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
2022-01-08 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-01-08_final.stac-item
2022-01-09 10:38:06	ga_ls9c_ard_3-2-1_103077_2022-01-09_final.stac-item
2022-01-25 10:38:07	ga_ls9c_ard_3-2-1_103077_2022-01-25_final.stac-item
2022-01-26 09:43:17	ga_ls9c_ard_3-2-1_094079_2022-01-26_final.stac-item
2022-02-15 09:22:53	ga_ls9c_ard_3-2-1_090090_2022-02-14_final.stac-item
2022-02-21 10:17:26	ga_ls9c_ard_3-2-1_100072_2022-02-21_final.stac-item
2022-03-12 10:52:13	ga_ls9c_ard_3-2-1_105082_2022-03-12_final.stac-item
2022-04-08 10:32:23	ga_ls9c_ard_3-2-1_102079_2022-04-08_final.stac-item
2022-04-08 10:33:34	ga_ls9c_ard_3-2-1_102082_2022-04-08_final.stac-item
2022-04-09 09:35:33	ga_ls9c_ard_3-2-1_093076_2022-04-09_final.stac-item
2022-04-24 10:27:49	ga_ls9c_ard_3-2-1_102068_2022-04-24_final.stac-item
2022-04-28 10:05:06	ga_ls9c_ard_3-2-1_098073_2022-04-28_final.stac-item
2022-05-06 10:54:29	ga_ls9c_ard_3-2-1_106073_2022-05-06_final.stac-item
2022-06-23 09:20:55	ga_ls9c_ard_3-2-1_090086_2022-06-22_final.stac-item
2022-06-26 09:47:29	ga_ls9c_ard_3-2-1_095075_2022-06-26_final.stac-item
2022-07-01 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-07-01_final.stac-item
2022-07-16 11:01:11	ga_ls9c_ard_3-2-1_107074_2022-07-16_final.stac-item
2022-07-31 10:17:21	ga_ls9c_ard_3-2-1_100072_2022-07-31_final.stac-item
2022-07-31 10:18:09	ga_ls9c_ard_3-2-1_100074_2022-07-31_final.stac-item
2022-07-31 10:18:33	ga_ls9c_ard_3-2-1_100075_2022-07-31_final.stac-item
2022-08-02 10:05:25	ga_ls9c_ard_3-2-1_098073_2022-08-02_final.stac-item
2022-09-12 10:03:25	ga_ls9c_ard_3-2-1_097083_2022-09-12_final.stac-item
2022-09-27 09:20:15	ga_ls9c_ard_3-2-1_090083_2022-09-26_final.stac-item
2022-10-07 09:53:20	ga_ls9c_ard_3-2-1_096073_2022-10-07_final.stac-item
2022-11-10 11:19:58	ga_ls9c_ard_3-2-1_110073_2022-11-10_final.stac-item
2022-11-11 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-11-11_final.stac-item
2022-12-01 09:59:34	ga_ls9c_ard_3-2-1_097073_2022-12-01_final.stac-item
2022-12-01 10:02:46	ga_ls9c_ard_3-2-1_097081_2022-12-01_final.stac-item
2022-12-03 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-12-03_final.stac-item
2022-12-10 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-12-10_final.stac-item
2022-12-14 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-12-14_final.stac-item
2022-12-26 11:35:52	ga_ls9c_ard_3-2-1_112082_2022-12-26_final.stac-item
2023-01-01 10:57:38	ga_ls9c_ard_3-2-1_106079_2023-01-01_final.stac-item
2023-01-04 09:48:27	ga_ls9c_ard_3-2-1_095076_2023-01-04_final.stac-item
2023-01-09 10:06:11	ga_ls9c_ard_3-2-1_098074_2023-01-09_final.stac-item
2023-01-10 10:47:51	ga_ls9c_ard_3-2-1_105070_2023-01-10_final.stac-item
2023-01-18 10:00:41	ga_ls9c_ard_3-2-1_097076_2023-01-18_final.stac-item
2023-01-19 10:44:20	ga_ls9c_ard_3-2-1_104077_2023-01-19_final.stac-item
2023-01-21 10:31:33	ga_ls9c_ard_3-2-1_102076_2023-01-21_final.stac-item
2023-01-24 09:25:14	ga_ls9c_ard_3-2-1_091080_2023-01-23_final.stac-item
2023-01-25 10:07:19	ga_ls9c_ard_3-2-1_098077_2023-01-25_final.stac-item
2023-01-25 10:08:54	ga_ls9c_ard_3-2-1_098081_2023-01-25_final.stac-item
2023-02-03 11:40:08	ga_ls9c_ard_3-2-1_113077_2023-02-03_final.stac-item
2023-02-03 11:40:56	ga_ls9c_ard_3-2-1_113079_2023-02-03_final.stac-item
2023-02-09 09:28:59	ga_ls9c_ard_3-2-1_091089_2023-02-08_final.stac-item
2023-02-09 11:03:52	ga_ls9c_ard_3-2-1_107079_2023-02-09_final.stac-item
2023-02-10 11:45:32	ga_ls9c_ard_3-2-1_114075_2023-02-10_final.stac-item
2023-02-11 09:13:25	ga_ls9c_ard_3-2-1_089081_2023-02-10_final.stac-item
2023-04-22 10:14:10	ga_ls9c_ard_3-2-1_099080_2023-04-22_final.stac-item
