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

59 results

Time (local)	Label
2021-11-11 10:19:03	ga_ls9c_ard_3-2-1_100076_2021-11-11_final.stac-item
2021-12-08 10:34:37	ga_ls9c_ard_3-2-1_103068_2021-12-08_final.stac-item
2022-01-13 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-01-13_final.stac-item
2022-01-14 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-01-14_final.stac-item
2022-03-01 11:07:58	ga_ls9c_ard_3-2-1_108075_2022-03-01_final.stac-item
2022-03-03 09:21:54	ga_ls9c_ard_3-2-1_090088_2022-03-02_final.stac-item
2022-03-06 11:24:07	ga_ls9c_ard_3-2-1_111069_2022-03-06_final.stac-item
2022-04-19 11:51:48	ga_ls9c_ard_3-2-1_115077_2022-04-19_final.stac-item
2022-04-23 11:24:14	ga_ls9c_ard_3-2-1_111070_2022-04-23_final.stac-item
2022-04-23 11:24:38	ga_ls9c_ard_3-2-1_111071_2022-04-23_final.stac-item
2022-05-13 09:21:18	ga_ls9c_ard_3-2-1_091072_2022-05-12_final.stac-item
2022-05-22 09:21:24	ga_ls9c_ard_3-2-1_090088_2022-05-21_final.stac-item
2022-05-29 09:22:00	ga_ls9c_ard_3-2-1_091074_2022-05-28_final.stac-item
2022-05-30 10:02:28	ga_ls9c_ard_3-2-1_098067_2022-05-30_final.stac-item
2022-06-05 09:27:24	ga_ls9c_ard_3-2-1_092072_2022-06-04_final.stac-item
2022-07-03 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-07-03_final.stac-item
2022-07-12 09:51:00	ga_ls9c_ard_3-2-1_095084_2022-07-12_final.stac-item
2022-10-18 09:34:06	ga_ls9c_ard_3-2-1_093071_2022-10-18_final.stac-item
2022-10-29 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-10-29_final.stac-item
2022-11-14 09:17:58	ga_ls9c_ard_3-2-1_090077_2022-11-13_final.stac-item
2022-11-14 10:59:15	ga_ls9c_ard_3-2-1_106083_2022-11-14_final.stac-item
2022-11-19 09:34:07	ga_ls9c_ard_3-2-1_093071_2022-11-19_final.stac-item
2022-12-09 09:12:10	ga_ls9c_ard_3-2-1_089078_2022-12-08_final.stac-item
2022-12-09 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-12-08_final.stac-item
2023-01-26 10:48:12	ga_ls9c_ard_3-2-1_105071_2023-01-26_final.stac-item
2023-02-25 09:22:45	ga_ls9c_ard_3-2-1_091074_2023-02-24_final.stac-item
2023-03-04 09:29:18	ga_ls9c_ard_3-2-1_092075_2023-03-03_final.stac-item
2023-03-05 10:14:08	ga_ls9c_ard_3-2-1_099079_2023-03-05_final.stac-item
2023-03-25 11:24:33	ga_ls9c_ard_3-2-1_111070_2023-03-25_final.stac-item
2023-04-01 11:31:25	ga_ls9c_ard_3-2-1_112072_2023-04-01_final.stac-item
2023-04-06 10:13:52	ga_ls9c_ard_3-2-1_099079_2023-04-06_final.stac-item
2023-06-09 10:08:09	ga_ls9c_ard_3-2-1_099066_2023-06-09_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-07-19 09:22:05	ga_ls9c_ard_3-2-1_091074_2023-07-18_final.stac-item
2023-07-28 09:16:20	ga_ls9c_ard_3-2-1_090075_2023-07-27_final.stac-item
2023-08-03 10:19:25	ga_ls9c_ard_3-2-1_100078_2023-08-03_final.stac-item
2023-08-03 11:58:18	ga_ls9c_ard_3-2-1_116078_2023-08-03_final.stac-item
2023-08-13 09:19:40	ga_ls9c_ard_3-2-1_090083_2023-08-12_final.stac-item
2023-09-10 09:40:16	ga_ls9c_ard_3-2-1_094072_2023-09-10_final.stac-item
2023-09-13 10:09:12	ga_ls9c_ard_3-2-1_099067_2023-09-13_final.stac-item
2023-09-30 10:55:37	ga_ls9c_ard_3-2-1_106075_2023-09-30_final.stac-item
2023-10-03 11:24:10	ga_ls9c_ard_3-2-1_111069_2023-10-03_final.stac-item
2023-10-09 09:11:27	ga_ls9c_ard_3-2-1_089077_2023-10-08_final.stac-item
2023-10-12 11:20:06	ga_ls9c_ard_3-2-1_110074_2023-10-12_final.stac-item
2023-10-21 09:34:18	ga_ls9c_ard_3-2-1_093072_2023-10-21_final.stac-item
2023-10-26 09:57:36	ga_ls9c_ard_3-2-1_096084_2023-10-26_final.stac-item
2023-12-05 09:07:00	ga_ls9c_ard_3-2-1_088081_2023-12-04_final.stac-item
2023-12-18 10:13:27	ga_ls9c_ard_3-2-1_099077_2023-12-18_final.stac-item
2023-12-25 11:58:32	ga_ls9c_ard_3-2-1_116077_2023-12-25_final.stac-item
2023-12-30 10:39:45	ga_ls9c_ard_3-2-1_103081_2023-12-30_final.stac-item
2024-01-02 11:08:13	ga_ls9c_ard_3-2-1_108075_2024-01-02_final.stac-item
2024-01-21 11:37:54	ga_ls9c_ard_3-2-1_113072_2024-01-21_final.stac-item
2024-01-28 10:03:12	ga_ls9c_ard_3-2-1_098067_2024-01-28_final.stac-item
2024-02-08 09:47:07	ga_ls9c_ard_3-2-1_095073_2024-02-08_final.stac-item
2024-03-02 09:58:20	ga_ls9c_ard_3-2-1_096086_2024-03-02_final.stac-item
2024-03-02 11:32:26	ga_ls9c_ard_3-2-1_112074_2024-03-02_final.stac-item
2024-03-13 11:14:17	ga_ls9c_ard_3-2-1_109075_2024-03-13_final.stac-item
2024-05-09 09:33:27	ga_ls9c_ard_3-2-1_092087_2024-05-09_final.stac-item
2024-05-09 11:07:09	ga_ls9c_ard_3-2-1_108074_2024-05-09_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