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
2021-11-20 09:45:12	ga_ls9c_ard_3-2-1_094079_2021-11-20_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 09:54:34	ga_ls9c_ard_3-2-1_096076_2021-12-07_final.stac-item
2021-12-23 09:54:28	ga_ls9c_ard_3-2-1_096076_2021-12-23_final.stac-item
2021-12-30 10:00:15	ga_ls9c_ard_3-2-1_097075_2021-12-30_final.stac-item
2022-01-08 09:54:26	ga_ls9c_ard_3-2-1_096076_2022-01-08_final.stac-item
2022-01-10 09:42:52	ga_ls9c_ard_3-2-1_094078_2022-01-10_final.stac-item
2022-01-26 09:43:17	ga_ls9c_ard_3-2-1_094079_2022-01-26_final.stac-item
2022-01-31 10:02:14	ga_ls9c_ard_3-2-1_097080_2022-01-31_final.stac-item
2022-02-25 09:52:40	ga_ls9c_ard_3-2-1_096072_2022-02-25_final.stac-item
2022-03-11 10:08:58	ga_ls9c_ard_3-2-1_098082_2022-03-11_final.stac-item
2022-03-27 10:08:52	ga_ls9c_ard_3-2-1_098082_2022-03-27_final.stac-item
2022-04-16 09:42:27	ga_ls9c_ard_3-2-1_094078_2022-04-16_final.stac-item
2022-04-21 09:59:43	ga_ls9c_ard_3-2-1_097075_2022-04-21_final.stac-item
2022-07-03 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-03_final.stac-item
2022-07-03 11:32:56	ga_ls9c_ard_3-2-1_112076_2022-07-03_final.stac-item
2022-07-05 09:40:29	ga_ls9c_ard_3-2-1_094073_2022-07-05_final.stac-item
2022-07-12 09:49:25	ga_ls9c_ard_3-2-1_095080_2022-07-12_final.stac-item
2022-07-18 09:09:58	ga_ls9c_ard_3-2-1_089074_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
2022-08-08 09:32:00	ga_ls9c_ard_3-2-1_092082_2022-08-08_final.stac-item
2022-08-22 09:42:51	ga_ls9c_ard_3-2-1_094078_2022-08-22_final.stac-item
2022-08-29 09:48:38	ga_ls9c_ard_3-2-1_095077_2022-08-29_final.stac-item
2022-09-02 09:23:55	ga_ls9c_ard_3-2-1_091077_2022-09-01_final.stac-item
2022-09-30 09:48:46	ga_ls9c_ard_3-2-1_095077_2022-09-30_final.stac-item
2022-09-30 09:49:09	ga_ls9c_ard_3-2-1_095078_2022-09-30_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-17 09:49:16	ga_ls9c_ard_3-2-1_095078_2022-11-17_final.stac-item
2022-11-23 09:10:59	ga_ls9c_ard_3-2-1_089075_2022-11-22_final.stac-item
2022-11-28 11:09:34	ga_ls9c_ard_3-2-1_108078_2022-11-28_final.stac-item
2022-12-10 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-12-10_final.stac-item
2022-12-14 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-14_final.stac-item
2022-12-15 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-15_final.stac-item
2022-12-22 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-12-22_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2022-12-30 11:09:35	ga_ls9c_ard_3-2-1_108078_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
2023-01-11 11:34:41	ga_ls9c_ard_3-2-1_112079_2023-01-11_final.stac-item
2023-01-15 11:09:08	ga_ls9c_ard_3-2-1_108077_2023-01-15_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-18 11:39:58	ga_ls9c_ard_3-2-1_113077_2023-01-18_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-29 09:43:27	ga_ls9c_ard_3-2-1_094079_2023-01-29_final.stac-item
2023-01-31 11:09:12	ga_ls9c_ard_3-2-1_108077_2023-01-31_final.stac-item
2023-01-31 11:09:36	ga_ls9c_ard_3-2-1_108078_2023-01-31_final.stac-item
2023-02-05 09:48:54	ga_ls9c_ard_3-2-1_095077_2023-02-05_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-03-02 09:42:52	ga_ls9c_ard_3-2-1_094078_2023-03-02_final.stac-item
2023-03-02 09:43:16	ga_ls9c_ard_3-2-1_094079_2023-03-02_final.stac-item
2023-03-03 10:26:55	ga_ls9c_ard_3-2-1_101080_2023-03-03_final.stac-item
2023-03-11 09:38:10	ga_ls9c_ard_3-2-1_093082_2023-03-11_final.stac-item
