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

46 results

Time (local)	Label
2021-11-11 10:19:03	ga_ls9c_ard_3-2-1_100076_2021-11-11_final.stac-item
2022-01-24 09:56:03	ga_ls9c_ard_3-2-1_096080_2022-01-24_final.stac-item
2022-02-14 10:13:20	ga_ls9c_ard_3-2-1_099077_2022-02-14_final.stac-item
2022-02-17 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-03-24 11:14:05	ga_ls9c_ard_3-2-1_109075_2022-03-24_final.stac-item
2022-04-03 11:52:45	ga_ls9c_ard_3-2-1_115079_2022-04-03_final.stac-item
2022-04-16 09:40:03	ga_ls9c_ard_3-2-1_094072_2022-04-16_final.stac-item
2022-05-31 09:11:38	ga_ls9c_ard_3-2-1_089079_2022-05-30_final.stac-item
2022-06-07 09:22:13	ga_ls9c_ard_3-2-1_090090_2022-06-06_final.stac-item
2022-06-19 09:45:54	ga_ls9c_ard_3-2-1_094087_2022-06-19_final.stac-item
2022-06-22 10:10:07	ga_ls9c_ard_3-2-1_099070_2022-06-22_final.stac-item
2022-07-08 10:13:46	ga_ls9c_ard_3-2-1_099079_2022-07-08_final.stac-item
2022-09-03 11:44:52	ga_ls9c_ard_3-2-1_114074_2022-09-03_final.stac-item
2022-09-18 09:22:00	ga_ls9c_ard_3-2-1_091072_2022-09-17_final.stac-item
2022-09-28 10:04:19	ga_ls9c_ard_3-2-1_097085_2022-09-28_final.stac-item
2022-10-11 09:28:16	ga_ls9c_ard_3-2-1_092072_2022-10-10_final.stac-item
2022-10-28 10:10:22	ga_ls9c_ard_3-2-1_099069_2022-10-28_final.stac-item
2022-10-28 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-10-28_final.stac-item
2022-11-17 09:52:52	ga_ls9c_ard_3-2-1_095087_2022-11-17_final.stac-item
2022-11-29 10:10:21	ga_ls9c_ard_3-2-1_099069_2022-11-29_final.stac-item
2022-12-09 09:13:46	ga_ls9c_ard_3-2-1_089082_2022-12-08_final.stac-item
2022-12-16 09:17:09	ga_ls9c_ard_3-2-1_090075_2022-12-15_final.stac-item
2022-12-22 10:19:42	ga_ls9c_ard_3-2-1_100077_2022-12-22_final.stac-item
2022-12-24 10:03:20	ga_ls9c_ard_3-2-1_098067_2022-12-24_final.stac-item
2023-02-19 09:58:21	ga_ls9c_ard_3-2-1_097070_2023-02-19_final.stac-item
2023-02-27 09:16:23	ga_ls9c_ard_3-2-1_089089_2023-02-26_final.stac-item
2023-03-29 11:04:55	ga_ls9c_ard_3-2-1_107083_2023-03-29_final.stac-item
2023-04-13 10:19:34	ga_ls9c_ard_3-2-1_100078_2023-04-13_final.stac-item
2023-04-14 09:22:44	ga_ls9c_ard_3-2-1_091075_2023-04-13_final.stac-item
2023-04-26 11:23:54	ga_ls9c_ard_3-2-1_111069_2023-04-26_final.stac-item
2023-05-08 10:13:34	ga_ls9c_ard_3-2-1_099079_2023-05-08_final.stac-item
2023-08-03 11:58:18	ga_ls9c_ard_3-2-1_116078_2023-08-03_final.stac-item
2023-08-09 11:18:05	ga_ls9c_ard_3-2-1_110070_2023-08-09_final.stac-item
2023-09-15 09:57:15	ga_ls9c_ard_3-2-1_097068_2023-09-15_final.stac-item
2023-09-17 09:46:29	ga_ls9c_ard_3-2-1_095072_2023-09-17_final.stac-item
2023-10-25 09:10:45	ga_ls9c_ard_3-2-1_089075_2023-10-24_final.stac-item
2023-11-25 10:10:26	ga_ls9c_ard_3-2-1_098085_2023-11-25_final.stac-item
2023-11-29 09:40:08	ga_ls9c_ard_3-2-1_094071_2023-11-29_final.stac-item
2023-12-04 09:57:50	ga_ls9c_ard_3-2-1_097069_2023-12-04_final.stac-item
2023-12-27 10:04:53	ga_ls9c_ard_3-2-1_098071_2023-12-27_final.stac-item
2024-01-13 10:49:17	ga_ls9c_ard_3-2-1_105074_2024-01-13_final.stac-item
2024-01-21 11:37:54	ga_ls9c_ard_3-2-1_113072_2024-01-21_final.stac-item
2024-02-20 10:11:40	ga_ls9c_ard_3-2-1_099073_2024-02-20_final.stac-item
2024-03-24 09:17:36	ga_ls9c_ard_3-2-1_090077_2024-03-23_final.stac-item
2024-04-08 10:09:54	ga_ls9c_ard_3-2-1_099069_2024-04-08_final.stac-item
2024-04-08 10:09:54	ga_ls9c_ard_3-2-1_099069_2024-04-08_interim.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