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

79 results

Time (local)	Label
2021-11-07 10:56:32	ga_ls9c_ard_3-2-1_106076_2021-11-07_final.stac-item
2021-11-08 09:54:15	ga_ls9c_ard_3-2-1_097067_2021-11-08_final.stac-item
2021-12-22 09:10:24	ga_ls9c_ard_3-2-1_089074_2021-12-21_final.stac-item
2021-12-23 11:32:33	ga_ls9c_ard_3-2-1_112074_2021-12-23_final.stac-item
2022-01-08 11:31:44	ga_ls9c_ard_3-2-1_112072_2022-01-08_final.stac-item
2022-01-23 09:13:35	ga_ls9c_ard_3-2-1_089082_2022-01-22_final.stac-item
2022-02-01 09:06:37	ga_ls9c_ard_3-2-1_088080_2022-01-31_final.stac-item
2022-02-02 11:24:22	ga_ls9c_ard_3-2-1_111069_2022-02-02_final.stac-item
2022-02-05 10:17:34	ga_ls9c_ard_3-2-1_100072_2022-02-05_final.stac-item
2022-02-09 11:32:31	ga_ls9c_ard_3-2-1_112074_2022-02-09_final.stac-item
2022-03-11 10:03:47	ga_ls9c_ard_3-2-1_098069_2022-03-11_final.stac-item
2022-03-20 09:57:10	ga_ls9c_ard_3-2-1_097068_2022-03-20_final.stac-item
2022-04-07 09:45:56	ga_ls9c_ard_3-2-1_095071_2022-04-07_final.stac-item
2022-04-18 11:07:21	ga_ls9c_ard_3-2-1_108074_2022-04-18_final.stac-item
2022-05-05 10:09:38	ga_ls9c_ard_3-2-1_099069_2022-05-05_final.stac-item
2022-05-15 10:46:12	ga_ls9c_ard_3-2-1_105068_2022-05-15_final.stac-item
2022-05-21 10:09:50	ga_ls9c_ard_3-2-1_099070_2022-05-21_final.stac-item
2022-05-23 09:56:17	ga_ls9c_ard_3-2-1_097067_2022-05-23_final.stac-item
2022-05-23 11:37:09	ga_ls9c_ard_3-2-1_113072_2022-05-23_final.stac-item
2022-05-27 11:14:26	ga_ls9c_ard_3-2-1_109077_2022-05-27_final.stac-item
2022-05-29 09:27:11	ga_ls9c_ard_3-2-1_091087_2022-05-28_final.stac-item
2022-07-05 09:46:04	ga_ls9c_ard_3-2-1_094087_2022-07-05_final.stac-item
2022-07-11 09:06:57	ga_ls9c_ard_3-2-1_088082_2022-07-10_final.stac-item
2022-07-25 10:53:34	ga_ls9c_ard_3-2-1_106070_2022-07-25_final.stac-item
2022-08-10 09:21:39	ga_ls9c_ard_3-2-1_090087_2022-08-09_final.stac-item
2022-08-26 09:22:55	ga_ls9c_ard_3-2-1_090090_2022-08-25_final.stac-item
2022-09-06 10:36:04	ga_ls9c_ard_3-2-1_103072_2022-09-06_final.stac-item
2022-09-09 09:34:52	ga_ls9c_ard_3-2-1_092089_2022-09-09_final.stac-item
2022-09-15 10:33:57	ga_ls9c_ard_3-2-1_102082_2022-09-15_final.stac-item
2022-09-20 10:50:08	ga_ls9c_ard_3-2-1_105076_2022-09-20_final.stac-item
2022-10-09 09:40:36	ga_ls9c_ard_3-2-1_094072_2022-10-09_final.stac-item
2022-10-14 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-14_final.stac-item
2022-10-15 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-15_final.stac-item
2022-10-24 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-10-24_final.stac-item
2022-10-31 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-30_final.stac-item
2022-11-03 09:40:02	ga_ls9c_ard_3-2-1_093086_2022-11-03_final.stac-item
2022-11-07 10:47:27	ga_ls9c_ard_3-2-1_105069_2022-11-07_final.stac-item
2022-11-15 09:57:38	ga_ls9c_ard_3-2-1_097068_2022-11-15_final.stac-item
