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

56 results

Time (local)	Label
2022-01-13 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-01-13_final.stac-item
2022-01-14 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-01-13_final.stac-item
2022-02-09 11:32:07	ga_ls9c_ard_3-2-1_112073_2022-02-09_final.stac-item
2022-02-25 09:52:16	ga_ls9c_ard_3-2-1_096071_2022-02-25_final.stac-item
2022-03-02 10:08:45	ga_ls9c_ard_3-2-1_099066_2022-03-02_final.stac-item
2022-04-13 09:12:47	ga_ls9c_ard_3-2-1_089081_2022-04-12_final.stac-item
2022-04-13 10:49:40	ga_ls9c_ard_3-2-1_105076_2022-04-13_final.stac-item
2022-04-15 10:34:06	ga_ls9c_ard_3-2-1_103068_2022-04-15_final.stac-item
2022-05-05 10:09:38	ga_ls9c_ard_3-2-1_099069_2022-05-05_final.stac-item
2022-05-27 09:39:32	ga_ls9c_ard_3-2-1_093087_2022-05-27_final.stac-item
2022-06-19 09:39:55	ga_ls9c_ard_3-2-1_094072_2022-06-19_final.stac-item
2022-07-09 09:20:56	ga_ls9c_ard_3-2-1_090086_2022-07-08_final.stac-item
2022-07-15 10:19:30	ga_ls9c_ard_3-2-1_100078_2022-07-15_final.stac-item
2022-08-08 09:35:11	ga_ls9c_ard_3-2-1_092090_2022-08-08_final.stac-item
2022-09-01 10:18:44	ga_ls9c_ard_3-2-1_100075_2022-09-01_final.stac-item
2022-09-10 10:13:21	ga_ls9c_ard_3-2-1_099077_2022-09-10_final.stac-item
2022-09-26 10:09:29	ga_ls9c_ard_3-2-1_099067_2022-09-26_final.stac-item
2022-09-26 10:10:41	ga_ls9c_ard_3-2-1_099070_2022-09-26_final.stac-item
2022-09-27 09:21:03	ga_ls9c_ard_3-2-1_090085_2022-09-26_final.stac-item
2022-09-27 09:22:39	ga_ls9c_ard_3-2-1_090089_2022-09-26_final.stac-item
2022-10-19 11:58:14	ga_ls9c_ard_3-2-1_116076_2022-10-19_final.stac-item
2022-10-29 09:21:56	ga_ls9c_ard_3-2-1_090087_2022-10-28_final.stac-item
2022-11-28 09:34:17	ga_ls9c_ard_3-2-1_092087_2022-11-28_final.stac-item
2022-11-30 10:59:11	ga_ls9c_ard_3-2-1_106083_2022-11-30_final.stac-item
2022-12-10 11:32:19	ga_ls9c_ard_3-2-1_112073_2022-12-10_final.stac-item
2023-01-20 11:24:47	ga_ls9c_ard_3-2-1_111070_2023-01-20_final.stac-item
2023-01-25 10:04:31	ga_ls9c_ard_3-2-1_098070_2023-01-25_final.stac-item
2023-02-01 10:10:24	ga_ls9c_ard_3-2-1_099069_2023-02-01_final.stac-item
2023-02-13 10:35:08	ga_ls9c_ard_3-2-1_103069_2023-02-13_final.stac-item
2023-02-25 09:23:09	ga_ls9c_ard_3-2-1_091075_2023-02-24_final.stac-item
2023-03-07 09:56:57	ga_ls9c_ard_3-2-1_097067_2023-03-07_final.stac-item
2023-04-19 11:17:46	ga_ls9c_ard_3-2-1_110069_2023-04-19_final.stac-item
2023-05-10 11:41:41	ga_ls9c_ard_3-2-1_113083_2023-05-10_final.stac-item
2023-06-09 10:09:44	ga_ls9c_ard_3-2-1_099070_2023-06-09_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-11 11:41:49	ga_ls9c_ard_3-2-1_113084_2023-06-11_final.stac-item
2023-06-17 09:21:48	ga_ls9c_ard_3-2-1_091074_2023-06-16_final.stac-item
2023-07-15 09:45:36	ga_ls9c_ard_3-2-1_095071_2023-07-15_final.stac-item
2023-08-14 09:57:20	ga_ls9c_ard_3-2-1_097069_2023-08-14_final.stac-item
2023-08-18 09:33:48	ga_ls9c_ard_3-2-1_093072_2023-08-18_final.stac-item
2023-08-22 10:49:38	ga_ls9c_ard_3-2-1_105076_2023-08-22_final.stac-item
2023-08-28 10:10:14	ga_ls9c_ard_3-2-1_099070_2023-08-28_final.stac-item
2023-09-04 10:19:40	ga_ls9c_ard_3-2-1_100078_2023-09-04_final.stac-item
2023-09-06 10:03:45	ga_ls9c_ard_3-2-1_098069_2023-09-06_final.stac-item
2023-09-06 11:47:25	ga_ls9c_ard_3-2-1_114081_2023-09-06_final.stac-item
2023-10-02 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-10-01_final.stac-item
2023-11-27 11:31:47	ga_ls9c_ard_3-2-1_112072_2023-11-27_final.stac-item
2023-12-05 09:07:00	ga_ls9c_ard_3-2-1_088081_2023-12-04_final.stac-item
2024-01-02 09:29:44	ga_ls9c_ard_3-2-1_092076_2024-01-01_final.stac-item
2024-01-24 10:33:27	ga_ls9c_ard_3-2-1_102081_2024-01-24_final.stac-item
2024-02-17 09:40:26	ga_ls9c_ard_3-2-1_094072_2024-02-17_final.stac-item
2024-02-26 09:34:57	ga_ls9c_ard_3-2-1_093074_2024-02-26_final.stac-item
2024-04-01 10:07:45	ga_ls9c_ard_3-2-1_098079_2024-04-01_final.stac-item
2024-04-02 10:48:37	ga_ls9c_ard_3-2-1_105073_2024-04-02_final.stac-item
2024-04-08 10:15:53	ga_ls9c_ard_3-2-1_099084_2024-04-08_final.stac-item
2024-04-14 09:34:21	ga_ls9c_ard_3-2-1_093073_2024-04-14_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