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

50 results

Time (local)	Label
2021-11-07 09:17:52	ga_ls9c_ard_3-2-1_090076_2021-11-06_final.stac-item
2021-11-20 11:19:54	ga_ls9c_ard_3-2-1_110069_2021-11-20_final.stac-item
2022-01-03 09:34:43	ga_ls9c_ard_3-2-1_093073_2022-01-03_final.stac-item
2022-01-21 09:22:45	ga_ls9c_ard_3-2-1_091074_2022-01-20_final.stac-item
2022-02-03 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-02-03_final.stac-item
2022-02-15 09:16:54	ga_ls9c_ard_3-2-1_090075_2022-02-14_final.stac-item
2022-04-04 10:55:31	ga_ls9c_ard_3-2-1_106075_2022-04-04_final.stac-item
2022-04-07 11:24:49	ga_ls9c_ard_3-2-1_111071_2022-04-07_final.stac-item
2022-04-19 10:12:55	ga_ls9c_ard_3-2-1_099077_2022-04-19_final.stac-item
2022-05-18 09:39:46	ga_ls9c_ard_3-2-1_094072_2022-05-18_final.stac-item
2022-07-05 11:18:10	ga_ls9c_ard_3-2-1_110070_2022-07-05_final.stac-item
2022-07-07 11:07:24	ga_ls9c_ard_3-2-1_108074_2022-07-07_final.stac-item
2022-08-31 11:11:58	ga_ls9c_ard_3-2-1_109069_2022-08-31_final.stac-item
2022-09-13 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-09-13_final.stac-item
2022-09-28 09:57:08	ga_ls9c_ard_3-2-1_097067_2022-09-28_final.stac-item
2022-10-11 11:08:21	ga_ls9c_ard_3-2-1_108075_2022-10-11_final.stac-item
2022-10-12 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-10-12_final.stac-item
2022-10-22 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-10-22_final.stac-item
2022-10-29 10:58:49	ga_ls9c_ard_3-2-1_106082_2022-10-29_final.stac-item
2022-11-25 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-11-25_final.stac-item
2022-11-30 10:53:12	ga_ls9c_ard_3-2-1_106068_2022-11-30_final.stac-item
2022-12-05 09:34:52	ga_ls9c_ard_3-2-1_093073_2022-12-05_final.stac-item
2022-12-28 09:41:03	ga_ls9c_ard_3-2-1_094073_2022-12-28_final.stac-item
2022-12-31 10:09:11	ga_ls9c_ard_3-2-1_099066_2022-12-31_final.stac-item
2023-01-29 11:18:44	ga_ls9c_ard_3-2-1_110070_2023-01-29_final.stac-item
2023-02-19 09:58:21	ga_ls9c_ard_3-2-1_097070_2023-02-19_final.stac-item
2023-03-09 09:46:09	ga_ls9c_ard_3-2-1_095071_2023-03-09_final.stac-item
2023-04-24 11:41:28	ga_ls9c_ard_3-2-1_113082_2023-04-24_final.stac-item
2023-06-08 11:07:22	ga_ls9c_ard_3-2-1_108075_2023-06-08_final.stac-item
2023-07-03 11:01:16	ga_ls9c_ard_3-2-1_107075_2023-07-03_final.stac-item
2023-09-07 09:12:08	ga_ls9c_ard_3-2-1_089079_2023-09-06_final.stac-item
2023-09-19 09:34:31	ga_ls9c_ard_3-2-1_093073_2023-09-19_final.stac-item
2023-10-21 09:34:18	ga_ls9c_ard_3-2-1_093072_2023-10-21_final.stac-item
2024-01-03 10:10:59	ga_ls9c_ard_3-2-1_099071_2024-01-03_final.stac-item
2024-01-07 11:24:43	ga_ls9c_ard_3-2-1_111070_2024-01-07_final.stac-item
2024-01-10 11:57:39	ga_ls9c_ard_3-2-1_116075_2024-01-10_final.stac-item
2024-01-10 11:58:03	ga_ls9c_ard_3-2-1_116076_2024-01-10_final.stac-item
2024-01-11 09:22:45	ga_ls9c_ard_3-2-1_091074_2024-01-10_final.stac-item
2024-01-20 09:17:21	ga_ls9c_ard_3-2-1_090076_2024-01-19_final.stac-item
2024-01-27 09:26:19	ga_ls9c_ard_3-2-1_091083_2024-01-26_final.stac-item
2024-02-01 09:41:19	ga_ls9c_ard_3-2-1_094074_2024-02-01_final.stac-item
2024-02-03 09:28:10	ga_ls9c_ard_3-2-1_092072_2024-02-02_final.stac-item
2024-02-04 10:09:02	ga_ls9c_ard_3-2-1_099066_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
2024-02-12 09:21:58	ga_ls9c_ard_3-2-1_091072_2024-02-11_final.stac-item
2024-02-19 09:28:02	ga_ls9c_ard_3-2-1_092072_2024-02-18_final.stac-item
2024-03-06 11:07:20	ga_ls9c_ard_3-2-1_108073_2024-03-06_final.stac-item
2024-03-13 11:14:17	ga_ls9c_ard_3-2-1_109075_2024-03-13_final.stac-item
2024-03-14 11:57:56	ga_ls9c_ard_3-2-1_116076_2024-03-14_final.stac-item
2024-05-14 11:25:37	ga_ls9c_ard_3-2-1_111074_2024-05-14_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