Search ga_ls9c_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

78 results

Time (local)	Label
2021-11-25 09:47:39	ga_ls9c_ard_3-2-1_095079_2021-11-25_final.stac-item
2021-12-11 11:09:28	ga_ls9c_ard_3-2-1_108078_2021-12-11_final.stac-item
2021-12-16 09:49:04	ga_ls9c_ard_3-2-1_095078_2021-12-16_final.stac-item
2021-12-27 11:09:26	ga_ls9c_ard_3-2-1_108078_2021-12-27_final.stac-item
2022-01-17 09:49:03	ga_ls9c_ard_3-2-1_095078_2022-01-17_final.stac-item
2022-02-13 11:09:21	ga_ls9c_ard_3-2-1_108078_2022-02-13_final.stac-item
2022-03-29 11:33:48	ga_ls9c_ard_3-2-1_112078_2022-03-29_final.stac-item
2022-04-18 11:08:33	ga_ls9c_ard_3-2-1_108077_2022-04-18_final.stac-item
2022-06-10 09:47:57	ga_ls9c_ard_3-2-1_095077_2022-06-10_final.stac-item
2022-06-26 09:48:17	ga_ls9c_ard_3-2-1_095077_2022-06-26_final.stac-item
2022-07-03 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-03_final.stac-item
2022-07-07 11:08:59	ga_ls9c_ard_3-2-1_108078_2022-07-07_final.stac-item
2022-07-19 11:33:20	ga_ls9c_ard_3-2-1_112077_2022-07-19_final.stac-item
2022-07-19 11:33:44	ga_ls9c_ard_3-2-1_112078_2022-07-19_final.stac-item
2022-07-25 10:58:45	ga_ls9c_ard_3-2-1_106083_2022-07-25_final.stac-item
2022-08-13 09:48:59	ga_ls9c_ard_3-2-1_095078_2022-08-13_final.stac-item
2022-08-22 09:42:51	ga_ls9c_ard_3-2-1_094078_2022-08-22_final.stac-item
2022-08-30 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-08-30_final.stac-item
2022-09-17 11:58:29	ga_ls9c_ard_3-2-1_116077_2022-09-17_final.stac-item
2022-09-30 09:48:46	ga_ls9c_ard_3-2-1_095077_2022-09-30_final.stac-item
2022-10-03 11:58:32	ga_ls9c_ard_3-2-1_116077_2022-10-03_final.stac-item
2022-10-07 09:54:32	ga_ls9c_ard_3-2-1_096076_2022-10-07_final.stac-item
2022-10-19 11:58:38	ga_ls9c_ard_3-2-1_116077_2022-10-19_final.stac-item
2022-10-27 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-10-27_final.stac-item
2022-11-04 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-11-04_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-18 10:31:44	ga_ls9c_ard_3-2-1_102076_2022-11-18_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-21 10:31:33	ga_ls9c_ard_3-2-1_102076_2023-01-21_final.stac-item
2023-02-16 11:09:35	ga_ls9c_ard_3-2-1_108078_2023-02-16_final.stac-item
2023-02-25 12:37:43	ga_ls9c_ard_3-2-1_123067_2023-02-25_final.stac-item
2023-03-04 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-03-04_final.stac-item
2023-03-16 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-03-16_final.stac-item
2023-03-25 09:48:27	ga_ls9c_ard_3-2-1_095077_2023-03-25_final.stac-item
2023-04-03 09:42:34	ga_ls9c_ard_3-2-1_094078_2023-04-03_final.stac-item
2023-04-19 09:42:28	ga_ls9c_ard_3-2-1_094078_2023-04-19_final.stac-item
2023-04-19 11:18:10	ga_ls9c_ard_3-2-1_110070_2023-04-19_final.stac-item
2023-04-21 11:08:59	ga_ls9c_ard_3-2-1_108078_2023-04-21_final.stac-item
2023-05-03 11:33:56	ga_ls9c_ard_3-2-1_112079_2023-05-03_final.stac-item
