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
2021-06-18 11:57:14	ga_ls8c_ard_3-2-0_116075_2021-06-18_final
2021-06-27 10:15:24	ga_ls8c_ard_3-2-0_099083_2021-06-27_final
2021-06-29 09:56:40	ga_ls8c_ard_3-2-0_097067_2021-06-29_final
2021-07-07 10:49:18	ga_ls8c_ard_3-2-0_105075_2021-07-07_final
2021-07-10 11:19:49	ga_ls8c_ard_3-2-0_110074_2021-07-10_final
2021-07-19 09:34:23	ga_ls8c_ard_3-2-0_093073_2021-07-19_final
2021-07-25 10:35:51	ga_ls8c_ard_3-2-0_103072_2021-07-25_final
2021-08-02 11:24:33	ga_ls8c_ard_3-2-0_111070_2021-08-02_final
2021-08-04 11:14:36	ga_ls8c_ard_3-2-0_109076_2021-08-04_final
2021-08-29 11:10:57	ga_ls8c_ard_3-2-0_108082_2021-08-29_final
2021-08-31 09:21:43	ga_ls8c_ard_3-2-0_090087_2021-08-30_final
2021-09-16 09:16:59	ga_ls8c_ard_3-2-0_090075_2021-09-15_final
2021-09-28 09:38:34	ga_ls8c_ard_3-2-0_094067_2021-09-28_final
2021-10-01 10:10:41	ga_ls8c_ard_3-2-0_099070_2021-10-01_final
2021-10-30 11:19:32	ga_ls8c_ard_3-2-0_110072_2021-10-30_final
2021-11-12 10:49:22	ga_ls8c_ard_3-2-0_105074_2021-11-12_final
2021-11-24 11:12:05	ga_ls8c_ard_3-2-0_109069_2021-11-24_final
2021-12-08 11:24:51	ga_ls8c_ard_3-2-1_111070_2021-12-08_final
2021-12-11 10:22:03	ga_ls8c_ard_3-2-1_100083_2021-12-11_final
2021-12-14 10:49:21	ga_ls8c_ard_3-2-1_105074_2021-12-14_final
2022-01-20 09:29:15	ga_ls8c_ard_3-2-1_092075_2022-01-19_final
2022-01-22 09:22:04	ga_ls8c_ard_3-2-1_090088_2022-01-21_final
2022-01-23 09:57:21	ga_ls8c_ard_3-2-1_097068_2022-01-23_final
2022-02-06 11:52:32	ga_ls8c_ard_3-2-1_115078_2022-02-06_final
2022-02-07 09:21:13	ga_ls8c_ard_3-2-1_090086_2022-02-06_final
2022-02-15 10:04:13	ga_ls8c_ard_3-2-1_098070_2022-02-15_final
2022-02-18 10:34:18	ga_ls8c_ard_3-2-1_103068_2022-02-18_final
2022-03-02 09:23:18	ga_ls8c_ard_3-2-1_091076_2022-03-01_final
2022-03-04 09:16:31	ga_ls8c_ard_3-2-1_089090_2022-03-03_final
2022-03-14 11:25:38	ga_ls8c_ard_3-2-1_111073_2022-03-14_final
2022-04-23 10:35:39	ga_ls8c_ard_3-2-1_103072_2022-04-23_final
2022-05-15 11:38:22	ga_ls8c_ard_3-2-1_113074_2022-05-15_final
2022-07-02 09:57:25	ga_ls8c_ard_3-2-1_097068_2022-07-02_final
2022-07-06 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-07-06_final
2022-07-06 11:17:10	ga_ls8c_ard_3-2-1_109082_2022-07-06_final
2022-07-10 10:46:51	ga_ls8c_ard_3-2-1_105068_2022-07-10_final
2022-07-16 10:10:33	ga_ls8c_ard_3-2-1_099070_2022-07-16_final
2022-07-18 11:42:17	ga_ls8c_ard_3-2-1_113083_2022-07-18_final
2022-07-24 11:02:06	ga_ls8c_ard_3-2-1_107075_2022-07-24_final
2022-08-04 09:07:35	ga_ls8c_ard_3-2-1_088082_2022-08-03_final
2022-08-09 09:28:10	ga_ls8c_ard_3-2-1_091087_2022-08-08_final
2022-08-10 10:05:02	ga_ls8c_ard_3-2-1_098071_2022-08-10_final
2022-08-11 09:16:37	ga_ls8c_ard_3-2-1_089089_2022-08-10_final
2022-08-17 10:11:39	ga_ls8c_ard_3-2-1_099072_2022-08-17_final
2022-08-21 09:52:32	ga_ls8c_ard_3-2-1_095086_2022-08-21_final
2022-09-13 09:58:47	ga_ls8c_ard_3-2-1_096086_2022-09-13_final
2022-09-27 10:05:12	ga_ls8c_ard_3-2-1_098071_2022-09-27_final
2022-10-04 10:14:56	ga_ls8c_ard_3-2-1_099080_2022-10-04_final
2022-11-04 09:32:54	ga_ls8c_ard_3-2-1_092083_2022-11-04_final
2022-11-05 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-11-05_final
