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

73 results

Time (local)	Label
2021-12-12 10:16:38	ga_ls9c_ard_3-2-1_099085_2021-12-12_final.stac-item
2021-12-14 09:57:52	ga_ls9c_ard_3-2-1_097069_2021-12-14_final.stac-item
2021-12-28 11:51:54	ga_ls9c_ard_3-2-1_115076_2021-12-28_final.stac-item
2022-01-06 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-06_final.stac-item
2022-01-19 09:36:42	ga_ls9c_ard_3-2-1_093078_2022-01-19_final.stac-item
2022-01-22 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-22_final.stac-item
2022-02-17 09:06:55	ga_ls9c_ard_3-2-1_088081_2022-02-16_final.stac-item
2022-02-21 10:17:26	ga_ls9c_ard_3-2-1_100072_2022-02-21_final.stac-item
2022-02-22 09:26:36	ga_ls9c_ard_3-2-1_091084_2022-02-21_final.stac-item
2022-03-21 09:06:19	ga_ls9c_ard_3-2-1_088080_2022-03-20_final.stac-item
2022-03-21 09:06:43	ga_ls9c_ard_3-2-1_088081_2022-03-20_final.stac-item
2022-04-04 10:55:55	ga_ls9c_ard_3-2-1_106076_2022-04-04_final.stac-item
2022-04-16 11:18:56	ga_ls9c_ard_3-2-1_110072_2022-04-16_final.stac-item
2022-04-16 11:20:32	ga_ls9c_ard_3-2-1_110076_2022-04-16_final.stac-item
2022-04-28 10:02:42	ga_ls9c_ard_3-2-1_098067_2022-04-28_final.stac-item
2022-05-09 11:28:33	ga_ls9c_ard_3-2-1_111081_2022-05-09_final.stac-item
2022-05-13 09:21:18	ga_ls9c_ard_3-2-1_091072_2022-05-12_final.stac-item
2022-05-15 10:46:12	ga_ls9c_ard_3-2-1_105068_2022-05-15_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-08 09:56:42	ga_ls9c_ard_3-2-1_097068_2022-06-08_final.stac-item
2022-06-10 09:45:33	ga_ls9c_ard_3-2-1_095071_2022-06-10_final.stac-item
2022-06-24 09:57:26	ga_ls9c_ard_3-2-1_097069_2022-06-24_final.stac-item
2022-06-28 09:36:19	ga_ls9c_ard_3-2-1_093078_2022-06-28_final.stac-item
2022-06-29 10:21:34	ga_ls9c_ard_3-2-1_100083_2022-06-29_final.stac-item
2022-07-16 10:59:35	ga_ls9c_ard_3-2-1_107070_2022-07-16_final.stac-item
2022-07-24 11:51:10	ga_ls9c_ard_3-2-1_115075_2022-07-24_final.stac-item
2022-08-09 11:52:33	ga_ls9c_ard_3-2-1_115078_2022-08-09_final.stac-item
2022-09-03 10:03:11	ga_ls9c_ard_3-2-1_098067_2022-09-03_final.stac-item
2022-09-10 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-09-10_final.stac-item
2022-09-16 09:35:32	ga_ls9c_ard_3-2-1_093075_2022-09-16_final.stac-item
2022-10-09 09:40:36	ga_ls9c_ard_3-2-1_094072_2022-10-09_final.stac-item
2022-10-31 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-30_final.stac-item
2022-11-21 09:23:45	ga_ls9c_ard_3-2-1_091076_2022-11-20_final.stac-item
2022-11-21 09:28:32	ga_ls9c_ard_3-2-1_091088_2022-11-20_final.stac-item
2022-12-11 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-12-11_final.stac-item
2022-12-17 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-12-17_final.stac-item
