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
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2021-12-29 10:56:40	ga_ls9c_ard_3-2-1_106077_2021-12-29_final.stac-item
2022-01-28 09:30:08	ga_ls9c_ard_3-2-1_092077_2022-01-28_final.stac-item
2022-02-13 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-02-13_final.stac-item
2022-02-15 09:20:06	ga_ls9c_ard_3-2-1_090083_2022-02-14_final.stac-item
2022-03-27 10:08:05	ga_ls9c_ard_3-2-1_098080_2022-03-27_final.stac-item
2022-03-31 09:43:46	ga_ls9c_ard_3-2-1_094081_2022-03-31_final.stac-item
2022-04-02 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-04-02_final.stac-item
2022-04-06 10:45:09	ga_ls9c_ard_3-2-1_104080_2022-04-06_final.stac-item
2022-06-16 10:48:14	ga_ls9c_ard_3-2-1_105073_2022-06-16_final.stac-item
2022-06-23 09:19:43	ga_ls9c_ard_3-2-1_090083_2022-06-22_final.stac-item
2022-07-02 10:48:29	ga_ls9c_ard_3-2-1_105073_2022-07-02_final.stac-item
2022-07-18 10:48:28	ga_ls9c_ard_3-2-1_105073_2022-07-18_final.stac-item
2022-08-05 10:39:09	ga_ls9c_ard_3-2-1_103080_2022-08-05_final.stac-item
2022-08-21 10:39:16	ga_ls9c_ard_3-2-1_103080_2022-08-21_final.stac-item
2022-10-05 11:45:22	ga_ls9c_ard_3-2-1_114075_2022-10-05_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-29 09:20:20	ga_ls9c_ard_3-2-1_090083_2022-10-28_final.stac-item
2022-10-29 10:58:25	ga_ls9c_ard_3-2-1_106081_2022-10-29_final.stac-item
2022-11-13 10:11:59	ga_ls9c_ard_3-2-1_099073_2022-11-13_final.stac-item
2022-11-21 09:24:09	ga_ls9c_ard_3-2-1_091077_2022-11-20_final.stac-item
2022-12-06 10:20:32	ga_ls9c_ard_3-2-1_100079_2022-12-06_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 09:55:50	ga_ls9c_ard_3-2-1_096079_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
2023-01-01 10:57:38	ga_ls9c_ard_3-2-1_106079_2023-01-01_final.stac-item
2023-01-17 09:19:03	ga_ls9c_ard_3-2-1_090080_2023-01-16_final.stac-item
2023-01-27 09:54:59	ga_ls9c_ard_3-2-1_096077_2023-01-27_final.stac-item
2023-01-29 09:42:39	ga_ls9c_ard_3-2-1_094077_2023-01-29_final.stac-item
2023-02-01 11:51:16	ga_ls9c_ard_3-2-1_115074_2023-02-01_final.stac-item
2023-02-07 11:13:02	ga_ls9c_ard_3-2-1_109071_2023-02-07_final.stac-item
2023-02-10 10:08:15	ga_ls9c_ard_3-2-1_098079_2023-02-10_final.stac-item
2023-02-11 10:48:43	ga_ls9c_ard_3-2-1_105072_2023-02-11_final.stac-item
2023-02-13 10:36:44	ga_ls9c_ard_3-2-1_103073_2023-02-13_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2023-04-22_final.stac-item
2023-04-25 10:41:27	ga_ls9c_ard_3-2-1_104071_2023-04-25_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-25 10:45:02	ga_ls9c_ard_3-2-1_104080_2023-04-25_final.stac-item
2023-04-26 09:49:48	ga_ls9c_ard_3-2-1_095081_2023-04-26_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-28 11:12:18	ga_ls9c_ard_3-2-1_109071_2023-04-28_final.stac-item
2023-04-29 10:20:39	ga_ls9c_ard_3-2-1_100081_2023-04-29_final.stac-item
2023-04-30 09:24:37	ga_ls9c_ard_3-2-1_091080_2023-04-29_final.stac-item
2023-04-30 11:04:18	ga_ls9c_ard_3-2-1_107082_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
2023-05-30 09:37:54	ga_ls9c_ard_3-2-1_093083_2023-05-30_final.stac-item
2023-06-01 09:23:09	ga_ls9c_ard_3-2-1_091077_2023-05-31_final.stac-item
2023-07-16 10:30:04	ga_ls9c_ard_3-2-1_102074_2023-07-16_final.stac-item
