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

43 results

Time (local)	Label
2021-11-08 11:38:53	ga_ls9c_ard_3-2-1_113082_2021-11-08_final.stac-item
2022-02-11 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-02-11_final.stac-item
2022-02-17 09:06:55	ga_ls9c_ard_3-2-1_088081_2022-02-16_final.stac-item
2022-03-01 09:28:41	ga_ls9c_ard_3-2-1_092074_2022-02-28_final.stac-item
2022-04-21 10:03:43	ga_ls9c_ard_3-2-1_097085_2022-04-21_final.stac-item
2022-04-30 09:57:31	ga_ls9c_ard_3-2-1_096085_2022-04-30_final.stac-item
2022-06-30 11:03:38	ga_ls9c_ard_3-2-1_107080_2022-06-30_final.stac-item
2022-07-21 11:19:25	ga_ls9c_ard_3-2-1_110073_2022-07-21_final.stac-item
2022-07-25 09:21:28	ga_ls9c_ard_3-2-1_090087_2022-07-24_final.stac-item
2022-08-01 11:01:50	ga_ls9c_ard_3-2-1_107075_2022-08-01_final.stac-item
2022-08-23 10:27:18	ga_ls9c_ard_3-2-1_101081_2022-08-23_final.stac-item
2022-09-02 11:00:00	ga_ls9c_ard_3-2-1_107070_2022-09-02_final.stac-item
2022-09-24 10:26:38	ga_ls9c_ard_3-2-1_101079_2022-09-24_final.stac-item
2022-09-26 10:14:40	ga_ls9c_ard_3-2-1_099080_2022-09-26_final.stac-item
2022-11-12 09:33:07	ga_ls9c_ard_3-2-1_092084_2022-11-12_final.stac-item
2022-11-26 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-11-26_final.stac-item
2022-11-28 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-11-28_final.stac-item
2022-12-03 09:46:49	ga_ls9c_ard_3-2-1_095072_2022-12-03_final.stac-item
2022-12-19 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-12-19_final.stac-item
2022-12-21 09:40:27	ga_ls9c_ard_3-2-1_093087_2022-12-21_final.stac-item
2022-12-25 09:12:31	ga_ls9c_ard_3-2-1_089079_2022-12-24_final.stac-item
2023-02-18 10:55:11	ga_ls9c_ard_3-2-1_106073_2023-02-18_final.stac-item
2023-03-08 10:41:24	ga_ls9c_ard_3-2-1_104070_2023-03-08_final.stac-item
2023-04-14 09:22:44	ga_ls9c_ard_3-2-1_091075_2023-04-13_final.stac-item
2023-05-28 09:46:17	ga_ls9c_ard_3-2-1_095073_2023-05-28_final.stac-item
2023-08-28 11:52:19	ga_ls9c_ard_3-2-1_115078_2023-08-28_final.stac-item
2023-09-12 09:33:55	ga_ls9c_ard_3-2-1_092087_2023-09-12_final.stac-item
2023-09-16 09:07:13	ga_ls9c_ard_3-2-1_088082_2023-09-15_final.stac-item
2023-10-03 11:24:10	ga_ls9c_ard_3-2-1_111069_2023-10-03_final.stac-item
2023-10-04 10:28:58	ga_ls9c_ard_3-2-1_102070_2023-10-04_final.stac-item
2023-10-05 11:14:38	ga_ls9c_ard_3-2-1_109076_2023-10-05_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-10-25 09:14:45	ga_ls9c_ard_3-2-1_089085_2023-10-24_final.stac-item
2023-10-28 09:40:02	ga_ls9c_ard_3-2-1_094071_2023-10-28_final.stac-item
2023-11-02 10:04:05	ga_ls9c_ard_3-2-1_097085_2023-11-02_final.stac-item
2023-11-10 09:14:17	ga_ls9c_ard_3-2-1_089084_2023-11-09_final.stac-item
2023-11-20 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-11-20_final.stac-item
2023-12-02 10:15:49	ga_ls9c_ard_3-2-1_099083_2023-12-02_final.stac-item
2023-12-10 11:05:36	ga_ls9c_ard_3-2-1_107084_2023-12-10_final.stac-item
2023-12-13 11:36:33	ga_ls9c_ard_3-2-1_112084_2023-12-13_final.stac-item
2024-01-11 09:29:08	ga_ls9c_ard_3-2-1_091090_2024-01-10_final.stac-item
2024-03-25 10:01:15	ga_ls9c_ard_3-2-1_097078_2024-03-25_final.stac-item
2024-04-26 09:58:23	ga_ls9c_ard_3-2-1_097072_2024-04-26_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