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

69 results

Time (local)	Label
2021-11-07 09:17:29	ga_ls9c_ard_3-2-1_090075_2021-11-06_final.stac-item
2021-11-22 09:24:52	ga_ls9c_ard_3-2-1_091075_2021-11-21_final.stac-item
2021-12-17 10:30:20	ga_ls9c_ard_3-2-1_102073_2021-12-17_final.stac-item
2021-12-29 10:54:17	ga_ls9c_ard_3-2-1_106071_2021-12-29_final.stac-item
2022-01-04 10:18:47	ga_ls9c_ard_3-2-1_100075_2022-01-04_final.stac-item
2022-01-21 11:00:50	ga_ls9c_ard_3-2-1_107072_2022-01-21_final.stac-item
2022-03-10 11:00:36	ga_ls9c_ard_3-2-1_107072_2022-03-10_final.stac-item
2022-03-12 10:52:13	ga_ls9c_ard_3-2-1_105082_2022-03-12_final.stac-item
2022-04-07 11:24:01	ga_ls9c_ard_3-2-1_111069_2022-04-07_final.stac-item
2022-06-27 10:29:09	ga_ls9c_ard_3-2-1_102071_2022-06-27_final.stac-item
2022-07-18 09:11:58	ga_ls9c_ard_3-2-1_089079_2022-07-17_final.stac-item
2022-08-22 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-08-22_final.stac-item
2022-09-02 11:00:00	ga_ls9c_ard_3-2-1_107070_2022-09-02_final.stac-item
2022-09-07 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-09-07_final.stac-item
2022-10-09 09:41:00	ga_ls9c_ard_3-2-1_094073_2022-10-09_final.stac-item
2022-10-17 10:32:06	ga_ls9c_ard_3-2-1_102077_2022-10-17_final.stac-item
2022-11-03 11:17:43	ga_ls9c_ard_3-2-1_109083_2022-11-03_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-12-08 10:04:35	ga_ls9c_ard_3-2-1_098070_2022-12-08_final.stac-item
2022-12-12 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-12-12_final.stac-item
2022-12-20 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-20_final.stac-item
2023-02-06 10:34:10	ga_ls9c_ard_3-2-1_102082_2023-02-06_final.stac-item
2023-02-07 09:35:45	ga_ls9c_ard_3-2-1_093075_2023-02-07_final.stac-item
2023-02-11 10:49:30	ga_ls9c_ard_3-2-1_105074_2023-02-11_final.stac-item
2023-02-24 10:21:57	ga_ls9c_ard_3-2-1_100083_2023-02-24_final.stac-item
2023-04-14 11:03:37	ga_ls9c_ard_3-2-1_107080_2023-04-14_final.stac-item
2023-05-12 09:50:50	ga_ls9c_ard_3-2-1_095084_2023-05-12_final.stac-item
2023-05-12 11:24:32	ga_ls9c_ard_3-2-1_111071_2023-05-12_final.stac-item
2023-06-09 10:10:32	ga_ls9c_ard_3-2-1_099072_2023-06-09_final.stac-item
2023-06-09 11:51:49	ga_ls9c_ard_3-2-1_115078_2023-06-09_final.stac-item
2023-06-24 11:05:16	ga_ls9c_ard_3-2-1_108070_2023-06-24_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-07-03 11:03:39	ga_ls9c_ard_3-2-1_107081_2023-07-03_final.stac-item
2023-07-08 11:19:52	ga_ls9c_ard_3-2-1_110075_2023-07-08_final.stac-item
2023-07-12 09:17:05	ga_ls9c_ard_3-2-1_090077_2023-07-11_final.stac-item
2023-07-19 09:26:52	ga_ls9c_ard_3-2-1_091086_2023-07-18_final.stac-item
2023-07-24 11:23:05	ga_ls9c_ard_3-2-1_110083_2023-07-24_final.stac-item
2023-07-27 10:10:44	ga_ls9c_ard_3-2-1_099072_2023-07-27_final.stac-item
2023-08-01 10:29:46	ga_ls9c_ard_3-2-1_102073_2023-08-01_final.stac-item
2023-08-13 10:55:45	ga_ls9c_ard_3-2-1_106076_2023-08-13_final.stac-item
2023-09-01 09:46:21	ga_ls9c_ard_3-2-1_095072_2023-09-01_final.stac-item
2023-09-01 09:50:44	ga_ls9c_ard_3-2-1_095083_2023-09-01_final.stac-item
2023-09-22 10:04:36	ga_ls9c_ard_3-2-1_098071_2023-09-22_final.stac-item
2023-10-17 11:38:41	ga_ls9c_ard_3-2-1_113074_2023-10-17_final.stac-item
2023-10-23 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-10-23_final.stac-item
2023-10-30 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-10-30_final.stac-item
2023-11-12 10:38:25	ga_ls9c_ard_3-2-1_103078_2023-11-12_final.stac-item
2023-11-15 09:34:25	ga_ls9c_ard_3-2-1_092088_2023-11-15_final.stac-item
2023-12-06 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-12-06_final.stac-item
2023-12-09 10:17:08	ga_ls9c_ard_3-2-1_100071_2023-12-09_final.stac-item
2024-01-02 11:06:13	ga_ls9c_ard_3-2-1_108070_2024-01-02_final.stac-item
2024-01-03 10:09:47	ga_ls9c_ard_3-2-1_099068_2024-01-03_final.stac-item
2024-01-29 10:50:04	ga_ls9c_ard_3-2-1_105076_2024-01-29_final.stac-item
2024-02-04 11:51:07	ga_ls9c_ard_3-2-1_115074_2024-02-04_final.stac-item
2024-02-04 11:51:31	ga_ls9c_ard_3-2-1_115075_2024-02-04_final.stac-item
2024-02-10 11:12:02	ga_ls9c_ard_3-2-1_109069_2024-02-10_final.stac-item
2024-02-14 09:16:22	ga_ls9c_ard_3-2-1_089089_2024-02-13_final.stac-item
2024-02-19 11:05:43	ga_ls9c_ard_3-2-1_108069_2024-02-19_final.stac-item
2024-03-22 09:28:00	ga_ls9c_ard_3-2-1_092072_2024-03-21_final.stac-item
2024-03-26 10:45:17	ga_ls9c_ard_3-2-1_104080_2024-03-26_final.stac-item
2024-04-02 09:14:07	ga_ls9c_ard_3-2-1_089084_2024-04-01_final.stac-item
2024-04-05 11:19:06	ga_ls9c_ard_3-2-1_110072_2024-04-05_final.stac-item
2024-04-09 09:21:28	ga_ls9c_ard_3-2-1_090087_2024-04-08_final.stac-item
2024-04-23 11:10:47	ga_ls9c_ard_3-2-1_108083_2024-04-23_final.stac-item
2024-05-23 11:18:33	ga_ls9c_ard_3-2-1_110072_2024-05-23_final.stac-item
2024-05-27 10:52:34	ga_ls9c_ard_3-2-1_106069_2024-05-27_final.stac-item
2024-05-31 10:27:50	ga_ls9c_ard_3-2-1_102069_2024-05-31_nrt.stac-item
2024-06-02 10:17:04	ga_ls9c_ard_3-2-1_100073_2024-06-02_nrt.stac-item
2024-06-05 10:48:22	ga_ls9c_ard_3-2-1_105074_2024-06-05_nrt.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