2023-04-03 09:42:58	ga_ls9c_ard_3-2-1_094079_2023-04-03_final.stac-item
2023-04-07 09:18:38	ga_ls9c_ard_3-2-1_090080_2023-04-06_final.stac-item
2023-04-24 10:02:35	ga_ls9c_ard_3-2-1_097082_2023-04-24_final.stac-item
2023-04-27 10:31:03	ga_ls9c_ard_3-2-1_102076_2023-04-27_final.stac-item
2023-05-03 09:53:51	ga_ls9c_ard_3-2-1_096076_2023-05-03_final.stac-item
2023-05-03 11:33:08	ga_ls9c_ard_3-2-1_112077_2023-05-03_final.stac-item
2023-05-03 11:33:32	ga_ls9c_ard_3-2-1_112078_2023-05-03_final.stac-item
2023-05-03 11:33:56	ga_ls9c_ard_3-2-1_112079_2023-05-03_final.stac-item
2023-05-05 09:42:16	ga_ls9c_ard_3-2-1_094078_2023-05-05_final.stac-item
2023-05-05 09:42:40	ga_ls9c_ard_3-2-1_094079_2023-05-05_final.stac-item
2023-05-05 11:17:57	ga_ls9c_ard_3-2-1_110070_2023-05-05_final.stac-item
2023-05-07 11:08:47	ga_ls9c_ard_3-2-1_108078_2023-05-07_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-09 10:58:26	ga_ls9c_ard_3-2-1_106083_2023-05-09_final.stac-item
2023-05-10 10:00:24	ga_ls9c_ard_3-2-1_097077_2023-05-10_final.stac-item
2023-05-14 09:36:28	ga_ls9c_ard_3-2-1_093079_2023-05-14_final.stac-item
2023-05-15 11:57:48	ga_ls9c_ard_3-2-1_116077_2023-05-15_final.stac-item
2023-06-20 09:53:30	ga_ls9c_ard_3-2-1_096076_2023-06-20_final.stac-item
2023-06-22 09:41:57	ga_ls9c_ard_3-2-1_094078_2023-06-22_final.stac-item
2023-06-22 11:21:14	ga_ls9c_ard_3-2-1_110079_2023-06-22_final.stac-item
2023-06-24 11:08:28	ga_ls9c_ard_3-2-1_108078_2023-06-24_final.stac-item
2023-06-25 10:14:02	ga_ls9c_ard_3-2-1_099081_2023-06-25_final.stac-item
2023-06-27 11:38:36	ga_ls9c_ard_3-2-1_113076_2023-06-27_final.stac-item
2023-06-30 10:29:07	ga_ls9c_ard_3-2-1_102072_2023-06-30_final.stac-item
2023-07-15 09:48:24	ga_ls9c_ard_3-2-1_095078_2023-07-15_final.stac-item
2023-07-22 09:56:34	ga_ls9c_ard_3-2-1_096083_2023-07-22_final.stac-item
2023-07-22 11:33:03	ga_ls9c_ard_3-2-1_112077_2023-07-22_final.stac-item
2023-08-05 10:06:17	ga_ls9c_ard_3-2-1_098076_2023-08-05_final.stac-item
2023-10-13 10:26:53	ga_ls9c_ard_3-2-1_101080_2023-10-13_final.stac-item
2023-10-17 11:39:53	ga_ls9c_ard_3-2-1_113077_2023-10-17_final.stac-item
2023-10-19 09:49:03	ga_ls9c_ard_3-2-1_095078_2023-10-19_final.stac-item
2023-10-24 10:06:47	ga_ls9c_ard_3-2-1_098076_2023-10-24_final.stac-item
2023-10-24 10:08:46	ga_ls9c_ard_3-2-1_098081_2023-10-24_final.stac-item
2023-10-26 09:54:24	ga_ls9c_ard_3-2-1_096076_2023-10-26_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-26 11:34:29	ga_ls9c_ard_3-2-1_112079_2023-10-26_final.stac-item
2023-10-28 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-28_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 10:26:52	ga_ls9c_ard_3-2-1_101080_2023-10-29_final.stac-item
2023-10-30 11:08:55	ga_ls9c_ard_3-2-1_108077_2023-10-30_final.stac-item
2023-10-31 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-10-31_final.stac-item
2023-11-04 09:48:32	ga_ls9c_ard_3-2-1_095077_2023-11-04_final.stac-item
2023-11-04 09:48:56	ga_ls9c_ard_3-2-1_095078_2023-11-04_final.stac-item
2023-11-04 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-11-04_final.stac-item
2023-11-14 10:26:27	ga_ls9c_ard_3-2-1_101079_2023-11-14_final.stac-item
2023-11-15 11:08:55	ga_ls9c_ard_3-2-1_108077_2023-11-15_final.stac-item
2023-11-15 11:09:18	ga_ls9c_ard_3-2-1_108078_2023-11-15_final.stac-item
2023-11-16 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-11-16_final.stac-item
2023-11-18 11:39:51	ga_ls9c_ard_3-2-1_113077_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