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
2021-11-02 10:56:03	ga_ls9c_ard_3-2-1_106081_2021-11-02_final.stac-item
2021-11-14 10:40:16	ga_ls9c_ard_3-2-1_103076_2021-11-14_final.stac-item
2021-11-15 09:42:45	ga_ls9c_ard_3-2-1_094079_2021-11-15_final.stac-item
2021-11-15 09:43:57	ga_ls9c_ard_3-2-1_094082_2021-11-15_final.stac-item
2021-12-04 11:04:34	ga_ls9c_ard_3-2-1_107081_2021-12-04_final.stac-item
2021-12-05 10:06:09	ga_ls9c_ard_3-2-1_098074_2021-12-05_final.stac-item
2021-12-09 09:45:22	ga_ls9c_ard_3-2-1_094084_2021-12-09_final.stac-item
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2021-12-23 09:53:40	ga_ls9c_ard_3-2-1_096074_2021-12-23_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2022-01-03 09:36:19	ga_ls9c_ard_3-2-1_093077_2022-01-03_final.stac-item
2022-01-12 09:30:30	ga_ls9c_ard_3-2-1_092078_2022-01-12_final.stac-item
2022-01-13 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-01-13_final.stac-item
2022-02-07 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-02-07_final.stac-item
2022-03-19 10:58:47	ga_ls9c_ard_3-2-1_106083_2022-03-19_final.stac-item
2022-03-21 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-03-21_final.stac-item
2022-05-04 11:06:28	ga_ls9c_ard_3-2-1_108072_2022-05-04_final.stac-item
2022-05-18 09:43:21	ga_ls9c_ard_3-2-1_094081_2022-05-18_final.stac-item
2022-05-29 11:00:05	ga_ls9c_ard_3-2-1_107072_2022-05-29_final.stac-item
2022-05-31 10:52:07	ga_ls9c_ard_3-2-1_105083_2022-05-31_final.stac-item
2022-06-09 10:43:57	ga_ls9c_ard_3-2-1_104078_2022-06-09_final.stac-item
2022-06-15 11:46:38	ga_ls9c_ard_3-2-1_114080_2022-06-15_final.stac-item
2022-06-20 10:22:25	ga_ls9c_ard_3-2-1_101070_2022-06-20_final.stac-item
2022-06-28 09:37:07	ga_ls9c_ard_3-2-1_093080_2022-06-28_final.stac-item
2022-07-08 10:11:46	ga_ls9c_ard_3-2-1_099074_2022-07-08_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final.stac-item
2022-08-27 09:59:48	ga_ls9c_ard_3-2-1_097074_2022-08-27_final.stac-item
2022-09-01 10:18:20	ga_ls9c_ard_3-2-1_100074_2022-09-01_final.stac-item
2022-09-05 09:52:25	ga_ls9c_ard_3-2-1_096071_2022-09-05_final.stac-item
2022-09-09 09:32:28	ga_ls9c_ard_3-2-1_092083_2022-09-09_final.stac-item
2022-09-09 11:10:57	ga_ls9c_ard_3-2-1_108082_2022-09-09_final.stac-item
2022-09-14 09:48:17	ga_ls9c_ard_3-2-1_095076_2022-09-14_final.stac-item
2022-09-23 11:21:27	ga_ls9c_ard_3-2-1_110077_2022-09-23_final.stac-item
2022-10-14 11:41:16	ga_ls9c_ard_3-2-1_113080_2022-10-14_final.stac-item
2022-10-27 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-10-27_final.stac-item
2022-11-01 11:26:54	ga_ls9c_ard_3-2-1_111075_2022-11-01_final.stac-item
2022-11-05 09:24:29	ga_ls9c_ard_3-2-1_091078_2022-11-04_final.stac-item
2022-11-08 09:55:25	ga_ls9c_ard_3-2-1_096078_2022-11-08_final.stac-item
2022-11-08 09:55:49	ga_ls9c_ard_3-2-1_096079_2022-11-08_final.stac-item
2022-11-08 09:57:01	ga_ls9c_ard_3-2-1_096082_2022-11-08_final.stac-item
2022-11-14 10:57:15	ga_ls9c_ard_3-2-1_106078_2022-11-14_final.stac-item
2022-11-17 09:46:29	ga_ls9c_ard_3-2-1_095071_2022-11-17_final.stac-item
2022-12-03 09:48:25	ga_ls9c_ard_3-2-1_095076_2022-12-03_final.stac-item
2022-12-08 10:06:11	ga_ls9c_ard_3-2-1_098074_2022-12-08_final.stac-item
2022-12-28 09:41:51	ga_ls9c_ard_3-2-1_094075_2022-12-28_final.stac-item
2022-12-30 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-30_final.stac-item
2023-01-06 11:15:47	ga_ls9c_ard_3-2-1_109078_2023-01-06_final.stac-item
2023-01-13 09:43:50	ga_ls9c_ard_3-2-1_094080_2023-01-13_final.stac-item
2023-01-14 10:25:29	ga_ls9c_ard_3-2-1_101076_2023-01-14_final.stac-item