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-12 09:48:26	ga_ls9c_ard_3-2-1_095078_2023-05-12_final.stac-item
2023-05-19 11:33:02	ga_ls9c_ard_3-2-1_112077_2023-05-19_final.stac-item
2023-05-19 11:33:50	ga_ls9c_ard_3-2-1_112079_2023-05-19_final.stac-item
2023-05-28 09:49:28	ga_ls9c_ard_3-2-1_095081_2023-05-28_final.stac-item
2023-06-04 09:54:02	ga_ls9c_ard_3-2-1_096077_2023-06-04_final.stac-item
2023-06-13 09:48:09	ga_ls9c_ard_3-2-1_095078_2023-06-13_final.stac-item
2023-06-20 11:33:35	ga_ls9c_ard_3-2-1_112079_2023-06-20_final.stac-item
2023-06-22 09:41:57	ga_ls9c_ard_3-2-1_094078_2023-06-22_final.stac-item
2023-06-24 11:08:28	ga_ls9c_ard_3-2-1_108078_2023-06-24_final.stac-item
2023-07-02 11:57:40	ga_ls9c_ard_3-2-1_116077_2023-07-02_final.stac-item
2023-07-18 11:57:47	ga_ls9c_ard_3-2-1_116077_2023-07-18_final.stac-item
2023-07-22 11:33:03	ga_ls9c_ard_3-2-1_112077_2023-07-22_final.stac-item
2023-08-11 11:08:55	ga_ls9c_ard_3-2-1_108078_2023-08-11_final.stac-item
2023-08-23 11:31:43	ga_ls9c_ard_3-2-1_112073_2023-08-23_final.stac-item
2023-08-29 12:31:12	ga_ls9c_ard_3-2-1_122067_2023-08-29_final.stac-item
2023-09-08 11:34:17	ga_ls9c_ard_3-2-1_112079_2023-09-08_final.stac-item
2023-09-12 11:09:12	ga_ls9c_ard_3-2-1_108078_2023-09-12_final.stac-item
2023-09-24 11:33:30	ga_ls9c_ard_3-2-1_112077_2023-09-24_final.stac-item
2023-10-03 09:48:29	ga_ls9c_ard_3-2-1_095077_2023-10-03_final.stac-item
2023-10-10 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-10-10_final.stac-item
2023-10-12 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-12_final.stac-item
2023-10-14 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-10-14_final.stac-item
2023-10-19 09:49:03	ga_ls9c_ard_3-2-1_095078_2023-10-19_final.stac-item
2023-11-04 09:48:56	ga_ls9c_ard_3-2-1_095078_2023-11-04_final.stac-item
2023-11-04 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-11-04_final.stac-item
2023-12-01 09:30:34	ga_ls9c_ard_3-2-1_092078_2023-12-01_final.stac-item
2023-12-22 08:11:03	ga_ls9c_ard_3-2-1_079080_2023-12-21_final.stac-item
2024-01-18 11:09:25	ga_ls9c_ard_3-2-1_108078_2024-01-18_final.stac-item
2024-02-05 09:20:12	ga_ls9c_ard_3-2-1_090083_2024-02-04_final.stac-item
2024-03-11 09:48:58	ga_ls9c_ard_3-2-1_095078_2024-03-11_final.stac-item
2024-04-03 11:34:16	ga_ls9c_ard_3-2-1_112079_2024-04-03_final.stac-item
2024-04-12 09:48:20	ga_ls9c_ard_3-2-1_095077_2024-04-12_final.stac-item
2024-04-19 11:33:39	ga_ls9c_ard_3-2-1_112078_2024-04-19_final.stac-item
2024-04-19 11:34:03	ga_ls9c_ard_3-2-1_112079_2024-04-19_final.stac-item
2024-04-28 09:48:01	ga_ls9c_ard_3-2-1_095077_2024-04-28_final.stac-item
2024-04-28 11:26:54	ga_ls9c_ard_3-2-1_111077_2024-04-28_final.stac-item
2024-04-28 11:27:18	ga_ls9c_ard_3-2-1_111078_2024-04-28_final.stac-item
2024-05-05 11:33:52	ga_ls9c_ard_3-2-1_112079_2024-05-05_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 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