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
2022-02-04 10:27:36	ga_ls8c_ard_3-2-1_101082_2022-02-04_final
2022-02-06 10:16:26	ga_ls8c_ard_3-2-1_099085_2022-02-06_final
2022-02-19 11:24:20	ga_ls8c_ard_3-2-1_110085_2022-02-19_final
2022-02-22 10:15:56	ga_ls8c_ard_3-2-1_099084_2022-02-22_final
2022-06-03 10:28:29	ga_ls8c_ard_3-2-1_102069_2022-06-03_final
2022-06-18 11:29:28	ga_ls8c_ard_3-2-1_111082_2022-06-18_final
2022-06-20 09:39:26	ga_ls8c_ard_3-2-1_093085_2022-06-20_final
2022-06-28 10:25:19	ga_ls8c_ard_3-2-1_101076_2022-06-28_final
2022-06-30 10:15:45	ga_ls8c_ard_3-2-1_099083_2022-06-30_final
2022-07-13 09:45:38	ga_ls8c_ard_3-2-1_094085_2022-07-13_final
2022-07-13 11:19:20	ga_ls8c_ard_3-2-1_110072_2022-07-13_final
2022-07-14 10:28:06	ga_ls8c_ard_3-2-1_101083_2022-07-14_final
2022-07-22 09:40:44	ga_ls8c_ard_3-2-1_093088_2022-07-22_final
2022-08-01 10:15:56	ga_ls8c_ard_3-2-1_099083_2022-08-01_final
2022-08-24 10:17:27	ga_ls8c_ard_3-2-1_100071_2022-08-24_final
2022-09-13 09:52:24	ga_ls8c_ard_3-2-1_096070_2022-09-13_final
2022-09-17 09:34:05	ga_ls8c_ard_3-2-1_092086_2022-09-17_final
2022-09-19 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-09-19_final
2022-09-24 11:15:10	ga_ls8c_ard_3-2-1_109076_2022-09-24_final
2022-10-08 09:47:23	ga_ls8c_ard_3-2-1_095073_2022-10-08_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-13 10:04:39	ga_ls8c_ard_3-2-1_098070_2022-10-13_final
2022-10-16 10:39:58	ga_ls8c_ard_3-2-1_103081_2022-10-16_final
2022-10-21 10:55:22	ga_ls8c_ard_3-2-1_106073_2022-10-21_final
2022-11-09 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-11-09_final
2022-11-09 09:53:00	ga_ls8c_ard_3-2-1_095087_2022-11-09_final
2022-11-14 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-14_final
2022-11-14 11:47:59	ga_ls8c_ard_3-2-1_114081_2022-11-14_final
2022-11-27 11:13:05	ga_ls8c_ard_3-2-1_109071_2022-11-27_final
2022-11-28 10:19:28	ga_ls8c_ard_3-2-1_100076_2022-11-28_final
2022-11-29 09:28:14	ga_ls8c_ard_3-2-1_091087_2022-11-28_final
2022-12-12 10:28:35	ga_ls8c_ard_3-2-1_102068_2022-12-12_final
2022-12-12 10:28:59	ga_ls8c_ard_3-2-1_102069_2022-12-12_final
2023-01-02 09:14:08	ga_ls8c_ard_3-2-1_089083_2023-01-01_final
2023-01-03 11:33:05	ga_ls8c_ard_3-2-1_112075_2023-01-03_final
2023-01-08 10:15:55	ga_ls8c_ard_3-2-1_099083_2023-01-08_final
2023-01-09 09:21:05	ga_ls8c_ard_3-2-1_090085_2023-01-08_final
2023-01-19 11:34:09	ga_ls8c_ard_3-2-1_112078_2023-01-19_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-01-24 11:51:58	ga_ls8c_ard_3-2-1_115076_2023-01-24_final
2023-01-30 09:40:25	ga_ls8c_ard_3-2-1_093087_2023-01-30_final
2023-02-01 11:02:33	ga_ls8c_ard_3-2-1_107076_2023-02-01_final
2023-02-02 11:47:24	ga_ls8c_ard_3-2-1_114080_2023-02-02_final
2023-02-04 11:36:38	ga_ls8c_ard_3-2-1_112084_2023-02-04_final
2023-02-06 11:20:16	ga_ls8c_ard_3-2-1_110074_2023-02-06_final
2023-02-10 09:22:13	ga_ls8c_ard_3-2-1_090088_2023-02-09_final
2023-02-16 10:18:21	ga_ls8c_ard_3-2-1_100074_2023-02-16_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-02-19 09:14:18	ga_ls8c_ard_3-2-1_089084_2023-02-18_final