2023-01-14 10:26:17	ga_ls9c_ard_3-2-1_101078_2023-01-14_final.stac-item
2023-01-19 10:43:08	ga_ls9c_ard_3-2-1_104074_2023-01-19_final.stac-item
2023-01-20 11:28:46	ga_ls9c_ard_3-2-1_111080_2023-01-20_final.stac-item
2023-01-21 10:31:57	ga_ls9c_ard_3-2-1_102077_2023-01-21_final.stac-item
2023-01-27 09:55:47	ga_ls9c_ard_3-2-1_096079_2023-01-27_final.stac-item
2023-01-27 11:34:16	ga_ls9c_ard_3-2-1_112078_2023-01-27_final.stac-item
2023-02-05 09:50:06	ga_ls9c_ard_3-2-1_095080_2023-02-05_final.stac-item
2023-02-07 11:16:14	ga_ls9c_ard_3-2-1_109079_2023-02-07_final.stac-item
2023-02-08 10:20:37	ga_ls9c_ard_3-2-1_100079_2023-02-08_final.stac-item
2023-02-09 11:04:40	ga_ls9c_ard_3-2-1_107081_2023-02-09_final.stac-item
2023-02-24 10:20:46	ga_ls9c_ard_3-2-1_100080_2023-02-24_final.stac-item
2023-02-26 11:45:42	ga_ls9c_ard_3-2-1_114076_2023-02-26_final.stac-item
2023-03-02 09:46:04	ga_ls9c_ard_3-2-1_094086_2023-03-02_final.stac-item
2023-03-06 09:19:18	ga_ls9c_ard_3-2-1_090081_2023-03-05_final.stac-item
2023-03-13 11:00:43	ga_ls9c_ard_3-2-1_107072_2023-03-13_final.stac-item
2023-03-16 09:53:32	ga_ls9c_ard_3-2-1_096074_2023-03-16_final.stac-item
2023-04-04 10:24:38	ga_ls9c_ard_3-2-1_101075_2023-04-04_final.stac-item
2023-04-09 10:45:08	ga_ls9c_ard_3-2-1_104080_2023-04-09_final.stac-item
2023-04-10 11:29:11	ga_ls9c_ard_3-2-1_111082_2023-04-10_final.stac-item
2023-04-25 10:42:38	ga_ls9c_ard_3-2-1_104074_2023-04-25_final.stac-item
2023-04-30 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-04-30_final.stac-item
2023-05-01 11:46:20	ga_ls9c_ard_3-2-1_114079_2023-05-01_final.stac-item
2023-05-05 11:21:09	ga_ls9c_ard_3-2-1_110078_2023-05-05_final.stac-item
2023-05-07 09:32:18	ga_ls9c_ard_3-2-1_092084_2023-05-07_final.stac-item
2023-05-07 11:06:24	ga_ls9c_ard_3-2-1_108072_2023-05-07_final.stac-item
2023-05-09 09:17:57	ga_ls9c_ard_3-2-1_090079_2023-05-08_final.stac-item
2023-05-15 10:20:55	ga_ls9c_ard_3-2-1_100082_2023-05-15_final.stac-item
2023-05-20 10:34:12	ga_ls9c_ard_3-2-1_103069_2023-05-20_final.stac-item
2023-05-21 09:41:45	ga_ls9c_ard_3-2-1_094077_2023-05-21_final.stac-item
2023-05-22 10:24:36	ga_ls9c_ard_3-2-1_101076_2023-05-22_final.stac-item
2023-06-18 10:05:04	ga_ls9c_ard_3-2-1_098074_2023-06-18_final.stac-item
2023-06-18 10:05:28	ga_ls9c_ard_3-2-1_098075_2023-06-18_final.stac-item
2023-06-20 09:56:18	ga_ls9c_ard_3-2-1_096083_2023-06-20_final.stac-item
2023-06-26 10:56:54	ga_ls9c_ard_3-2-1_106080_2023-06-26_final.stac-item
2023-06-29 09:47:25	ga_ls9c_ard_3-2-1_095076_2023-06-29_final.stac-item
2023-07-26 09:30:15	ga_ls9c_ard_3-2-1_092079_2023-07-26_final.stac-item
2023-08-06 10:47:57	ga_ls9c_ard_3-2-1_105072_2023-08-06_final.stac-item
2023-08-06 10:50:45	ga_ls9c_ard_3-2-1_105079_2023-08-06_final.stac-item
2023-08-17 10:32:37	ga_ls9c_ard_3-2-1_102080_2023-08-17_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-14 11:09:46	ga_ls9c_ard_3-2-1_108079_2023-10-14_final.stac-item
2023-10-15 10:15:21	ga_ls9c_ard_3-2-1_099082_2023-10-15_final.stac-item
2023-10-21 11:15:34	ga_ls9c_ard_3-2-1_109078_2023-10-21_final.stac-item
2023-10-26 09:52:48	ga_ls9c_ard_3-2-1_096072_2023-10-26_final.stac-item
2023-10-26 09:55:36	ga_ls9c_ard_3-2-1_096079_2023-10-26_final.stac-item
2023-10-30 11:11:43	ga_ls9c_ard_3-2-1_108084_2023-10-30_final.stac-item
2023-11-03 10:43:44	ga_ls9c_ard_3-2-1_104076_2023-11-03_final.stac-item
2023-11-04 11:26:37	ga_ls9c_ard_3-2-1_111075_2023-11-04_final.stac-item
2023-11-04 11:29:24	ga_ls9c_ard_3-2-1_111082_2023-11-04_final.stac-item
2023-11-20 09:49:50	ga_ls9c_ard_3-2-1_095080_2023-11-20_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