2023-07-16 10:30:28	ga_ls9c_ard_3-2-1_102075_2023-07-16_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 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-20 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-07-20_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-07-26 09:31:51	ga_ls9c_ard_3-2-1_092083_2023-07-26_final.stac-item
2023-07-28 09:17:56	ga_ls9c_ard_3-2-1_090079_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
2023-07-28 10:56:49	ga_ls9c_ard_3-2-1_106079_2023-07-28_final.stac-item
2023-07-29 09:58:49	ga_ls9c_ard_3-2-1_097073_2023-07-29_final.stac-item
2023-08-02 09:37:21	ga_ls9c_ard_3-2-1_093081_2023-08-02_final.stac-item
2023-08-02 11:15:02	ga_ls9c_ard_3-2-1_109078_2023-08-02_final.stac-item
2023-08-02 11:15:50	ga_ls9c_ard_3-2-1_109080_2023-08-02_final.stac-item
2023-08-04 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-08-04_final.stac-item
2023-08-05 11:44:46	ga_ls9c_ard_3-2-1_114075_2023-08-05_final.stac-item
2023-08-08 10:36:24	ga_ls9c_ard_3-2-1_103074_2023-08-08_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 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-10-15_final.stac-item
2023-10-15 10:15:21	ga_ls9c_ard_3-2-1_099082_2023-10-15_final.stac-item
2023-10-16 09:19:20	ga_ls9c_ard_3-2-1_090081_2023-10-15_final.stac-item
2023-10-16 10:58:13	ga_ls9c_ard_3-2-1_106081_2023-10-16_final.stac-item
2023-10-17 10:03:24	ga_ls9c_ard_3-2-1_097083_2023-10-17_final.stac-item
2023-10-18 10:45:28	ga_ls9c_ard_3-2-1_104080_2023-10-18_final.stac-item
2023-10-19 09:50:15	ga_ls9c_ard_3-2-1_095081_2023-10-19_final.stac-item
2023-10-19 11:23:56	ga_ls9c_ard_3-2-1_111068_2023-10-19_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-21 09:38:17	ga_ls9c_ard_3-2-1_093082_2023-10-21_final.stac-item
2023-10-23 11:03:12	ga_ls9c_ard_3-2-1_107078_2023-10-23_final.stac-item
2023-10-25 09:12:45	ga_ls9c_ard_3-2-1_089080_2023-10-24_final.stac-item
2023-10-25 10:47:38	ga_ls9c_ard_3-2-1_105070_2023-10-25_final.stac-item
2023-10-26 09:56:48	ga_ls9c_ard_3-2-1_096082_2023-10-26_final.stac-item
2023-10-26 11:35:17	ga_ls9c_ard_3-2-1_112081_2023-10-26_final.stac-item
2023-10-28 11:23:18	ga_ls9c_ard_3-2-1_110082_2023-10-28_final.stac-item
2023-10-28 11:23:42	ga_ls9c_ard_3-2-1_110083_2023-10-28_final.stac-item
2023-10-29 10:23:41	ga_ls9c_ard_3-2-1_101072_2023-10-29_final.stac-item
2023-10-29 10:26:04	ga_ls9c_ard_3-2-1_101078_2023-10-29_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-10-30 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-10-30_final.stac-item
2023-10-30 11:09:43	ga_ls9c_ard_3-2-1_108079_2023-10-30_final.stac-item
2023-10-31 10:12:05	ga_ls9c_ard_3-2-1_099074_2023-10-31_final.stac-item
2023-10-31 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-10-31_final.stac-item
2023-10-31 11:50:58	ga_ls9c_ard_3-2-1_115074_2023-10-31_final.stac-item
2023-11-01 10:56:55	ga_ls9c_ard_3-2-1_106078_2023-11-01_final.stac-item
2023-11-02 10:01:41	ga_ls9c_ard_3-2-1_097079_2023-11-02_final.stac-item
2023-11-14 10:22:52	ga_ls9c_ard_3-2-1_101070_2023-11-14_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-17 10:56:34	ga_ls9c_ard_3-2-1_106077_2023-11-17_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_2023-11-20_final.stac-item
2023-11-21 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-11-21_final.stac-item
2023-11-25 11:44:56	ga_ls9c_ard_3-2-1_114074_2023-11-25_final.stac-item
2023-11-25 11:45:44	ga_ls9c_ard_3-2-1_114076_2023-11-25_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