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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
2021-11-10 09:37:30	ga_ls9c_ard_3-2-1_094072_2021-11-10_final.stac-item
2021-11-12 10:56:37	ga_ls9c_ard_3-2-1_106070_2021-11-12_final.stac-item
2021-12-27 11:08:14	ga_ls9c_ard_3-2-1_108075_2021-12-27_final.stac-item
2022-01-13 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-01-13_final.stac-item
2022-01-30 09:16:58	ga_ls9c_ard_3-2-1_090075_2022-01-29_final.stac-item
2022-04-29 09:11:04	ga_ls9c_ard_3-2-1_089077_2022-04-28_final.stac-item
2022-05-18 11:19:27	ga_ls9c_ard_3-2-1_110074_2022-05-18_final.stac-item
2022-06-03 09:44:33	ga_ls9c_ard_3-2-1_094084_2022-06-03_final.stac-item
2022-06-19 11:17:36	ga_ls9c_ard_3-2-1_110069_2022-06-19_final.stac-item
2022-07-17 10:09:34	ga_ls9c_ard_3-2-1_098084_2022-07-17_final.stac-item
2022-08-03 09:11:24	ga_ls9c_ard_3-2-1_089077_2022-08-02_final.stac-item
2022-08-13 11:29:52	ga_ls9c_ard_3-2-1_111083_2022-08-13_final.stac-item
2022-08-19 10:50:01	ga_ls9c_ard_3-2-1_105076_2022-08-19_final.stac-item
2022-10-21 10:03:00	ga_ls9c_ard_3-2-1_098066_2022-10-21_final.stac-item
2022-11-05 09:26:53	ga_ls9c_ard_3-2-1_091084_2022-11-04_final.stac-item
2022-11-26 09:46:15	ga_ls9c_ard_3-2-1_094086_2022-11-26_final.stac-item
2022-12-11 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-12-11_final.stac-item
2022-12-15 10:09:11	ga_ls9c_ard_3-2-1_099066_2022-12-15_final.stac-item
2022-12-22 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-12-22_final.stac-item
2022-12-23 09:23:16	ga_ls9c_ard_3-2-1_091075_2022-12-22_final.stac-item
2023-01-08 09:23:20	ga_ls9c_ard_3-2-1_091075_2023-01-07_final.stac-item
2023-01-23 10:17:38	ga_ls9c_ard_3-2-1_100072_2023-01-23_final.stac-item
2023-01-26 10:49:23	ga_ls9c_ard_3-2-1_105074_2023-01-26_final.stac-item
2023-03-25 11:24:57	ga_ls9c_ard_3-2-1_111071_2023-03-25_final.stac-item
2023-03-27 11:14:08	ga_ls9c_ard_3-2-1_109075_2023-03-27_final.stac-item
2023-03-31 09:13:16	ga_ls9c_ard_3-2-1_089082_2023-03-30_final.stac-item
2023-04-21 09:28:31	ga_ls9c_ard_3-2-1_092074_2023-04-20_final.stac-item
2023-05-01 10:07:03	ga_ls9c_ard_3-2-1_098078_2023-05-01_final.stac-item
2023-05-09 09:22:20	ga_ls9c_ard_3-2-1_090090_2023-05-08_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-06-22 09:45:08	ga_ls9c_ard_3-2-1_094086_2023-06-22_final.stac-item
2023-08-08 10:39:12	ga_ls9c_ard_3-2-1_103081_2023-08-08_final.stac-item
2023-08-26 10:25:46	ga_ls9c_ard_3-2-1_101078_2023-08-26_final.stac-item
2023-08-28 10:09:50	ga_ls9c_ard_3-2-1_099069_2023-08-28_final.stac-item
2023-09-03 09:40:23	ga_ls9c_ard_3-2-1_093088_2023-09-03_final.stac-item
2023-09-10 11:19:57	ga_ls9c_ard_3-2-1_110074_2023-09-10_final.stac-item
2023-09-25 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-25_final.stac-item
2023-10-17 09:57:49	ga_ls9c_ard_3-2-1_097069_2023-10-17_final.stac-item
2023-11-15 11:07:19	ga_ls9c_ard_3-2-1_108073_2023-11-15_final.stac-item
2023-11-22 09:34:43	ga_ls9c_ard_3-2-1_093073_2023-11-22_final.stac-item
2023-12-02 10:10:13	ga_ls9c_ard_3-2-1_099069_2023-12-02_final.stac-item
2023-12-12 10:46:53	ga_ls9c_ard_3-2-1_105068_2023-12-12_final.stac-item
2023-12-25 10:20:03	ga_ls9c_ard_3-2-1_100078_2023-12-25_final.stac-item
2024-01-28 10:07:36	ga_ls9c_ard_3-2-1_098078_2024-01-28_final.stac-item
2024-03-10 09:07:19	ga_ls9c_ard_3-2-1_088082_2024-03-09_final.stac-item
2024-03-16 10:09:53	ga_ls9c_ard_3-2-1_098084_2024-03-16_final.stac-item
2024-03-22 09:28:48	ga_ls9c_ard_3-2-1_092074_2024-03-21_final.stac-item
2024-03-25 09:57:40	ga_ls9c_ard_3-2-1_097069_2024-03-25_final.stac-item
2024-03-31 09:21:42	ga_ls9c_ard_3-2-1_091072_2024-03-30_final.stac-item
2024-04-08 10:11:06	ga_ls9c_ard_3-2-1_099072_2024-04-08_final.stac-item
2024-04-27 10:42:03	ga_ls9c_ard_3-2-1_104073_2024-04-27_final.stac-item
2024-05-09 09:33:51	ga_ls9c_ard_3-2-1_092088_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years