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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

52 results

Time (local)	Label
2021-11-11 10:17:04	ga_ls9c_ard_3-2-1_100071_2021-11-11_final.stac-item
2021-12-12 10:16:14	ga_ls9c_ard_3-2-1_099084_2021-12-12_final.stac-item
2021-12-12 11:53:07	ga_ls9c_ard_3-2-1_115079_2021-12-12_final.stac-item
2022-01-07 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-07_final.stac-item
2022-04-01 10:27:25	ga_ls9c_ard_3-2-1_101082_2022-04-01_final.stac-item
2022-04-03 10:09:52	ga_ls9c_ard_3-2-1_099069_2022-04-03_final.stac-item
2022-04-03 11:52:45	ga_ls9c_ard_3-2-1_115079_2022-04-03_final.stac-item
2022-04-06 09:06:16	ga_ls9c_ard_3-2-1_088080_2022-04-05_final.stac-item
2022-04-09 09:34:21	ga_ls9c_ard_3-2-1_093073_2022-04-09_final.stac-item
2022-05-22 09:16:36	ga_ls9c_ard_3-2-1_090076_2022-05-21_final.stac-item
2022-05-22 09:21:24	ga_ls9c_ard_3-2-1_090088_2022-05-21_final.stac-item
2022-06-22 10:10:31	ga_ls9c_ard_3-2-1_099071_2022-06-22_final.stac-item
2022-07-02 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-02_final.stac-item
2022-07-09 09:22:07	ga_ls9c_ard_3-2-1_090089_2022-07-08_final.stac-item
2022-07-09 10:52:38	ga_ls9c_ard_3-2-1_106068_2022-07-09_final.stac-item
2022-07-17 10:07:10	ga_ls9c_ard_3-2-1_098078_2022-07-17_final.stac-item
2022-07-31 10:16:57	ga_ls9c_ard_3-2-1_100071_2022-07-31_final.stac-item
2022-08-01 09:22:09	ga_ls9c_ard_3-2-1_091073_2022-07-31_final.stac-item
2022-08-17 09:28:16	ga_ls9c_ard_3-2-1_091088_2022-08-16_final.stac-item
2022-08-22 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-08-22_final.stac-item
2022-09-25 11:06:18	ga_ls9c_ard_3-2-1_108070_2022-09-25_final.stac-item
2022-10-28 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-10-28_final.stac-item
2023-01-01 09:17:33	ga_ls9c_ard_3-2-1_090076_2022-12-31_final.stac-item
2023-01-15 11:08:20	ga_ls9c_ard_3-2-1_108075_2023-01-15_final.stac-item
2023-01-16 11:53:10	ga_ls9c_ard_3-2-1_115079_2023-01-16_final.stac-item
2023-01-27 11:31:52	ga_ls9c_ard_3-2-1_112072_2023-01-27_final.stac-item
2023-02-13 10:35:08	ga_ls9c_ard_3-2-1_103069_2023-02-13_final.stac-item
2023-03-06 09:17:42	ga_ls9c_ard_3-2-1_090077_2023-03-05_final.stac-item
2023-03-15 09:10:16	ga_ls9c_ard_3-2-1_089074_2023-03-14_final.stac-item
2023-03-31 10:46:34	ga_ls9c_ard_3-2-1_105068_2023-03-31_final.stac-item
2023-04-12 09:33:56	ga_ls9c_ard_3-2-1_093072_2023-04-12_final.stac-item
2023-05-25 09:16:10	ga_ls9c_ard_3-2-1_090075_2023-05-24_final.stac-item
2023-06-08 09:28:05	ga_ls9c_ard_3-2-1_092074_2023-06-07_final.stac-item
2023-06-10 09:21:41	ga_ls9c_ard_3-2-1_090089_2023-06-09_final.stac-item
2023-07-21 10:49:24	ga_ls9c_ard_3-2-1_105076_2023-07-21_final.stac-item
2023-07-31 09:51:40	ga_ls9c_ard_3-2-1_095086_2023-07-31_final.stac-item
2023-08-14 09:56:56	ga_ls9c_ard_3-2-1_097068_2023-08-14_final.stac-item
2023-08-28 10:15:50	ga_ls9c_ard_3-2-1_099084_2023-08-28_final.stac-item
2023-09-14 10:56:03	ga_ls9c_ard_3-2-1_106076_2023-09-14_final.stac-item
2023-10-14 11:06:10	ga_ls9c_ard_3-2-1_108070_2023-10-14_final.stac-item
2023-10-25 10:49:38	ga_ls9c_ard_3-2-1_105075_2023-10-25_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-12-02 10:13:49	ga_ls9c_ard_3-2-1_099078_2023-12-02_final.stac-item
2023-12-19 09:22:13	ga_ls9c_ard_3-2-1_090088_2023-12-18_final.stac-item
2024-02-11 10:19:12	ga_ls9c_ard_3-2-1_100076_2024-02-11_final.stac-item
2024-02-20 10:14:04	ga_ls9c_ard_3-2-1_099079_2024-02-20_final.stac-item
2024-02-21 09:17:13	ga_ls9c_ard_3-2-1_090076_2024-02-20_final.stac-item
2024-04-14 11:14:02	ga_ls9c_ard_3-2-1_109075_2024-04-14_final.stac-item
2024-04-26 10:01:11	ga_ls9c_ard_3-2-1_097079_2024-04-26_final.stac-item
2024-04-29 10:28:29	ga_ls9c_ard_3-2-1_102070_2024-04-29_final.stac-item
2024-05-09 09:33:03	ga_ls9c_ard_3-2-1_092086_2024-05-09_final.stac-item
2024-05-09 09:33:27	ga_ls9c_ard_3-2-1_092087_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years