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
2021-11-08 10:00:37	ga_ls9c_ard_3-2-1_097083_2021-11-08_final.stac-item
2021-11-17 09:24:28	ga_ls9c_ard_3-2-1_091080_2021-11-16_final.stac-item
2021-12-10 10:23:02	ga_ls9c_ard_3-2-1_101070_2021-12-10_final.stac-item
2022-02-12 10:27:18	ga_ls9c_ard_3-2-1_101081_2022-02-12_final.stac-item
2022-02-23 10:09:03	ga_ls9c_ard_3-2-1_098082_2022-02-23_final.stac-item
2022-03-21 10:45:12	ga_ls9c_ard_3-2-1_104080_2022-03-21_final.stac-item
2022-03-24 09:37:36	ga_ls9c_ard_3-2-1_093081_2022-03-24_final.stac-item
2022-04-07 09:49:31	ga_ls9c_ard_3-2-1_095080_2022-04-07_final.stac-item
2022-04-14 09:54:50	ga_ls9c_ard_3-2-1_096078_2022-04-14_final.stac-item
2022-04-23 09:49:21	ga_ls9c_ard_3-2-1_095080_2022-04-23_final.stac-item
2022-05-23 09:59:28	ga_ls9c_ard_3-2-1_097075_2022-05-23_final.stac-item
2022-05-23 10:02:40	ga_ls9c_ard_3-2-1_097083_2022-05-23_final.stac-item
2022-06-07 10:56:19	ga_ls9c_ard_3-2-1_106078_2022-06-07_final.stac-item
2022-06-14 09:23:41	ga_ls9c_ard_3-2-1_091078_2022-06-13_final.stac-item
2022-06-26 09:49:05	ga_ls9c_ard_3-2-1_095079_2022-06-26_final.stac-item
2022-07-03 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-03_final.stac-item
2022-07-17 10:05:35	ga_ls9c_ard_3-2-1_098074_2022-07-17_final.stac-item
2022-07-19 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-19_final.stac-item
2022-07-20 10:38:56	ga_ls9c_ard_3-2-1_103080_2022-07-20_final.stac-item
2022-07-23 09:30:36	ga_ls9c_ard_3-2-1_092079_2022-07-23_final.stac-item
2022-07-23 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-07-23_final.stac-item
2022-07-28 09:49:36	ga_ls9c_ard_3-2-1_095080_2022-07-28_final.stac-item
2022-08-07 10:22:49	ga_ls9c_ard_3-2-1_101070_2022-08-07_final.stac-item
2022-08-08 09:30:48	ga_ls9c_ard_3-2-1_092079_2022-08-08_final.stac-item
2022-08-22 11:21:44	ga_ls9c_ard_3-2-1_110078_2022-08-22_final.stac-item
2022-08-26 10:57:25	ga_ls9c_ard_3-2-1_106079_2022-08-26_final.stac-item
2022-08-28 10:43:51	ga_ls9c_ard_3-2-1_104076_2022-08-28_final.stac-item
2022-09-13 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-09-13_final.stac-item
2022-09-29 10:45:59	ga_ls9c_ard_3-2-1_104081_2022-09-29_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 10:27:28	ga_ls9c_ard_3-2-1_101081_2022-10-10_final.stac-item
2022-10-21 10:06:12	ga_ls9c_ard_3-2-1_098074_2022-10-21_final.stac-item
2022-11-05 11:04:58	ga_ls9c_ard_3-2-1_107082_2022-11-05_final.stac-item
2022-11-08 11:34:18	ga_ls9c_ard_3-2-1_112078_2022-11-08_final.stac-item
2022-11-11 10:23:09	ga_ls9c_ard_3-2-1_101070_2022-11-11_final.stac-item
2022-11-15 11:40:31	ga_ls9c_ard_3-2-1_113078_2022-11-15_final.stac-item
2022-11-19 09:38:30	ga_ls9c_ard_3-2-1_093082_2022-11-19_final.stac-item
2022-11-20 11:58:39	ga_ls9c_ard_3-2-1_116077_2022-11-20_final.stac-item
2022-11-21 11:05:01	ga_ls9c_ard_3-2-1_107082_2022-11-21_final.stac-item
2022-11-26 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-11-26_final.stac-item
2022-12-01 11:40:27	ga_ls9c_ard_3-2-1_113078_2022-12-01_final.stac-item
2022-12-10 09:54:14	ga_ls9c_ard_3-2-1_096075_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 11:35:31	ga_ls9c_ard_3-2-1_112081_2022-12-10_final.stac-item
2022-12-19 11:28:31	ga_ls9c_ard_3-2-1_111079_2022-12-19_final.stac-item
2022-12-22 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-12-22_final.stac-item
2022-12-25 10:51:00	ga_ls9c_ard_3-2-1_105078_2022-12-25_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2023-01-06 09:38:29	ga_ls9c_ard_3-2-1_093082_2023-01-06_final.stac-item
2023-01-08 09:24:55	ga_ls9c_ard_3-2-1_091079_2023-01-07_final.stac-item
