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 11:37:42	ga_ls9c_ard_3-2-1_113079_2021-11-08_final.stac-item
2021-11-18 10:02:22	ga_ls9c_ard_3-2-1_097075_2021-11-18_final.stac-item
2021-12-26 10:26:58	ga_ls9c_ard_3-2-1_101080_2021-12-26_final.stac-item
2021-12-27 11:09:02	ga_ls9c_ard_3-2-1_108077_2021-12-27_final.stac-item
2021-12-30 10:00:15	ga_ls9c_ard_3-2-1_097075_2021-12-30_final.stac-item
2022-01-19 09:37:05	ga_ls9c_ard_3-2-1_093079_2022-01-19_final.stac-item
2022-03-01 11:08:46	ga_ls9c_ard_3-2-1_108077_2022-03-01_final.stac-item
2022-03-01 11:09:10	ga_ls9c_ard_3-2-1_108078_2022-03-01_final.stac-item
2022-03-31 09:42:34	ga_ls9c_ard_3-2-1_094078_2022-03-31_final.stac-item
2022-04-14 09:54:02	ga_ls9c_ard_3-2-1_096076_2022-04-14_final.stac-item
2022-04-14 11:32:55	ga_ls9c_ard_3-2-1_112076_2022-04-14_final.stac-item
2022-04-14 11:33:19	ga_ls9c_ard_3-2-1_112077_2022-04-14_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
2022-04-21 11:39:00	ga_ls9c_ard_3-2-1_113076_2022-04-21_final.stac-item
2022-04-24 10:31:01	ga_ls9c_ard_3-2-1_102076_2022-04-24_final.stac-item
2022-05-23 09:57:05	ga_ls9c_ard_3-2-1_097069_2022-05-23_final.stac-item
2022-06-10 09:47:57	ga_ls9c_ard_3-2-1_095077_2022-06-10_final.stac-item
2022-06-10 09:48:20	ga_ls9c_ard_3-2-1_095078_2022-06-10_final.stac-item
2022-06-12 09:38:24	ga_ls9c_ard_3-2-1_093084_2022-06-12_final.stac-item
2022-06-26 09:48:17	ga_ls9c_ard_3-2-1_095077_2022-06-26_final.stac-item
2022-06-26 09:48:41	ga_ls9c_ard_3-2-1_095078_2022-06-26_final.stac-item
2022-06-27 10:32:20	ga_ls9c_ard_3-2-1_102079_2022-06-27_final.stac-item
2022-07-07 11:08:59	ga_ls9c_ard_3-2-1_108078_2022-07-07_final.stac-item
2022-07-12 09:48:37	ga_ls9c_ard_3-2-1_095078_2022-07-12_final.stac-item
2022-07-19 11:33:44	ga_ls9c_ard_3-2-1_112078_2022-07-19_final.stac-item
2022-07-26 11:39:14	ga_ls9c_ard_3-2-1_113076_2022-07-26_final.stac-item
2022-07-28 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-07-28_final.stac-item
2022-07-29 10:31:17	ga_ls9c_ard_3-2-1_102076_2022-07-29_final.stac-item
2022-08-04 09:54:17	ga_ls9c_ard_3-2-1_096076_2022-08-04_final.stac-item
2022-08-06 11:24:25	ga_ls9c_ard_3-2-1_110085_2022-08-06_final.stac-item
2022-08-11 11:39:25	ga_ls9c_ard_3-2-1_113076_2022-08-11_final.stac-item
2022-08-13 09:48:59	ga_ls9c_ard_3-2-1_095078_2022-08-13_final.stac-item
2022-08-13 11:25:04	ga_ls9c_ard_3-2-1_111071_2022-08-13_final.stac-item
2022-08-18 10:09:09	ga_ls9c_ard_3-2-1_098082_2022-08-18_final.stac-item
2022-08-20 11:33:41	ga_ls9c_ard_3-2-1_112077_2022-08-20_final.stac-item
2022-08-20 11:34:05	ga_ls9c_ard_3-2-1_112078_2022-08-20_final.stac-item
2022-08-22 09:42:51	ga_ls9c_ard_3-2-1_094078_2022-08-22_final.stac-item
2022-08-27 11:39:29	ga_ls9c_ard_3-2-1_113076_2022-08-27_final.stac-item
2022-08-30 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-08-30_final.stac-item
2022-09-12 10:03:01	ga_ls9c_ard_3-2-1_097082_2022-09-12_final.stac-item
2022-09-19 10:09:15	ga_ls9c_ard_3-2-1_098082_2022-09-19_final.stac-item
2022-09-21 09:54:07	ga_ls9c_ard_3-2-1_096075_2022-09-21_final.stac-item
2022-09-25 11:09:30	ga_ls9c_ard_3-2-1_108078_2022-09-25_final.stac-item
2022-10-27 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-10-27_final.stac-item
2022-10-27 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-10-27_final.stac-item
2022-11-28 09:34:41	ga_ls9c_ard_3-2-1_092088_2022-11-28_final.stac-item
2022-11-28 11:09:34	ga_ls9c_ard_3-2-1_108078_2022-11-28_final.stac-item
