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
2021-12-12 10:15:02	ga_ls9c_ard_3-2-1_099081_2021-12-12_final.stac-item
2021-12-16 09:47:52	ga_ls9c_ard_3-2-1_095075_2021-12-16_final.stac-item
2021-12-24 10:37:44	ga_ls9c_ard_3-2-1_103076_2021-12-24_final.stac-item
2022-01-24 09:53:15	ga_ls9c_ard_3-2-1_096073_2022-01-24_final.stac-item
2022-01-31 10:02:38	ga_ls9c_ard_3-2-1_097081_2022-01-31_final.stac-item
2022-03-30 10:37:47	ga_ls9c_ard_3-2-1_103077_2022-03-30_final.stac-item
2022-03-31 09:40:58	ga_ls9c_ard_3-2-1_094074_2022-03-31_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-12 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-04-12_final.stac-item
2022-04-16 09:40:27	ga_ls9c_ard_3-2-1_094073_2022-04-16_final.stac-item
2022-05-22 10:54:18	ga_ls9c_ard_3-2-1_106073_2022-05-22_final.stac-item
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-09-27 10:54:45	ga_ls9c_ard_3-2-1_106072_2022-09-27_final.stac-item
2022-09-30 09:52:45	ga_ls9c_ard_3-2-1_095087_2022-09-30_final.stac-item
2022-10-04 09:28:25	ga_ls9c_ard_3-2-1_091088_2022-10-03_final.stac-item
2022-10-04 11:02:55	ga_ls9c_ard_3-2-1_107077_2022-10-04_final.stac-item
2022-10-10 10:27:52	ga_ls9c_ard_3-2-1_101082_2022-10-10_final.stac-item
2022-10-29 09:19:56	ga_ls9c_ard_3-2-1_090082_2022-10-28_final.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-06 11:45:27	ga_ls9c_ard_3-2-1_114075_2022-11-06_final.stac-item
2022-11-17 09:48:04	ga_ls9c_ard_3-2-1_095075_2022-11-17_final.stac-item
2022-11-18 10:28:56	ga_ls9c_ard_3-2-1_102069_2022-11-18_final.stac-item
2022-11-21 11:03:50	ga_ls9c_ard_3-2-1_107079_2022-11-21_final.stac-item
2022-11-26 09:45:03	ga_ls9c_ard_3-2-1_094083_2022-11-26_final.stac-item
2022-11-29 11:51:14	ga_ls9c_ard_3-2-1_115074_2022-11-29_final.stac-item
2022-12-01 09:59:34	ga_ls9c_ard_3-2-1_097073_2022-12-01_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-14 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-14_final.stac-item
2022-12-14 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-14_final.stac-item
2022-12-16 09:18:44	ga_ls9c_ard_3-2-1_090079_2022-12-15_final.stac-item
2022-12-17 09:59:12	ga_ls9c_ard_3-2-1_097072_2022-12-17_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2022-12-30 11:11:35	ga_ls9c_ard_3-2-1_108083_2022-12-30_final.stac-item
2023-01-01 09:18:45	ga_ls9c_ard_3-2-1_090079_2022-12-31_final.stac-item
2023-01-04 09:47:15	ga_ls9c_ard_3-2-1_095073_2023-01-04_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-07 10:20:33	ga_ls9c_ard_3-2-1_100079_2023-01-07_final.stac-item
2023-01-10 10:48:39	ga_ls9c_ard_3-2-1_105072_2023-01-10_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-17 09:23:02	ga_ls9c_ard_3-2-1_090090_2023-01-16_final.stac-item
2023-01-20 11:30:22	ga_ls9c_ard_3-2-1_111084_2023-01-20_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-01-25 10:07:19	ga_ls9c_ard_3-2-1_098077_2023-01-25_final.stac-item
2023-01-31 09:33:06	ga_ls9c_ard_3-2-1_092084_2023-01-31_final.stac-item
2023-02-01 10:14:47	ga_ls9c_ard_3-2-1_099080_2023-02-01_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-05 11:30:11	ga_ls9c_ard_3-2-1_111083_2023-02-05_final.stac-item
2023-02-06 10:34:10	ga_ls9c_ard_3-2-1_102082_2023-02-06_final.stac-item
2023-02-07 11:17:50	ga_ls9c_ard_3-2-1_109083_2023-02-07_final.stac-item