2023-01-11 09:56:12	ga_ls9c_ard_3-2-1_096080_2023-01-11_final.stac-item
2023-01-18 10:00:18	ga_ls9c_ard_3-2-1_097075_2023-01-18_final.stac-item
2023-01-19 10:45:08	ga_ls9c_ard_3-2-1_104079_2023-01-19_final.stac-item
2023-01-25 10:08:54	ga_ls9c_ard_3-2-1_098081_2023-01-25_final.stac-item
2023-01-29 11:21:56	ga_ls9c_ard_3-2-1_110078_2023-01-29_final.stac-item
2023-02-09 11:03:28	ga_ls9c_ard_3-2-1_107078_2023-02-09_final.stac-item
2023-02-12 09:54:41	ga_ls9c_ard_3-2-1_096076_2023-02-12_final.stac-item
2023-03-02 09:43:40	ga_ls9c_ard_3-2-1_094080_2023-03-02_final.stac-item
2023-03-06 09:20:06	ga_ls9c_ard_3-2-1_090083_2023-03-05_final.stac-item
2023-03-16 09:54:44	ga_ls9c_ard_3-2-1_096077_2023-03-16_final.stac-item
2023-03-26 10:32:29	ga_ls9c_ard_3-2-1_102079_2023-03-26_final.stac-item
2023-04-22 11:50:39	ga_ls9c_ard_3-2-1_115074_2023-04-22_final.stac-item
2023-04-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2023-04-23_final.stac-item
2023-04-24 11:40:40	ga_ls9c_ard_3-2-1_113080_2023-04-24_final.stac-item
2023-04-26 11:26:41	ga_ls9c_ard_3-2-1_111076_2023-04-26_final.stac-item
2023-04-28 09:36:13	ga_ls9c_ard_3-2-1_093078_2023-04-28_final.stac-item
2023-04-30 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-04-29_final.stac-item
2023-05-03 09:55:27	ga_ls9c_ard_3-2-1_096080_2023-05-03_final.stac-item
2023-05-04 10:35:06	ga_ls9c_ard_3-2-1_103071_2023-05-04_final.stac-item
2023-05-14 09:36:04	ga_ls9c_ard_3-2-1_093078_2023-05-14_final.stac-item
2023-05-19 09:55:21	ga_ls9c_ard_3-2-1_096080_2023-05-19_final.stac-item
2023-05-19 11:32:14	ga_ls9c_ard_3-2-1_112075_2023-05-19_final.stac-item
2023-05-29 10:29:08	ga_ls9c_ard_3-2-1_102072_2023-05-29_final.stac-item
2023-05-30 09:35:31	ga_ls9c_ard_3-2-1_093077_2023-05-30_final.stac-item
2023-06-19 10:47:08	ga_ls9c_ard_3-2-1_105071_2023-06-19_final.stac-item
2023-06-22 11:22:01	ga_ls9c_ard_3-2-1_110081_2023-06-22_final.stac-item
2023-06-24 09:29:59	ga_ls9c_ard_3-2-1_092079_2023-06-23_final.stac-item
2023-07-05 10:46:56	ga_ls9c_ard_3-2-1_105070_2023-07-05_final.stac-item
2023-07-06 11:33:24	ga_ls9c_ard_3-2-1_112078_2023-07-06_final.stac-item
2023-07-15 09:50:00	ga_ls9c_ard_3-2-1_095082_2023-07-15_final.stac-item
2023-07-16 10:31:16	ga_ls9c_ard_3-2-1_102077_2023-07-16_final.stac-item
2023-07-20 10:05:45	ga_ls9c_ard_3-2-1_098075_2023-07-20_final.stac-item
2023-07-22 09:54:58	ga_ls9c_ard_3-2-1_096079_2023-07-22_final.stac-item
2023-07-23 10:36:14	ga_ls9c_ard_3-2-1_103074_2023-07-23_final.stac-item
2023-07-26 11:09:08	ga_ls9c_ard_3-2-1_108079_2023-07-26_final.stac-item
2023-07-26 11:10:20	ga_ls9c_ard_3-2-1_108082_2023-07-26_final.stac-item
2023-07-28 10:56:49	ga_ls9c_ard_3-2-1_106079_2023-07-28_final.stac-item
2023-08-02 09:36:57	ga_ls9c_ard_3-2-1_093080_2023-08-02_final.stac-item
2023-08-05 10:08:41	ga_ls9c_ard_3-2-1_098082_2023-08-05_final.stac-item
2023-08-08 10:36:24	ga_ls9c_ard_3-2-1_103074_2023-08-08_final.stac-item
2023-10-15 10:15:21	ga_ls9c_ard_3-2-1_099082_2023-10-15_final.stac-item
2023-10-17 11:39:29	ga_ls9c_ard_3-2-1_113076_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
2023-10-22 10:20:45	ga_ls9c_ard_3-2-1_100080_2023-10-22_final.stac-item
2023-10-25 10:51:14	ga_ls9c_ard_3-2-1_105079_2023-10-25_final.stac-item
2023-10-26 09:54:00	ga_ls9c_ard_3-2-1_096075_2023-10-26_final.stac-item
2023-10-28 09:41:38	ga_ls9c_ard_3-2-1_094075_2023-10-28_final.stac-item
2023-11-04 09:48:08	ga_ls9c_ard_3-2-1_095076_2023-11-04_final.stac-item
2023-11-18 10:02:58	ga_ls9c_ard_3-2-1_097082_2023-11-18_final.stac-item
2023-11-20 11:28:19	ga_ls9c_ard_3-2-1_111079_2023-11-20_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