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

57 results

Time (local)	Label
2021-12-12 10:11:03	ga_ls9c_ard_3-2-1_099071_2021-12-12_final.stac-item
2021-12-18 09:34:43	ga_ls9c_ard_3-2-1_093073_2021-12-18_final.stac-item
2022-01-07 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-06_final.stac-item
2022-01-23 09:16:23	ga_ls9c_ard_3-2-1_089089_2022-01-22_final.stac-item
2022-01-28 09:28:56	ga_ls9c_ard_3-2-1_092074_2022-01-27_final.stac-item
2022-02-11 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-02-11_final.stac-item
2022-03-10 09:22:55	ga_ls9c_ard_3-2-1_091075_2022-03-09_final.stac-item
2022-03-26 09:24:49	ga_ls9c_ard_3-2-1_091080_2022-03-25_final.stac-item
2022-04-09 11:14:26	ga_ls9c_ard_3-2-1_109076_2022-04-09_final.stac-item
2022-05-13 09:22:06	ga_ls9c_ard_3-2-1_091074_2022-05-12_final.stac-item
2022-05-15 10:49:24	ga_ls9c_ard_3-2-1_105076_2022-05-15_final.stac-item
2022-05-30 10:06:51	ga_ls9c_ard_3-2-1_098078_2022-05-30_final.stac-item
2022-06-09 09:07:04	ga_ls9c_ard_3-2-1_088083_2022-06-08_final.stac-item
2022-06-14 09:21:17	ga_ls9c_ard_3-2-1_091072_2022-06-13_final.stac-item
2022-06-14 09:28:04	ga_ls9c_ard_3-2-1_091089_2022-06-13_final.stac-item
2022-06-19 09:45:54	ga_ls9c_ard_3-2-1_094087_2022-06-19_final.stac-item
2022-07-10 09:57:00	ga_ls9c_ard_3-2-1_097068_2022-07-10_final.stac-item
2022-07-15 10:21:53	ga_ls9c_ard_3-2-1_100084_2022-07-15_final.stac-item
2022-08-13 11:24:40	ga_ls9c_ard_3-2-1_111070_2022-08-13_final.stac-item
2022-08-17 09:22:41	ga_ls9c_ard_3-2-1_091074_2022-08-16_final.stac-item
2022-09-07 11:24:07	ga_ls9c_ard_3-2-1_110084_2022-09-07_final.stac-item
2022-09-15 10:33:33	ga_ls9c_ard_3-2-1_102081_2022-09-15_final.stac-item
2022-09-16 09:33:56	ga_ls9c_ard_3-2-1_093071_2022-09-16_final.stac-item
2022-10-13 10:56:00	ga_ls9c_ard_3-2-1_106075_2022-10-13_final.stac-item
2022-11-21 09:22:57	ga_ls9c_ard_3-2-1_091074_2022-11-20_final.stac-item
2022-11-23 09:10:59	ga_ls9c_ard_3-2-1_089075_2022-11-22_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_final.stac-item
2022-12-09 09:10:34	ga_ls9c_ard_3-2-1_089074_2022-12-08_final.stac-item
2022-12-19 09:46:26	ga_ls9c_ard_3-2-1_095071_2022-12-19_final.stac-item
2023-03-29 09:22:26	ga_ls9c_ard_3-2-1_091074_2023-03-28_final.stac-item
2023-04-14 09:22:44	ga_ls9c_ard_3-2-1_091075_2023-04-13_final.stac-item
2023-04-28 11:13:54	ga_ls9c_ard_3-2-1_109075_2023-04-28_final.stac-item
2023-05-08 10:13:34	ga_ls9c_ard_3-2-1_099079_2023-05-08_final.stac-item
2023-05-09 09:21:08	ga_ls9c_ard_3-2-1_090087_2023-05-08_final.stac-item
2023-05-16 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-05-15_final.stac-item
2023-05-30 09:33:07	ga_ls9c_ard_3-2-1_093071_2023-05-30_final.stac-item
2023-05-30 11:13:36	ga_ls9c_ard_3-2-1_109075_2023-05-30_final.stac-item
2023-06-03 09:13:10	ga_ls9c_ard_3-2-1_089083_2023-06-02_final.stac-item
2023-06-09 10:13:20	ga_ls9c_ard_3-2-1_099079_2023-06-09_final.stac-item
2023-06-12 09:06:54	ga_ls9c_ard_3-2-1_088083_2023-06-11_final.stac-item
2023-06-17 09:27:47	ga_ls9c_ard_3-2-1_091089_2023-06-16_final.stac-item
2023-07-01 11:14:00	ga_ls9c_ard_3-2-1_109076_2023-07-01_final.stac-item
2023-07-27 10:14:44	ga_ls9c_ard_3-2-1_099082_2023-07-27_final.stac-item
2023-09-05 09:22:04	ga_ls9c_ard_3-2-1_091073_2023-09-04_final.stac-item
2023-09-24 11:31:31	ga_ls9c_ard_3-2-1_112072_2023-09-24_final.stac-item
2023-10-01 09:57:37	ga_ls9c_ard_3-2-1_097069_2023-10-01_final.stac-item
2023-10-07 09:23:00	ga_ls9c_ard_3-2-1_091075_2023-10-06_final.stac-item
2023-11-08 09:21:51	ga_ls9c_ard_3-2-1_091072_2023-11-07_final.stac-item
2023-12-02 10:09:02	ga_ls9c_ard_3-2-1_099066_2023-12-02_final.stac-item
2023-12-02 10:13:25	ga_ls9c_ard_3-2-1_099077_2023-12-02_final.stac-item
2023-12-31 09:40:08	ga_ls9c_ard_3-2-1_094071_2023-12-31_final.stac-item
2024-01-07 09:46:14	ga_ls9c_ard_3-2-1_095071_2024-01-07_final.stac-item
2024-01-21 09:57:01	ga_ls9c_ard_3-2-1_097067_2024-01-21_final.stac-item
2024-02-20 10:13:40	ga_ls9c_ard_3-2-1_099078_2024-02-20_final.stac-item
2024-03-01 10:47:10	ga_ls9c_ard_3-2-1_105069_2024-03-01_final.stac-item
2024-03-08 10:53:46	ga_ls9c_ard_3-2-1_106070_2024-03-08_final.stac-item
2024-05-15 10:27:35	ga_ls9c_ard_3-2-1_102068_2024-05-15_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