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
2021-11-17 09:26:04	ga_ls9c_ard_3-2-1_091084_2021-11-16_final.stac-item
2021-11-25 09:48:03	ga_ls9c_ard_3-2-1_095080_2021-11-25_final.stac-item
2021-12-07 09:53:46	ga_ls9c_ard_3-2-1_096074_2021-12-07_final.stac-item
2021-12-08 10:37:49	ga_ls9c_ard_3-2-1_103076_2021-12-08_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2021-12-21 10:05:38	ga_ls9c_ard_3-2-1_098073_2021-12-21_final.stac-item
2022-01-12 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-01-12_final.stac-item
2022-01-12 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-01-12_final.stac-item
2022-01-17 09:49:51	ga_ls9c_ard_3-2-1_095080_2022-01-17_final.stac-item
2022-02-03 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-02-03_final.stac-item
2022-02-04 09:37:06	ga_ls9c_ard_3-2-1_093079_2022-02-04_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-03-04 11:38:52	ga_ls9c_ard_3-2-1_113075_2022-03-04_final.stac-item
2022-03-08 09:35:40	ga_ls9c_ard_3-2-1_093076_2022-03-08_final.stac-item
2022-03-22 09:47:35	ga_ls9c_ard_3-2-1_095075_2022-03-22_final.stac-item
2022-03-24 09:36:24	ga_ls9c_ard_3-2-1_093078_2022-03-24_final.stac-item
2022-03-24 09:38:48	ga_ls9c_ard_3-2-1_093084_2022-03-24_final.stac-item
2022-03-24 09:39:36	ga_ls9c_ard_3-2-1_093086_2022-03-24_final.stac-item
2022-05-12 10:17:44	ga_ls9c_ard_3-2-1_100074_2022-05-12_final.stac-item
2022-06-01 09:51:43	ga_ls9c_ard_3-2-1_096071_2022-06-01_final.stac-item
2022-06-18 10:34:18	ga_ls9c_ard_3-2-1_103069_2022-06-18_final.stac-item
2022-06-24 10:03:01	ga_ls9c_ard_3-2-1_097083_2022-06-24_final.stac-item
2022-07-23 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-07-22_final.stac-item
2022-07-25 09:19:04	ga_ls9c_ard_3-2-1_090081_2022-07-24_final.stac-item
2022-08-04 09:53:29	ga_ls9c_ard_3-2-1_096074_2022-08-04_final.stac-item
2022-08-05 10:34:45	ga_ls9c_ard_3-2-1_103069_2022-08-05_final.stac-item
2022-08-08 09:32:00	ga_ls9c_ard_3-2-1_092082_2022-08-08_final.stac-item
2022-08-26 09:19:20	ga_ls9c_ard_3-2-1_090081_2022-08-25_final.stac-item
2022-10-05 11:45:22	ga_ls9c_ard_3-2-1_114075_2022-10-05_final.stac-item
2022-10-13 09:19:31	ga_ls9c_ard_3-2-1_090081_2022-10-12_final.stac-item
2022-10-13 10:57:36	ga_ls9c_ard_3-2-1_106079_2022-10-13_final.stac-item
2022-10-13 10:58:24	ga_ls9c_ard_3-2-1_106081_2022-10-13_final.stac-item
2022-10-17 10:30:54	ga_ls9c_ard_3-2-1_102074_2022-10-17_final.stac-item
2022-10-25 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-10-25_final.stac-item
2022-10-27 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-10-27_final.stac-item
2022-11-08 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-11-08_final.stac-item
2022-11-09 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-11-09_final.stac-item
2022-11-12 11:07:13	ga_ls9c_ard_3-2-1_108072_2022-11-12_final.stac-item
2022-12-03 11:27:18	ga_ls9c_ard_3-2-1_111076_2022-12-03_final.stac-item
2022-12-03 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-03_final.stac-item
2022-12-07 09:24:31	ga_ls9c_ard_3-2-1_091078_2022-12-06_final.stac-item
2022-12-11 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-12-11_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2023-01-02 10:01:37	ga_ls9c_ard_3-2-1_097078_2023-01-02_final.stac-item
2023-01-02 10:03:12	ga_ls9c_ard_3-2-1_097082_2023-01-02_final.stac-item
2023-01-06 11:15:23	ga_ls9c_ard_3-2-1_109077_2023-01-06_final.stac-item
2023-01-07 10:20:33	ga_ls9c_ard_3-2-1_100079_2023-01-07_final.stac-item
