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
2021-11-11 11:58:31	ga_ls9c_ard_3-2-1_116078_2021-11-11_final.stac-item
2021-11-20 09:45:36	ga_ls9c_ard_3-2-1_094080_2021-11-20_final.stac-item
2021-12-04 11:02:34	ga_ls9c_ard_3-2-1_107076_2021-12-04_final.stac-item
2021-12-05 10:07:20	ga_ls9c_ard_3-2-1_098077_2021-12-05_final.stac-item
2021-12-25 11:24:11	ga_ls9c_ard_3-2-1_110084_2021-12-25_final.stac-item
2022-01-01 09:50:17	ga_ls9c_ard_3-2-1_095081_2022-01-01_final.stac-item
2022-01-21 09:25:32	ga_ls9c_ard_3-2-1_091081_2022-01-20_final.stac-item
2022-01-29 11:51:05	ga_ls9c_ard_3-2-1_115074_2022-01-29_final.stac-item
2022-02-07 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-02-07_final.stac-item
2022-02-07 10:08:47	ga_ls9c_ard_3-2-1_098081_2022-02-07_final.stac-item
2022-02-11 11:23:20	ga_ls9c_ard_3-2-1_110082_2022-02-11_final.stac-item
2022-02-27 09:43:52	ga_ls9c_ard_3-2-1_094081_2022-02-27_final.stac-item
2022-03-02 10:15:32	ga_ls9c_ard_3-2-1_099083_2022-03-02_final.stac-item
2022-03-04 10:01:11	ga_ls9c_ard_3-2-1_097078_2022-03-04_final.stac-item
2022-03-09 10:21:19	ga_ls9c_ard_3-2-1_100082_2022-03-09_final.stac-item
2022-03-20 10:02:21	ga_ls9c_ard_3-2-1_097081_2022-03-20_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-04-04 10:55:07	ga_ls9c_ard_3-2-1_106074_2022-04-04_final.stac-item
2022-04-13 09:12:47	ga_ls9c_ard_3-2-1_089081_2022-04-12_final.stac-item
2022-04-21 09:58:31	ga_ls9c_ard_3-2-1_097072_2022-04-21_final.stac-item
2022-05-05 11:50:31	ga_ls9c_ard_3-2-1_115074_2022-05-05_final.stac-item
2022-05-09 09:52:04	ga_ls9c_ard_3-2-1_095087_2022-05-09_final.stac-item
2022-05-14 11:45:26	ga_ls9c_ard_3-2-1_114077_2022-05-14_final.stac-item
2022-05-19 10:23:01	ga_ls9c_ard_3-2-1_101072_2022-05-19_final.stac-item
2022-06-02 10:38:10	ga_ls9c_ard_3-2-1_103079_2022-06-02_final.stac-item
2022-06-05 11:09:04	ga_ls9c_ard_3-2-1_108079_2022-06-05_final.stac-item
2022-06-21 11:05:19	ga_ls9c_ard_3-2-1_108069_2022-06-21_final.stac-item
2022-06-27 10:30:21	ga_ls9c_ard_3-2-1_102074_2022-06-27_final.stac-item
2022-06-28 11:12:25	ga_ls9c_ard_3-2-1_109071_2022-06-28_final.stac-item
2022-07-10 11:41:52	ga_ls9c_ard_3-2-1_113083_2022-07-10_final.stac-item
2022-07-23 09:27:48	ga_ls9c_ard_3-2-1_092072_2022-07-22_final.stac-item
2022-07-29 10:32:53	ga_ls9c_ard_3-2-1_102080_2022-07-29_final.stac-item
2022-07-31 10:21:21	ga_ls9c_ard_3-2-1_100082_2022-07-31_final.stac-item
2022-08-20 11:31:41	ga_ls9c_ard_3-2-1_112072_2022-08-20_final.stac-item
2022-08-21 10:35:16	ga_ls9c_ard_3-2-1_103070_2022-08-21_final.stac-item
2022-09-11 10:54:38	ga_ls9c_ard_3-2-1_106072_2022-09-11_final.stac-item
2022-09-20 09:15:14	ga_ls9c_ard_3-2-1_089086_2022-09-19_final.stac-item
2022-10-06 10:50:57	ga_ls9c_ard_3-2-1_105078_2022-10-06_final.stac-item
2022-10-09 11:21:29	ga_ls9c_ard_3-2-1_110077_2022-10-09_final.stac-item
2022-10-21 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-10-21_final.stac-item
2022-10-27 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-10-27_final.stac-item
2022-11-26 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-11-26_final.stac-item
2022-12-10 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-12-10_final.stac-item
2022-12-11 10:38:41	ga_ls9c_ard_3-2-1_103078_2022-12-11_final.stac-item
2022-12-19 09:48:26	ga_ls9c_ard_3-2-1_095076_2022-12-19_final.stac-item
2022-12-28 11:23:31	ga_ls9c_ard_3-2-1_110082_2022-12-28_final.stac-item
2022-12-30 11:07:11	ga_ls9c_ard_3-2-1_108072_2022-12-30_final.stac-item
2022-12-31 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-31_final.stac-item
2023-01-06 11:16:58	ga_ls9c_ard_3-2-1_109081_2023-01-06_final.stac-item
