3-2-1_098082_2022-10-29_final
2022-10-29 10:10:46	ga_ls8c_ard_3-2-1_098085_2022-10-29_final
2022-11-05 10:16:57	ga_ls8c_ard_3-2-1_099085_2022-11-05_final
2022-11-06 10:54:13	ga_ls8c_ard_3-2-1_106070_2022-11-06_final
2022-11-11 09:39:02	ga_ls8c_ard_3-2-1_093083_2022-11-11_final
2022-11-14 10:05:06	ga_ls8c_ard_3-2-1_098071_2022-11-14_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-16 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-11-16_final
2022-11-20 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-11-20_final
2022-12-07 10:14:52	ga_ls8c_ard_3-2-1_099080_2022-12-07_final
2022-12-14 10:18:12	ga_ls8c_ard_3-2-1_100073_2022-12-14_final
2022-12-16 10:04:13	ga_ls8c_ard_3-2-1_098069_2022-12-16_final
2022-12-17 09:13:22	ga_ls8c_ard_3-2-1_089081_2022-12-16_final
2022-12-29 09:40:26	ga_ls8c_ard_3-2-1_093087_2022-12-29_final
2023-01-05 09:41:02	ga_ls8c_ard_3-2-1_094073_2023-01-05_final
2023-01-10 09:58:45	ga_ls8c_ard_3-2-1_097071_2023-01-10_final
2023-01-15 10:19:13	ga_ls8c_ard_3-2-1_100076_2023-01-15_final
2023-01-21 11:19:02	ga_ls8c_ard_3-2-1_110071_2023-01-21_final
2023-01-21 11:24:13	ga_ls8c_ard_3-2-1_110084_2023-01-21_final
2023-01-26 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-26_final
2023-01-30 11:14:06	ga_ls8c_ard_3-2-1_109074_2023-01-30_final
2023-02-04 09:52:58	ga_ls8c_ard_3-2-1_096072_2023-02-04_final
2023-02-25 11:53:15	ga_ls8c_ard_3-2-1_115080_2023-02-25_final
2023-03-03 11:12:10	ga_ls8c_ard_3-2-1_109070_2023-03-03_final
2023-03-10 11:20:17	ga_ls8c_ard_3-2-1_110075_2023-03-10_final
2023-03-10 11:23:52	ga_ls8c_ard_3-2-1_110084_2023-03-10_final
2023-03-15 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-03-15_final
2023-04-01 10:40:12	ga_ls8c_ard_3-2-1_104068_2023-04-01_final
2023-04-04 11:16:38	ga_ls8c_ard_3-2-1_109082_2023-04-04_final
2023-04-16 10:00:42	ga_ls8c_ard_3-2-1_097078_2023-04-16_final
2023-04-21 11:57:18	ga_ls8c_ard_3-2-1_116076_2023-04-21_final
2023-04-30 11:51:05	ga_ls8c_ard_3-2-1_115076_2023-04-30_final
2023-05-03 10:41:53	ga_ls8c_ard_3-2-1_104073_2023-05-03_final
2023-05-24 09:21:23	ga_ls8c_ard_3-2-1_091073_2023-05-23_final
2023-06-05 11:24:15	ga_ls8c_ard_3-2-1_111071_2023-06-05_final
2023-06-08 10:16:42	ga_ls8c_ard_3-2-1_100072_2023-06-08_final
2023-06-14 09:40:28	ga_ls8c_ard_3-2-1_094074_2023-06-14_final
2023-06-25 11:01:16	ga_ls8c_ard_3-2-1_107075_2023-06-25_final
2023-07-01 10:26:41	ga_ls8c_ard_3-2-1_101081_2023-07-01_final
2023-07-04 10:54:26	ga_ls8c_ard_3-2-1_106073_2023-07-04_final
2023-07-10 10:16:36	ga_ls8c_ard_3-2-1_100071_2023-07-10_final
2023-07-18 11:06:51	ga_ls8c_ard_3-2-1_108073_2023-07-18_final
2023-07-24 10:28:13	ga_ls8c_ard_3-2-1_102069_2023-07-24_final
2023-07-30 11:35:41	ga_ls8c_ard_3-2-1_112083_2023-07-30_final
2023-08-17 11:23:50	ga_ls8c_ard_3-2-1_110084_2023-08-17_final
2023-08-31 09:57:46	ga_ls8c_ard_3-2-1_096085_2023-08-31_nrt
2023-09-05 11:52:46	ga_ls8c_ard_3-2-1_115079_2023-09-05_final
2023-09-15 09:16:10	ga_ls8c_ard_3-2-1_089089_2023-09-14_final
2023-09-20 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-09-19_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