2023-01-08 11:04:12	ga_ls9c_ard_3-2-1_107080_2023-01-08_final.stac-item
2023-01-15 09:32:38	ga_ls9c_ard_3-2-1_092083_2023-01-15_final.stac-item
2023-01-16 10:15:05	ga_ls9c_ard_3-2-1_099081_2023-01-16_final.stac-item
2023-01-24 09:26:01	ga_ls9c_ard_3-2-1_091082_2023-01-23_final.stac-item
2023-01-29 09:43:51	ga_ls9c_ard_3-2-1_094080_2023-01-29_final.stac-item
2023-02-01 11:51:16	ga_ls9c_ard_3-2-1_115074_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
2023-02-07 11:17:02	ga_ls9c_ard_3-2-1_109081_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
2023-04-23 10:57:49	ga_ls9c_ard_3-2-1_106081_2023-04-23_final.stac-item
2023-04-25 10:41:03	ga_ls9c_ard_3-2-1_104070_2023-04-25_final.stac-item
2023-04-25 10:42:38	ga_ls9c_ard_3-2-1_104074_2023-04-25_final.stac-item
2023-04-25 10:45:26	ga_ls9c_ard_3-2-1_104081_2023-04-25_final.stac-item
2023-04-26 11:29:53	ga_ls9c_ard_3-2-1_111084_2023-04-26_final.stac-item
2023-04-28 09:37:01	ga_ls9c_ard_3-2-1_093080_2023-04-28_final.stac-item
2023-04-30 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-04-30_final.stac-item
2023-05-28 09:46:41	ga_ls9c_ard_3-2-1_095074_2023-05-28_final.stac-item
2023-06-24 09:28:47	ga_ls9c_ard_3-2-1_092076_2023-06-23_final.stac-item
2023-06-24 11:08:52	ga_ls9c_ard_3-2-1_108079_2023-06-24_final.stac-item
2023-06-25 10:10:50	ga_ls9c_ard_3-2-1_099073_2023-06-25_final.stac-item
2023-06-26 09:19:13	ga_ls9c_ard_3-2-1_090083_2023-06-25_final.stac-item
2023-06-29 09:46:37	ga_ls9c_ard_3-2-1_095074_2023-06-29_final.stac-item
2023-07-17 09:36:50	ga_ls9c_ard_3-2-1_093080_2023-07-17_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-19 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-07-18_final.stac-item
2023-07-21 10:52:12	ga_ls9c_ard_3-2-1_105083_2023-07-21_final.stac-item
2023-07-23 10:37:50	ga_ls9c_ard_3-2-1_103078_2023-07-23_final.stac-item
2023-07-25 10:23:28	ga_ls9c_ard_3-2-1_101073_2023-07-25_final.stac-item
2023-07-26 09:31:27	ga_ls9c_ard_3-2-1_092082_2023-07-26_final.stac-item
2023-07-28 10:54:01	ga_ls9c_ard_3-2-1_106072_2023-07-28_final.stac-item
2023-08-04 09:25:24	ga_ls9c_ard_3-2-1_091082_2023-08-03_final.stac-item
2023-08-05 11:44:46	ga_ls9c_ard_3-2-1_114075_2023-08-05_final.stac-item
2023-08-05 11:46:22	ga_ls9c_ard_3-2-1_114079_2023-08-05_final.stac-item
2023-10-16 10:57:25	ga_ls9c_ard_3-2-1_106079_2023-10-16_final.stac-item
2023-10-17 11:41:53	ga_ls9c_ard_3-2-1_113082_2023-10-17_final.stac-item
2023-10-19 09:51:03	ga_ls9c_ard_3-2-1_095083_2023-10-19_final.stac-item
2023-10-20 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-10-20_final.stac-item
2023-10-21 09:38:41	ga_ls9c_ard_3-2-1_093083_2023-10-21_final.stac-item
2023-10-22 10:20:21	ga_ls9c_ard_3-2-1_100079_2023-10-22_final.stac-item
2023-10-22 11:58:50	ga_ls9c_ard_3-2-1_116078_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
2023-10-27 10:36:52	ga_ls9c_ard_3-2-1_103074_2023-10-27_final.stac-item
2023-10-30 11:11:19	ga_ls9c_ard_3-2-1_108083_2023-10-30_final.stac-item
2023-11-01 09:18:50	ga_ls9c_ard_3-2-1_090080_2023-10-31_final.stac-item
2023-11-03 10:44:08	ga_ls9c_ard_3-2-1_104077_2023-11-03_final.stac-item
2023-11-05 10:29:49	ga_ls9c_ard_3-2-1_102072_2023-11-05_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-11-18 09:59:22	ga_ls9c_ard_3-2-1_097073_2023-11-18_final.stac-item
2023-11-18 11:39:27	ga_ls9c_ard_3-2-1_113076_2023-11-18_final.stac-item
2023-11-25 11:44:56	ga_ls9c_ard_3-2-1_114074_2023-11-25_final.stac-item
2024-02-16 10:36:52	ga_ls9c_ard_3-2-1_103074_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