2023-01-09 10:06:59	ga_ls9c_ard_3-2-1_098076_2023-01-09_final.stac-item
2023-01-18 11:41:34	ga_ls9c_ard_3-2-1_113081_2023-01-18_final.stac-item
2023-02-04 10:42:07	ga_ls9c_ard_3-2-1_104071_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 11:03:04	ga_ls9c_ard_3-2-1_107077_2023-02-09_final.stac-item
2023-02-17 11:52:26	ga_ls9c_ard_3-2-1_115077_2023-02-17_final.stac-item
2023-02-19 11:41:37	ga_ls9c_ard_3-2-1_113081_2023-02-19_final.stac-item
2023-03-12 11:58:44	ga_ls9c_ard_3-2-1_116078_2023-03-12_final.stac-item
2023-03-14 10:06:18	ga_ls9c_ard_3-2-1_098075_2023-03-14_final.stac-item
2023-03-19 10:25:13	ga_ls9c_ard_3-2-1_101076_2023-03-19_final.stac-item
2023-04-03 09:44:58	ga_ls9c_ard_3-2-1_094084_2023-04-03_final.stac-item
2023-04-04 10:25:02	ga_ls9c_ard_3-2-1_101076_2023-04-04_final.stac-item
2023-04-30 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-04-30_final.stac-item
2023-05-02 10:47:06	ga_ls9c_ard_3-2-1_105070_2023-05-02_final.stac-item
2023-05-17 11:46:37	ga_ls9c_ard_3-2-1_114080_2023-05-17_final.stac-item
2023-06-13 11:25:50	ga_ls9c_ard_3-2-1_111075_2023-06-13_final.stac-item
2023-06-18 10:02:16	ga_ls9c_ard_3-2-1_098067_2023-06-18_final.stac-item
2023-06-20 11:33:59	ga_ls9c_ard_3-2-1_112080_2023-06-20_final.stac-item
2023-06-23 10:23:12	ga_ls9c_ard_3-2-1_101073_2023-06-23_final.stac-item
2023-06-29 11:27:06	ga_ls9c_ard_3-2-1_111078_2023-06-29_final.stac-item
2023-07-01 11:15:35	ga_ls9c_ard_3-2-1_109080_2023-07-01_final.stac-item
2023-07-01 11:16:47	ga_ls9c_ard_3-2-1_109083_2023-07-01_final.stac-item
2023-07-13 10:01:09	ga_ls9c_ard_3-2-1_097079_2023-07-13_final.stac-item
2023-07-17 09:36:03	ga_ls9c_ard_3-2-1_093078_2023-07-17_final.stac-item
2023-07-20 10:02:33	ga_ls9c_ard_3-2-1_098067_2023-07-20_final.stac-item
2023-07-26 09:30:39	ga_ls9c_ard_3-2-1_092080_2023-07-26_final.stac-item
2023-07-27 11:52:25	ga_ls9c_ard_3-2-1_115079_2023-07-27_final.stac-item
2023-08-09 11:22:52	ga_ls9c_ard_3-2-1_110082_2023-08-09_final.stac-item
2023-08-20 09:25:28	ga_ls9c_ard_3-2-1_091082_2023-08-19_final.stac-item
2023-09-06 10:10:08	ga_ls9c_ard_3-2-1_098085_2023-09-06_final.stac-item
2023-09-06 11:46:13	ga_ls9c_ard_3-2-1_114078_2023-09-06_final.stac-item
2023-09-15 09:59:14	ga_ls9c_ard_3-2-1_097073_2023-09-15_final.stac-item
2023-09-15 10:03:38	ga_ls9c_ard_3-2-1_097084_2023-09-15_final.stac-item
2023-10-05 09:34:57	ga_ls9c_ard_3-2-1_093074_2023-10-05_final.stac-item
2023-10-05 11:17:02	ga_ls9c_ard_3-2-1_109082_2023-10-05_final.stac-item
2023-10-07 11:00:41	ga_ls9c_ard_3-2-1_107072_2023-10-07_final.stac-item
2023-10-19 09:48:39	ga_ls9c_ard_3-2-1_095077_2023-10-19_final.stac-item
2023-11-07 10:18:16	ga_ls9c_ard_3-2-1_100074_2023-11-07_final.stac-item
2023-11-09 10:06:19	ga_ls9c_ard_3-2-1_098075_2023-11-09_final.stac-item
2023-11-20 09:49:26	ga_ls9c_ard_3-2-1_095079_2023-11-20_final.stac-item
2023-11-26 09:14:01	ga_ls9c_ard_3-2-1_089083_2023-11-25_final.stac-item
2023-11-26 10:48:31	ga_ls9c_ard_3-2-1_105072_2023-11-26_final.stac-item
2023-12-01 09:31:45	ga_ls9c_ard_3-2-1_092081_2023-12-01_final.stac-item
2023-12-01 11:09:51	ga_ls9c_ard_3-2-1_108079_2023-12-01_final.stac-item
2023-12-13 09:56:28	ga_ls9c_ard_3-2-1_096081_2023-12-13_final.stac-item
2023-12-22 11:30:25	ga_ls9c_ard_3-2-1_111084_2023-12-22_final.stac-item
2023-12-27 10:06:29	ga_ls9c_ard_3-2-1_098075_2023-12-27_final.stac-item
2024-01-25 09:37:51	ga_ls9c_ard_3-2-1_093081_2024-01-25_final.stac-item
2024-01-31 10:36:56	ga_ls9c_ard_3-2-1_103074_2024-01-31_final.stac-item
2024-01-31 10:38:08	ga_ls9c_ard_3-2-1_103077_2024-01-31_final.stac-item
2024-02-24 09:50:05	ga_ls9c_ard_3-2-1_095081_2024-02-24_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