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
2021-11-10 09:39:53	ga_ls9c_ard_3-2-1_094078_2021-11-10_final.stac-item
2021-11-15 09:42:21	ga_ls9c_ard_3-2-1_094078_2021-11-15_final.stac-item
2021-12-09 09:42:59	ga_ls9c_ard_3-2-1_094078_2021-12-09_final.stac-item
2021-12-09 09:45:46	ga_ls9c_ard_3-2-1_094085_2021-12-09_final.stac-item
2021-12-23 09:54:28	ga_ls9c_ard_3-2-1_096076_2021-12-23_final.stac-item
2022-01-10 09:42:52	ga_ls9c_ard_3-2-1_094078_2022-01-10_final.stac-item
2022-01-19 09:37:05	ga_ls9c_ard_3-2-1_093079_2022-01-19_final.stac-item
2022-02-12 10:27:18	ga_ls9c_ard_3-2-1_101081_2022-02-12_final.stac-item
2022-03-22 09:49:35	ga_ls9c_ard_3-2-1_095080_2022-03-22_final.stac-item
2022-05-04 11:08:28	ga_ls9c_ard_3-2-1_108077_2022-05-04_final.stac-item
2022-06-05 11:08:17	ga_ls9c_ard_3-2-1_108077_2022-06-05_final.stac-item
2022-06-10 09:48:44	ga_ls9c_ard_3-2-1_095079_2022-06-10_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-07-22 10:26:12	ga_ls9c_ard_3-2-1_101079_2022-07-22_final.stac-item
2022-08-04 09:53:53	ga_ls9c_ard_3-2-1_096075_2022-08-04_final.stac-item
2022-08-07 10:22:49	ga_ls9c_ard_3-2-1_101070_2022-08-07_final.stac-item
2022-08-17 11:03:10	ga_ls9c_ard_3-2-1_107078_2022-08-17_final.stac-item
2022-08-28 10:43:51	ga_ls9c_ard_3-2-1_104076_2022-08-28_final.stac-item
2022-09-13 10:43:53	ga_ls9c_ard_3-2-1_104076_2022-09-13_final.stac-item
2022-09-18 11:03:16	ga_ls9c_ard_3-2-1_107078_2022-09-18_final.stac-item
2022-10-14 11:40:04	ga_ls9c_ard_3-2-1_113077_2022-10-14_final.stac-item
2022-10-17 10:34:06	ga_ls9c_ard_3-2-1_102082_2022-10-17_final.stac-item
2022-11-07 10:51:02	ga_ls9c_ard_3-2-1_105078_2022-11-07_final.stac-item
2022-11-10 09:41:53	ga_ls9c_ard_3-2-1_094075_2022-11-10_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-11-17 09:50:04	ga_ls9c_ard_3-2-1_095080_2022-11-17_final.stac-item
2022-12-01 10:00:22	ga_ls9c_ard_3-2-1_097075_2022-12-01_final.stac-item
2022-12-06 10:21:20	ga_ls9c_ard_3-2-1_100081_2022-12-06_final.stac-item
2022-12-09 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-12-09_final.stac-item
2022-12-10 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-12-10_final.stac-item
2022-12-13 10:27:32	ga_ls9c_ard_3-2-1_101081_2022-12-13_final.stac-item
2022-12-17 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-12-17_final.stac-item
2022-12-26 11:34:16	ga_ls9c_ard_3-2-1_112078_2022-12-26_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-26 10:50:59	ga_ls9c_ard_3-2-1_105078_2023-01-26_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-02-05 09:49:42	ga_ls9c_ard_3-2-1_095079_2023-02-05_final.stac-item
2023-02-14 09:43:06	ga_ls9c_ard_3-2-1_094078_2023-02-14_final.stac-item
2023-04-22 10:14:33	ga_ls9c_ard_3-2-1_099081_2023-04-22_final.stac-item
2023-04-24 09:59:47	ga_ls9c_ard_3-2-1_097075_2023-04-24_final.stac-item
2023-04-24 10:02:59	ga_ls9c_ard_3-2-1_097083_2023-04-24_final.stac-item
2023-04-25 10:41:50	ga_ls9c_ard_3-2-1_104072_2023-04-25_final.stac-item
2023-04-25 10:43:50	ga_ls9c_ard_3-2-1_104077_2023-04-25_final.stac-item
2023-04-26 09:47:48	ga_ls9c_ard_3-2-1_095076_2023-04-26_final.stac-item
2023-04-26 11:27:53	ga_ls9c_ard_3-2-1_111079_2023-04-26_final.stac-item
2023-04-27 10:31:51	ga_ls9c_ard_3-2-1_102078_2023-04-27_final.stac-item
2023-04-27 10:32:15	ga_ls9c_ard_3-2-1_102079_2023-04-27_final.stac-item
2023-05-01 11:45:09	ga_ls9c_ard_3-2-1_114076_2023-05-01_final.stac-item
2023-05-02 10:51:30	ga_ls9c_ard_3-2-1_105081_2023-05-02_final.stac-item
