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

61 results

Time (local)	Label
2021-11-23 11:44:17	ga_ls9c_ard_3-2-1_114077_2021-11-23_final.stac-item
2021-12-21 10:10:01	ga_ls9c_ard_3-2-1_098084_2021-12-21_final.stac-item
2022-01-05 09:23:57	ga_ls9c_ard_3-2-1_091077_2022-01-04_final.stac-item
2022-01-19 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-01-19_final.stac-item
2022-01-21 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-01-20_final.stac-item
2022-01-24 09:58:26	ga_ls9c_ard_3-2-1_096086_2022-01-24_final.stac-item
2022-01-24 11:36:32	ga_ls9c_ard_3-2-1_112084_2022-01-24_final.stac-item
2022-01-28 11:08:13	ga_ls9c_ard_3-2-1_108075_2022-01-28_final.stac-item
2022-04-07 11:24:01	ga_ls9c_ard_3-2-1_111069_2022-04-07_final.stac-item
2022-04-13 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-04-13_final.stac-item
2022-04-28 10:03:30	ga_ls9c_ard_3-2-1_098069_2022-04-28_final.stac-item
2022-05-09 09:51:16	ga_ls9c_ard_3-2-1_095085_2022-05-09_final.stac-item
2022-07-26 09:57:33	ga_ls9c_ard_3-2-1_097069_2022-07-26_final.stac-item
2022-08-12 10:45:48	ga_ls9c_ard_3-2-1_104081_2022-08-12_final.stac-item
2022-08-15 09:39:26	ga_ls9c_ard_3-2-1_093085_2022-08-15_final.stac-item
2022-08-22 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-08-22_final.stac-item
2022-09-03 10:10:22	ga_ls9c_ard_3-2-1_098085_2022-09-03_final.stac-item
2022-09-13 10:45:53	ga_ls9c_ard_3-2-1_104081_2022-09-13_final.stac-item
2022-10-09 09:46:35	ga_ls9c_ard_3-2-1_094087_2022-10-09_final.stac-item
2022-10-29 10:56:25	ga_ls9c_ard_3-2-1_106076_2022-10-29_final.stac-item
2022-11-15 10:04:01	ga_ls9c_ard_3-2-1_097084_2022-11-15_final.stac-item
2022-11-15 10:04:25	ga_ls9c_ard_3-2-1_097085_2022-11-15_final.stac-item
2022-11-19 09:35:19	ga_ls9c_ard_3-2-1_093074_2022-11-19_final.stac-item
2022-11-20 11:58:15	ga_ls9c_ard_3-2-1_116076_2022-11-20_final.stac-item
2022-11-26 11:18:45	ga_ls9c_ard_3-2-1_110070_2022-11-26_final.stac-item
2023-01-10 09:10:33	ga_ls9c_ard_3-2-1_089074_2023-01-09_final.stac-item
2023-01-12 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-12_final.stac-item
2023-02-05 09:52:05	ga_ls9c_ard_3-2-1_095085_2023-02-05_final.stac-item
2023-02-06 10:28:34	ga_ls9c_ard_3-2-1_102068_2023-02-06_final.stac-item
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final.stac-item
2023-02-23 09:39:31	ga_ls9c_ard_3-2-1_093085_2023-02-23_final.stac-item
2023-03-04 09:34:05	ga_ls9c_ard_3-2-1_092087_2023-03-04_final.stac-item
2023-03-10 10:28:12	ga_ls9c_ard_3-2-1_102068_2023-03-10_final.stac-item
2023-03-23 10:03:38	ga_ls9c_ard_3-2-1_097084_2023-03-23_final.stac-item
2023-03-31 10:46:58	ga_ls9c_ard_3-2-1_105069_2023-03-31_final.stac-item
2023-04-03 11:20:40	ga_ls9c_ard_3-2-1_110076_2023-04-03_final.stac-item
2023-05-16 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-05-16_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-05-28 11:23:34	ga_ls9c_ard_3-2-1_111069_2023-05-28_final.stac-item
2023-06-03 09:13:10	ga_ls9c_ard_3-2-1_089083_2023-06-02_final.stac-item
2023-06-17 11:00:41	ga_ls9c_ard_3-2-1_107074_2023-06-17_final.stac-item
2023-06-22 11:18:02	ga_ls9c_ard_3-2-1_110071_2023-06-22_final.stac-item
2023-06-29 09:45:25	ga_ls9c_ard_3-2-1_095071_2023-06-29_final.stac-item
2023-07-11 10:12:42	ga_ls9c_ard_3-2-1_099077_2023-07-11_final.stac-item
2023-07-21 09:11:19	ga_ls9c_ard_3-2-1_089078_2023-07-20_final.stac-item
2023-08-19 10:21:29	ga_ls9c_ard_3-2-1_100083_2023-08-19_final.stac-item
2023-09-14 10:54:28	ga_ls9c_ard_3-2-1_106072_2023-09-14_final.stac-item
2023-09-30 10:57:37	ga_ls9c_ard_3-2-1_106080_2023-09-30_final.stac-item
2023-10-01 11:41:41	ga_ls9c_ard_3-2-1_113082_2023-10-01_final.stac-item
2023-11-05 10:29:01	ga_ls9c_ard_3-2-1_102070_2023-11-05_final.stac-item
2023-11-09 10:10:19	ga_ls9c_ard_3-2-1_098085_2023-11-09_final.stac-item
2023-12-19 09:19:26	ga_ls9c_ard_3-2-1_090081_2023-12-18_final.stac-item
2024-01-04 10:56:38	ga_ls9c_ard_3-2-1_106077_2024-01-04_final.stac-item
2024-01-09 11:17:10	ga_ls9c_ard_3-2-1_109082_2024-01-09_final.stac-item
2024-01-13 10:50:05	ga_ls9c_ard_3-2-1_105076_2024-01-13_final.stac-item
2024-01-16 09:44:54	ga_ls9c_ard_3-2-1_094083_2024-01-16_final.stac-item
2024-01-26 10:21:56	ga_ls9c_ard_3-2-1_100083_2024-01-26_final.stac-item
2024-01-29 10:46:29	ga_ls9c_ard_3-2-1_105067_2024-01-29_final.stac-item
2024-02-07 10:45:32	ga_ls9c_ard_3-2-1_104080_2024-02-07_final.stac-item
2024-02-27 10:17:50	ga_ls9c_ard_3-2-1_100073_2024-02-27_final.stac-item
2024-05-05 11:32:16	ga_ls9c_ard_3-2-1_112075_2024-05-05_nrt.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