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
2021-12-09 09:42:59	ga_ls9c_ard_3-2-1_094078_2021-12-09_final.stac-item
2021-12-23 09:54:52	ga_ls9c_ard_3-2-1_096077_2021-12-23_final.stac-item
2022-03-22 09:47:59	ga_ls9c_ard_3-2-1_095076_2022-03-22_final.stac-item
2022-03-24 09:37:36	ga_ls9c_ard_3-2-1_093081_2022-03-24_final.stac-item
2022-03-24 09:38:00	ga_ls9c_ard_3-2-1_093082_2022-03-24_final.stac-item
2022-05-08 10:44:54	ga_ls9c_ard_3-2-1_104080_2022-05-08_final.stac-item
2022-06-21 09:31:13	ga_ls9c_ard_3-2-1_092081_2022-06-21_final.stac-item
2022-07-03 09:54:51	ga_ls9c_ard_3-2-1_096078_2022-07-03_final.stac-item
2022-07-11 10:44:14	ga_ls9c_ard_3-2-1_104078_2022-07-11_final.stac-item
2022-07-12 09:49:25	ga_ls9c_ard_3-2-1_095080_2022-07-12_final.stac-item
2022-07-12 09:49:49	ga_ls9c_ard_3-2-1_095081_2022-07-12_final.stac-item
2022-07-28 09:49:36	ga_ls9c_ard_3-2-1_095080_2022-07-28_final.stac-item
2022-08-04 09:55:05	ga_ls9c_ard_3-2-1_096078_2022-08-04_final.stac-item
2022-08-20 09:55:12	ga_ls9c_ard_3-2-1_096078_2022-08-20_final.stac-item
2022-08-21 10:38:28	ga_ls9c_ard_3-2-1_103078_2022-08-21_final.stac-item
2022-08-22 09:41:39	ga_ls9c_ard_3-2-1_094075_2022-08-22_final.stac-item
2022-09-23 09:43:22	ga_ls9c_ard_3-2-1_094079_2022-09-23_final.stac-item
2022-10-01 10:31:13	ga_ls9c_ard_3-2-1_102075_2022-10-01_final.stac-item
2022-10-08 10:37:24	ga_ls9c_ard_3-2-1_103075_2022-10-08_final.stac-item
2022-10-09 11:22:17	ga_ls9c_ard_3-2-1_110079_2022-10-09_final.stac-item
2022-10-16 09:49:38	ga_ls9c_ard_3-2-1_095079_2022-10-16_final.stac-item
2022-10-17 10:33:42	ga_ls9c_ard_3-2-1_102081_2022-10-17_final.stac-item
2022-10-27 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-10-27_final.stac-item
2022-11-01 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-11-01_final.stac-item
2022-11-18 10:31:20	ga_ls9c_ard_3-2-1_102075_2022-11-18_final.stac-item
2022-12-03 09:49:13	ga_ls9c_ard_3-2-1_095078_2022-12-03_final.stac-item
2022-12-03 11:28:30	ga_ls9c_ard_3-2-1_111079_2022-12-03_final.stac-item
2022-12-17 10:00:24	ga_ls9c_ard_3-2-1_097075_2022-12-17_final.stac-item
2022-12-23 11:03:21	ga_ls9c_ard_3-2-1_107078_2022-12-23_final.stac-item
2022-12-26 11:34:16	ga_ls9c_ard_3-2-1_112078_2022-12-26_final.stac-item
2022-12-30 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-30_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-07 10:21:21	ga_ls9c_ard_3-2-1_100081_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
2023-01-20 09:49:29	ga_ls9c_ard_3-2-1_095079_2023-01-20_final.stac-item
2023-01-20 11:28:22	ga_ls9c_ard_3-2-1_111079_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
2023-01-29 09:43:03	ga_ls9c_ard_3-2-1_094078_2023-01-29_final.stac-item
2023-01-29 11:21:56	ga_ls9c_ard_3-2-1_110078_2023-01-29_final.stac-item
2023-02-06 10:33:22	ga_ls9c_ard_3-2-1_102080_2023-02-06_final.stac-item
2023-02-14 09:43:06	ga_ls9c_ard_3-2-1_094078_2023-02-14_final.stac-item
2023-04-23 10:56:13	ga_ls9c_ard_3-2-1_106077_2023-04-23_final.stac-item
2023-04-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2023-04-23_final.stac-item
2023-04-25 10:43:50	ga_ls9c_ard_3-2-1_104077_2023-04-25_final.stac-item
2023-04-26 11:27:05	ga_ls9c_ard_3-2-1_111077_2023-04-26_final.stac-item
2023-04-27 10:31:51	ga_ls9c_ard_3-2-1_102078_2023-04-27_final.stac-item
2023-04-30 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-04-29_final.stac-item
2023-05-02 10:49:54	ga_ls9c_ard_3-2-1_105077_2023-05-02_final.stac-item
2023-05-02 10:51:06	ga_ls9c_ard_3-2-1_105080_2023-05-02_final.stac-item
