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
2021-11-05 09:37:25	ga_ls9c_ard_3-2-1_093078_2021-11-05_final.stac-item
2021-11-10 11:16:57	ga_ls9c_ard_3-2-1_110074_2021-11-10_final.stac-item
2022-01-08 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-01-08_final.stac-item
2022-03-11 10:09:22	ga_ls9c_ard_3-2-1_098083_2022-03-11_final.stac-item
2022-03-27 10:08:05	ga_ls9c_ard_3-2-1_098080_2022-03-27_final.stac-item
2022-05-30 10:04:28	ga_ls9c_ard_3-2-1_098072_2022-05-30_final.stac-item
2022-06-05 09:30:35	ga_ls9c_ard_3-2-1_092080_2022-06-05_final.stac-item
2022-06-12 09:36:25	ga_ls9c_ard_3-2-1_093079_2022-06-12_final.stac-item
2022-06-13 10:20:53	ga_ls9c_ard_3-2-1_100082_2022-06-13_final.stac-item
2022-06-15 10:09:45	ga_ls9c_ard_3-2-1_098085_2022-06-15_final.stac-item
2022-07-26 09:58:21	ga_ls9c_ard_3-2-1_097071_2022-07-26_final.stac-item
2022-08-15 09:37:50	ga_ls9c_ard_3-2-1_093081_2022-08-15_final.stac-item
2022-08-27 10:03:23	ga_ls9c_ard_3-2-1_097083_2022-08-27_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-19 10:10:27	ga_ls9c_ard_3-2-1_098085_2022-09-19_final.stac-item
2022-09-27 09:19:03	ga_ls9c_ard_3-2-1_090080_2022-09-26_final.stac-item
2022-10-01 10:32:01	ga_ls9c_ard_3-2-1_102077_2022-10-01_final.stac-item
2022-10-10 10:26:16	ga_ls9c_ard_3-2-1_101078_2022-10-10_final.stac-item
2022-10-11 09:35:27	ga_ls9c_ard_3-2-1_092090_2022-10-11_final.stac-item
2022-10-12 11:52:01	ga_ls9c_ard_3-2-1_115076_2022-10-12_final.stac-item
2022-11-05 11:02:11	ga_ls9c_ard_3-2-1_107075_2022-11-05_final.stac-item
2022-11-10 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-11-10_final.stac-item
2022-11-21 09:24:57	ga_ls9c_ard_3-2-1_091079_2022-11-20_final.stac-item
2022-11-22 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-11-22_final.stac-item
2022-11-24 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-11-24_final.stac-item
2022-11-24 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-11-24_final.stac-item
2022-11-30 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-11-30_final.stac-item
2022-12-07 11:03:48	ga_ls9c_ard_3-2-1_107079_2022-12-07_final.stac-item
2022-12-09 10:47:51	ga_ls9c_ard_3-2-1_105070_2022-12-09_final.stac-item
2022-12-21 09:36:27	ga_ls9c_ard_3-2-1_093077_2022-12-21_final.stac-item
2022-12-21 09:36:51	ga_ls9c_ard_3-2-1_093078_2022-12-21_final.stac-item
2022-12-23 09:24:28	ga_ls9c_ard_3-2-1_091078_2022-12-22_final.stac-item
2022-12-23 11:03:45	ga_ls9c_ard_3-2-1_107079_2022-12-23_final.stac-item
2022-12-25 09:15:19	ga_ls9c_ard_3-2-1_089086_2022-12-24_final.stac-item
2022-12-28 11:23:31	ga_ls9c_ard_3-2-1_110082_2022-12-28_final.stac-item
2022-12-31 10:12:22	ga_ls9c_ard_3-2-1_099074_2022-12-31_final.stac-item
2023-01-02 10:01:13	ga_ls9c_ard_3-2-1_097077_2023-01-02_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-08 09:24:32	ga_ls9c_ard_3-2-1_091078_2023-01-07_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_final.stac-item
2023-01-19 10:43:08	ga_ls9c_ard_3-2-1_104074_2023-01-19_final.stac-item
2023-01-19 10:45:32	ga_ls9c_ard_3-2-1_104080_2023-01-19_final.stac-item
2023-01-22 09:35:57	ga_ls9c_ard_3-2-1_093076_2023-01-22_final.stac-item
2023-01-24 11:03:43	ga_ls9c_ard_3-2-1_107079_2023-01-24_final.stac-item
2023-01-26 09:14:30	ga_ls9c_ard_3-2-1_089084_2023-01-25_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-01-30 10:24:44	ga_ls9c_ard_3-2-1_101074_2023-01-30_final.stac-item
2023-02-02 09:19:34	ga_ls9c_ard_3-2-1_090081_2023-02-01_final.stac-item
2023-04-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2023-04-22_final.stac-item
2023-04-26 09:47:00	ga_ls9c_ard_3-2-1_095074_2023-04-26_final.stac-item
