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

First 100 results (query limit)

Time (local)	Label
2021-12-14 10:03:27	ga_ls9c_ard_3-2-1_097083_2021-12-14_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-02-17 10:41:24	ga_ls9c_ard_3-2-1_104070_2022-02-17_final.stac-item
2022-02-28 10:27:07	ga_ls9c_ard_3-2-1_101081_2022-02-28_final.stac-item
2022-03-01 11:11:34	ga_ls9c_ard_3-2-1_108084_2022-03-01_final.stac-item
2022-03-08 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-03-08_final.stac-item
2022-04-02 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-04-02_final.stac-item
2022-06-21 11:08:30	ga_ls9c_ard_3-2-1_108077_2022-06-21_final.stac-item
2022-07-04 10:34:31	ga_ls9c_ard_3-2-1_103069_2022-07-04_final.stac-item
2022-07-11 10:44:14	ga_ls9c_ard_3-2-1_104078_2022-07-11_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-12 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-08-12_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-08-22 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-08-22_final.stac-item
2022-08-26 09:19:20	ga_ls9c_ard_3-2-1_090081_2022-08-25_final.stac-item
2022-10-02 09:38:48	ga_ls9c_ard_3-2-1_093083_2022-10-02_final.stac-item
2022-10-07 11:32:13	ga_ls9c_ard_3-2-1_112073_2022-10-07_final.stac-item
2022-10-08 10:37:48	ga_ls9c_ard_3-2-1_103076_2022-10-08_final.stac-item
2022-10-16 09:48:02	ga_ls9c_ard_3-2-1_095075_2022-10-16_final.stac-item
2022-10-19 11:59:02	ga_ls9c_ard_3-2-1_116078_2022-10-19_final.stac-item
2022-10-21 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-10-21_final.stac-item
2022-10-25 09:42:16	ga_ls9c_ard_3-2-1_094076_2022-10-25_final.stac-item
2022-10-30 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-10-30_final.stac-item
2022-11-04 10:20:54	ga_ls9c_ard_3-2-1_100080_2022-11-04_final.stac-item
2022-11-08 09:55:49	ga_ls9c_ard_3-2-1_096079_2022-11-08_final.stac-item
2022-11-22 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-11-22_final.stac-item
2022-11-25 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-11-25_final.stac-item
2022-11-28 09:30:41	ga_ls9c_ard_3-2-1_092078_2022-11-28_final.stac-item
2022-12-07 11:05:00	ga_ls9c_ard_3-2-1_107082_2022-12-07_final.stac-item
2022-12-10 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-12-10_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-21 09:39:15	ga_ls9c_ard_3-2-1_093084_2022-12-21_final.stac-item
2022-12-23 11:04:09	ga_ls9c_ard_3-2-1_107080_2022-12-23_final.stac-item
2023-01-04 09:48:27	ga_ls9c_ard_3-2-1_095076_2023-01-04_final.stac-item
2023-01-14 10:26:41	ga_ls9c_ard_3-2-1_101079_2023-01-14_final.stac-item
2023-01-27 09:54:59	ga_ls9c_ard_3-2-1_096077_2023-01-27_final.stac-item
2023-01-28 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-28_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-02-02 10:56:27	ga_ls9c_ard_3-2-1_106076_2023-02-02_final.stac-item
2023-02-02 10:58:27	ga_ls9c_ard_3-2-1_106081_2023-02-02_final.stac-item
2023-02-03 10:01:15	ga_ls9c_ard_3-2-1_097077_2023-02-03_final.stac-item
2023-02-04 10:41:43	ga_ls9c_ard_3-2-1_104070_2023-02-04_final.stac-item
2023-02-05 11:24:35	ga_ls9c_ard_3-2-1_111069_2023-02-05_final.stac-item
2023-02-05 11:27:23	ga_ls9c_ard_3-2-1_111076_2023-02-05_final.stac-item
2023-02-09 11:03:52	ga_ls9c_ard_3-2-1_107079_2023-02-09_final.stac-item
2023-02-13 10:36:44	ga_ls9c_ard_3-2-1_103073_2023-02-13_final.stac-item
2023-02-14 09:42:18	ga_ls9c_ard_3-2-1_094076_2023-02-14_final.stac-item
2023-04-24 10:03:47	ga_ls9c_ard_3-2-1_097085_2023-04-24_final.stac-item
