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
2021-11-02 09:16:59	ga_ls9c_ard_3-2-1_090080_2021-11-01_final.stac-item
2021-11-06 10:16:59	ga_ls9c_ard_3-2-1_100077_2021-11-06_final.stac-item
2021-11-07 09:18:40	ga_ls9c_ard_3-2-1_090078_2021-11-06_final.stac-item
2021-11-10 09:40:41	ga_ls9c_ard_3-2-1_094080_2021-11-10_final.stac-item
2021-12-06 09:10:55	ga_ls9c_ard_3-2-1_089075_2021-12-05_final.stac-item
2021-12-11 09:34:11	ga_ls9c_ard_3-2-1_092087_2021-12-11_final.stac-item
2021-12-11 09:34:59	ga_ls9c_ard_3-2-1_092089_2021-12-11_final.stac-item
2022-01-17 11:25:56	ga_ls9c_ard_3-2-1_111073_2022-01-17_final.stac-item
2022-01-23 09:12:23	ga_ls9c_ard_3-2-1_089079_2022-01-22_final.stac-item
2022-01-24 09:55:39	ga_ls9c_ard_3-2-1_096079_2022-01-24_final.stac-item
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final.stac-item
2022-01-28 09:29:20	ga_ls9c_ard_3-2-1_092075_2022-01-27_final.stac-item
2022-02-21 08:42:33	ga_ls9c_ard_3-2-1_084082_2022-02-20_final.stac-item
2022-03-06 11:23:43	ga_ls9c_ard_3-2-1_111068_2022-03-06_final.stac-item
2022-04-04 09:17:50	ga_ls9c_ard_3-2-1_090078_2022-04-03_final.stac-item
2022-04-16 11:20:32	ga_ls9c_ard_3-2-1_110076_2022-04-16_final.stac-item
2022-04-22 09:06:05	ga_ls9c_ard_3-2-1_088080_2022-04-21_final.stac-item
2022-04-27 09:22:38	ga_ls9c_ard_3-2-1_091075_2022-04-26_final.stac-item
2022-05-20 11:07:27	ga_ls9c_ard_3-2-1_108075_2022-05-20_final.stac-item
2022-05-21 10:09:02	ga_ls9c_ard_3-2-1_099068_2022-05-21_final.stac-item
2022-06-01 11:31:48	ga_ls9c_ard_3-2-1_112074_2022-06-01_final.stac-item
2022-06-10 09:45:33	ga_ls9c_ard_3-2-1_095071_2022-06-10_final.stac-item
2022-06-13 11:57:23	ga_ls9c_ard_3-2-1_116076_2022-06-13_final.stac-item
2022-06-23 09:22:31	ga_ls9c_ard_3-2-1_090090_2022-06-22_final.stac-item
2022-07-16 09:27:05	ga_ls9c_ard_3-2-1_091086_2022-07-15_final.stac-item
2022-08-07 10:28:00	ga_ls9c_ard_3-2-1_101083_2022-08-07_final.stac-item
2022-09-03 11:46:51	ga_ls9c_ard_3-2-1_114079_2022-09-03_final.stac-item
2022-09-16 09:36:20	ga_ls9c_ard_3-2-1_093077_2022-09-16_final.stac-item
2022-09-28 10:01:07	ga_ls9c_ard_3-2-1_097077_2022-09-28_final.stac-item
2022-10-03 10:19:39	ga_ls9c_ard_3-2-1_100077_2022-10-03_final.stac-item
2022-10-27 11:08:24	ga_ls9c_ard_3-2-1_108075_2022-10-27_final.stac-item
2022-10-31 10:46:27	ga_ls9c_ard_3-2-1_104082_2022-10-31_final.stac-item
2022-11-04 10:19:42	ga_ls9c_ard_3-2-1_100077_2022-11-04_final.stac-item
2022-11-07 09:11:45	ga_ls9c_ard_3-2-1_089077_2022-11-06_final.stac-item
2022-11-17 11:26:10	ga_ls9c_ard_3-2-1_111073_2022-11-17_final.stac-item