2023-04-28 11:12:18	ga_ls9c_ard_3-2-1_109071_2023-04-28_final.stac-item
2023-04-30 09:23:01	ga_ls9c_ard_3-2-1_091076_2023-04-29_final.stac-item
2023-04-30 09:25:25	ga_ls9c_ard_3-2-1_091082_2023-04-29_final.stac-item
2023-04-30 11:05:06	ga_ls9c_ard_3-2-1_107084_2023-04-30_final.stac-item
2023-05-01 11:46:44	ga_ls9c_ard_3-2-1_114080_2023-05-01_final.stac-item
2023-05-03 11:35:08	ga_ls9c_ard_3-2-1_112082_2023-05-03_final.stac-item
2023-05-05 09:40:16	ga_ls9c_ard_3-2-1_094073_2023-05-05_final.stac-item
2023-05-06 10:24:44	ga_ls9c_ard_3-2-1_101076_2023-05-06_final.stac-item
2023-05-09 09:17:33	ga_ls9c_ard_3-2-1_090078_2023-05-08_final.stac-item
2023-05-09 10:53:38	ga_ls9c_ard_3-2-1_106071_2023-05-09_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-06-01 09:23:09	ga_ls9c_ard_3-2-1_091077_2023-05-31_final.stac-item
2023-06-01 09:25:33	ga_ls9c_ard_3-2-1_091083_2023-05-31_final.stac-item
2023-06-21 10:39:10	ga_ls9c_ard_3-2-1_103082_2023-06-21_final.stac-item
2023-06-22 11:22:25	ga_ls9c_ard_3-2-1_110082_2023-06-22_final.stac-item
2023-06-23 10:24:24	ga_ls9c_ard_3-2-1_101076_2023-06-23_final.stac-item
2023-06-26 09:18:25	ga_ls9c_ard_3-2-1_090081_2023-06-25_final.stac-item
2023-06-27 09:58:55	ga_ls9c_ard_3-2-1_097074_2023-06-27_final.stac-item
2023-07-19 11:03:22	ga_ls9c_ard_3-2-1_107080_2023-07-19_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-20 11:46:37	ga_ls9c_ard_3-2-1_114080_2023-07-20_final.stac-item
2023-07-21 09:12:31	ga_ls9c_ard_3-2-1_089081_2023-07-20_final.stac-item
2023-07-26 11:05:57	ga_ls9c_ard_3-2-1_108071_2023-07-26_final.stac-item
2023-07-27 10:11:08	ga_ls9c_ard_3-2-1_099073_2023-07-27_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 10:53:37	ga_ls9c_ard_3-2-1_106071_2023-07-28_final.stac-item
2023-07-28 10:54:25	ga_ls9c_ard_3-2-1_106073_2023-07-28_final.stac-item
2023-07-29 10:00:49	ga_ls9c_ard_3-2-1_097078_2023-07-29_final.stac-item
2023-07-29 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-07-29_final.stac-item
2023-08-02 11:11:50	ga_ls9c_ard_3-2-1_109070_2023-08-02_final.stac-item
2023-08-05 11:45:10	ga_ls9c_ard_3-2-1_114076_2023-08-05_final.stac-item
2023-10-14 11:07:46	ga_ls9c_ard_3-2-1_108074_2023-10-14_final.stac-item
2023-10-14 11:11:21	ga_ls9c_ard_3-2-1_108083_2023-10-14_final.stac-item
2023-10-17 10:03:48	ga_ls9c_ard_3-2-1_097084_2023-10-17_final.stac-item
2023-10-19 09:52:38	ga_ls9c_ard_3-2-1_095087_2023-10-19_final.stac-item
2023-10-24 11:44:52	ga_ls9c_ard_3-2-1_114074_2023-10-24_final.stac-item
2023-10-29 10:23:41	ga_ls9c_ard_3-2-1_101072_2023-10-29_final.stac-item
2023-11-02 10:01:41	ga_ls9c_ard_3-2-1_097079_2023-11-02_final.stac-item
2023-11-03 10:40:56	ga_ls9c_ard_3-2-1_104069_2023-11-03_final.stac-item
2023-11-03 10:41:20	ga_ls9c_ard_3-2-1_104070_2023-11-03_final.stac-item
2023-11-05 10:28:37	ga_ls9c_ard_3-2-1_102069_2023-11-05_final.stac-item
2023-11-05 10:31:48	ga_ls9c_ard_3-2-1_102077_2023-11-05_final.stac-item
2023-11-15 11:10:54	ga_ls9c_ard_3-2-1_108082_2023-11-15_final.stac-item
2023-11-20 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-11-20_final.stac-item
2023-11-22 11:12:48	ga_ls9c_ard_3-2-1_109071_2023-11-22_final.stac-item
2023-11-24 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_final.stac-item
2023-11-24 11:00:04	ga_ls9c_ard_3-2-1_107070_2023-11-24_final.stac-item
2023-11-24 11:01:16	ga_ls9c_ard_3-2-1_107073_2023-11-24_final.stac-item
2023-11-25 10:06:27	ga_ls9c_ard_3-2-1_098075_2023-11-25_final.stac-item
2023-11-26 10:49:43	ga_ls9c_ard_3-2-1_105075_2023-11-26_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