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
2018-10-01 12:37:12	ga_ls8c_ard_3-2-1_123067_2018-10-01_final
2022-04-03 11:01:06	ga_ls8c_ard_3-2-1_107074_2022-04-03_final
2022-04-24 11:19:18	ga_ls8c_ard_3-2-1_110073_2022-04-24_final
2022-05-19 09:39:34	ga_ls8c_ard_3-2-1_093086_2022-05-19_final
2022-05-20 10:20:50	ga_ls8c_ard_3-2-1_100081_2022-05-20_final
2022-05-28 09:30:35	ga_ls8c_ard_3-2-1_092079_2022-05-28_final
2022-06-02 09:46:49	ga_ls8c_ard_3-2-1_095073_2022-06-02_final
2022-06-02 11:25:42	ga_ls8c_ard_3-2-1_111073_2022-06-02_final
2022-06-13 11:07:18	ga_ls8c_ard_3-2-1_108073_2022-06-13_final
2022-06-22 09:25:06	ga_ls8c_ard_3-2-1_091080_2022-06-21_final
2022-06-27 11:24:08	ga_ls8c_ard_3-2-1_110084_2022-06-27_final
2022-07-02 10:01:24	ga_ls8c_ard_3-2-1_097078_2022-07-02_final
2022-07-13 09:41:15	ga_ls8c_ard_3-2-1_094074_2022-07-13_final
2022-07-17 09:20:32	ga_ls8c_ard_3-2-1_090084_2022-07-16_final
2022-07-20 11:25:58	ga_ls8c_ard_3-2-1_111073_2022-07-20_final
2022-07-24 11:02:06	ga_ls8c_ard_3-2-1_107075_2022-07-24_final
2022-07-26 10:46:58	ga_ls8c_ard_3-2-1_105068_2022-07-26_final
2022-08-02 10:58:01	ga_ls8c_ard_3-2-1_106080_2022-08-02_final
2022-08-03 11:38:53	ga_ls8c_ard_3-2-1_113074_2022-08-03_final
2022-08-09 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-08-08_final
2022-08-15 10:27:36	ga_ls8c_ard_3-2-1_101081_2022-08-15_final
2022-08-16 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-08-15_final
2022-08-16 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-08-16_final
2022-08-23 09:40:10	ga_ls8c_ard_3-2-1_093086_2022-08-23_final
2022-09-06 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-09-06_final
2022-09-08 09:35:01	ga_ls8c_ard_3-2-1_093073_2022-09-08_final
2022-09-10 09:23:53	ga_ls8c_ard_3-2-1_091076_2022-09-09_final
2022-09-19 10:54:38	ga_ls8c_ard_3-2-1_106071_2022-09-19_final
2022-09-25 11:58:50	ga_ls8c_ard_3-2-1_116077_2022-09-25_final
2022-09-26 09:22:44	ga_ls8c_ard_3-2-1_091073_2022-09-25_final
2022-09-28 09:14:21	ga_ls8c_ard_3-2-1_089083_2022-09-27_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-22 09:59:21	ga_ls8c_ard_3-2-1_097072_2022-10-22_final
2022-10-26 09:35:28	ga_ls8c_ard_3-2-1_093074_2022-10-26_final
2022-10-26 11:17:32	ga_ls8c_ard_3-2-1_109082_2022-10-26_final
2022-11-10 10:30:40	ga_ls8c_ard_3-2-1_102073_2022-11-10_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-11 09:37:50	ga_ls8c_ard_3-2-1_093080_2022-11-11_final
2022-11-27 11:12:41	ga_ls8c_ard_3-2-1_109070_2022-11-27_final
2022-12-09 10:02:06	ga_ls8c_ard_3-2-1_097079_2022-12-09_final
2022-12-12 10:29:47	ga_ls8c_ard_3-2-1_102071_2022-12-12_final
2022-12-15 09:22:10	ga_ls8c_ard_3-2-1_091072_2022-12-14_final
2022-12-15 09:25:46	ga_ls8c_ard_3-2-1_091081_2022-12-14_final
2022-12-22 11:11:31	ga_ls8c_ard_3-2-1_108083_2022-12-22_final
2023-01-15 10:21:13	ga_ls8c_ard_3-2-1_100081_2023-01-15_final
2023-01-19 09:58:04	ga_ls8c_ard_3-2-1_096085_2023-01-19_final
2023-01-26 09:58:44	ga_ls8c_ard_3-2-1_097071_2023-01-26_final
2023-02-03 10:49:47	ga_ls8c_ard_3-2-1_105075_2023-02-03_final
2023-02-07 10:27:50	ga_ls8c_ard_3-2-1_101082_2023-02-07_final
2023-02-17 09:29:06	ga_ls8c_ard_3-2-1_091090_2023-02-16_final