2023-02-18 09:22:18	ga_ls9c_ard_3-2-1_090088_2023-02-17_final.stac-item
2023-02-20 09:05:06	ga_ls9c_ard_3-2-1_088076_2023-02-19_interim.stac-item
2023-03-04 11:08:11	ga_ls9c_ard_3-2-1_108075_2023-03-04_final.stac-item
2023-04-13 11:58:27	ga_ls9c_ard_3-2-1_116078_2023-04-13_final.stac-item
2023-05-02 09:11:25	ga_ls9c_ard_3-2-1_089078_2023-05-01_final.stac-item
2023-05-06 10:27:07	ga_ls9c_ard_3-2-1_101082_2023-05-06_final.stac-item
2023-05-08 10:10:23	ga_ls9c_ard_3-2-1_099071_2023-05-08_final.stac-item
2023-06-13 11:25:26	ga_ls9c_ard_3-2-1_111074_2023-06-13_final.stac-item
2023-06-17 11:04:40	ga_ls9c_ard_3-2-1_107084_2023-06-17_final.stac-item
2023-07-22 09:57:22	ga_ls9c_ard_3-2-1_096085_2023-07-22_final.stac-item
2023-09-01 09:50:44	ga_ls9c_ard_3-2-1_095083_2023-09-01_final.stac-item
2023-10-18 10:42:40	ga_ls9c_ard_3-2-1_104073_2023-10-18_final.stac-item
2023-10-20 10:30:19	ga_ls9c_ard_3-2-1_102073_2023-10-20_final.stac-item
2023-10-28 09:46:25	ga_ls9c_ard_3-2-1_094087_2023-10-28_final.stac-item
2023-11-08 09:22:15	ga_ls9c_ard_3-2-1_091073_2023-11-07_final.stac-item
2023-11-14 10:25:39	ga_ls9c_ard_3-2-1_101077_2023-11-14_final.stac-item
2023-11-19 09:06:57	ga_ls9c_ard_3-2-1_088081_2023-11-18_final.stac-item
2023-11-27 09:58:05	ga_ls9c_ard_3-2-1_096085_2023-11-27_final.stac-item
2023-12-10 11:00:01	ga_ls9c_ard_3-2-1_107070_2023-12-10_final.stac-item
2023-12-10 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-12-10_final.stac-item
2024-01-03 11:53:04	ga_ls9c_ard_3-2-1_115079_2024-01-03_final.stac-item
2024-01-05 09:58:12	ga_ls9c_ard_3-2-1_097070_2024-01-05_final.stac-item
2024-01-09 11:17:58	ga_ls9c_ard_3-2-1_109084_2024-01-09_final.stac-item
2024-01-26 10:17:32	ga_ls9c_ard_3-2-1_100072_2024-01-26_final.stac-item
2024-01-26 10:22:19	ga_ls9c_ard_3-2-1_100084_2024-01-26_final.stac-item
2024-01-28 11:47:41	ga_ls9c_ard_3-2-1_114081_2024-01-28_final.stac-item
2024-02-06 10:01:52	ga_ls9c_ard_3-2-1_097079_2024-02-06_final.stac-item
2024-02-17 11:23:18	ga_ls9c_ard_3-2-1_110082_2024-02-17_final.stac-item
2024-02-19 11:11:18	ga_ls9c_ard_3-2-1_108083_2024-02-19_final.stac-item
2024-02-21 09:22:24	ga_ls9c_ard_3-2-1_090089_2024-02-20_final.stac-item
2024-02-28 11:01:30	ga_ls9c_ard_3-2-1_107074_2024-02-28_final.stac-item
2024-03-16 11:47:35	ga_ls9c_ard_3-2-1_114081_2024-03-16_final.stac-item
2024-03-17 10:52:45	ga_ls9c_ard_3-2-1_105083_2024-03-17_final.stac-item
2024-04-30 11:17:20	ga_ls9c_ard_3-2-1_109084_2024-04-30_final.stac-item
2024-05-04 09:14:30	ga_ls9c_ard_3-2-1_089086_2024-05-03_final.stac-item
2024-05-12 09:57:33	ga_ls9c_ard_3-2-1_097070_2024-05-12_nrt.stac-item
2024-05-13 09:05:54	ga_ls9c_ard_3-2-1_088080_2024-05-12_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