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
2021-11-15 09:42:45	ga_ls9c_ard_3-2-1_094079_2021-11-15_final.stac-item
2021-12-16 09:48:16	ga_ls9c_ard_3-2-1_095076_2021-12-16_final.stac-item
2022-01-02 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-01-02_final.stac-item
2022-01-12 11:10:11	ga_ls9c_ard_3-2-1_108080_2022-01-12_final.stac-item
2022-02-13 09:30:05	ga_ls9c_ard_3-2-1_092077_2022-02-13_final.stac-item
2022-02-13 09:35:16	ga_ls9c_ard_3-2-1_092090_2022-02-13_final.stac-item
2022-02-25 09:52:40	ga_ls9c_ard_3-2-1_096072_2022-02-25_final.stac-item
2022-02-28 10:27:07	ga_ls9c_ard_3-2-1_101081_2022-02-28_final.stac-item
2022-03-20 11:38:50	ga_ls9c_ard_3-2-1_113075_2022-03-20_final.stac-item
2022-04-04 09:19:50	ga_ls9c_ard_3-2-1_090083_2022-04-03_final.stac-item
2022-05-02 09:41:33	ga_ls9c_ard_3-2-1_094076_2022-05-02_final.stac-item
2022-05-07 09:59:39	ga_ls9c_ard_3-2-1_097075_2022-05-07_final.stac-item
2022-05-13 09:23:42	ga_ls9c_ard_3-2-1_091078_2022-05-12_final.stac-item
2022-05-18 09:42:34	ga_ls9c_ard_3-2-1_094079_2022-05-18_final.stac-item
2022-05-28 10:18:01	ga_ls9c_ard_3-2-1_100075_2022-05-28_final.stac-item
2022-05-31 10:48:08	ga_ls9c_ard_3-2-1_105073_2022-05-31_final.stac-item
2022-06-25 10:44:18	ga_ls9c_ard_3-2-1_104078_2022-06-25_final.stac-item
2022-07-02 10:48:29	ga_ls9c_ard_3-2-1_105073_2022-07-02_final.stac-item
2022-07-10 10:02:11	ga_ls9c_ard_3-2-1_097081_2022-07-10_final.stac-item
2022-07-14 11:11:32	ga_ls9c_ard_3-2-1_109069_2022-07-14_final.stac-item
2022-08-06 09:44:44	ga_ls9c_ard_3-2-1_094083_2022-08-06_final.stac-item
2022-08-26 09:18:56	ga_ls9c_ard_3-2-1_090080_2022-08-25_final.stac-item
2022-10-04 11:03:19	ga_ls9c_ard_3-2-1_107078_2022-10-04_final.stac-item
2022-10-08 10:38:36	ga_ls9c_ard_3-2-1_103078_2022-10-08_final.stac-item
2022-10-13 10:57:12	ga_ls9c_ard_3-2-1_106078_2022-10-13_final.stac-item
2022-10-15 10:44:51	ga_ls9c_ard_3-2-1_104078_2022-10-15_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-10-26 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-10-26_final.stac-item
2022-10-28 10:12:22	ga_ls9c_ard_3-2-1_099074_2022-10-28_final.stac-item
2022-10-30 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-10-30_final.stac-item
2022-11-08 09:56:13	ga_ls9c_ard_3-2-1_096080_2022-11-08_final.stac-item
2022-11-25 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-11-25_final.stac-item
2022-11-26 09:42:40	ga_ls9c_ard_3-2-1_094077_2022-11-26_final.stac-item
2022-12-01 10:03:34	ga_ls9c_ard_3-2-1_097083_2022-12-01_final.stac-item
2022-12-06 10:20:32	ga_ls9c_ard_3-2-1_100079_2022-12-06_final.stac-item
2022-12-18 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-12-18_final.stac-item
2022-12-23 11:04:09	ga_ls9c_ard_3-2-1_107080_2022-12-23_final.stac-item
2022-12-23 11:04:57	ga_ls9c_ard_3-2-1_107082_2022-12-23_final.stac-item
2022-12-24 10:08:55	ga_ls9c_ard_3-2-1_098081_2022-12-24_final.stac-item
2023-01-03 10:41:17	ga_ls9c_ard_3-2-1_104069_2023-01-03_final.stac-item
2023-01-06 11:14:59	ga_ls9c_ard_3-2-1_109076_2023-01-06_final.stac-item
2023-01-14 10:26:17	ga_ls9c_ard_3-2-1_101078_2023-01-14_final.stac-item
2023-01-15 11:08:44	ga_ls9c_ard_3-2-1_108076_2023-01-15_final.stac-item
2023-01-23 10:21:38	ga_ls9c_ard_3-2-1_100082_2023-01-23_final.stac-item
2023-01-24 11:04:07	ga_ls9c_ard_3-2-1_107080_2023-01-24_final.stac-item
2023-01-25 10:08:54	ga_ls9c_ard_3-2-1_098081_2023-01-25_final.stac-item
2023-01-27 09:56:59	ga_ls9c_ard_3-2-1_096082_2023-01-27_final.stac-item
