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

75 results

Time (local)	Label
2021-12-10 10:26:37	ga_ls9c_ard_3-2-1_101079_2021-12-10_final.stac-item
2021-12-13 10:55:06	ga_ls9c_ard_3-2-1_106073_2021-12-13_final.stac-item
2021-12-21 10:03:38	ga_ls9c_ard_3-2-1_098068_2021-12-21_final.stac-item
2021-12-29 09:19:47	ga_ls9c_ard_3-2-1_090082_2021-12-28_final.stac-item
2022-01-04 10:18:23	ga_ls9c_ard_3-2-1_100074_2022-01-04_final.stac-item
2022-01-10 11:19:21	ga_ls9c_ard_3-2-1_110072_2022-01-10_final.stac-item
2022-01-14 09:19:19	ga_ls9c_ard_3-2-1_090081_2022-01-13_final.stac-item
2022-01-26 09:45:41	ga_ls9c_ard_3-2-1_094085_2022-01-26_final.stac-item
2022-02-06 09:27:08	ga_ls9c_ard_3-2-1_091085_2022-02-05_final.stac-item
2022-03-22 11:24:52	ga_ls9c_ard_3-2-1_111071_2022-03-22_final.stac-item
2022-05-28 11:58:06	ga_ls9c_ard_3-2-1_116078_2022-05-28_final.stac-item
2022-06-03 11:17:50	ga_ls9c_ard_3-2-1_110070_2022-06-03_final.stac-item
2022-06-10 09:45:57	ga_ls9c_ard_3-2-1_095072_2022-06-10_final.stac-item
2022-07-04 10:34:07	ga_ls9c_ard_3-2-1_103068_2022-07-04_final.stac-item
2022-07-18 09:11:34	ga_ls9c_ard_3-2-1_089078_2022-07-17_final.stac-item
2022-07-26 11:41:37	ga_ls9c_ard_3-2-1_113082_2022-07-26_final.stac-item
2022-07-29 10:30:05	ga_ls9c_ard_3-2-1_102073_2022-07-29_final.stac-item
2022-07-30 11:17:21	ga_ls9c_ard_3-2-1_109083_2022-07-30_final.stac-item
2022-09-18 09:22:48	ga_ls9c_ard_3-2-1_091074_2022-09-17_final.stac-item
2022-09-26 10:09:29	ga_ls9c_ard_3-2-1_099067_2022-09-26_final.stac-item
2022-10-20 11:02:13	ga_ls9c_ard_3-2-1_107075_2022-10-20_final.stac-item
2022-11-03 09:37:14	ga_ls9c_ard_3-2-1_093079_2022-11-03_final.stac-item
2022-11-26 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-11-26_final.stac-item
2022-12-05 09:38:28	ga_ls9c_ard_3-2-1_093082_2022-12-05_final.stac-item
2022-12-12 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-12-12_final.stac-item
2022-12-22 10:18:30	ga_ls9c_ard_3-2-1_100074_2022-12-22_final.stac-item
2022-12-24 10:08:32	ga_ls9c_ard_3-2-1_098080_2022-12-24_final.stac-item
2023-01-03 10:44:52	ga_ls9c_ard_3-2-1_104078_2023-01-03_final.stac-item
2023-01-08 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-16 10:11:54	ga_ls9c_ard_3-2-1_099073_2023-01-16_final.stac-item
2023-02-07 09:37:21	ga_ls9c_ard_3-2-1_093079_2023-02-07_final.stac-item
2023-02-09 09:26:59	ga_ls9c_ard_3-2-1_091084_2023-02-08_final.stac-item
2023-02-27 10:49:40	ga_ls9c_ard_3-2-1_105075_2023-02-27_final.stac-item
2023-03-13 11:01:55	ga_ls9c_ard_3-2-1_107075_2023-03-13_final.stac-item
2023-03-29 09:25:14	ga_ls9c_ard_3-2-1_091081_2023-03-28_final.stac-item
2023-04-23 09:20:08	ga_ls9c_ard_3-2-1_090084_2023-04-22_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_2023-04-29_final.stac-item