2023-04-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2023-04-23_final.stac-item
2023-04-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2023-04-23_final.stac-item
2023-04-24 09:58:59	ga_ls9c_ard_3-2-1_097073_2023-04-24_final.stac-item
2023-04-24 11:39:04	ga_ls9c_ard_3-2-1_113076_2023-04-24_final.stac-item
2023-04-24 11:40:40	ga_ls9c_ard_3-2-1_113080_2023-04-24_final.stac-item
2023-04-26 11:26:17	ga_ls9c_ard_3-2-1_111075_2023-04-26_final.stac-item
2023-04-27 10:29:27	ga_ls9c_ard_3-2-1_102072_2023-04-27_final.stac-item
2023-04-30 09:23:25	ga_ls9c_ard_3-2-1_091077_2023-04-29_final.stac-item
2023-07-16 10:30:52	ga_ls9c_ard_3-2-1_102076_2023-07-16_final.stac-item
2023-07-16 10:31:16	ga_ls9c_ard_3-2-1_102077_2023-07-16_final.stac-item
2023-07-17 11:13:20	ga_ls9c_ard_3-2-1_109074_2023-07-17_final.stac-item
2023-07-18 10:16:55	ga_ls9c_ard_3-2-1_100072_2023-07-18_final.stac-item
2023-07-19 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-07-18_final.stac-item
2023-07-20 10:07:44	ga_ls9c_ard_3-2-1_098080_2023-07-20_final.stac-item
2023-07-20 10:08:08	ga_ls9c_ard_3-2-1_098081_2023-07-20_final.stac-item
2023-07-24 11:22:17	ga_ls9c_ard_3-2-1_110081_2023-07-24_final.stac-item
2023-07-24 11:23:52	ga_ls9c_ard_3-2-1_110085_2023-07-24_final.stac-item
2023-07-29 09:58:49	ga_ls9c_ard_3-2-1_097073_2023-07-29_final.stac-item
2023-07-29 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-07-29_final.stac-item
2023-08-03 10:21:01	ga_ls9c_ard_3-2-1_100082_2023-08-03_final.stac-item
2023-08-05 10:04:41	ga_ls9c_ard_3-2-1_098072_2023-08-05_final.stac-item
2023-08-05 10:05:05	ga_ls9c_ard_3-2-1_098073_2023-08-05_final.stac-item
2023-08-06 09:14:16	ga_ls9c_ard_3-2-1_089085_2023-08-05_final.stac-item
2023-10-14 11:07:22	ga_ls9c_ard_3-2-1_108073_2023-10-14_final.stac-item
2023-10-15 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-10-15_final.stac-item
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-17 09:59:24	ga_ls9c_ard_3-2-1_097073_2023-10-17_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 11:40:17	ga_ls9c_ard_3-2-1_113078_2023-10-17_final.stac-item
2023-10-21 09:33:54	ga_ls9c_ard_3-2-1_093071_2023-10-21_final.stac-item
2023-10-23 09:25:31	ga_ls9c_ard_3-2-1_091081_2023-10-22_final.stac-item
2023-10-24 10:05:35	ga_ls9c_ard_3-2-1_098073_2023-10-24_final.stac-item
2023-10-24 11:46:52	ga_ls9c_ard_3-2-1_114079_2023-10-24_final.stac-item
2023-10-26 09:57:12	ga_ls9c_ard_3-2-1_096083_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 09:41:14	ga_ls9c_ard_3-2-1_094074_2023-10-28_final.stac-item
2023-10-28 11:23:18	ga_ls9c_ard_3-2-1_110082_2023-10-28_final.stac-item
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final.stac-item
2023-11-02 11:40:34	ga_ls9c_ard_3-2-1_113079_2023-11-02_final.stac-item
2023-11-03 10:41:44	ga_ls9c_ard_3-2-1_104071_2023-11-03_final.stac-item
2023-11-05 10:32:36	ga_ls9c_ard_3-2-1_102079_2023-11-05_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-17 10:53:47	ga_ls9c_ard_3-2-1_106070_2023-11-17_final.stac-item
2023-11-19 10:42:15	ga_ls9c_ard_3-2-1_104072_2023-11-19_final.stac-item
2023-11-20 11:29:55	ga_ls9c_ard_3-2-1_111083_2023-11-20_final.stac-item
2023-11-22 09:35:31	ga_ls9c_ard_3-2-1_093075_2023-11-22_final.stac-item
2023-11-22 11:17:35	ga_ls9c_ard_3-2-1_109083_2023-11-22_final.stac-item
2023-11-24 11:03:39	ga_ls9c_ard_3-2-1_107079_2023-11-24_final.stac-item
2023-11-25 11:45:20	ga_ls9c_ard_3-2-1_114075_2023-11-25_final.stac-item
2023-11-26 10:47:19	ga_ls9c_ard_3-2-1_105069_2023-11-26_final.stac-item
2024-02-16 10:37:40	ga_ls9c_ard_3-2-1_103076_2024-02-16_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