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

62 results

Time (local)	Label
2021-12-05 10:10:08	ga_ls9c_ard_3-2-1_098084_2021-12-05_final.stac-item
2022-01-10 11:18:10	ga_ls9c_ard_3-2-1_110069_2022-01-10_final.stac-item
2022-01-14 09:17:44	ga_ls9c_ard_3-2-1_090077_2022-01-13_final.stac-item
2022-01-25 10:35:19	ga_ls9c_ard_3-2-1_103070_2022-01-25_final.stac-item
2022-03-28 10:48:57	ga_ls9c_ard_3-2-1_105074_2022-03-28_final.stac-item
2022-04-02 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-04-01_final.stac-item
2022-04-02 11:07:53	ga_ls9c_ard_3-2-1_108075_2022-04-02_final.stac-item
2022-04-04 09:17:26	ga_ls9c_ard_3-2-1_090077_2022-04-03_final.stac-item
2022-04-09 09:33:57	ga_ls9c_ard_3-2-1_093072_2022-04-09_final.stac-item
2022-05-09 11:25:21	ga_ls9c_ard_3-2-1_111073_2022-05-09_final.stac-item
2022-05-13 11:04:11	ga_ls9c_ard_3-2-1_107082_2022-05-13_final.stac-item
2022-05-27 09:39:08	ga_ls9c_ard_3-2-1_093086_2022-05-27_final.stac-item
2022-07-03 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-07-03_final.stac-item
2022-08-18 10:04:45	ga_ls9c_ard_3-2-1_098071_2022-08-18_final.stac-item
2022-09-11 09:18:08	ga_ls9c_ard_3-2-1_090078_2022-09-10_final.stac-item
2022-09-12 10:04:13	ga_ls9c_ard_3-2-1_097085_2022-09-12_final.stac-item
2022-09-20 10:49:20	ga_ls9c_ard_3-2-1_105074_2022-09-20_final.stac-item
2022-10-02 11:16:29	ga_ls9c_ard_3-2-1_109080_2022-10-02_final.stac-item
2022-10-05 10:09:41	ga_ls9c_ard_3-2-1_098083_2022-10-05_final.stac-item
2022-10-18 11:14:34	ga_ls9c_ard_3-2-1_109075_2022-10-18_final.stac-item
2022-10-22 10:49:28	ga_ls9c_ard_3-2-1_105074_2022-10-22_final.stac-item
2022-11-14 10:53:16	ga_ls9c_ard_3-2-1_106068_2022-11-14_final.stac-item
2022-11-28 11:07:59	ga_ls9c_ard_3-2-1_108074_2022-11-28_final.stac-item
2022-11-29 10:16:20	ga_ls9c_ard_3-2-1_099084_2022-11-29_final.stac-item
2022-11-29 11:53:14	ga_ls9c_ard_3-2-1_115079_2022-11-29_final.stac-item
2022-12-09 09:13:46	ga_ls9c_ard_3-2-1_089082_2022-12-08_final.stac-item
2022-12-23 09:26:04	ga_ls9c_ard_3-2-1_091082_2022-12-22_final.stac-item
2022-12-24 10:10:07	ga_ls9c_ard_3-2-1_098084_2022-12-24_final.stac-item
2023-01-30 10:28:19	ga_ls9c_ard_3-2-1_101083_2023-01-30_final.stac-item
2023-02-01 10:09:36	ga_ls9c_ard_3-2-1_099067_2023-02-01_final.stac-item
2023-02-02 09:22:46	ga_ls9c_ard_3-2-1_090089_2023-02-01_final.stac-item
2023-02-03 09:57:39	ga_ls9c_ard_3-2-1_097068_2023-02-03_final.stac-item
2023-02-07 11:14:38	ga_ls9c_ard_3-2-1_109075_2023-02-07_final.stac-item
2023-02-21 09:47:08	ga_ls9c_ard_3-2-1_095073_2023-02-21_final.stac-item
2023-02-25 09:21:57	ga_ls9c_ard_3-2-1_091072_2023-02-24_final.stac-item
2023-03-14 10:09:53	ga_ls9c_ard_3-2-1_098084_2023-03-14_final.stac-item
2023-03-23 09:58:03	ga_ls9c_ard_3-2-1_097070_2023-03-23_final.stac-item
2023-03-30 10:02:30	ga_ls9c_ard_3-2-1_098066_2023-03-30_final.stac-item
2023-04-03 11:19:52	ga_ls9c_ard_3-2-1_110074_2023-04-03_final.stac-item
2023-05-01 10:09:51	ga_ls9c_ard_3-2-1_098085_2023-05-01_final.stac-item
2023-05-25 10:55:27	ga_ls9c_ard_3-2-1_106076_2023-05-25_final.stac-item
2023-06-04 09:56:50	ga_ls9c_ard_3-2-1_096084_2023-06-04_final.stac-item
2023-06-06 11:23:20	ga_ls9c_ard_3-2-1_110084_2023-06-06_final.stac-item
2023-07-28 09:21:55	ga_ls9c_ard_3-2-1_090089_2023-07-27_final.stac-item
2023-08-22 10:48:50	ga_ls9c_ard_3-2-1_105074_2023-08-22_final.stac-item
2023-08-23 11:31:19	ga_ls9c_ard_3-2-1_112072_2023-08-23_final.stac-item
2023-09-15 11:37:44	ga_ls9c_ard_3-2-1_113072_2023-09-15_final.stac-item
2023-09-23 09:13:22	ga_ls9c_ard_3-2-1_089082_2023-09-22_final.stac-item
2023-09-23 10:49:03	ga_ls9c_ard_3-2-1_105074_2023-09-23_final.stac-item
2023-10-11 10:39:37	ga_ls9c_ard_3-2-1_103081_2023-10-11_final.stac-item
2023-11-18 11:37:51	ga_ls9c_ard_3-2-1_113072_2023-11-18_final.stac-item
2023-11-20 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-11-20_final.stac-item
2023-11-21 10:30:19	ga_ls9c_ard_3-2-1_102073_2023-11-21_final.stac-item
2023-12-04 11:41:31	ga_ls9c_ard_3-2-1_113081_2023-12-04_final.stac-item
2023-12-05 09:07:00	ga_ls9c_ard_3-2-1_088081_2023-12-04_final.stac-item
2023-12-13 11:32:33	ga_ls9c_ard_3-2-1_112074_2023-12-13_final.stac-item
2023-12-14 10:34:33	ga_ls9c_ard_3-2-1_103068_2023-12-14_final.stac-item
2024-01-08 10:29:07	ga_ls9c_ard_3-2-1_102070_2024-01-08_final.stac-item
2024-02-26 11:13:50	ga_ls9c_ard_3-2-1_109074_2024-02-26_final.stac-item
2024-03-17 10:46:46	ga_ls9c_ard_3-2-1_105068_2024-03-17_final.stac-item
2024-03-23 10:09:15	ga_ls9c_ard_3-2-1_099067_2024-03-23_final.stac-item
2024-05-13 10:45:35	ga_ls9c_ard_3-2-1_104082_2024-05-13_nrt.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