2022-11-24 09:54:38	ga_ls9c_ard_3-2-1_096076_2022-11-24_final.stac-item
2022-12-28 11:20:20	ga_ls9c_ard_3-2-1_110074_2022-12-28_final.stac-item
2023-02-01 10:12:23	ga_ls9c_ard_3-2-1_099074_2023-02-01_final.stac-item
2023-02-23 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-02-23_final.stac-item
2023-03-14 10:03:54	ga_ls9c_ard_3-2-1_098069_2023-03-14_final.stac-item
2023-03-28 10:19:17	ga_ls9c_ard_3-2-1_100077_2023-03-28_final.stac-item
2023-04-30 09:27:01	ga_ls9c_ard_3-2-1_091086_2023-04-29_final.stac-item
2023-05-02 09:10:13	ga_ls9c_ard_3-2-1_089075_2023-05-01_final.stac-item
2023-05-15 10:18:55	ga_ls9c_ard_3-2-1_100077_2023-05-15_final.stac-item
2023-05-18 09:10:54	ga_ls9c_ard_3-2-1_089077_2023-05-17_final.stac-item
2023-05-24 11:51:53	ga_ls9c_ard_3-2-1_115078_2023-05-24_final.stac-item
2023-06-17 09:22:12	ga_ls9c_ard_3-2-1_091075_2023-06-16_final.stac-item
2023-06-18 11:46:21	ga_ls9c_ard_3-2-1_114080_2023-06-18_final.stac-item
2023-08-04 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-08-04_final.stac-item
2023-08-11 11:11:18	ga_ls9c_ard_3-2-1_108084_2023-08-11_final.stac-item
2023-08-18 11:13:29	ga_ls9c_ard_3-2-1_109074_2023-08-18_final.stac-item
2023-08-22 09:11:09	ga_ls9c_ard_3-2-1_089077_2023-08-21_final.stac-item
2023-08-26 10:22:35	ga_ls9c_ard_3-2-1_101070_2023-08-26_final.stac-item
2023-09-13 10:16:23	ga_ls9c_ard_3-2-1_099085_2023-09-13_final.stac-item
2023-09-29 10:16:19	ga_ls9c_ard_3-2-1_099085_2023-09-29_final.stac-item
2023-11-12 10:36:01	ga_ls9c_ard_3-2-1_103072_2023-11-12_final.stac-item
2024-01-04 09:20:32	ga_ls9c_ard_3-2-1_090084_2024-01-03_final.stac-item
2024-01-10 10:17:34	ga_ls9c_ard_3-2-1_100072_2024-01-10_final.stac-item
2024-01-26 11:58:49	ga_ls9c_ard_3-2-1_116078_2024-01-26_final.stac-item
2024-02-08 11:24:00	ga_ls9c_ard_3-2-1_111068_2024-02-08_final.stac-item
2024-03-01 10:48:22	ga_ls9c_ard_3-2-1_105072_2024-03-01_final.stac-item
2024-03-24 09:17:12	ga_ls9c_ard_3-2-1_090076_2024-03-23_final.stac-item
2024-04-03 09:51:48	ga_ls9c_ard_3-2-1_096070_2024-04-03_final.stac-item
2024-04-10 09:57:32	ga_ls9c_ard_3-2-1_097069_2024-04-10_final.stac-item
2024-04-18 09:13:32	ga_ls9c_ard_3-2-1_089083_2024-04-17_final.stac-item
2024-04-24 10:09:57	ga_ls9c_ard_3-2-1_099070_2024-04-24_final.stac-item
2024-04-27 10:42:03	ga_ls9c_ard_3-2-1_104073_2024-04-27_final.stac-item
2024-05-14 11:23:14	ga_ls9c_ard_3-2-1_111068_2024-05-14_interim.stac-item
2024-05-17 10:18:46	ga_ls9c_ard_3-2-1_100077_2024-05-17_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