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
2022-01-23 09:56:57	ga_ls8c_ard_3-2-1_097067_2022-01-23_final
2022-01-25 09:46:10	ga_ls8c_ard_3-2-1_095071_2022-01-25_final
2022-01-25 09:46:34	ga_ls8c_ard_3-2-1_095072_2022-01-25_final
2022-01-25 09:46:58	ga_ls8c_ard_3-2-1_095073_2022-01-25_final
2022-01-25 09:47:22	ga_ls8c_ard_3-2-1_095074_2022-01-25_final
2022-01-25 09:47:46	ga_ls8c_ard_3-2-1_095075_2022-01-25_final
2022-01-25 09:48:09	ga_ls8c_ard_3-2-1_095076_2022-01-25_final
2022-03-23 09:41:16	ga_ls8c_ard_3-2-1_094075_2022-03-23_final
2022-03-23 09:41:39	ga_ls8c_ard_3-2-1_094076_2022-03-23_final
2022-03-23 09:42:03	ga_ls8c_ard_3-2-1_094077_2022-03-23_final
2022-03-23 09:42:27	ga_ls8c_ard_3-2-1_094078_2022-03-23_final
2022-03-23 09:42:51	ga_ls8c_ard_3-2-1_094079_2022-03-23_final
2022-03-23 09:43:15	ga_ls8c_ard_3-2-1_094080_2022-03-23_final
2022-03-23 09:43:39	ga_ls8c_ard_3-2-1_094081_2022-03-23_final
2022-03-25 09:32:28	ga_ls8c_ard_3-2-1_092084_2022-03-25_final
2022-03-25 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-03-25_final
2022-03-25 09:33:16	ga_ls8c_ard_3-2-1_092086_2022-03-25_final
2022-03-25 09:33:40	ga_ls8c_ard_3-2-1_092087_2022-03-25_final
2022-03-25 09:34:04	ga_ls8c_ard_3-2-1_092088_2022-03-25_final
2022-03-25 09:34:27	ga_ls8c_ard_3-2-1_092089_2022-03-25_final
2022-03-27 09:22:28	ga_ls8c_ard_3-2-1_090090_2022-03-26_final
2022-03-27 09:22:52	ga_ls8c_ard_3-2-1_090091_2022-03-26_final
2022-03-28 09:56:32	ga_ls8c_ard_3-2-1_097067_2022-03-28_final
2022-04-03 09:27:24	ga_ls8c_ard_3-2-1_091087_2022-04-02_final
2022-04-03 09:27:48	ga_ls8c_ard_3-2-1_091088_2022-04-02_final
2022-04-03 09:28:12	ga_ls8c_ard_3-2-1_091089_2022-04-02_final
2022-04-03 09:28:36	ga_ls8c_ard_3-2-1_091090_2022-04-02_final
2022-04-06 09:51:33	ga_ls8c_ard_3-2-1_096070_2022-04-06_final
2022-04-06 09:51:57	ga_ls8c_ard_3-2-1_096071_2022-04-06_final
2022-04-06 09:52:21	ga_ls8c_ard_3-2-1_096072_2022-04-06_final
2022-04-15 09:45:51	ga_ls8c_ard_3-2-1_095071_2022-04-15_final
2022-04-15 09:46:39	ga_ls8c_ard_3-2-1_095073_2022-04-15_final
2022-04-15 09:47:02	ga_ls8c_ard_3-2-1_095074_2022-04-15_final
2022-04-15 09:47:26	ga_ls8c_ard_3-2-1_095075_2022-04-15_final
2022-04-15 09:47:50	ga_ls8c_ard_3-2-1_095076_2022-04-15_final
2022-04-22 09:51:36	ga_ls8c_ard_3-2-1_096070_2022-04-22_final
2022-04-22 09:52:00	ga_ls8c_ard_3-2-1_096071_2022-04-22_final
2022-04-22 09:52:24	ga_ls8c_ard_3-2-1_096072_2022-04-22_final
2022-04-24 09:41:13	ga_ls8c_ard_3-2-1_094075_2022-04-24_final
2022-04-24 09:41:37	ga_ls8c_ard_3-2-1_094076_2022-04-24_final
2022-04-24 09:42:01	ga_ls8c_ard_3-2-1_094077_2022-04-24_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-04-24 09:42:49	ga_ls8c_ard_3-2-1_094079_2022-04-24_final
2022-04-24 09:43:13	ga_ls8c_ard_3-2-1_094080_2022-04-24_final
2022-04-24 09:43:37	ga_ls8c_ard_3-2-1_094081_2022-04-24_final
2022-08-05 09:46:28	ga_ls8c_ard_3-2-1_095071_2022-08-05_final
2022-08-05 09:46:52	ga_ls8c_ard_3-2-1_095072_2022-08-05_final
2022-08-05 09:47:16	ga_ls8c_ard_3-2-1_095073_2022-08-05_final
