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
2021-11-03 09:54:57	ga_ls9c_ard_3-2-1_096075_2021-11-03_final.stac-item
2021-11-17 09:25:40	ga_ls9c_ard_3-2-1_091083_2021-11-16_final.stac-item
2021-12-07 11:34:14	ga_ls9c_ard_3-2-1_112078_2021-12-07_final.stac-item
2021-12-14 11:39:56	ga_ls9c_ard_3-2-1_113077_2021-12-14_final.stac-item
2021-12-23 09:57:16	ga_ls9c_ard_3-2-1_096083_2021-12-23_final.stac-item
2021-12-30 11:40:44	ga_ls9c_ard_3-2-1_113079_2021-12-30_final.stac-item
2022-01-08 09:55:14	ga_ls9c_ard_3-2-1_096078_2022-01-08_final.stac-item
2022-01-17 11:27:32	ga_ls9c_ard_3-2-1_111077_2022-01-17_final.stac-item
2022-01-21 09:29:08	ga_ls9c_ard_3-2-1_091090_2022-01-20_final.stac-item
2022-02-02 11:28:45	ga_ls9c_ard_3-2-1_111080_2022-02-02_final.stac-item
2022-02-22 11:03:05	ga_ls9c_ard_3-2-1_107078_2022-02-22_final.stac-item
2022-03-04 11:39:16	ga_ls9c_ard_3-2-1_113076_2022-03-04_final.stac-item
2022-03-29 09:54:31	ga_ls9c_ard_3-2-1_096077_2022-03-29_final.stac-item
2022-03-30 10:35:23	ga_ls9c_ard_3-2-1_103071_2022-03-30_final.stac-item
2022-04-04 09:19:50	ga_ls9c_ard_3-2-1_090083_2022-04-03_final.stac-item
2022-04-07 11:28:24	ga_ls9c_ard_3-2-1_111080_2022-04-07_final.stac-item
2022-04-20 10:56:57	ga_ls9c_ard_3-2-1_106079_2022-04-20_final.stac-item
2022-04-29 10:48:21	ga_ls9c_ard_3-2-1_105073_2022-04-29_final.stac-item
2022-05-05 10:11:38	ga_ls9c_ard_3-2-1_099074_2022-05-05_final.stac-item
2022-05-15 10:50:12	ga_ls9c_ard_3-2-1_105078_2022-05-15_final.stac-item
2022-05-16 09:55:45	ga_ls9c_ard_3-2-1_096081_2022-05-16_final.stac-item
2022-05-16 09:56:09	ga_ls9c_ard_3-2-1_096082_2022-05-16_final.stac-item
2022-05-18 09:40:58	ga_ls9c_ard_3-2-1_094075_2022-05-18_final.stac-item
2022-06-01 09:56:06	ga_ls9c_ard_3-2-1_096082_2022-06-01_final.stac-item
2022-06-08 10:00:18	ga_ls9c_ard_3-2-1_097077_2022-06-08_final.stac-item
2022-06-15 10:08:33	ga_ls9c_ard_3-2-1_098082_2022-06-15_final.stac-item
2022-06-16 10:47:26	ga_ls9c_ard_3-2-1_105071_2022-06-16_final.stac-item
2022-06-24 10:00:37	ga_ls9c_ard_3-2-1_097077_2022-06-24_final.stac-item
2022-07-04 10:36:54	ga_ls9c_ard_3-2-1_103075_2022-07-04_final.stac-item
2022-07-26 11:38:50	ga_ls9c_ard_3-2-1_113075_2022-07-26_final.stac-item
2022-08-02 11:45:54	ga_ls9c_ard_3-2-1_114077_2022-08-02_final.stac-item
2022-08-11 11:39:01	ga_ls9c_ard_3-2-1_113075_2022-08-11_final.stac-item
2022-08-12 10:42:12	ga_ls9c_ard_3-2-1_104072_2022-08-12_final.stac-item
