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

48 results

Time (local)	Label
2021-11-12 10:58:37	ga_ls9c_ard_3-2-1_106075_2021-11-12_final.stac-item
2021-12-04 09:22:06	ga_ls9c_ard_3-2-1_091072_2021-12-03_final.stac-item
2021-12-12 11:52:44	ga_ls9c_ard_3-2-1_115078_2021-12-12_final.stac-item
2022-05-04 09:31:10	ga_ls9c_ard_3-2-1_092081_2022-05-04_final.stac-item
2022-05-09 11:24:57	ga_ls9c_ard_3-2-1_111072_2022-05-09_final.stac-item
2022-05-13 11:02:11	ga_ls9c_ard_3-2-1_107077_2022-05-13_final.stac-item
2022-05-30 10:09:39	ga_ls9c_ard_3-2-1_098085_2022-05-30_final.stac-item
2022-06-12 09:39:12	ga_ls9c_ard_3-2-1_093086_2022-06-12_final.stac-item
2022-06-30 11:04:50	ga_ls9c_ard_3-2-1_107083_2022-06-30_final.stac-item
2022-07-12 11:24:18	ga_ls9c_ard_3-2-1_111070_2022-07-12_final.stac-item
2022-07-16 11:01:35	ga_ls9c_ard_3-2-1_107075_2022-07-16_final.stac-item
2022-08-29 09:51:26	ga_ls9c_ard_3-2-1_095084_2022-08-29_final.stac-item
2022-09-09 09:34:52	ga_ls9c_ard_3-2-1_092089_2022-09-09_final.stac-item
2022-09-18 11:05:16	ga_ls9c_ard_3-2-1_107083_2022-09-18_final.stac-item
2022-10-11 09:31:51	ga_ls9c_ard_3-2-1_092081_2022-10-11_final.stac-item
2022-10-25 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-10-25_final.stac-item
2022-11-10 09:46:40	ga_ls9c_ard_3-2-1_094087_2022-11-10_final.stac-item
2022-11-28 11:07:35	ga_ls9c_ard_3-2-1_108073_2022-11-28_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_final.stac-item
2022-12-21 09:40:51	ga_ls9c_ard_3-2-1_093088_2022-12-21_final.stac-item
2023-01-29 09:40:39	ga_ls9c_ard_3-2-1_094072_2023-01-29_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-11 11:14:40	ga_ls9c_ard_3-2-1_109076_2023-03-11_final.stac-item
2023-03-22 10:53:17	ga_ls9c_ard_3-2-1_106069_2023-03-22_final.stac-item
2023-03-23 09:58:51	ga_ls9c_ard_3-2-1_097072_2023-03-23_final.stac-item
2023-04-21 09:28:54	ga_ls9c_ard_3-2-1_092075_2023-04-20_final.stac-item
2023-04-23 09:21:43	ga_ls9c_ard_3-2-1_090088_2023-04-22_final.stac-item
2023-04-24 11:39:52	ga_ls9c_ard_3-2-1_113078_2023-04-24_final.stac-item
2023-06-29 11:24:42	ga_ls9c_ard_3-2-1_111072_2023-06-29_final.stac-item
2023-07-23 10:35:26	ga_ls9c_ard_3-2-1_103072_2023-07-23_final.stac-item
2023-08-05 10:04:17	ga_ls9c_ard_3-2-1_098071_2023-08-05_final.stac-item
2023-08-16 11:26:39	ga_ls9c_ard_3-2-1_111076_2023-08-16_final.stac-item
2023-08-24 10:35:43	ga_ls9c_ard_3-2-1_103072_2023-08-24_final.stac-item
2023-08-28 11:51:07	ga_ls9c_ard_3-2-1_115075_2023-08-28_final.stac-item
2023-08-30 11:37:35	ga_ls9c_ard_3-2-1_113072_2023-08-30_final.stac-item
2023-10-10 11:31:38	ga_ls9c_ard_3-2-1_112072_2023-10-10_final.stac-item
2023-11-10 10:49:11	ga_ls9c_ard_3-2-1_105074_2023-11-10_final.stac-item
2023-11-28 10:36:09	ga_ls9c_ard_3-2-1_103072_2023-11-28_final.stac-item
2023-12-10 11:05:36	ga_ls9c_ard_3-2-1_107084_2023-12-10_final.stac-item
2024-01-14 11:36:32	ga_ls9c_ard_3-2-1_112084_2024-01-14_final.stac-item
2024-02-06 09:58:41	ga_ls9c_ard_3-2-1_097071_2024-02-06_final.stac-item
2024-03-04 11:19:17	ga_ls9c_ard_3-2-1_110072_2024-03-04_final.stac-item
2024-03-04 11:19:17	ga_ls9c_ard_3-2-1_110072_2024-03-04_interim.stac-item
2024-03-29 11:14:56	ga_ls9c_ard_3-2-1_109077_2024-03-29_final.stac-item
2024-04-13 10:28:47	ga_ls9c_ard_3-2-1_102070_2024-04-13_final.stac-item
2024-04-16 11:01:14	ga_ls9c_ard_3-2-1_107074_2024-04-16_final.stac-item
2024-04-24 10:09:09	ga_ls9c_ard_3-2-1_099068_2024-04-24_final.stac-item
2024-04-25 10:52:25	ga_ls9c_ard_3-2-1_106068_2024-04-25_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