2023-02-04 10:42:31	ga_ls9c_ard_3-2-1_104072_2023-02-04_final.stac-item
2023-02-05 11:28:11	ga_ls9c_ard_3-2-1_111078_2023-02-05_final.stac-item
2023-02-09 09:28:59	ga_ls9c_ard_3-2-1_091089_2023-02-08_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 09:18:32	ga_ls9c_ard_3-2-1_090080_2023-04-22_final.stac-item
2023-04-24 10:00:35	ga_ls9c_ard_3-2-1_097077_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
2023-04-27 10:29:27	ga_ls9c_ard_3-2-1_102072_2023-04-27_final.stac-item
2023-05-01 10:05:52	ga_ls9c_ard_3-2-1_098075_2023-05-01_final.stac-item
2023-05-01 10:06:16	ga_ls9c_ard_3-2-1_098076_2023-05-01_final.stac-item
2023-05-05 09:43:28	ga_ls9c_ard_3-2-1_094081_2023-05-05_final.stac-item
2023-05-09 09:19:33	ga_ls9c_ard_3-2-1_090083_2023-05-08_final.stac-item
2023-05-13 10:29:18	ga_ls9c_ard_3-2-1_102072_2023-05-13_final.stac-item
2023-06-21 10:35:58	ga_ls9c_ard_3-2-1_103074_2023-06-21_final.stac-item
2023-06-22 09:40:45	ga_ls9c_ard_3-2-1_094075_2023-06-22_final.stac-item
2023-06-22 09:44:20	ga_ls9c_ard_3-2-1_094084_2023-06-22_final.stac-item
2023-06-22 11:22:01	ga_ls9c_ard_3-2-1_110081_2023-06-22_final.stac-item
2023-06-24 09:30:46	ga_ls9c_ard_3-2-1_092081_2023-06-24_final.stac-item
2023-06-25 10:11:38	ga_ls9c_ard_3-2-1_099075_2023-06-25_final.stac-item
2023-06-29 09:47:01	ga_ls9c_ard_3-2-1_095075_2023-06-29_final.stac-item
2023-06-29 11:25:54	ga_ls9c_ard_3-2-1_111075_2023-06-29_final.stac-item
2023-07-06 09:55:19	ga_ls9c_ard_3-2-1_096080_2023-07-06_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 09:38:02	ga_ls9c_ard_3-2-1_093083_2023-07-17_final.stac-item
2023-07-20 11:44:38	ga_ls9c_ard_3-2-1_114075_2023-07-20_final.stac-item
2023-07-21 10:50:36	ga_ls9c_ard_3-2-1_105079_2023-07-21_final.stac-item
2023-07-22 09:52:11	ga_ls9c_ard_3-2-1_096072_2023-07-22_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 10:35:50	ga_ls9c_ard_3-2-1_103073_2023-07-23_final.stac-item
2023-07-24 09:41:24	ga_ls9c_ard_3-2-1_094076_2023-07-24_final.stac-item
2023-07-25 10:23:04	ga_ls9c_ard_3-2-1_101072_2023-07-25_final.stac-item
2023-07-26 09:31:51	ga_ls9c_ard_3-2-1_092083_2023-07-26_final.stac-item
2023-08-02 11:11:27	ga_ls9c_ard_3-2-1_109069_2023-08-02_final.stac-item
2023-08-03 10:21:49	ga_ls9c_ard_3-2-1_100084_2023-08-03_final.stac-item
2023-08-08 10:34:49	ga_ls9c_ard_3-2-1_103070_2023-08-08_final.stac-item
2023-08-17 10:29:26	ga_ls9c_ard_3-2-1_102072_2023-08-17_final.stac-item
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_final.stac-item
2023-10-21 09:36:41	ga_ls9c_ard_3-2-1_093078_2023-10-21_final.stac-item
2023-10-22 11:58:50	ga_ls9c_ard_3-2-1_116078_2023-10-22_final.stac-item
2023-10-26 09:54:48	ga_ls9c_ard_3-2-1_096077_2023-10-26_final.stac-item
2023-10-26 09:56:24	ga_ls9c_ard_3-2-1_096081_2023-10-26_final.stac-item
2023-10-27 10:37:15	ga_ls9c_ard_3-2-1_103075_2023-10-27_final.stac-item
2023-10-28 09:43:37	ga_ls9c_ard_3-2-1_094080_2023-10-28_final.stac-item
2023-11-01 10:56:32	ga_ls9c_ard_3-2-1_106077_2023-11-01_final.stac-item
2023-11-01 10:58:07	ga_ls9c_ard_3-2-1_106081_2023-11-01_final.stac-item
2023-11-16 10:12:06	ga_ls9c_ard_3-2-1_099074_2023-11-16_final.stac-item
2023-11-18 10:00:58	ga_ls9c_ard_3-2-1_097077_2023-11-18_final.stac-item
2023-11-18 11:40:39	ga_ls9c_ard_3-2-1_113079_2023-11-18_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_2023-11-20_final.stac-item
2023-11-20 11:29:55	ga_ls9c_ard_3-2-1_111083_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

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