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

49 results

Time (local)	Label
2021-12-10 10:25:02	ga_ls9c_ard_3-2-1_101075_2021-12-10_final.stac-item
2021-12-18 09:34:43	ga_ls9c_ard_3-2-1_093073_2021-12-18_final.stac-item
2021-12-29 09:21:23	ga_ls9c_ard_3-2-1_090086_2021-12-28_final.stac-item
2022-01-19 11:13:59	ga_ls9c_ard_3-2-1_109074_2022-01-19_final.stac-item
2022-03-06 11:25:19	ga_ls9c_ard_3-2-1_111072_2022-03-06_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-04-02 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-04-01_final.stac-item
2022-06-09 09:06:40	ga_ls9c_ard_3-2-1_088082_2022-06-08_final.stac-item
2022-09-21 11:32:36	ga_ls9c_ard_3-2-1_112074_2022-09-21_final.stac-item
2022-10-04 11:01:43	ga_ls9c_ard_3-2-1_107074_2022-10-04_final.stac-item
2022-11-12 09:35:07	ga_ls9c_ard_3-2-1_092089_2022-11-12_final.stac-item
2022-11-14 10:54:04	ga_ls9c_ard_3-2-1_106070_2022-11-14_final.stac-item
2022-12-19 11:24:07	ga_ls9c_ard_3-2-1_111068_2022-12-19_final.stac-item
2023-01-03 10:43:17	ga_ls9c_ard_3-2-1_104074_2023-01-03_final.stac-item
2023-02-08 10:19:01	ga_ls9c_ard_3-2-1_100075_2023-02-08_final.stac-item
2023-02-11 10:49:30	ga_ls9c_ard_3-2-1_105074_2023-02-11_final.stac-item
2023-02-19 11:38:50	ga_ls9c_ard_3-2-1_113074_2023-02-19_final.stac-item
2023-02-27 10:46:29	ga_ls9c_ard_3-2-1_105067_2023-02-27_final.stac-item
2023-03-04 09:33:41	ga_ls9c_ard_3-2-1_092086_2023-03-04_final.stac-item
2023-03-07 11:38:38	ga_ls9c_ard_3-2-1_113074_2023-03-07_final.stac-item
2023-03-15 09:12:16	ga_ls9c_ard_3-2-1_089079_2023-03-14_final.stac-item
2023-03-30 10:03:18	ga_ls9c_ard_3-2-1_098068_2023-03-30_final.stac-item
2023-04-03 11:20:40	ga_ls9c_ard_3-2-1_110076_2023-04-03_final.stac-item
2023-04-24 11:40:16	ga_ls9c_ard_3-2-1_113079_2023-04-24_final.stac-item
2023-05-01 11:44:45	ga_ls9c_ard_3-2-1_114075_2023-05-01_final.stac-item
2023-06-30 10:28:19	ga_ls9c_ard_3-2-1_102070_2023-06-30_final.stac-item
2023-08-02 09:39:21	ga_ls9c_ard_3-2-1_093086_2023-08-02_final.stac-item
2023-08-03 10:18:13	ga_ls9c_ard_3-2-1_100075_2023-08-03_final.stac-item
2023-08-28 10:12:38	ga_ls9c_ard_3-2-1_099076_2023-08-28_final.stac-item
2023-10-07 09:22:36	ga_ls9c_ard_3-2-1_091074_2023-10-06_final.stac-item
2023-12-04 11:42:42	ga_ls9c_ard_3-2-1_113084_2023-12-04_final.stac-item
2023-12-12 09:12:47	ga_ls9c_ard_3-2-1_089080_2023-12-11_final.stac-item
2023-12-20 11:42:23	ga_ls9c_ard_3-2-1_113083_2023-12-20_final.stac-item
2023-12-26 09:22:49	ga_ls9c_ard_3-2-1_091074_2023-12-25_final.stac-item
2023-12-31 11:23:48	ga_ls9c_ard_3-2-1_110083_2023-12-31_final.stac-item
2024-01-03 10:15:23	ga_ls9c_ard_3-2-1_099082_2024-01-03_final.stac-item
2024-01-03 11:53:04	ga_ls9c_ard_3-2-1_115079_2024-01-03_final.stac-item
2024-01-05 09:59:48	ga_ls9c_ard_3-2-1_097074_2024-01-05_final.stac-item
2024-01-10 10:21:57	ga_ls9c_ard_3-2-1_100083_2024-01-10_final.stac-item
2024-01-14 09:58:27	ga_ls9c_ard_3-2-1_096086_2024-01-14_final.stac-item
2024-01-22 09:07:22	ga_ls9c_ard_3-2-1_088082_2024-01-21_final.stac-item
2024-02-04 11:51:31	ga_ls9c_ard_3-2-1_115075_2024-02-04_final.stac-item
2024-02-08 11:24:24	ga_ls9c_ard_3-2-1_111069_2024-02-08_final.stac-item
2024-02-10 09:34:45	ga_ls9c_ard_3-2-1_093073_2024-02-10_final.stac-item
2024-02-28 11:01:30	ga_ls9c_ard_3-2-1_107074_2024-02-28_final.stac-item
2024-03-06 09:33:14	ga_ls9c_ard_3-2-1_092085_2024-03-06_final.stac-item
2024-03-14 11:58:20	ga_ls9c_ard_3-2-1_116077_2024-03-14_final.stac-item
2024-04-01 10:08:09	ga_ls9c_ard_3-2-1_098080_2024-04-01_final.stac-item
2024-04-24 10:08:45	ga_ls9c_ard_3-2-1_099067_2024-04-24_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