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

70 results

Time (local)	Label
2022-02-10 10:35:17	ga_ls9c_ard_3-2-1_103070_2022-02-10_final.stac-item
2022-02-15 10:54:11	ga_ls9c_ard_3-2-1_106071_2022-02-15_final.stac-item
2022-03-10 11:04:59	ga_ls9c_ard_3-2-1_107083_2022-03-10_final.stac-item
2022-04-13 09:11:11	ga_ls9c_ard_3-2-1_089077_2022-04-12_final.stac-item
2022-05-13 11:01:23	ga_ls9c_ard_3-2-1_107075_2022-05-13_final.stac-item
2022-05-27 09:33:09	ga_ls9c_ard_3-2-1_093071_2022-05-27_final.stac-item
2022-07-08 11:51:03	ga_ls9c_ard_3-2-1_115075_2022-07-08_final.stac-item
2022-07-16 11:01:35	ga_ls9c_ard_3-2-1_107075_2022-07-16_final.stac-item
2022-07-21 09:46:07	ga_ls9c_ard_3-2-1_094087_2022-07-21_final.stac-item
2022-07-25 10:52:46	ga_ls9c_ard_3-2-1_106068_2022-07-25_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-11 10:02:31	ga_ls9c_ard_3-2-1_097081_2022-08-11_final.stac-item
2022-08-18 10:04:45	ga_ls9c_ard_3-2-1_098071_2022-08-18_final.stac-item
2022-08-28 09:07:46	ga_ls9c_ard_3-2-1_088083_2022-08-27_final.stac-item
2022-08-31 09:34:17	ga_ls9c_ard_3-2-1_093072_2022-08-31_final.stac-item
2022-09-14 11:24:22	ga_ls9c_ard_3-2-1_111069_2022-09-14_final.stac-item
2022-10-31 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-30_final.stac-item
2022-11-08 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-11-08_final.stac-item
2022-11-24 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-24_final.stac-item
2022-12-15 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-12-15_final.stac-item
2022-12-16 09:17:56	ga_ls9c_ard_3-2-1_090077_2022-12-15_final.stac-item
2022-12-16 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-12-16_final.stac-item
2022-12-27 10:39:51	ga_ls9c_ard_3-2-1_103081_2022-12-27_final.stac-item
2023-01-09 10:03:48	ga_ls9c_ard_3-2-1_098068_2023-01-09_final.stac-item
2023-02-19 09:57:33	ga_ls9c_ard_3-2-1_097068_2023-02-19_final.stac-item
2023-03-06 10:55:47	ga_ls9c_ard_3-2-1_106075_2023-03-06_final.stac-item
2023-03-25 11:29:20	ga_ls9c_ard_3-2-1_111082_2023-03-25_final.stac-item
2023-04-10 09:52:18	ga_ls9c_ard_3-2-1_095087_2023-04-10_final.stac-item
2023-04-20 10:27:44	ga_ls9c_ard_3-2-1_101083_2023-04-20_final.stac-item
2023-04-30 09:28:36	ga_ls9c_ard_3-2-1_091090_2023-04-29_final.stac-item
2023-05-05 11:19:33	ga_ls9c_ard_3-2-1_110074_2023-05-05_final.stac-item
2023-05-15 10:16:31	ga_ls9c_ard_3-2-1_100071_2023-05-15_final.stac-item
2023-06-02 10:02:49	ga_ls9c_ard_3-2-1_098068_2023-06-02_final.stac-item
2023-06-22 11:23:13	ga_ls9c_ard_3-2-1_110084_2023-06-22_final.stac-item
2023-06-25 10:08:27	ga_ls9c_ard_3-2-1_099067_2023-06-25_final.stac-item
2023-06-26 09:21:13	ga_ls9c_ard_3-2-1_090088_2023-06-25_final.stac-item
2023-07-03 10:59:16	ga_ls9c_ard_3-2-1_107070_2023-07-03_final.stac-item
2023-07-28 09:22:19	ga_ls9c_ard_3-2-1_090090_2023-07-27_final.stac-item
2023-08-07 11:31:14	ga_ls9c_ard_3-2-1_112072_2023-08-07_final.stac-item
2023-08-12 10:08:54	ga_ls9c_ard_3-2-1_099067_2023-08-12_final.stac-item
2023-08-23 09:58:01	ga_ls9c_ard_3-2-1_096086_2023-08-23_final.stac-item
2023-09-05 09:27:39	ga_ls9c_ard_3-2-1_091087_2023-09-04_final.stac-item
2023-09-06 10:03:21	ga_ls9c_ard_3-2-1_098068_2023-09-06_final.stac-item
2023-09-29 10:10:20	ga_ls9c_ard_3-2-1_099070_2023-09-29_final.stac-item
2023-10-08 10:09:52	ga_ls9c_ard_3-2-1_098084_2023-10-08_final.stac-item
2023-10-16 10:53:02	ga_ls9c_ard_3-2-1_106068_2023-10-16_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-11-04 11:25:49	ga_ls9c_ard_3-2-1_111073_2023-11-04_final.stac-item
2023-11-15 11:11:42	ga_ls9c_ard_3-2-1_108084_2023-11-15_final.stac-item
2023-11-20 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-11-20_final.stac-item
2023-11-26 10:50:07	ga_ls9c_ard_3-2-1_105076_2023-11-26_final.stac-item
2023-11-27 11:36:10	ga_ls9c_ard_3-2-1_112083_2023-11-27_final.stac-item
2023-12-08 11:11:57	ga_ls9c_ard_3-2-1_109069_2023-12-08_final.stac-item
2023-12-11 10:07:36	ga_ls9c_ard_3-2-1_098078_2023-12-11_final.stac-item
2023-12-12 10:49:41	ga_ls9c_ard_3-2-1_105075_2023-12-12_final.stac-item
2023-12-19 09:22:37	ga_ls9c_ard_3-2-1_090089_2023-12-18_final.stac-item
2024-01-03 10:11:23	ga_ls9c_ard_3-2-1_099072_2024-01-03_final.stac-item
2024-01-04 10:55:02	ga_ls9c_ard_3-2-1_106073_2024-01-04_final.stac-item
2024-01-08 10:29:07	ga_ls9c_ard_3-2-1_102070_2024-01-08_final.stac-item
2024-01-12 10:08:01	ga_ls9c_ard_3-2-1_098079_2024-01-12_final.stac-item
2024-01-26 10:21:56	ga_ls9c_ard_3-2-1_100083_2024-01-26_final.stac-item
2024-02-03 11:06:15	ga_ls9c_ard_3-2-1_108070_2024-02-03_final.stac-item
2024-02-05 09:17:49	ga_ls9c_ard_3-2-1_090077_2024-02-04_final.stac-item
2024-02-05 09:18:13	ga_ls9c_ard_3-2-1_090078_2024-02-04_final.stac-item
2024-02-05 10:54:18	ga_ls9c_ard_3-2-1_106071_2024-02-05_final.stac-item
2024-02-13 10:03:14	ga_ls9c_ard_3-2-1_098067_2024-02-13_final.stac-item
2024-02-27 10:18:14	ga_ls9c_ard_3-2-1_100074_2024-02-27_final.stac-item
2024-03-10 09:06:55	ga_ls9c_ard_3-2-1_088081_2024-03-09_final.stac-item
2024-03-13 11:12:17	ga_ls9c_ard_3-2-1_109070_2024-03-13_final.stac-item
2024-03-31 10:59:47	ga_ls9c_ard_3-2-1_107070_2024-03-31_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years