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

66 results

Time (local)	Label
2021-11-13 09:57:55	ga_ls9c_ard_3-2-1_097070_2021-11-13_final.stac-item
2021-12-04 09:26:53	ga_ls9c_ard_3-2-1_091084_2021-12-03_final.stac-item
2021-12-28 10:16:36	ga_ls9c_ard_3-2-1_099085_2021-12-28_final.stac-item
2022-01-05 09:27:09	ga_ls9c_ard_3-2-1_091085_2022-01-04_final.stac-item
2022-01-20 10:21:33	ga_ls9c_ard_3-2-1_100082_2022-01-20_final.stac-item
2022-02-18 11:26:15	ga_ls9c_ard_3-2-1_111074_2022-02-18_final.stac-item
2022-03-03 10:53:12	ga_ls9c_ard_3-2-1_106069_2022-03-03_final.stac-item
2022-03-10 09:21:43	ga_ls9c_ard_3-2-1_091072_2022-03-09_final.stac-item
2022-04-19 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-04-19_final.stac-item
2022-04-29 10:46:22	ga_ls9c_ard_3-2-1_105068_2022-04-29_final.stac-item
2022-05-14 11:46:38	ga_ls9c_ard_3-2-1_114080_2022-05-14_final.stac-item
2022-05-27 09:39:08	ga_ls9c_ard_3-2-1_093086_2022-05-27_final.stac-item
2022-07-01 10:03:13	ga_ls9c_ard_3-2-1_098068_2022-07-01_final.stac-item
2022-08-02 10:04:13	ga_ls9c_ard_3-2-1_098070_2022-08-02_final.stac-item
2022-09-02 09:26:18	ga_ls9c_ard_3-2-1_091083_2022-09-01_final.stac-item
2022-09-02 09:27:30	ga_ls9c_ard_3-2-1_091086_2022-09-01_final.stac-item
2022-09-07 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-09-07_final.stac-item
2022-09-16 11:12:02	ga_ls9c_ard_3-2-1_109069_2022-09-16_final.stac-item
2022-10-11 09:34:15	ga_ls9c_ard_3-2-1_092087_2022-10-11_final.stac-item
2022-10-25 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-10-25_final.stac-item
2022-11-05 09:23:17	ga_ls9c_ard_3-2-1_091075_2022-11-04_final.stac-item
2022-11-12 09:29:08	ga_ls9c_ard_3-2-1_092074_2022-11-11_final.stac-item
2022-11-22 10:10:36	ga_ls9c_ard_3-2-1_098085_2022-11-22_final.stac-item
2022-11-30 10:53:36	ga_ls9c_ard_3-2-1_106069_2022-11-30_final.stac-item
2022-12-01 09:57:58	ga_ls9c_ard_3-2-1_097069_2022-12-01_final.stac-item
2022-12-28 09:46:14	ga_ls9c_ard_3-2-1_094086_2022-12-28_final.stac-item
2023-01-01 09:17:33	ga_ls9c_ard_3-2-1_090076_2022-12-31_final.stac-item
2023-02-01 11:53:16	ga_ls9c_ard_3-2-1_115079_2023-02-01_final.stac-item
2023-02-09 11:01:05	ga_ls9c_ard_3-2-1_107072_2023-02-09_final.stac-item
2023-02-20 09:05:06	ga_ls9c_ard_3-2-1_088076_2023-02-19_interim.stac-item
2023-03-16 11:32:25	ga_ls9c_ard_3-2-1_112074_2023-03-16_final.stac-item
2023-03-23 10:01:39	ga_ls9c_ard_3-2-1_097079_2023-03-23_final.stac-item
2023-03-25 11:28:08	ga_ls9c_ard_3-2-1_111079_2023-03-25_final.stac-item
2023-03-31 10:49:21	ga_ls9c_ard_3-2-1_105075_2023-03-31_final.stac-item
2023-05-05 09:39:52	ga_ls9c_ard_3-2-1_094072_2023-05-05_final.stac-item
2023-05-12 09:51:38	ga_ls9c_ard_3-2-1_095086_2023-05-12_final.stac-item
2023-05-25 09:16:10	ga_ls9c_ard_3-2-1_090075_2023-05-24_final.stac-item
2023-06-08 09:28:05	ga_ls9c_ard_3-2-1_092074_2023-06-07_final.stac-item
2023-06-17 09:28:11	ga_ls9c_ard_3-2-1_091090_2023-06-16_final.stac-item
2023-06-27 09:57:19	ga_ls9c_ard_3-2-1_097070_2023-06-27_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-23 10:35:26	ga_ls9c_ard_3-2-1_103072_2023-07-23_final.stac-item
2023-07-29 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-07-29_final.stac-item
2023-08-03 11:57:55	ga_ls9c_ard_3-2-1_116077_2023-08-03_final.stac-item
2023-08-12 11:51:47	ga_ls9c_ard_3-2-1_115077_2023-08-12_final.stac-item
2023-10-09 10:49:56	ga_ls9c_ard_3-2-1_105076_2023-10-09_final.stac-item
2023-11-03 10:42:32	ga_ls9c_ard_3-2-1_104073_2023-11-03_final.stac-item
2023-11-04 09:46:32	ga_ls9c_ard_3-2-1_095072_2023-11-04_final.stac-item
2023-12-06 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-12-06_final.stac-item
2023-12-08 09:34:16	ga_ls9c_ard_3-2-1_093072_2023-12-08_final.stac-item
2024-01-13 09:11:36	ga_ls9c_ard_3-2-1_089077_2024-01-12_final.stac-item
2024-02-04 10:09:26	ga_ls9c_ard_3-2-1_099067_2024-02-04_final.stac-item
2024-02-05 10:54:42	ga_ls9c_ard_3-2-1_106072_2024-02-05_final.stac-item
2024-02-06 09:58:17	ga_ls9c_ard_3-2-1_097070_2024-02-06_final.stac-item
2024-02-06 11:41:33	ga_ls9c_ard_3-2-1_113081_2024-02-06_final.stac-item
2024-02-10 09:35:09	ga_ls9c_ard_3-2-1_093074_2024-02-10_final.stac-item
2024-02-13 10:09:37	ga_ls9c_ard_3-2-1_098083_2024-02-13_final.stac-item
2024-02-13 11:47:42	ga_ls9c_ard_3-2-1_114081_2024-02-13_final.stac-item
2024-02-15 11:32:31	ga_ls9c_ard_3-2-1_112074_2024-02-15_final.stac-item
2024-02-28 09:22:37	ga_ls9c_ard_3-2-1_091074_2024-02-27_final.stac-item
2024-03-06 09:28:03	ga_ls9c_ard_3-2-1_092072_2024-03-05_final.stac-item
2024-03-16 10:07:30	ga_ls9c_ard_3-2-1_098078_2024-03-16_final.stac-item
2024-03-17 10:47:34	ga_ls9c_ard_3-2-1_105070_2024-03-17_final.stac-item
2024-05-02 09:22:05	ga_ls9c_ard_3-2-1_091074_2024-05-01_final.stac-item
2024-05-03 11:47:01	ga_ls9c_ard_3-2-1_114081_2024-05-03_final.stac-item
2024-05-09 09:29:04	ga_ls9c_ard_3-2-1_092076_2024-05-08_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