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
2021-11-25 09:46:04	ga_ls9c_ard_3-2-1_095075_2021-11-25_final.stac-item
2021-12-08 10:37:49	ga_ls9c_ard_3-2-1_103076_2021-12-08_final.stac-item
2022-01-17 09:49:51	ga_ls9c_ard_3-2-1_095080_2022-01-17_final.stac-item
2022-01-28 09:30:08	ga_ls9c_ard_3-2-1_092077_2022-01-28_final.stac-item
2022-02-01 10:41:30	ga_ls9c_ard_3-2-1_104070_2022-02-01_final.stac-item
2022-02-11 09:43:39	ga_ls9c_ard_3-2-1_094080_2022-02-11_final.stac-item
2022-02-20 11:15:28	ga_ls9c_ard_3-2-1_109078_2022-02-20_final.stac-item
2022-02-23 10:08:15	ga_ls9c_ard_3-2-1_098080_2022-02-23_final.stac-item
2022-03-09 10:18:32	ga_ls9c_ard_3-2-1_100075_2022-03-09_final.stac-item
2022-04-22 10:41:23	ga_ls9c_ard_3-2-1_104071_2022-04-22_final.stac-item
2022-04-22 10:41:46	ga_ls9c_ard_3-2-1_104072_2022-04-22_final.stac-item
2022-05-27 09:36:20	ga_ls9c_ard_3-2-1_093079_2022-05-27_final.stac-item
2022-05-28 10:17:37	ga_ls9c_ard_3-2-1_100074_2022-05-28_final.stac-item
2022-06-01 09:51:43	ga_ls9c_ard_3-2-1_096071_2022-06-01_final.stac-item
2022-07-07 11:10:11	ga_ls9c_ard_3-2-1_108081_2022-07-07_final.stac-item
2022-07-18 10:48:04	ga_ls9c_ard_3-2-1_105072_2022-07-18_final.stac-item
2022-07-23 09:31:24	ga_ls9c_ard_3-2-1_092081_2022-07-23_final.stac-item
2022-07-25 09:19:04	ga_ls9c_ard_3-2-1_090081_2022-07-24_final.stac-item
2022-07-30 09:37:40	ga_ls9c_ard_3-2-1_093081_2022-07-30_final.stac-item
2022-08-04 09:53:29	ga_ls9c_ard_3-2-1_096074_2022-08-04_final.stac-item
2022-08-10 09:20:03	ga_ls9c_ard_3-2-1_090083_2022-08-09_final.stac-item
2022-08-12 10:41:48	ga_ls9c_ard_3-2-1_104071_2022-08-12_final.stac-item
2022-08-31 11:13:10	ga_ls9c_ard_3-2-1_109072_2022-08-31_final.stac-item
2022-09-13 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-09-13_final.stac-item
2022-09-28 09:59:55	ga_ls9c_ard_3-2-1_097074_2022-09-28_final.stac-item
2022-09-30 11:27:15	ga_ls9c_ard_3-2-1_111076_2022-09-30_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-08 10:37:00	ga_ls9c_ard_3-2-1_103074_2022-10-08_final.stac-item
2022-10-13 10:57:36	ga_ls9c_ard_3-2-1_106079_2022-10-13_final.stac-item
2022-10-25 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-10-25_final.stac-item
2022-10-25 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-10-25_final.stac-item
2022-10-28 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-10-28_final.stac-item
2022-10-30 10:00:48	ga_ls9c_ard_3-2-1_097076_2022-10-30_final.stac-item
2022-11-03 11:16:55	ga_ls9c_ard_3-2-1_109081_2022-11-03_final.stac-item
2022-11-10 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-10_final.stac-item
2022-11-19 09:37:18	ga_ls9c_ard_3-2-1_093079_2022-11-19_final.stac-item
2022-11-19 11:16:59	ga_ls9c_ard_3-2-1_109081_2022-11-19_final.stac-item
2022-11-22 10:09:48	ga_ls9c_ard_3-2-1_098083_2022-11-22_final.stac-item
2022-11-26 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-26_final.stac-item
2022-12-02 10:42:26	ga_ls9c_ard_3-2-1_104072_2022-12-02_final.stac-item
2022-12-03 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-03_final.stac-item
2022-12-03 11:30:05	ga_ls9c_ard_3-2-1_111083_2022-12-03_final.stac-item
2022-12-10 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-12-10_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-20 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-20_final.stac-item
2022-12-26 09:56:35	ga_ls9c_ard_3-2-1_096081_2022-12-26_final.stac-item
2022-12-26 09:56:59	ga_ls9c_ard_3-2-1_096082_2022-12-26_final.stac-item
2022-12-31 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-12-31_final.stac-item
2023-01-02 10:01:13	ga_ls9c_ard_3-2-1_097077_2023-01-02_final.stac-item