2022-08-05 09:47:40	ga_ls8c_ard_3-2-1_095074_2022-08-05_final
2022-08-05 09:48:04	ga_ls8c_ard_3-2-1_095075_2022-08-05_final
2022-08-05 09:48:27	ga_ls8c_ard_3-2-1_095076_2022-08-05_final
2022-08-19 09:57:18	ga_ls8c_ard_3-2-1_097067_2022-08-19_final
2022-08-21 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-08-21_final
2022-08-21 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-08-21_final
2022-08-21 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-08-21_final
2022-08-21 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-08-21_final
2022-08-21 09:48:08	ga_ls8c_ard_3-2-1_095075_2022-08-21_final
2022-08-21 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-08-21_final
2022-08-30 09:41:57	ga_ls8c_ard_3-2-1_094075_2022-08-30_final
2022-08-30 09:42:21	ga_ls8c_ard_3-2-1_094076_2022-08-30_final
2022-08-30 09:42:45	ga_ls8c_ard_3-2-1_094077_2022-08-30_final
2022-08-30 09:43:09	ga_ls8c_ard_3-2-1_094078_2022-08-30_final
2022-08-30 09:43:33	ga_ls8c_ard_3-2-1_094079_2022-08-30_final
2022-08-30 09:43:57	ga_ls8c_ard_3-2-1_094080_2022-08-30_final
2022-08-30 09:44:21	ga_ls8c_ard_3-2-1_094081_2022-08-30_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
2022-09-01 09:35:11	ga_ls8c_ard_3-2-1_092089_2022-09-01_final
2022-09-10 09:28:16	ga_ls8c_ard_3-2-1_091087_2022-09-09_final
2022-09-10 09:28:40	ga_ls8c_ard_3-2-1_091088_2022-09-09_final
2022-09-10 09:29:04	ga_ls8c_ard_3-2-1_091089_2022-09-09_final
2022-09-10 09:29:28	ga_ls8c_ard_3-2-1_091090_2022-09-09_final
2023-05-01 09:22:10	ga_ls8c_ard_3-2-1_090090_2023-04-30_final
2023-05-01 09:22:34	ga_ls8c_ard_3-2-1_090091_2023-04-30_final
2023-05-06 09:36:39	ga_ls8c_ard_3-2-1_093080_2023-05-06_final
2023-05-06 09:37:03	ga_ls8c_ard_3-2-1_093081_2023-05-06_final
2023-05-06 09:37:27	ga_ls8c_ard_3-2-1_093082_2023-05-06_final
2023-05-06 09:37:51	ga_ls8c_ard_3-2-1_093083_2023-05-06_final
2023-05-06 09:38:15	ga_ls8c_ard_3-2-1_093084_2023-05-06_final
2023-05-06 09:38:39	ga_ls8c_ard_3-2-1_093085_2023-05-06_final
2023-05-08 09:27:03	ga_ls8c_ard_3-2-1_091087_2023-05-07_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-08 09:27:51	ga_ls8c_ard_3-2-1_091089_2023-05-07_final
2023-05-08 09:28:15	ga_ls8c_ard_3-2-1_091090_2023-05-07_final
2024-04-27 09:51:12	ga_ls8c_ard_3-2-1_096070_2024-04-27_final
2024-04-27 09:51:36	ga_ls8c_ard_3-2-1_096071_2024-04-27_final
2024-04-27 09:52:00	ga_ls8c_ard_3-2-1_096072_2024-04-27_final
2024-05-08 09:36:31	ga_ls8c_ard_3-2-1_093080_2024-05-08_final
2024-05-08 09:36:55	ga_ls8c_ard_3-2-1_093081_2024-05-08_final
2024-05-08 09:37:19	ga_ls8c_ard_3-2-1_093082_2024-05-08_final
2024-05-08 09:37:43	ga_ls8c_ard_3-2-1_093083_2024-05-08_final
2024-05-08 09:38:07	ga_ls8c_ard_3-2-1_093084_2024-05-08_final
2024-05-08 09:38:31	ga_ls8c_ard_3-2-1_093085_2024-05-08_final
2024-05-10 09:26:56	ga_ls8c_ard_3-2-1_091087_2024-05-09_final
2024-05-10 09:27:20	ga_ls8c_ard_3-2-1_091088_2024-05-09_final
2024-05-10 09:27:44	ga_ls8c_ard_3-2-1_091089_2024-05-09_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years