2023-04-24 11:38:40	ga_ls9c_ard_3-2-1_113075_2023-04-24_final.stac-item
2023-04-25 10:42:38	ga_ls9c_ard_3-2-1_104074_2023-04-25_final.stac-item
2023-04-26 09:49:24	ga_ls9c_ard_3-2-1_095080_2023-04-26_final.stac-item
2023-04-28 09:35:25	ga_ls9c_ard_3-2-1_093076_2023-04-28_final.stac-item
2023-04-28 09:36:37	ga_ls9c_ard_3-2-1_093079_2023-04-28_final.stac-item
2023-04-28 09:37:48	ga_ls9c_ard_3-2-1_093082_2023-04-28_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-04-30 11:02:42	ga_ls9c_ard_3-2-1_107078_2023-04-30_final.stac-item
2023-05-28 09:46:41	ga_ls9c_ard_3-2-1_095074_2023-05-28_final.stac-item
2023-07-05 10:47:44	ga_ls9c_ard_3-2-1_105072_2023-07-05_final.stac-item
2023-07-15 09:47:36	ga_ls9c_ard_3-2-1_095076_2023-07-15_final.stac-item
2023-07-15 11:26:29	ga_ls9c_ard_3-2-1_111076_2023-07-15_final.stac-item
2023-07-17 09:36:27	ga_ls9c_ard_3-2-1_093079_2023-07-17_final.stac-item
2023-07-17 09:36:50	ga_ls9c_ard_3-2-1_093080_2023-07-17_final.stac-item
2023-07-17 09:37:14	ga_ls9c_ard_3-2-1_093081_2023-07-17_final.stac-item
2023-07-20 10:05:21	ga_ls9c_ard_3-2-1_098074_2023-07-20_final.stac-item
2023-07-21 10:52:12	ga_ls9c_ard_3-2-1_105083_2023-07-21_final.stac-item
2023-07-22 09:55:46	ga_ls9c_ard_3-2-1_096081_2023-07-22_final.stac-item
2023-07-23 10:34:38	ga_ls9c_ard_3-2-1_103070_2023-07-23_final.stac-item
2023-07-25 10:26:39	ga_ls9c_ard_3-2-1_101081_2023-07-25_final.stac-item
2023-07-28 09:18:44	ga_ls9c_ard_3-2-1_090081_2023-07-27_final.stac-item
2023-07-28 10:56:01	ga_ls9c_ard_3-2-1_106077_2023-07-28_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-07-29 11:39:18	ga_ls9c_ard_3-2-1_113077_2023-07-29_final.stac-item
2023-08-05 10:05:29	ga_ls9c_ard_3-2-1_098074_2023-08-05_final.stac-item
2023-08-05 11:47:10	ga_ls9c_ard_3-2-1_114081_2023-08-05_final.stac-item
2023-08-08 10:37:36	ga_ls9c_ard_3-2-1_103077_2023-08-08_final.stac-item
2023-10-14 09:30:52	ga_ls9c_ard_3-2-1_092079_2023-10-14_final.stac-item
2023-10-15 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-10-15_final.stac-item
2023-10-18 10:44:16	ga_ls9c_ard_3-2-1_104077_2023-10-18_final.stac-item
2023-10-21 09:36:41	ga_ls9c_ard_3-2-1_093078_2023-10-21_final.stac-item
2023-10-23 11:03:36	ga_ls9c_ard_3-2-1_107079_2023-10-23_final.stac-item
2023-10-24 10:05:35	ga_ls9c_ard_3-2-1_098073_2023-10-24_final.stac-item
2023-10-27 10:35:16	ga_ls9c_ard_3-2-1_103070_2023-10-27_final.stac-item
2023-10-29 10:25:16	ga_ls9c_ard_3-2-1_101076_2023-10-29_final.stac-item
2023-11-02 10:03:17	ga_ls9c_ard_3-2-1_097083_2023-11-02_final.stac-item
2023-11-04 09:50:31	ga_ls9c_ard_3-2-1_095082_2023-11-04_final.stac-item
2023-11-04 09:51:19	ga_ls9c_ard_3-2-1_095084_2023-11-04_final.stac-item
2023-11-05 10:31:00	ga_ls9c_ard_3-2-1_102075_2023-11-05_final.stac-item
2023-11-14 10:26:27	ga_ls9c_ard_3-2-1_101079_2023-11-14_final.stac-item
2023-11-14 10:27:15	ga_ls9c_ard_3-2-1_101081_2023-11-14_final.stac-item
2023-11-15 11:10:06	ga_ls9c_ard_3-2-1_108080_2023-11-15_final.stac-item
2023-11-16 10:12:06	ga_ls9c_ard_3-2-1_099074_2023-11-16_final.stac-item
2023-11-16 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-11-16_final.stac-item
2023-11-18 09:59:22	ga_ls9c_ard_3-2-1_097073_2023-11-18_final.stac-item
2023-11-18 10:02:10	ga_ls9c_ard_3-2-1_097080_2023-11-18_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-20 11:29:07	ga_ls9c_ard_3-2-1_111081_2023-11-20_final.stac-item
2023-11-21 10:32:43	ga_ls9c_ard_3-2-1_102079_2023-11-21_final.stac-item
2023-11-24 11:02:03	ga_ls9c_ard_3-2-1_107075_2023-11-24_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