2022-12-13 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-12-13_final.stac-item
2023-01-15 11:09:08	ga_ls9c_ard_3-2-1_108077_2023-01-15_final.stac-item
2023-01-21 10:31:33	ga_ls9c_ard_3-2-1_102076_2023-01-21_final.stac-item
2023-02-15 10:27:08	ga_ls9c_ard_3-2-1_101080_2023-02-15_final.stac-item
2023-02-16 11:09:11	ga_ls9c_ard_3-2-1_108077_2023-02-16_final.stac-item
2023-03-03 10:26:55	ga_ls9c_ard_3-2-1_101080_2023-03-03_final.stac-item
2023-03-04 11:08:59	ga_ls9c_ard_3-2-1_108077_2023-03-04_final.stac-item
2023-03-04 11:09:22	ga_ls9c_ard_3-2-1_108078_2023-03-04_final.stac-item
2023-03-16 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-03-16_final.stac-item
2023-03-20 11:09:16	ga_ls9c_ard_3-2-1_108078_2023-03-20_final.stac-item
2023-03-25 09:48:51	ga_ls9c_ard_3-2-1_095078_2023-03-25_final.stac-item
2023-04-10 09:48:18	ga_ls9c_ard_3-2-1_095077_2023-04-10_final.stac-item
2023-04-21 11:08:59	ga_ls9c_ard_3-2-1_108078_2023-04-21_final.stac-item
2023-04-24 10:02:35	ga_ls9c_ard_3-2-1_097082_2023-04-24_final.stac-item
2023-04-26 09:48:12	ga_ls9c_ard_3-2-1_095077_2023-04-26_final.stac-item
2023-04-26 09:48:36	ga_ls9c_ard_3-2-1_095078_2023-04-26_final.stac-item
2023-05-01 11:45:09	ga_ls9c_ard_3-2-1_114076_2023-05-01_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 11:33:56	ga_ls9c_ard_3-2-1_112079_2023-05-03_final.stac-item
2023-05-07 11:08:47	ga_ls9c_ard_3-2-1_108078_2023-05-07_final.stac-item
2023-05-12 09:48:26	ga_ls9c_ard_3-2-1_095078_2023-05-12_final.stac-item
2023-05-19 11:32:38	ga_ls9c_ard_3-2-1_112076_2023-05-19_final.stac-item
2023-05-19 11:33:26	ga_ls9c_ard_3-2-1_112078_2023-05-19_final.stac-item
2023-05-23 11:08:38	ga_ls9c_ard_3-2-1_108078_2023-05-23_final.stac-item
2023-06-04 11:33:19	ga_ls9c_ard_3-2-1_112078_2023-06-04_final.stac-item
2023-06-08 11:08:34	ga_ls9c_ard_3-2-1_108078_2023-06-08_final.stac-item
2023-06-13 09:48:09	ga_ls9c_ard_3-2-1_095078_2023-06-13_final.stac-item
2023-06-14 10:31:48	ga_ls9c_ard_3-2-1_102079_2023-06-14_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
2023-09-06 10:08:56	ga_ls9c_ard_3-2-1_098082_2023-09-06_final.stac-item
2023-09-08 11:34:17	ga_ls9c_ard_3-2-1_112079_2023-09-08_final.stac-item
2023-09-09 10:39:52	ga_ls9c_ard_3-2-1_103082_2023-09-09_final.stac-item
2023-09-12 11:09:12	ga_ls9c_ard_3-2-1_108078_2023-09-12_final.stac-item
2023-09-15 10:02:50	ga_ls9c_ard_3-2-1_097082_2023-09-15_final.stac-item
2023-09-17 09:48:29	ga_ls9c_ard_3-2-1_095077_2023-09-17_final.stac-item
2023-09-26 09:42:38	ga_ls9c_ard_3-2-1_094078_2023-09-26_final.stac-item
2023-09-27 10:26:41	ga_ls9c_ard_3-2-1_101080_2023-09-27_final.stac-item
2023-09-28 11:08:44	ga_ls9c_ard_3-2-1_108077_2023-09-28_final.stac-item
2023-10-03 09:48:53	ga_ls9c_ard_3-2-1_095078_2023-10-03_final.stac-item
2023-10-08 10:08:40	ga_ls9c_ard_3-2-1_098081_2023-10-08_final.stac-item
2023-10-10 11:33:37	ga_ls9c_ard_3-2-1_112077_2023-10-10_final.stac-item
2023-10-12 09:42:49	ga_ls9c_ard_3-2-1_094078_2023-10-12_final.stac-item
2023-10-13 10:26:53	ga_ls9c_ard_3-2-1_101080_2023-10-13_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
2023-11-15 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
2023-12-01 11:09:03	ga_ls9c_ard_3-2-1_108077_2023-12-01_final.stac-item
2024-01-02 11:09:01	ga_ls9c_ard_3-2-1_108077_2024-01-02_final.stac-item
2024-01-02 11:09:25	ga_ls9c_ard_3-2-1_108078_2024-01-02_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