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
2018-02-13 09:56:35	ga_ls8c_ard_3-0-0_097067_2018-02-13_final
2018-02-15 09:45:49	ga_ls8c_ard_3-0-0_095071_2018-02-15_final
2018-02-15 09:46:13	ga_ls8c_ard_3-0-0_095072_2018-02-15_final
2018-02-15 09:46:37	ga_ls8c_ard_3-0-0_095073_2018-02-15_final
2018-02-15 09:47:01	ga_ls8c_ard_3-0-0_095074_2018-02-15_final
2018-02-15 09:47:24	ga_ls8c_ard_3-0-0_095075_2018-02-15_final
2018-02-15 09:47:48	ga_ls8c_ard_3-0-0_095076_2018-02-15_final
2018-03-03 09:45:41	ga_ls8c_ard_3-0-0_095071_2018-03-03_final
2018-03-03 09:46:05	ga_ls8c_ard_3-0-0_095072_2018-03-03_final
2018-03-03 09:46:29	ga_ls8c_ard_3-0-0_095073_2018-03-03_final
2018-03-03 09:46:53	ga_ls8c_ard_3-0-0_095074_2018-03-03_final
2018-03-03 09:47:17	ga_ls8c_ard_3-0-0_095075_2018-03-03_final
2018-03-03 09:47:41	ga_ls8c_ard_3-0-0_095076_2018-03-03_final
2018-03-10 09:50:12	ga_ls8c_ard_3-0-0_096067_2018-03-10_final
2018-03-10 09:50:36	ga_ls8c_ard_3-0-0_096068_2018-03-10_final
2018-03-10 09:51:00	ga_ls8c_ard_3-0-0_096069_2018-03-10_final
2018-03-10 09:51:24	ga_ls8c_ard_3-0-0_096070_2018-03-10_final
2018-03-10 09:51:48	ga_ls8c_ard_3-0-0_096071_2018-03-10_final
2018-03-16 09:22:15	ga_ls8c_ard_3-0-0_090090_2018-03-15_final
2018-03-16 09:22:39	ga_ls8c_ard_3-0-0_090091_2018-03-15_final
2018-03-17 09:56:19	ga_ls8c_ard_3-0-0_097067_2018-03-17_final
2018-04-17 09:21:59	ga_ls8c_ard_3-0-0_090090_2018-04-16_final
2018-04-17 09:22:23	ga_ls8c_ard_3-0-0_090091_2018-04-16_final
2018-05-29 09:49:25	ga_ls8c_ard_3-0-0_096067_2018-05-29_final
2018-05-29 09:49:49	ga_ls8c_ard_3-0-0_096068_2018-05-29_final
2018-05-29 09:50:13	ga_ls8c_ard_3-0-0_096069_2018-05-29_final
2018-05-29 09:50:37	ga_ls8c_ard_3-0-0_096070_2018-05-29_final
2018-05-29 09:51:01	ga_ls8c_ard_3-0-0_096071_2018-05-29_final
2018-06-07 09:44:48	ga_ls8c_ard_3-0-0_095071_2018-06-07_final
2018-06-07 09:45:12	ga_ls8c_ard_3-0-0_095072_2018-06-07_final
2018-06-07 09:45:36	ga_ls8c_ard_3-0-0_095073_2018-06-07_final
2018-06-07 09:45:59	ga_ls8c_ard_3-0-0_095074_2018-06-07_final
2018-06-07 09:46:23	ga_ls8c_ard_3-0-0_095075_2018-06-07_final
2018-06-07 09:46:47	ga_ls8c_ard_3-0-0_095076_2018-06-07_final
2018-06-20 09:21:38	ga_ls8c_ard_3-0-0_090090_2018-06-19_final
2018-06-20 09:22:02	ga_ls8c_ard_3-0-0_090091_2018-06-19_final
2018-07-06 09:21:47	ga_ls8c_ard_3-0-0_090090_2018-07-05_final
2018-07-06 09:22:11	ga_ls8c_ard_3-0-0_090091_2018-07-05_final
2022-08-09 09:28:10	ga_ls8c_ard_3-2-1_091087_2022-08-08_final
2022-08-09 09:28:34	ga_ls8c_ard_3-2-1_091088_2022-08-08_final
2022-08-09 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-08-08_final
2022-08-09 09:29:21	ga_ls8c_ard_3-2-1_091090_2022-08-08_final
2022-08-16 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-08-16_final
2022-08-16 09:33:11	ga_ls8c_ard_3-2-1_092084_2022-08-16_final
2022-08-16 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-08-16_final
2022-08-16 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-08-16_final
2022-08-16 09:34:22	ga_ls8c_ard_3-2-1_092087_2022-08-16_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-09-01 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-09-01_final