2023-05-21 09:43:45	ga_ls9c_ard_3-2-1_094082_2023-05-21_final.stac-item
2023-06-10 10:52:35	ga_ls9c_ard_3-2-1_106069_2023-06-10_final.stac-item
2023-06-19 10:45:56	ga_ls9c_ard_3-2-1_105068_2023-06-19_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-07-19 10:59:46	ga_ls9c_ard_3-2-1_107071_2023-07-19_final.stac-item
2023-07-25 10:26:39	ga_ls9c_ard_3-2-1_101081_2023-07-25_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-27 11:05:51	ga_ls9c_ard_3-2-1_108070_2023-08-27_final.stac-item
2023-09-05 09:26:03	ga_ls9c_ard_3-2-1_091083_2023-09-04_final.stac-item
2023-09-10 11:19:33	ga_ls9c_ard_3-2-1_110073_2023-09-10_final.stac-item
2023-09-13 10:15:35	ga_ls9c_ard_3-2-1_099083_2023-09-13_final.stac-item
2023-09-14 10:55:15	ga_ls9c_ard_3-2-1_106074_2023-09-14_final.stac-item
2023-09-14 10:58:27	ga_ls9c_ard_3-2-1_106082_2023-09-14_final.stac-item
2023-09-21 09:22:57	ga_ls9c_ard_3-2-1_091075_2023-09-20_final.stac-item
2023-09-21 09:22:57	ga_ls9c_ard_3-2-1_091075_2023-09-20_interim.stac-item
2023-09-24 11:35:54	ga_ls9c_ard_3-2-1_112083_2023-09-24_final.stac-item
2023-10-02 10:44:29	ga_ls9c_ard_3-2-1_104078_2023-10-02_final.stac-item
2023-10-10 11:35:37	ga_ls9c_ard_3-2-1_112082_2023-10-10_final.stac-item
2023-10-22 10:20:21	ga_ls9c_ard_3-2-1_100079_2023-10-22_final.stac-item
2023-10-29 10:26:28	ga_ls9c_ard_3-2-1_101079_2023-10-29_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-25 10:03:39	ga_ls9c_ard_3-2-1_098068_2023-11-25_final.stac-item
2023-11-27 11:36:10	ga_ls9c_ard_3-2-1_112083_2023-11-27_final.stac-item
2023-12-09 11:58:49	ga_ls9c_ard_3-2-1_116078_2023-12-09_final.stac-item
2023-12-14 10:38:32	ga_ls9c_ard_3-2-1_103078_2023-12-14_final.stac-item
2023-12-15 09:46:07	ga_ls9c_ard_3-2-1_094086_2023-12-15_final.stac-item
2023-12-15 11:20:37	ga_ls9c_ard_3-2-1_110075_2023-12-15_final.stac-item
2023-12-19 10:54:43	ga_ls9c_ard_3-2-1_106072_2023-12-19_final.stac-item
2024-01-22 10:41:04	ga_ls9c_ard_3-2-1_104069_2024-01-22_final.stac-item
2024-01-22 10:41:04	ga_ls9c_ard_3-2-1_104069_2024-01-22_interim.stac-item
2024-01-25 11:15:32	ga_ls9c_ard_3-2-1_109078_2024-01-25_final.stac-item
2024-01-25 11:15:32	ga_ls9c_ard_3-2-1_109078_2024-01-25_nrt.stac-item
2024-01-30 09:52:52	ga_ls9c_ard_3-2-1_096072_2024-01-30_final.stac-item
2024-02-13 10:03:37	ga_ls9c_ard_3-2-1_098068_2024-02-13_final.stac-item
2024-02-19 09:31:13	ga_ls9c_ard_3-2-1_092080_2024-02-19_final.stac-item
2024-02-28 11:00:42	ga_ls9c_ard_3-2-1_107072_2024-02-28_final.stac-item
2024-03-13 09:39:24	ga_ls9c_ard_3-2-1_093085_2024-03-13_final.stac-item
2024-03-16 11:47:11	ga_ls9c_ard_3-2-1_114080_2024-03-16_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