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 09:39:48	ga_ls9c_ard_3-2-1_093084_2021-11-05_final.stac-item
2021-11-08 11:36:54	ga_ls9c_ard_3-2-1_113077_2021-11-08_final.stac-item
2021-11-14 10:41:27	ga_ls9c_ard_3-2-1_103079_2021-11-14_final.stac-item
2021-12-23 09:54:28	ga_ls9c_ard_3-2-1_096076_2021-12-23_final.stac-item
2021-12-31 10:43:30	ga_ls9c_ard_3-2-1_104075_2021-12-31_final.stac-item
2022-01-01 09:49:05	ga_ls9c_ard_3-2-1_095078_2022-01-01_final.stac-item
2022-01-07 10:50:52	ga_ls9c_ard_3-2-1_105078_2022-01-07_final.stac-item
2022-02-25 09:54:16	ga_ls9c_ard_3-2-1_096076_2022-02-25_final.stac-item
2022-02-25 11:33:33	ga_ls9c_ard_3-2-1_112077_2022-02-25_final.stac-item
2022-02-26 10:38:43	ga_ls9c_ard_3-2-1_103079_2022-02-26_final.stac-item
2022-03-01 11:09:10	ga_ls9c_ard_3-2-1_108078_2022-03-01_final.stac-item
2022-03-06 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-03-06_final.stac-item
2022-03-12 10:50:38	ga_ls9c_ard_3-2-1_105078_2022-03-12_final.stac-item
2022-03-20 11:40:02	ga_ls9c_ard_3-2-1_113078_2022-03-20_final.stac-item
2022-04-01 10:26:37	ga_ls9c_ard_3-2-1_101080_2022-04-01_final.stac-item
2022-04-16 11:21:20	ga_ls9c_ard_3-2-1_110078_2022-04-16_final.stac-item
2022-05-01 10:38:23	ga_ls9c_ard_3-2-1_103079_2022-05-01_final.stac-item
2022-05-10 10:32:07	ga_ls9c_ard_3-2-1_102079_2022-05-10_final.stac-item
2022-05-23 10:02:16	ga_ls9c_ard_3-2-1_097082_2022-05-23_final.stac-item
2022-05-24 10:45:08	ga_ls9c_ard_3-2-1_104081_2022-05-24_final.stac-item
2022-05-25 11:27:35	ga_ls9c_ard_3-2-1_111079_2022-05-25_final.stac-item
2022-05-26 10:31:34	ga_ls9c_ard_3-2-1_102078_2022-05-26_final.stac-item
2022-06-01 11:33:23	ga_ls9c_ard_3-2-1_112078_2022-06-01_final.stac-item
2022-06-19 11:21:36	ga_ls9c_ard_3-2-1_110079_2022-06-19_final.stac-item
2022-07-05 11:21:46	ga_ls9c_ard_3-2-1_110079_2022-07-05_final.stac-item
2022-07-10 11:39:28	ga_ls9c_ard_3-2-1_113077_2022-07-10_final.stac-item
2022-07-13 10:32:16	ga_ls9c_ard_3-2-1_102079_2022-07-13_final.stac-item
2022-07-24 10:14:40	ga_ls9c_ard_3-2-1_099081_2022-07-24_final.stac-item
2022-08-09 10:14:52	ga_ls9c_ard_3-2-1_099081_2022-08-09_final.stac-item
2022-08-14 10:32:39	ga_ls9c_ard_3-2-1_102079_2022-08-14_final.stac-item
2022-08-29 11:28:19	ga_ls9c_ard_3-2-1_111079_2022-08-29_final.stac-item
2022-08-31 09:36:16	ga_ls9c_ard_3-2-1_093077_2022-08-31_final.stac-item
2022-09-14 09:48:41	ga_ls9c_ard_3-2-1_095077_2022-09-14_final.stac-item
2022-09-15 10:33:09	ga_ls9c_ard_3-2-1_102080_2022-09-15_final.stac-item
2022-09-19 10:08:51	ga_ls9c_ard_3-2-1_098081_2022-09-19_final.stac-item
2022-09-28 11:39:36	ga_ls9c_ard_3-2-1_113076_2022-09-28_final.stac-item
2022-10-10 10:26:40	ga_ls9c_ard_3-2-1_101079_2022-10-10_final.stac-item
2022-10-14 10:00:23	ga_ls9c_ard_3-2-1_097075_2022-10-14_final.stac-item
2022-10-23 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-10-23_final.stac-item
2022-10-24 10:39:06	ga_ls9c_ard_3-2-1_103079_2022-10-24_final.stac-item
2022-11-04 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-11-04_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-12-01 11:40:51	ga_ls9c_ard_3-2-1_113079_2022-12-01_final.stac-item
2022-12-09 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-12-09_final.stac-item
2022-12-10 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-12-10_final.stac-item
2022-12-15 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-15_final.stac-item
2022-12-16 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-12-16_final.stac-item
2022-12-17 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-12-17_final.stac-item