2022-08-20 09:55:36	ga_ls9c_ard_3-2-1_096079_2022-08-20_final.stac-item
2022-08-27 10:00:12	ga_ls9c_ard_3-2-1_097075_2022-08-27_final.stac-item
2022-08-27 10:02:59	ga_ls9c_ard_3-2-1_097082_2022-08-27_final.stac-item
2022-09-01 10:21:08	ga_ls9c_ard_3-2-1_100081_2022-09-01_final.stac-item
2022-09-18 11:03:40	ga_ls9c_ard_3-2-1_107079_2022-09-18_final.stac-item
2022-09-23 11:18:39	ga_ls9c_ard_3-2-1_110070_2022-09-23_final.stac-item
2022-09-27 10:56:44	ga_ls9c_ard_3-2-1_106077_2022-09-27_final.stac-item
2022-09-30 11:29:14	ga_ls9c_ard_3-2-1_111081_2022-09-30_final.stac-item
2022-10-10 10:23:05	ga_ls9c_ard_3-2-1_101070_2022-10-10_final.stac-item
2022-10-13 09:20:19	ga_ls9c_ard_3-2-1_090083_2022-10-12_final.stac-item
2022-10-15 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-10-15_final.stac-item
2022-10-16 11:28:07	ga_ls9c_ard_3-2-1_111078_2022-10-16_final.stac-item
2022-10-23 09:54:14	ga_ls9c_ard_3-2-1_096075_2022-10-23_final.stac-item
2022-10-25 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-10-25_final.stac-item
2022-10-29 10:58:25	ga_ls9c_ard_3-2-1_106081_2022-10-29_final.stac-item
2022-10-30 11:40:29	ga_ls9c_ard_3-2-1_113078_2022-10-30_final.stac-item
2022-10-31 10:42:27	ga_ls9c_ard_3-2-1_104072_2022-10-31_final.stac-item
2022-11-19 09:38:30	ga_ls9c_ard_3-2-1_093082_2022-11-19_final.stac-item
2022-12-02 10:41:38	ga_ls9c_ard_3-2-1_104070_2022-12-02_final.stac-item
2022-12-10 09:56:14	ga_ls9c_ard_3-2-1_096080_2022-12-10_final.stac-item
2022-12-10 09:57:01	ga_ls9c_ard_3-2-1_096082_2022-12-10_final.stac-item
2022-12-10 11:33:55	ga_ls9c_ard_3-2-1_112077_2022-12-10_final.stac-item
2022-12-10 11:34:43	ga_ls9c_ard_3-2-1_112079_2022-12-10_final.stac-item
2022-12-10 11:35:31	ga_ls9c_ard_3-2-1_112081_2022-12-10_final.stac-item
2023-01-04 11:28:08	ga_ls9c_ard_3-2-1_111078_2023-01-04_final.stac-item
2023-01-20 09:49:53	ga_ls9c_ard_3-2-1_095080_2023-01-20_final.stac-item
2023-01-24 11:03:19	ga_ls9c_ard_3-2-1_107078_2023-01-24_final.stac-item
2023-01-27 09:54:11	ga_ls9c_ard_3-2-1_096075_2023-01-27_final.stac-item
2023-02-06 10:33:22	ga_ls9c_ard_3-2-1_102080_2023-02-06_final.stac-item
2023-02-07 11:16:38	ga_ls9c_ard_3-2-1_109080_2023-02-07_final.stac-item
2023-02-08 10:19:25	ga_ls9c_ard_3-2-1_100076_2023-02-08_final.stac-item
2023-02-11 10:51:30	ga_ls9c_ard_3-2-1_105079_2023-02-11_final.stac-item
2023-02-12 09:54:17	ga_ls9c_ard_3-2-1_096075_2023-02-12_final.stac-item
2023-02-16 09:30:18	ga_ls9c_ard_3-2-1_092077_2023-02-16_final.stac-item