2022-09-01 09:33:11	ga_ls8c_ard_3-2-1_092084_2022-09-01_final
2022-09-01 09:33:35	ga_ls8c_ard_3-2-1_092085_2022-09-01_final
2022-09-01 09:33:59	ga_ls8c_ard_3-2-1_092086_2022-09-01_final
2022-09-01 09:34:23	ga_ls8c_ard_3-2-1_092087_2022-09-01_final
2022-09-01 09:34:47	ga_ls8c_ard_3-2-1_092088_2022-09-01_final
2022-09-03 09:23:13	ga_ls8c_ard_3-2-1_090090_2022-09-02_final
2022-09-03 09:23:37	ga_ls8c_ard_3-2-1_090091_2022-09-02_final
2022-10-26 09:37:27	ga_ls8c_ard_3-2-1_093079_2022-10-26_final
2022-10-26 09:37:51	ga_ls8c_ard_3-2-1_093080_2022-10-26_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-10-26 09:38:39	ga_ls8c_ard_3-2-1_093082_2022-10-26_final
2022-10-26 09:39:03	ga_ls8c_ard_3-2-1_093083_2022-10-26_final
2022-10-26 09:39:27	ga_ls8c_ard_3-2-1_093084_2022-10-26_final
2022-10-26 09:39:51	ga_ls8c_ard_3-2-1_093085_2022-10-26_final
2022-10-28 09:28:18	ga_ls8c_ard_3-2-1_091087_2022-10-27_final
2022-10-28 09:28:42	ga_ls8c_ard_3-2-1_091088_2022-10-27_final
2022-10-28 09:29:06	ga_ls8c_ard_3-2-1_091089_2022-10-27_final
2022-10-28 09:29:30	ga_ls8c_ard_3-2-1_091090_2022-10-27_final
2022-12-31 09:28:05	ga_ls8c_ard_3-2-1_091087_2022-12-30_final
2022-12-31 09:28:29	ga_ls8c_ard_3-2-1_091088_2022-12-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2022-12-31 09:29:17	ga_ls8c_ard_3-2-1_091090_2022-12-30_final
2023-01-03 09:52:12	ga_ls8c_ard_3-2-1_096070_2023-01-03_final
2023-01-03 09:52:36	ga_ls8c_ard_3-2-1_096071_2023-01-03_final
2023-01-05 09:41:50	ga_ls8c_ard_3-2-1_094075_2023-01-05_final
2023-01-05 09:42:14	ga_ls8c_ard_3-2-1_094076_2023-01-05_final
2023-01-05 09:42:38	ga_ls8c_ard_3-2-1_094077_2023-01-05_final
2023-01-05 09:43:02	ga_ls8c_ard_3-2-1_094078_2023-01-05_final
2023-01-05 09:43:26	ga_ls8c_ard_3-2-1_094079_2023-01-05_final
2023-01-05 09:43:50	ga_ls8c_ard_3-2-1_094080_2023-01-05_final
2023-01-05 09:44:14	ga_ls8c_ard_3-2-1_094081_2023-01-05_final
2023-01-07 09:32:39	ga_ls8c_ard_3-2-1_092083_2023-01-07_final
2023-01-07 09:33:03	ga_ls8c_ard_3-2-1_092084_2023-01-07_final
2023-01-07 09:33:27	ga_ls8c_ard_3-2-1_092085_2023-01-07_final
2023-01-07 09:33:51	ga_ls8c_ard_3-2-1_092086_2023-01-07_final
2023-01-07 09:34:15	ga_ls8c_ard_3-2-1_092087_2023-01-07_final
2023-01-07 09:34:39	ga_ls8c_ard_3-2-1_092088_2023-01-07_final
2024-03-05 09:36:44	ga_ls8c_ard_3-2-1_093079_2024-03-05_final
2024-03-05 09:37:08	ga_ls8c_ard_3-2-1_093080_2024-03-05_final
2024-03-05 09:37:32	ga_ls8c_ard_3-2-1_093081_2024-03-05_final
2024-03-05 09:37:56	ga_ls8c_ard_3-2-1_093082_2024-03-05_final
2024-03-05 09:38:20	ga_ls8c_ard_3-2-1_093083_2024-03-05_final
2024-03-05 09:38:44	ga_ls8c_ard_3-2-1_093084_2024-03-05_final
2024-03-05 09:39:08	ga_ls8c_ard_3-2-1_093085_2024-03-05_final
2024-03-07 09:27:32	ga_ls8c_ard_3-2-1_091087_2024-03-06_final
2024-03-07 09:27:56	ga_ls8c_ard_3-2-1_091088_2024-03-06_final
2024-03-07 09:28:20	ga_ls8c_ard_3-2-1_091089_2024-03-06_final
2024-03-07 09:28:44	ga_ls8c_ard_3-2-1_091090_2024-03-06_final
2024-04-04 09:46:49	ga_ls8c_ard_3-2-1_095074_2024-04-04_final
2024-04-08 09:27:16	ga_ls8c_ard_3-2-1_091087_2024-04-07_nrt
2024-04-08 09:27:40	ga_ls8c_ard_3-2-1_091088_2024-04-07_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years