2023-03-10 11:23:04	ga_ls8c_ard_3-2-1_110082_2023-03-10_final
2023-04-13 09:28:37	ga_ls8c_ard_3-2-1_092075_2023-04-12_final
2023-04-15 09:19:51	ga_ls8c_ard_3-2-1_090084_2023-04-14_final
2023-04-16 10:01:30	ga_ls8c_ard_3-2-1_097080_2023-04-16_final
2023-04-17 10:41:58	ga_ls8c_ard_3-2-1_104073_2023-04-17_final
2023-05-02 09:58:14	ga_ls8c_ard_3-2-1_097072_2023-05-02_final
2023-05-02 10:01:25	ga_ls8c_ard_3-2-1_097080_2023-05-02_final
2023-05-10 10:46:21	ga_ls8c_ard_3-2-1_105069_2023-05-10_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-15 09:27:08	ga_ls8c_ard_3-2-1_092072_2023-05-14_final
2023-05-29 11:22:25	ga_ls8c_ard_3-2-1_110082_2023-05-29_final
2023-06-02 10:53:18	ga_ls8c_ard_3-2-1_106071_2023-06-02_final
2023-06-09 09:22:41	ga_ls8c_ard_3-2-1_091076_2023-06-08_final
2023-06-09 11:04:22	ga_ls8c_ard_3-2-1_107083_2023-06-09_final
2023-06-10 11:44:51	ga_ls8c_ard_3-2-1_114076_2023-06-10_final
2023-06-16 09:27:19	ga_ls8c_ard_3-2-1_092072_2023-06-15_final
2023-07-05 10:03:12	ga_ls8c_ard_3-2-1_097084_2023-07-05_final
2023-07-07 09:51:16	ga_ls8c_ard_3-2-1_095085_2023-07-07_final
2023-07-18 11:07:15	ga_ls8c_ard_3-2-1_108074_2023-07-18_final
2023-08-05 10:58:14	ga_ls8c_ard_3-2-1_106082_2023-08-05_final
2023-08-08 09:51:27	ga_ls8c_ard_3-2-1_095085_2023-08-08_final
2023-08-26 11:17:43	ga_ls8c_ard_3-2-1_109084_2023-08-26_final
2023-08-29 10:03:45	ga_ls8c_ard_3-2-1_098069_2023-08-29_final
2023-09-02 11:20:18	ga_ls8c_ard_3-2-1_110075_2023-09-02_final
2023-09-14 10:05:00	ga_ls8c_ard_3-2-1_098072_2023-09-14_final
2023-09-16 09:51:51	ga_ls8c_ard_3-2-1_096070_2023-09-16_final
2023-09-18 11:23:10	ga_ls8c_ard_3-2-1_110082_2023-09-18_final
2023-09-25 09:50:53	ga_ls8c_ard_3-2-1_095083_2023-09-25_final
2023-10-25 10:01:21	ga_ls8c_ard_3-2-1_097078_2023-10-25_final
2023-10-26 10:40:38	ga_ls8c_ard_3-2-1_104068_2023-10-26_final
2023-11-03 11:35:40	ga_ls8c_ard_3-2-1_112082_2023-11-03_final
2023-11-11 10:40:58	ga_ls8c_ard_3-2-1_104069_2023-11-11_final
2023-11-25 10:55:50	ga_ls8c_ard_3-2-1_106075_2023-11-25_final
2023-11-26 10:00:12	ga_ls8c_ard_3-2-1_097075_2023-11-26_final
2023-11-27 10:41:28	ga_ls8c_ard_3-2-1_104070_2023-11-27_final
2023-12-02 11:02:21	ga_ls8c_ard_3-2-1_107076_2023-12-02_final
2023-12-05 09:57:54	ga_ls8c_ard_3-2-1_096085_2023-12-05_final
2023-12-07 11:23:35	ga_ls8c_ard_3-2-1_110083_2023-12-07_final
2023-12-09 11:10:27	ga_ls8c_ard_3-2-1_108081_2023-12-09_final
2023-12-24 10:25:42	ga_ls8c_ard_3-2-1_101077_2023-12-24_final
2024-01-18 11:58:42	ga_ls8c_ard_3-2-1_116078_2024-01-18_final
2024-01-20 10:08:14	ga_ls8c_ard_3-2-1_098080_2024-01-20_final
2024-02-02 09:36:54	ga_ls8c_ard_3-2-1_093079_2024-02-02_final
2024-02-11 09:27:58	ga_ls8c_ard_3-2-1_092072_2024-02-10_final
2024-02-18 09:34:54	ga_ls8c_ard_3-2-1_093074_2024-02-18_final
2024-02-18 11:17:47	ga_ls8c_ard_3-2-1_109084_2024-02-18_final
2024-03-11 10:34:30	ga_ls8c_ard_3-2-1_103069_2024-03-11_final
2024-03-14 11:06:59	ga_ls8c_ard_3-2-1_108073_2024-03-14_final
2024-03-20 10:28:14	ga_ls8c_ard_3-2-1_102069_2024-03-20_final
2024-03-31 10:15:07	ga_ls8c_ard_3-2-1_099083_2024-03-31_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