2022-11-05 10:10:10	ga_ls8c_ard_3-2-1_099068_2022-11-05_final
2022-11-11 11:14:19	ga_ls8c_ard_3-2-1_109074_2022-11-11_final
2022-11-25 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-11-25_final
2022-11-29 09:27:26	ga_ls8c_ard_3-2-1_091085_2022-11-28_final
2022-11-29 09:28:38	ga_ls8c_ard_3-2-1_091088_2022-11-28_final
2022-11-30 10:07:54	ga_ls8c_ard_3-2-1_098078_2022-11-30_final
2022-12-08 10:53:44	ga_ls8c_ard_3-2-1_106069_2022-12-08_final
2022-12-08 10:54:56	ga_ls8c_ard_3-2-1_106072_2022-12-08_final
2022-12-11 11:26:13	ga_ls8c_ard_3-2-1_111073_2022-12-11_final
2023-01-11 10:40:48	ga_ls8c_ard_3-2-1_104068_2023-01-11_final
2023-02-13 11:25:58	ga_ls8c_ard_3-2-1_111073_2023-02-13_final
2023-02-15 11:14:23	ga_ls8c_ard_3-2-1_109075_2023-02-15_final
2023-02-18 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-02-18_final
2023-03-03 11:13:46	ga_ls8c_ard_3-2-1_109074_2023-03-03_final
2023-03-03 11:14:10	ga_ls8c_ard_3-2-1_109075_2023-03-03_final
2023-03-23 09:11:10	ga_ls8c_ard_3-2-1_089077_2023-03-22_final
2023-04-06 09:22:10	ga_ls8c_ard_3-2-1_091074_2023-04-05_final
2023-04-26 10:34:10	ga_ls8c_ard_3-2-1_103069_2023-04-26_final
2023-05-14 10:27:09	ga_ls8c_ard_3-2-1_101083_2023-05-14_final
2023-05-16 10:09:36	ga_ls8c_ard_3-2-1_099070_2023-05-16_final
2023-05-18 11:37:42	ga_ls8c_ard_3-2-1_113074_2023-05-18_final
2023-06-01 10:14:49	ga_ls8c_ard_3-2-1_099083_2023-06-01_final
2023-06-02 09:21:36	ga_ls8c_ard_3-2-1_090089_2023-06-01_final
2023-06-07 09:33:50	ga_ls8c_ard_3-2-1_093073_2023-06-07_final
2023-06-18 09:21:45	ga_ls8c_ard_3-2-1_090089_2023-06-17_final
2023-06-20 09:06:36	ga_ls8c_ard_3-2-1_088082_2023-06-19_final
2023-06-25 09:21:12	ga_ls8c_ard_3-2-1_091072_2023-06-24_final
2023-07-16 11:18:49	ga_ls8c_ard_3-2-1_110072_2023-07-16_final
2023-07-18 11:05:39	ga_ls8c_ard_3-2-1_108070_2023-07-18_final
2023-07-19 10:08:26	ga_ls8c_ard_3-2-1_099066_2023-07-19_final
2023-08-04 10:09:47	ga_ls8c_ard_3-2-1_099069_2023-08-04_final
2023-08-17 09:44:57	ga_ls8c_ard_3-2-1_094084_2023-08-17_final
2023-08-26 11:17:43	ga_ls8c_ard_3-2-1_109084_2023-08-26_final
2023-09-08 09:06:43	ga_ls8c_ard_3-2-1_088081_2023-09-07_final
2023-09-29 09:23:24	ga_ls8c_ard_3-2-1_091076_2023-09-28_final
2023-10-25 09:57:46	ga_ls8c_ard_3-2-1_097069_2023-10-25_final
2023-11-07 11:07:43	ga_ls8c_ard_3-2-1_108074_2023-11-07_final
2023-11-17 10:03:10	ga_ls8c_ard_3-2-1_098067_2023-11-17_final
2023-12-11 09:22:02	ga_ls8c_ard_3-2-1_090088_2023-12-10_final
2023-12-13 09:06:54	ga_ls8c_ard_3-2-1_088081_2023-12-12_final
2023-12-21 11:32:29	ga_ls8c_ard_3-2-1_112074_2023-12-21_final
2023-12-29 09:07:42	ga_ls8c_ard_3-2-1_088083_2023-12-28_final
2024-01-17 11:14:15	ga_ls8c_ard_3-2-1_109075_2024-01-17_final
2024-01-24 11:19:57	ga_ls8c_ard_3-2-1_110074_2024-01-24_final
2024-02-09 11:24:24	ga_ls8c_ard_3-2-1_110085_2024-02-09_final
2024-03-23 09:27:23	ga_ls8c_ard_3-2-1_091087_2024-03-22_nrt
2024-03-23 09:27:47	ga_ls8c_ard_3-2-1_091088_2024-03-22_nrt
2024-03-26 09:52:13	ga_ls8c_ard_3-2-1_096072_2024-03-26_nrt
2024-04-04 11:24:54	ga_ls8c_ard_3-2-1_111072_2024-04-04_nrt
2024-04-05 10:28:29	ga_ls8c_ard_3-2-1_102070_2024-04-05_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