2022-12-26 11:34:16	ga_ls9c_ard_3-2-1_112078_2022-12-26_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2022-12-30 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-12-30_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-02-05 09:48:30	ga_ls9c_ard_3-2-1_095076_2023-02-05_final.stac-item
2023-02-16 11:09:35	ga_ls9c_ard_3-2-1_108078_2023-02-16_final.stac-item
2023-03-02 09:42:52	ga_ls9c_ard_3-2-1_094078_2023-03-02_final.stac-item
2023-03-07 10:02:56	ga_ls9c_ard_3-2-1_097082_2023-03-07_final.stac-item
2023-03-08 10:44:59	ga_ls9c_ard_3-2-1_104079_2023-03-08_final.stac-item
2023-03-24 10:44:53	ga_ls9c_ard_3-2-1_104079_2023-03-24_final.stac-item
2023-04-11 10:32:21	ga_ls9c_ard_3-2-1_102079_2023-04-11_final.stac-item
2023-04-21 11:08:35	ga_ls9c_ard_3-2-1_108077_2023-04-21_final.stac-item
2023-05-05 11:17:57	ga_ls9c_ard_3-2-1_110070_2023-05-05_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-10 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-05-10_final.stac-item
2023-05-13 10:30:54	ga_ls9c_ard_3-2-1_102076_2023-05-13_final.stac-item
2023-05-22 10:26:12	ga_ls9c_ard_3-2-1_101080_2023-05-22_final.stac-item
2023-05-24 10:14:12	ga_ls9c_ard_3-2-1_099081_2023-05-24_final.stac-item
2023-05-26 10:02:14	ga_ls9c_ard_3-2-1_097082_2023-05-26_final.stac-item
2023-05-26 11:39:31	ga_ls9c_ard_3-2-1_113078_2023-05-26_final.stac-item
2023-06-02 10:05:36	ga_ls9c_ard_3-2-1_098075_2023-06-02_final.stac-item
2023-06-06 09:40:52	ga_ls9c_ard_3-2-1_094075_2023-06-06_final.stac-item
2023-06-08 09:31:16	ga_ls9c_ard_3-2-1_092082_2023-06-08_final.stac-item
2023-06-13 11:27:26	ga_ls9c_ard_3-2-1_111079_2023-06-13_final.stac-item
2023-06-18 10:08:15	ga_ls9c_ard_3-2-1_098082_2023-06-18_final.stac-item
2023-06-25 10:14:02	ga_ls9c_ard_3-2-1_099081_2023-06-25_final.stac-item
2023-07-16 10:31:40	ga_ls9c_ard_3-2-1_102078_2023-07-16_final.stac-item
2023-09-06 10:08:56	ga_ls9c_ard_3-2-1_098082_2023-09-06_final.stac-item
2023-09-15 11:39:19	ga_ls9c_ard_3-2-1_113076_2023-09-15_final.stac-item
2023-09-18 10:31:21	ga_ls9c_ard_3-2-1_102076_2023-09-18_final.stac-item
2023-09-20 11:58:16	ga_ls9c_ard_3-2-1_116077_2023-09-20_final.stac-item
2023-09-22 10:08:36	ga_ls9c_ard_3-2-1_098081_2023-09-22_final.stac-item
2023-09-24 11:34:18	ga_ls9c_ard_3-2-1_112079_2023-09-24_final.stac-item
2023-09-25 10:38:40	ga_ls9c_ard_3-2-1_103079_2023-09-25_final.stac-item
2023-09-26 09:43:02	ga_ls9c_ard_3-2-1_094079_2023-09-26_final.stac-item
2023-10-01 10:02:48	ga_ls9c_ard_3-2-1_097082_2023-10-01_final.stac-item
2023-10-03 09:49:17	ga_ls9c_ard_3-2-1_095079_2023-10-03_final.stac-item
2023-10-09 10:50:44	ga_ls9c_ard_3-2-1_105078_2023-10-09_final.stac-item
2023-10-19 09:49:27	ga_ls9c_ard_3-2-1_095079_2023-10-19_final.stac-item
2023-10-24 10:08:46	ga_ls9c_ard_3-2-1_098081_2023-10-24_final.stac-item
2023-10-25 10:50:50	ga_ls9c_ard_3-2-1_105078_2023-10-25_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-11-03 10:44:56	ga_ls9c_ard_3-2-1_104079_2023-11-03_final.stac-item
2023-11-04 09:48:32	ga_ls9c_ard_3-2-1_095077_2023-11-04_final.stac-item
2023-11-04 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-11-04_final.stac-item
2023-11-04 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-11-04_final.stac-item
2023-11-10 10:52:22	ga_ls9c_ard_3-2-1_105082_2023-11-10_final.stac-item
2023-11-13 09:42:48	ga_ls9c_ard_3-2-1_094078_2023-11-13_final.stac-item
2023-12-20 10:00:18	ga_ls9c_ard_3-2-1_097075_2023-12-20_final.stac-item
2023-12-24 09:38:23	ga_ls9c_ard_3-2-1_093082_2023-12-24_final.stac-item
2024-01-05 10:00:12	ga_ls9c_ard_3-2-1_097075_2024-01-05_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years