2023-05-03 09:53:28	ga_ls9c_ard_3-2-1_096075_2023-05-03_final.stac-item
2023-05-03 11:34:20	ga_ls9c_ard_3-2-1_112080_2023-05-03_final.stac-item
2023-05-04 10:39:29	ga_ls9c_ard_3-2-1_103082_2023-05-04_final.stac-item
2023-05-05 09:41:04	ga_ls9c_ard_3-2-1_094075_2023-05-05_final.stac-item
2023-05-05 09:41:28	ga_ls9c_ard_3-2-1_094076_2023-05-05_final.stac-item
2023-05-05 09:42:40	ga_ls9c_ard_3-2-1_094079_2023-05-05_final.stac-item
2023-05-05 09:44:15	ga_ls9c_ard_3-2-1_094083_2023-05-05_final.stac-item
2023-05-28 09:47:29	ga_ls9c_ard_3-2-1_095076_2023-05-28_final.stac-item
2023-05-28 11:27:33	ga_ls9c_ard_3-2-1_111079_2023-05-28_final.stac-item
2023-05-28 11:27:57	ga_ls9c_ard_3-2-1_111080_2023-05-28_final.stac-item
2023-06-21 10:34:46	ga_ls9c_ard_3-2-1_103071_2023-06-21_final.stac-item
2023-06-22 09:41:33	ga_ls9c_ard_3-2-1_094077_2023-06-22_final.stac-item
2023-06-22 11:21:14	ga_ls9c_ard_3-2-1_110079_2023-06-22_final.stac-item
2023-06-23 10:22:01	ga_ls9c_ard_3-2-1_101070_2023-06-23_final.stac-item
2023-06-24 11:08:04	ga_ls9c_ard_3-2-1_108077_2023-06-24_final.stac-item
2023-06-26 09:18:49	ga_ls9c_ard_3-2-1_090082_2023-06-25_final.stac-item
2023-06-27 09:59:43	ga_ls9c_ard_3-2-1_097076_2023-06-27_final.stac-item
2023-06-27 11:39:24	ga_ls9c_ard_3-2-1_113078_2023-06-27_final.stac-item
2023-06-29 11:27:30	ga_ls9c_ard_3-2-1_111079_2023-06-29_final.stac-item
2023-07-06 09:54:07	ga_ls9c_ard_3-2-1_096077_2023-07-06_final.stac-item
2023-07-06 11:33:48	ga_ls9c_ard_3-2-1_112079_2023-07-06_final.stac-item
2023-07-15 11:26:53	ga_ls9c_ard_3-2-1_111077_2023-07-15_final.stac-item
2023-07-15 11:28:05	ga_ls9c_ard_3-2-1_111080_2023-07-15_final.stac-item
2023-07-16 10:31:40	ga_ls9c_ard_3-2-1_102078_2023-07-16_final.stac-item
2023-07-16 10:32:04	ga_ls9c_ard_3-2-1_102079_2023-07-16_final.stac-item
2023-07-17 11:15:20	ga_ls9c_ard_3-2-1_109079_2023-07-17_final.stac-item
2023-07-22 11:32:15	ga_ls9c_ard_3-2-1_112075_2023-07-22_final.stac-item
2023-07-22 11:34:15	ga_ls9c_ard_3-2-1_112080_2023-07-22_final.stac-item
2023-07-24 09:41:48	ga_ls9c_ard_3-2-1_094077_2023-07-24_final.stac-item
2023-07-24 11:21:29	ga_ls9c_ard_3-2-1_110079_2023-07-24_final.stac-item
2023-07-24 11:21:53	ga_ls9c_ard_3-2-1_110080_2023-07-24_final.stac-item
2023-07-26 11:08:20	ga_ls9c_ard_3-2-1_108077_2023-07-26_final.stac-item
2023-07-28 09:19:08	ga_ls9c_ard_3-2-1_090082_2023-07-27_final.stac-item
2023-07-29 11:39:42	ga_ls9c_ard_3-2-1_113078_2023-07-29_final.stac-item
2023-10-13 10:22:54	ga_ls9c_ard_3-2-1_101070_2023-10-13_final.stac-item
2023-10-14 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-10-14_final.stac-item
2023-10-17 11:39:53	ga_ls9c_ard_3-2-1_113077_2023-10-17_final.stac-item
2023-10-17 11:40:41	ga_ls9c_ard_3-2-1_113079_2023-10-17_final.stac-item
2023-10-18 10:45:04	ga_ls9c_ard_3-2-1_104079_2023-10-18_final.stac-item
2023-10-19 09:48:15	ga_ls9c_ard_3-2-1_095076_2023-10-19_final.stac-item
2023-10-19 09:49:03	ga_ls9c_ard_3-2-1_095078_2023-10-19_final.stac-item
2023-10-24 10:08:46	ga_ls9c_ard_3-2-1_098081_2023-10-24_final.stac-item
2023-10-25 10:50:50	ga_ls9c_ard_3-2-1_105078_2023-10-25_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-27 10:38:51	ga_ls9c_ard_3-2-1_103079_2023-10-27_final.stac-item
2023-10-28 09:44:49	ga_ls9c_ard_3-2-1_094083_2023-10-28_final.stac-item
2023-11-02 10:00:29	ga_ls9c_ard_3-2-1_097076_2023-11-02_final.stac-item
2023-11-16 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-11-16_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years