2023-01-02 10:03:36	ga_ls9c_ard_3-2-1_097083_2023-01-02_final.stac-item
2023-01-04 09:50:27	ga_ls9c_ard_3-2-1_095081_2023-01-04_final.stac-item
2023-01-13 11:23:07	ga_ls9c_ard_3-2-1_110081_2023-01-13_final.stac-item
2023-01-15 09:32:14	ga_ls9c_ard_3-2-1_092082_2023-01-15_final.stac-item
2023-01-17 09:19:03	ga_ls9c_ard_3-2-1_090080_2023-01-16_final.stac-item
2023-01-18 10:01:05	ga_ls9c_ard_3-2-1_097077_2023-01-18_final.stac-item
2023-01-22 09:36:21	ga_ls9c_ard_3-2-1_093077_2023-01-22_final.stac-item
2023-01-27 09:57:23	ga_ls9c_ard_3-2-1_096083_2023-01-27_final.stac-item
2023-01-31 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-01-31_final.stac-item
2023-02-03 10:00:27	ga_ls9c_ard_3-2-1_097075_2023-02-03_final.stac-item
2023-02-03 11:40:32	ga_ls9c_ard_3-2-1_113078_2023-02-03_final.stac-item
2023-02-06 10:31:46	ga_ls9c_ard_3-2-1_102076_2023-02-06_final.stac-item
2023-02-09 11:03:52	ga_ls9c_ard_3-2-1_107079_2023-02-09_final.stac-item
2023-04-23 10:58:13	ga_ls9c_ard_3-2-1_106082_2023-04-23_final.stac-item
2023-04-25 10:43:02	ga_ls9c_ard_3-2-1_104075_2023-04-25_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-28 09:40:12	ga_ls9c_ard_3-2-1_093088_2023-04-28_final.stac-item
2023-05-01 11:46:20	ga_ls9c_ard_3-2-1_114079_2023-05-01_final.stac-item
2023-05-02 09:13:49	ga_ls9c_ard_3-2-1_089084_2023-05-01_final.stac-item
2023-05-02 10:50:18	ga_ls9c_ard_3-2-1_105078_2023-05-02_final.stac-item
2023-05-05 11:17:57	ga_ls9c_ard_3-2-1_110070_2023-05-05_final.stac-item
2023-05-28 11:26:22	ga_ls9c_ard_3-2-1_111076_2023-05-28_final.stac-item
2023-06-26 10:57:42	ga_ls9c_ard_3-2-1_106082_2023-06-26_final.stac-item
2023-07-05 10:47:44	ga_ls9c_ard_3-2-1_105072_2023-07-05_final.stac-item
2023-07-06 09:55:43	ga_ls9c_ard_3-2-1_096081_2023-07-06_final.stac-item
2023-07-15 09:51:12	ga_ls9c_ard_3-2-1_095085_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
2023-07-18 10:20:30	ga_ls9c_ard_3-2-1_100081_2023-07-18_final.stac-item
2023-07-19 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-07-19_final.stac-item
2023-07-28 09:17:32	ga_ls9c_ard_3-2-1_090078_2023-07-27_final.stac-item
2023-07-28 10:54:01	ga_ls9c_ard_3-2-1_106072_2023-07-28_final.stac-item
2023-08-02 09:37:21	ga_ls9c_ard_3-2-1_093081_2023-08-02_final.stac-item
2023-08-02 09:38:33	ga_ls9c_ard_3-2-1_093084_2023-08-02_final.stac-item
2023-08-04 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-08-04_final.stac-item
2023-10-14 11:06:58	ga_ls9c_ard_3-2-1_108072_2023-10-14_final.stac-item
2023-10-16 09:20:08	ga_ls9c_ard_3-2-1_090083_2023-10-15_final.stac-item
2023-10-17 10:02:36	ga_ls9c_ard_3-2-1_097081_2023-10-17_final.stac-item
2023-10-18 10:42:16	ga_ls9c_ard_3-2-1_104072_2023-10-18_final.stac-item
2023-10-18 10:45:28	ga_ls9c_ard_3-2-1_104080_2023-10-18_final.stac-item
2023-10-19 09:50:39	ga_ls9c_ard_3-2-1_095082_2023-10-19_final.stac-item
2023-10-20 10:31:07	ga_ls9c_ard_3-2-1_102075_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
2023-10-24 10:05:59	ga_ls9c_ard_3-2-1_098074_2023-10-24_final.stac-item
2023-10-24 11:45:16	ga_ls9c_ard_3-2-1_114075_2023-10-24_final.stac-item
2023-10-27 10:35:16	ga_ls9c_ard_3-2-1_103070_2023-10-27_final.stac-item
2023-10-28 09:45:13	ga_ls9c_ard_3-2-1_094084_2023-10-28_final.stac-item
2023-10-29 10:26:28	ga_ls9c_ard_3-2-1_101079_2023-10-29_final.stac-item
2023-11-05 10:29:49	ga_ls9c_ard_3-2-1_102072_2023-11-05_final.stac-item
2023-11-05 10:31:00	ga_ls9c_ard_3-2-1_102075_2023-11-05_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-18 11:40:15	ga_ls9c_ard_3-2-1_113078_2023-11-18_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