2022-12-22 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-12-22_final.stac-item
2023-01-16 10:12:18	ga_ls9c_ard_3-2-1_099074_2023-01-16_final.stac-item
2023-01-31 09:31:55	ga_ls9c_ard_3-2-1_092081_2023-01-31_final.stac-item
2023-02-11 09:11:49	ga_ls9c_ard_3-2-1_089077_2023-02-10_final.stac-item
2023-02-13 10:36:20	ga_ls9c_ard_3-2-1_103072_2023-02-13_final.stac-item
2023-02-26 10:09:36	ga_ls9c_ard_3-2-1_098083_2023-02-26_final.stac-item
2023-03-15 09:10:40	ga_ls9c_ard_3-2-1_089075_2023-03-14_final.stac-item
2023-03-22 10:53:17	ga_ls9c_ard_3-2-1_106069_2023-03-22_final.stac-item
2023-04-03 11:23:51	ga_ls9c_ard_3-2-1_110084_2023-04-03_final.stac-item
2023-04-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2023-04-23_final.stac-item
2023-05-03 11:31:57	ga_ls9c_ard_3-2-1_112074_2023-05-03_final.stac-item
2023-05-24 10:08:13	ga_ls9c_ard_3-2-1_099066_2023-05-24_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-07-04 10:08:51	ga_ls9c_ard_3-2-1_098083_2023-07-04_final.stac-item
2023-07-18 10:19:42	ga_ls9c_ard_3-2-1_100079_2023-07-18_final.stac-item
2023-08-10 10:27:39	ga_ls9c_ard_3-2-1_101083_2023-08-10_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-10-06 11:57:30	ga_ls9c_ard_3-2-1_116075_2023-10-06_final.stac-item
2023-10-06 11:57:54	ga_ls9c_ard_3-2-1_116076_2023-10-06_final.stac-item
2023-10-13 10:27:41	ga_ls9c_ard_3-2-1_101082_2023-10-13_final.stac-item
2023-11-08 11:05:08	ga_ls9c_ard_3-2-1_107083_2023-11-08_final.stac-item
2023-11-10 10:49:11	ga_ls9c_ard_3-2-1_105074_2023-11-10_final.stac-item
2023-11-16 11:51:23	ga_ls9c_ard_3-2-1_115075_2023-11-16_final.stac-item
2023-11-26 09:12:01	ga_ls9c_ard_3-2-1_089078_2023-11-25_final.stac-item
2023-11-27 09:52:06	ga_ls9c_ard_3-2-1_096070_2023-11-27_final.stac-item
2023-12-08 11:16:44	ga_ls9c_ard_3-2-1_109081_2023-12-08_final.stac-item
2023-12-15 09:40:08	ga_ls9c_ard_3-2-1_094071_2023-12-15_final.stac-item
2023-12-15 11:19:25	ga_ls9c_ard_3-2-1_110072_2023-12-15_final.stac-item
2024-02-20 11:51:21	ga_ls9c_ard_3-2-1_115075_2024-02-20_final.stac-item
2024-02-23 09:06:24	ga_ls9c_ard_3-2-1_088080_2024-02-22_final.stac-item
2024-02-28 09:23:49	ga_ls9c_ard_3-2-1_091077_2024-02-27_final.stac-item
2024-03-01 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-02-29_final.stac-item
2024-03-11 11:27:51	ga_ls9c_ard_3-2-1_111078_2024-03-11_final.stac-item
2024-03-17 09:10:17	ga_ls9c_ard_3-2-1_089074_2024-03-16_final.stac-item
2024-03-17 10:49:10	ga_ls9c_ard_3-2-1_105074_2024-03-17_final.stac-item
2024-03-17 10:49:57	ga_ls9c_ard_3-2-1_105076_2024-03-17_final.stac-item
2024-03-18 11:32:25	ga_ls9c_ard_3-2-1_112074_2024-03-18_final.stac-item
2024-03-29 09:33:39	ga_ls9c_ard_3-2-1_093071_2024-03-29_final.stac-item
2024-04-03 09:57:23	ga_ls9c_ard_3-2-1_096084_2024-04-03_final.stac-item
2024-04-08 10:09:07	ga_ls9c_ard_3-2-1_099067_2024-04-08_final.stac-item
2024-04-20 10:35:37	ga_ls9c_ard_3-2-1_103072_2024-04-20_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