2023-02-23 10:27:35	ga_ls8c_ard_3-2-1_101082_2023-02-23_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-03-13 11:52:23	ga_ls8c_ard_3-2-1_115078_2023-03-13_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-03-28 11:06:10	ga_ls8c_ard_3-2-1_108071_2023-03-28_final
2023-04-01 09:06:31	ga_ls8c_ard_3-2-1_088081_2023-03-31_final
2023-04-11 11:19:04	ga_ls8c_ard_3-2-1_110073_2023-04-11_final
2023-04-14 10:10:41	ga_ls8c_ard_3-2-1_099072_2023-04-14_final
2023-04-30 11:52:41	ga_ls8c_ard_3-2-1_115080_2023-04-30_final
2023-05-09 10:06:18	ga_ls8c_ard_3-2-1_098077_2023-05-09_final
2023-05-14 10:26:46	ga_ls8c_ard_3-2-1_101082_2023-05-14_final
2023-05-15 11:06:25	ga_ls8c_ard_3-2-1_108073_2023-05-15_final
2023-05-23 11:57:05	ga_ls8c_ard_3-2-1_116076_2023-05-23_final
2023-05-24 11:01:04	ga_ls8c_ard_3-2-1_107075_2023-05-24_final
2023-05-30 10:23:36	ga_ls8c_ard_3-2-1_101074_2023-05-30_final
2023-06-05 11:23:27	ga_ls8c_ard_3-2-1_111069_2023-06-05_final
2023-06-14 11:20:09	ga_ls8c_ard_3-2-1_110076_2023-06-14_final
2023-06-16 11:05:25	ga_ls8c_ard_3-2-1_108070_2023-06-16_final
2023-06-17 10:09:48	ga_ls8c_ard_3-2-1_099070_2023-06-17_final
2023-06-19 09:56:14	ga_ls8c_ard_3-2-1_097067_2023-06-19_final
2023-06-24 10:20:47	ga_ls8c_ard_3-2-1_100082_2023-06-24_final
2023-06-25 10:59:17	ga_ls8c_ard_3-2-1_107070_2023-06-25_final
2023-07-08 10:27:45	ga_ls8c_ard_3-2-1_102068_2023-07-08_final
2023-07-10 10:21:23	ga_ls8c_ard_3-2-1_100083_2023-07-10_final
2023-08-11 10:17:09	ga_ls8c_ard_3-2-1_100072_2023-08-11_final
2023-09-03 10:25:28	ga_ls8c_ard_3-2-1_101077_2023-09-03_final
2023-09-05 10:09:30	ga_ls8c_ard_3-2-1_099068_2023-09-05_final
2023-09-06 10:58:44	ga_ls8c_ard_3-2-1_106083_2023-09-06_final
2023-09-15 09:14:34	ga_ls8c_ard_3-2-1_089085_2023-09-14_final
2023-09-21 11:51:40	ga_ls8c_ard_3-2-1_115076_2023-09-21_final
2023-09-26 10:28:58	ga_ls8c_ard_3-2-1_102070_2023-09-26_final
2023-10-08 10:53:20	ga_ls8c_ard_3-2-1_106069_2023-10-08_final
2023-10-23 10:10:54	ga_ls8c_ard_3-2-1_099071_2023-10-23_final
2023-11-10 10:03:40	ga_ls8c_ard_3-2-1_097084_2023-11-10_final
2023-11-16 09:23:53	ga_ls8c_ard_3-2-1_091077_2023-11-15_final
2023-11-26 11:42:41	ga_ls8c_ard_3-2-1_113084_2023-11-26_final
2023-12-18 09:23:29	ga_ls8c_ard_3-2-1_091076_2023-12-17_final
2023-12-27 09:18:05	ga_ls8c_ard_3-2-1_090078_2023-12-26_final
2023-12-27 10:58:10	ga_ls8c_ard_3-2-1_106081_2023-12-27_final
2023-12-28 11:42:13	ga_ls8c_ard_3-2-1_113083_2023-12-28_final
2024-01-08 09:44:19	ga_ls8c_ard_3-2-1_094082_2024-01-08_final
2024-01-12 10:54:31	ga_ls8c_ard_3-2-1_106072_2024-01-12_final
2024-01-21 09:13:24	ga_ls8c_ard_3-2-1_089082_2024-01-20_final
2024-01-24 11:20:21	ga_ls8c_ard_3-2-1_110075_2024-01-24_final
2024-02-19 10:21:46	ga_ls8c_ard_3-2-1_100083_2024-02-19_final
2024-03-19 11:27:28	ga_ls8c_ard_3-2-1_111078_2024-03-19_final
2024-03-30 09:34:15	ga_ls8c_ard_3-2-1_092089_2024-03-30_final
2024-04-08 09:26:28	ga_ls8c_ard_3-2-1_091085_2024-04-07_final
2024-04-15 11:06:41	ga_ls8c_ard_3-2-1_108073_2024-04-15_nrt
2024-04-17 09:21:47	ga_ls8c_ard_3-2-1_090089_2024-04-16_nrt
2024-04-19 09:05:48	ga_ls8c_ard_3-2-1_088080_2024-04-18_nrt

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