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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

56 results

Time (local)	Label
2021-11-11 10:20:39	ga_ls9c_ard_3-2-1_100080_2021-11-11_final.stac-item
2021-11-20 09:42:49	ga_ls9c_ard_3-2-1_094073_2021-11-20_final.stac-item
2021-12-04 11:05:46	ga_ls9c_ard_3-2-1_107084_2021-12-04_final.stac-item
2021-12-14 10:04:15	ga_ls9c_ard_3-2-1_097085_2021-12-14_final.stac-item
2021-12-20 09:28:45	ga_ls9c_ard_3-2-1_091089_2021-12-19_final.stac-item
2021-12-20 11:04:50	ga_ls9c_ard_3-2-1_107082_2021-12-20_final.stac-item
2022-02-03 10:28:20	ga_ls9c_ard_3-2-1_102068_2022-02-03_final.stac-item
2022-02-07 10:10:23	ga_ls9c_ard_3-2-1_098085_2022-02-07_final.stac-item
2022-02-23 10:10:15	ga_ls9c_ard_3-2-1_098085_2022-02-23_final.stac-item
2022-03-08 11:14:09	ga_ls9c_ard_3-2-1_109075_2022-03-08_final.stac-item
2022-04-03 10:16:15	ga_ls9c_ard_3-2-1_099085_2022-04-03_final.stac-item
2022-05-08 10:45:18	ga_ls9c_ard_3-2-1_104081_2022-05-08_final.stac-item
2022-05-19 10:22:13	ga_ls9c_ard_3-2-1_101070_2022-05-19_final.stac-item
2022-05-29 09:21:36	ga_ls9c_ard_3-2-1_091073_2022-05-28_final.stac-item
2022-06-09 10:44:45	ga_ls9c_ard_3-2-1_104080_2022-06-09_final.stac-item
2022-06-09 10:45:09	ga_ls9c_ard_3-2-1_104081_2022-06-09_final.stac-item
2022-07-21 09:46:07	ga_ls9c_ard_3-2-1_094087_2022-07-21_final.stac-item
2022-08-25 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-08-25_final.stac-item
2022-09-02 11:04:47	ga_ls9c_ard_3-2-1_107082_2022-09-02_final.stac-item
2022-09-27 09:17:03	ga_ls9c_ard_3-2-1_090075_2022-09-26_final.stac-item
2022-09-27 10:59:08	ga_ls9c_ard_3-2-1_106083_2022-09-27_final.stac-item
2022-10-07 09:58:31	ga_ls9c_ard_3-2-1_096086_2022-10-07_final.stac-item
2022-10-22 10:51:51	ga_ls9c_ard_3-2-1_105080_2022-10-22_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-16 10:46:29	ga_ls9c_ard_3-2-1_104082_2022-11-16_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-11-28 11:08:22	ga_ls9c_ard_3-2-1_108075_2022-11-28_final.stac-item
2022-12-16 10:58:25	ga_ls9c_ard_3-2-1_106081_2022-12-16_final.stac-item
2022-12-27 10:35:28	ga_ls9c_ard_3-2-1_103070_2022-12-27_final.stac-item
2023-01-12 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-12_final.stac-item
2023-03-21 10:16:26	ga_ls9c_ard_3-2-1_099085_2023-03-21_final.stac-item
2023-04-01 09:57:44	ga_ls9c_ard_3-2-1_096085_2023-04-01_final.stac-item
2023-04-02 10:39:24	ga_ls9c_ard_3-2-1_103081_2023-04-02_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-05-07 11:07:12	ga_ls9c_ard_3-2-1_108074_2023-05-07_final.stac-item
2023-05-27 10:44:42	ga_ls9c_ard_3-2-1_104080_2023-05-27_final.stac-item
2023-07-30 10:44:53	ga_ls9c_ard_3-2-1_104080_2023-07-30_final.stac-item
2023-07-30 10:45:17	ga_ls9c_ard_3-2-1_104081_2023-07-30_final.stac-item
2023-08-18 09:38:36	ga_ls9c_ard_3-2-1_093084_2023-08-18_final.stac-item
2023-08-21 10:09:57	ga_ls9c_ard_3-2-1_098085_2023-08-21_final.stac-item
2023-08-29 10:58:42	ga_ls9c_ard_3-2-1_106083_2023-08-29_final.stac-item
2023-10-04 10:28:10	ga_ls9c_ard_3-2-1_102068_2023-10-04_final.stac-item
2023-10-08 11:47:33	ga_ls9c_ard_3-2-1_114081_2023-10-08_final.stac-item
2024-01-02 09:32:32	ga_ls9c_ard_3-2-1_092083_2024-01-02_final.stac-item
2024-01-07 08:10:57	ga_ls9c_ard_3-2-1_079080_2024-01-06_final.stac-item
2024-01-12 10:10:24	ga_ls9c_ard_3-2-1_098085_2024-01-12_final.stac-item
2024-01-22 10:41:04	ga_ls9c_ard_3-2-1_104069_2024-01-22_final.stac-item
2024-02-12 11:04:51	ga_ls9c_ard_3-2-1_107082_2024-02-12_final.stac-item
2024-03-27 09:52:26	ga_ls9c_ard_3-2-1_095087_2024-03-27_final.stac-item
2024-04-05 09:41:25	ga_ls9c_ard_3-2-1_094075_2024-04-05_final.stac-item
2024-04-12 09:52:20	ga_ls9c_ard_3-2-1_095087_2024-04-12_final.stac-item
2024-04-16 11:04:50	ga_ls9c_ard_3-2-1_107083_2024-04-16_final.stac-item
2024-04-21 09:45:56	ga_ls9c_ard_3-2-1_094087_2024-04-21_final.stac-item
2024-04-27 10:45:15	ga_ls9c_ard_3-2-1_104081_2024-04-27_final.stac-item
2024-05-07 09:39:26	ga_ls9c_ard_3-2-1_094071_2024-05-07_final.stac-item
2024-05-16 11:17:12	ga_ls9c_ard_3-2-1_109084_2024-05-16_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