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

48 results

Time (local)	Label
2021-12-04 09:23:17	ga_ls9c_ard_3-2-1_091075_2021-12-03_final.stac-item
2022-01-19 09:39:29	ga_ls9c_ard_3-2-1_093085_2022-01-19_final.stac-item
2022-02-10 10:39:41	ga_ls9c_ard_3-2-1_103081_2022-02-10_final.stac-item
2022-02-22 09:26:36	ga_ls9c_ard_3-2-1_091084_2022-02-21_final.stac-item
2022-02-26 10:35:55	ga_ls9c_ard_3-2-1_103072_2022-02-26_final.stac-item
2022-04-13 09:09:59	ga_ls9c_ard_3-2-1_089074_2022-04-12_final.stac-item
2022-07-15 10:17:54	ga_ls9c_ard_3-2-1_100074_2022-07-15_final.stac-item
2022-07-29 10:28:30	ga_ls9c_ard_3-2-1_102069_2022-07-29_final.stac-item
2022-08-07 10:23:13	ga_ls9c_ard_3-2-1_101071_2022-08-07_final.stac-item
2022-08-17 09:26:41	ga_ls9c_ard_3-2-1_091084_2022-08-16_final.stac-item
2022-09-09 09:34:28	ga_ls9c_ard_3-2-1_092088_2022-09-09_final.stac-item
2022-09-20 09:11:39	ga_ls9c_ard_3-2-1_089077_2022-09-19_final.stac-item
2022-10-31 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-30_final.stac-item
2022-11-03 09:38:26	ga_ls9c_ard_3-2-1_093082_2022-11-03_final.stac-item
2022-11-21 09:23:45	ga_ls9c_ard_3-2-1_091076_2022-11-20_final.stac-item
2022-12-10 11:31:55	ga_ls9c_ard_3-2-1_112072_2022-12-10_final.stac-item
2023-01-01 10:56:26	ga_ls9c_ard_3-2-1_106076_2023-01-01_final.stac-item
2023-01-08 09:25:43	ga_ls9c_ard_3-2-1_091081_2023-01-07_final.stac-item
2023-01-11 11:36:41	ga_ls9c_ard_3-2-1_112084_2023-01-11_final.stac-item
2023-01-16 10:09:30	ga_ls9c_ard_3-2-1_099067_2023-01-16_final.stac-item
2023-01-21 10:33:56	ga_ls9c_ard_3-2-1_102082_2023-01-21_final.stac-item
2023-01-25 10:07:42	ga_ls9c_ard_3-2-1_098078_2023-01-25_final.stac-item
2023-04-05 09:34:12	ga_ls9c_ard_3-2-1_092088_2023-04-05_final.stac-item
2023-05-01 11:44:45	ga_ls9c_ard_3-2-1_114075_2023-05-01_final.stac-item
2023-05-02 09:12:37	ga_ls9c_ard_3-2-1_089081_2023-05-01_final.stac-item
2023-05-07 09:27:31	ga_ls9c_ard_3-2-1_092072_2023-05-06_final.stac-item
2023-05-09 09:21:08	ga_ls9c_ard_3-2-1_090087_2023-05-08_final.stac-item
2023-06-06 09:45:39	ga_ls9c_ard_3-2-1_094087_2023-06-06_final.stac-item
2023-06-11 09:56:33	ga_ls9c_ard_3-2-1_097068_2023-06-11_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-08-31 09:06:40	ga_ls9c_ard_3-2-1_088081_2023-08-30_final.stac-item
2023-10-31 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-10-31_final.stac-item
2023-11-03 09:06:51	ga_ls9c_ard_3-2-1_088081_2023-11-02_final.stac-item
2023-11-16 10:11:18	ga_ls9c_ard_3-2-1_099072_2023-11-16_final.stac-item
2023-11-27 09:58:05	ga_ls9c_ard_3-2-1_096085_2023-11-27_final.stac-item
2023-12-04 11:42:19	ga_ls9c_ard_3-2-1_113083_2023-12-04_final.stac-item
2023-12-05 09:06:36	ga_ls9c_ard_3-2-1_088080_2023-12-04_final.stac-item
2023-12-05 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-12-05_final.stac-item
2023-12-10 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-12-10_final.stac-item
2023-12-12 10:49:17	ga_ls9c_ard_3-2-1_105074_2023-12-12_final.stac-item
2023-12-24 09:37:11	ga_ls9c_ard_3-2-1_093079_2023-12-24_final.stac-item
2024-01-22 09:07:22	ga_ls9c_ard_3-2-1_088082_2024-01-21_final.stac-item
2024-02-12 09:23:10	ga_ls9c_ard_3-2-1_091075_2024-02-11_final.stac-item
2024-03-05 10:24:28	ga_ls9c_ard_3-2-1_101074_2024-03-05_final.stac-item
2024-03-08 09:22:52	ga_ls9c_ard_3-2-1_090090_2024-03-07_final.stac-item
2024-03-18 11:36:01	ga_ls9c_ard_3-2-1_112083_2024-03-18_final.stac-item
2024-03-20 11:19:15	ga_ls9c_ard_3-2-1_110072_2024-03-20_final.stac-item
2024-03-25 10:01:15	ga_ls9c_ard_3-2-1_097078_2024-03-25_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years