2023-05-03 09:55:03	ga_ls9c_ard_3-2-1_096079_2023-05-03_final.stac-item
2023-05-03 09:55:27	ga_ls9c_ard_3-2-1_096080_2023-05-03_final.stac-item
2023-05-03 09:56:15	ga_ls9c_ard_3-2-1_096082_2023-05-03_final.stac-item
2023-05-04 10:37:06	ga_ls9c_ard_3-2-1_103076_2023-05-04_final.stac-item
2023-05-04 10:39:29	ga_ls9c_ard_3-2-1_103082_2023-05-04_final.stac-item
2023-05-05 11:21:09	ga_ls9c_ard_3-2-1_110078_2023-05-05_final.stac-item
2023-05-07 09:30:18	ga_ls9c_ard_3-2-1_092079_2023-05-07_final.stac-item
2023-05-10 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-05-10_final.stac-item
2023-05-12 11:26:55	ga_ls9c_ard_3-2-1_111077_2023-05-12_final.stac-item
2023-05-28 11:26:46	ga_ls9c_ard_3-2-1_111077_2023-05-28_final.stac-item
2023-05-28 11:27:57	ga_ls9c_ard_3-2-1_111080_2023-05-28_final.stac-item
2023-06-20 09:53:06	ga_ls9c_ard_3-2-1_096075_2023-06-20_final.stac-item
2023-06-20 09:54:42	ga_ls9c_ard_3-2-1_096079_2023-06-20_final.stac-item
2023-06-22 09:43:08	ga_ls9c_ard_3-2-1_094081_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
2023-06-27 09:59:19	ga_ls9c_ard_3-2-1_097075_2023-06-27_final.stac-item
2023-07-06 09:53:19	ga_ls9c_ard_3-2-1_096075_2023-07-06_final.stac-item
2023-07-15 09:48:48	ga_ls9c_ard_3-2-1_095079_2023-07-15_final.stac-item
2023-07-15 11:26:53	ga_ls9c_ard_3-2-1_111077_2023-07-15_final.stac-item
2023-07-15 11:28:05	ga_ls9c_ard_3-2-1_111080_2023-07-15_final.stac-item
2023-07-16 10:31:40	ga_ls9c_ard_3-2-1_102078_2023-07-16_final.stac-item
2023-07-16 10:32:04	ga_ls9c_ard_3-2-1_102079_2023-07-16_final.stac-item
2023-07-19 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-07-19_final.stac-item
2023-07-22 11:32:15	ga_ls9c_ard_3-2-1_112075_2023-07-22_final.stac-item
2023-07-24 09:42:36	ga_ls9c_ard_3-2-1_094079_2023-07-24_final.stac-item
2023-07-25 10:25:51	ga_ls9c_ard_3-2-1_101079_2023-07-25_final.stac-item
2023-07-25 10:26:15	ga_ls9c_ard_3-2-1_101080_2023-07-25_final.stac-item
2023-07-26 09:31:51	ga_ls9c_ard_3-2-1_092083_2023-07-26_final.stac-item
2023-07-26 11:09:08	ga_ls9c_ard_3-2-1_108079_2023-07-26_final.stac-item
2023-07-29 10:02:24	ga_ls9c_ard_3-2-1_097082_2023-07-29_final.stac-item
2023-07-29 11:38:54	ga_ls9c_ard_3-2-1_113076_2023-07-29_final.stac-item
2023-08-02 11:15:26	ga_ls9c_ard_3-2-1_109079_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 10:36:48	ga_ls9c_ard_3-2-1_103075_2023-08-08_final.stac-item
2023-08-08 10:37:12	ga_ls9c_ard_3-2-1_103076_2023-08-08_final.stac-item
2023-08-08 10:38:00	ga_ls9c_ard_3-2-1_103078_2023-08-08_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_final.stac-item
2023-10-14 09:30:29	ga_ls9c_ard_3-2-1_092078_2023-10-14_final.stac-item
2023-10-15 10:15:21	ga_ls9c_ard_3-2-1_099082_2023-10-15_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-10-19 09:49:51	ga_ls9c_ard_3-2-1_095080_2023-10-19_final.stac-item
2023-10-21 09:37:29	ga_ls9c_ard_3-2-1_093080_2023-10-21_final.stac-item
2023-10-24 10:09:10	ga_ls9c_ard_3-2-1_098082_2023-10-24_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-27 10:40:03	ga_ls9c_ard_3-2-1_103082_2023-10-27_final.stac-item
2023-10-28 11:18:31	ga_ls9c_ard_3-2-1_110070_2023-10-28_final.stac-item
2023-10-29 10:27:16	ga_ls9c_ard_3-2-1_101081_2023-10-29_final.stac-item
2023-11-03 10:44:56	ga_ls9c_ard_3-2-1_104079_2023-11-03_final.stac-item
2023-11-18 10:00:10	ga_ls9c_ard_3-2-1_097075_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
2023-11-26 10:52:06	ga_ls9c_ard_3-2-1_105081_2023-11-26_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