2023-02-08 10:21:48	ga_ls9c_ard_3-2-1_100082_2023-02-08_final.stac-item
2023-02-10 10:07:51	ga_ls9c_ard_3-2-1_098078_2023-02-10_final.stac-item
2023-02-11 10:50:42	ga_ls9c_ard_3-2-1_105077_2023-02-11_final.stac-item
2023-02-14 11:23:34	ga_ls9c_ard_3-2-1_110082_2023-02-14_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 09:19:44	ga_ls9c_ard_3-2-1_090083_2023-04-22_final.stac-item
2023-04-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2023-04-23_final.stac-item
2023-04-27 10:29:03	ga_ls9c_ard_3-2-1_102071_2023-04-27_final.stac-item
2023-04-28 11:13:06	ga_ls9c_ard_3-2-1_109073_2023-04-28_final.stac-item
2023-06-01 09:25:09	ga_ls9c_ard_3-2-1_091082_2023-05-31_final.stac-item
2023-07-15 11:29:17	ga_ls9c_ard_3-2-1_111083_2023-07-15_final.stac-item
2023-07-17 09:34:51	ga_ls9c_ard_3-2-1_093075_2023-07-17_final.stac-item
2023-07-20 11:44:14	ga_ls9c_ard_3-2-1_114074_2023-07-20_final.stac-item
2023-07-21 09:14:07	ga_ls9c_ard_3-2-1_089085_2023-07-20_final.stac-item
2023-07-24 09:43:48	ga_ls9c_ard_3-2-1_094082_2023-07-24_final.stac-item
2023-07-26 11:05:09	ga_ls9c_ard_3-2-1_108069_2023-07-26_final.stac-item
2023-07-28 10:54:25	ga_ls9c_ard_3-2-1_106073_2023-07-28_final.stac-item
2023-07-28 10:58:01	ga_ls9c_ard_3-2-1_106082_2023-07-28_final.stac-item
2023-08-02 09:34:33	ga_ls9c_ard_3-2-1_093074_2023-08-02_final.stac-item
2023-08-02 11:16:14	ga_ls9c_ard_3-2-1_109081_2023-08-02_final.stac-item
2023-08-03 11:58:18	ga_ls9c_ard_3-2-1_116078_2023-08-03_final.stac-item
2023-08-04 09:26:36	ga_ls9c_ard_3-2-1_091085_2023-08-03_final.stac-item
2023-10-13 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-13_final.stac-item
2023-10-14 09:29:41	ga_ls9c_ard_3-2-1_092076_2023-10-13_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_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
2023-10-20 10:33:30	ga_ls9c_ard_3-2-1_102081_2023-10-20_final.stac-item
2023-10-23 09:23:55	ga_ls9c_ard_3-2-1_091077_2023-10-22_final.stac-item
2023-10-23 09:25:07	ga_ls9c_ard_3-2-1_091080_2023-10-22_final.stac-item
2023-10-23 09:26:19	ga_ls9c_ard_3-2-1_091083_2023-10-22_final.stac-item
2023-10-24 10:08:22	ga_ls9c_ard_3-2-1_098080_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
2023-10-25 09:13:57	ga_ls9c_ard_3-2-1_089083_2023-10-24_final.stac-item
2023-10-25 10:50:26	ga_ls9c_ard_3-2-1_105077_2023-10-25_final.stac-item
2023-10-27 10:34:52	ga_ls9c_ard_3-2-1_103069_2023-10-27_final.stac-item
2023-10-27 10:36:52	ga_ls9c_ard_3-2-1_103074_2023-10-27_final.stac-item
2023-10-29 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-29_final.stac-item
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final.stac-item
2023-11-01 09:19:38	ga_ls9c_ard_3-2-1_090082_2023-10-31_final.stac-item
2023-11-01 09:20:26	ga_ls9c_ard_3-2-1_090084_2023-10-31_final.stac-item
2023-11-05 10:30:36	ga_ls9c_ard_3-2-1_102074_2023-11-05_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 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_final.stac-item
2023-11-24 11:04:27	ga_ls9c_ard_3-2-1_107081_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 10:52:06	ga_ls9c_ard_3-2-1_105081_2023-11-26_final.stac-item
2024-02-19 11:10:54	ga_ls9c_ard_3-2-1_108082_2024-02-19_final.stac-item
2024-02-20 10:15:15	ga_ls9c_ard_3-2-1_099082_2024-02-20_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