2023-02-16 09:31:30	ga_ls9c_ard_3-2-1_092080_2023-02-16_final.stac-item
2023-02-18 09:20:18	ga_ls9c_ard_3-2-1_090083_2023-02-17_final.stac-item
2023-02-21 11:27:37	ga_ls9c_ard_3-2-1_111077_2023-02-21_final.stac-item
2023-02-25 11:04:49	ga_ls9c_ard_3-2-1_107082_2023-02-25_final.stac-item
2023-02-25 11:05:37	ga_ls9c_ard_3-2-1_107084_2023-02-25_final.stac-item
2023-03-16 09:53:56	ga_ls9c_ard_3-2-1_096075_2023-03-16_final.stac-item
2023-03-20 09:31:11	ga_ls9c_ard_3-2-1_092080_2023-03-20_final.stac-item
2023-04-03 09:42:10	ga_ls9c_ard_3-2-1_094077_2023-04-03_final.stac-item
2023-04-08 11:38:47	ga_ls9c_ard_3-2-1_113075_2023-04-08_final.stac-item
2023-04-10 11:27:12	ga_ls9c_ard_3-2-1_111077_2023-04-10_final.stac-item
2023-04-22 10:11:46	ga_ls9c_ard_3-2-1_099074_2023-04-22_final.stac-item
2023-04-26 11:27:05	ga_ls9c_ard_3-2-1_111077_2023-04-26_final.stac-item
2023-04-29 11:57:56	ga_ls9c_ard_3-2-1_116077_2023-04-29_final.stac-item
2023-05-02 10:47:30	ga_ls9c_ard_3-2-1_105071_2023-05-02_final.stac-item
2023-05-04 10:37:06	ga_ls9c_ard_3-2-1_103076_2023-05-04_final.stac-item
2023-05-09 10:56:02	ga_ls9c_ard_3-2-1_106077_2023-05-09_final.stac-item
2023-05-09 10:57:38	ga_ls9c_ard_3-2-1_106081_2023-05-09_final.stac-item
2023-05-16 11:02:58	ga_ls9c_ard_3-2-1_107079_2023-05-16_final.stac-item
2023-05-17 10:05:44	ga_ls9c_ard_3-2-1_098075_2023-05-17_final.stac-item
2023-05-22 10:23:00	ga_ls9c_ard_3-2-1_101072_2023-05-22_final.stac-item
2023-05-23 11:06:15	ga_ls9c_ard_3-2-1_108072_2023-05-23_final.stac-item
2023-05-24 10:11:24	ga_ls9c_ard_3-2-1_099074_2023-05-24_final.stac-item
2023-05-26 11:38:19	ga_ls9c_ard_3-2-1_113075_2023-05-26_final.stac-item
2023-05-28 11:26:46	ga_ls9c_ard_3-2-1_111077_2023-05-28_final.stac-item
2023-06-07 10:22:55	ga_ls9c_ard_3-2-1_101072_2023-06-07_final.stac-item
2023-07-04 10:08:27	ga_ls9c_ard_3-2-1_098082_2023-07-04_final.stac-item
2023-09-10 09:43:28	ga_ls9c_ard_3-2-1_094080_2023-09-10_final.stac-item
2023-09-24 11:31:55	ga_ls9c_ard_3-2-1_112073_2023-09-24_final.stac-item
2023-09-26 11:22:43	ga_ls9c_ard_3-2-1_110081_2023-09-26_final.stac-item
2023-09-28 09:30:15	ga_ls9c_ard_3-2-1_092078_2023-09-28_final.stac-item
2023-10-02 10:42:06	ga_ls9c_ard_3-2-1_104072_2023-10-02_final.stac-item
2023-10-07 09:25:48	ga_ls9c_ard_3-2-1_091082_2023-10-06_final.stac-item
2023-10-07 11:04:41	ga_ls9c_ard_3-2-1_107082_2023-10-07_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