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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

51 results

Time (local)	Label
2021-11-07 09:18:16	ga_ls9c_ard_3-2-1_090077_2021-11-06_final.stac-item
2021-12-18 11:14:24	ga_ls9c_ard_3-2-1_109075_2021-12-18_final.stac-item
2021-12-26 10:28:10	ga_ls9c_ard_3-2-1_101083_2021-12-26_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-01-15 11:38:41	ga_ls9c_ard_3-2-1_113074_2022-01-15_final.stac-item
2022-02-01 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-01-31_final.stac-item
2022-02-17 09:07:19	ga_ls9c_ard_3-2-1_088082_2022-02-16_final.stac-item
2022-02-24 10:49:06	ga_ls9c_ard_3-2-1_105074_2022-02-24_final.stac-item
2022-03-01 09:29:05	ga_ls9c_ard_3-2-1_092075_2022-02-28_final.stac-item
2022-03-08 09:34:28	ga_ls9c_ard_3-2-1_093073_2022-03-08_final.stac-item
2022-04-16 11:17:45	ga_ls9c_ard_3-2-1_110069_2022-04-16_final.stac-item
2022-05-01 10:35:35	ga_ls9c_ard_3-2-1_103072_2022-05-01_final.stac-item
2022-05-21 10:09:26	ga_ls9c_ard_3-2-1_099069_2022-05-21_final.stac-item
2022-05-22 09:17:00	ga_ls9c_ard_3-2-1_090077_2022-05-21_final.stac-item
2022-05-31 10:46:08	ga_ls9c_ard_3-2-1_105068_2022-05-31_final.stac-item
2022-06-30 09:27:57	ga_ls9c_ard_3-2-1_091088_2022-06-29_final.stac-item
2022-07-17 10:06:46	ga_ls9c_ard_3-2-1_098077_2022-07-17_final.stac-item
2022-07-28 11:29:17	ga_ls9c_ard_3-2-1_111082_2022-07-28_final.stac-item
2022-08-03 10:50:17	ga_ls9c_ard_3-2-1_105077_2022-08-03_final.stac-item
2022-09-26 10:09:53	ga_ls9c_ard_3-2-1_099068_2022-09-26_final.stac-item
2022-09-26 10:14:16	ga_ls9c_ard_3-2-1_099079_2022-09-26_final.stac-item
2022-09-27 10:58:44	ga_ls9c_ard_3-2-1_106082_2022-09-27_final.stac-item
2022-11-01 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-11-01_final.stac-item
2022-11-14 09:21:10	ga_ls9c_ard_3-2-1_090085_2022-11-13_final.stac-item
2022-11-19 09:34:55	ga_ls9c_ard_3-2-1_093073_2022-11-19_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_final.stac-item
2022-12-17 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-12-17_final.stac-item
2023-01-10 10:52:38	ga_ls9c_ard_3-2-1_105082_2023-01-10_final.stac-item
2023-02-23 11:14:24	ga_ls9c_ard_3-2-1_109075_2023-02-23_final.stac-item
2023-03-14 10:09:53	ga_ls9c_ard_3-2-1_098084_2023-03-14_final.stac-item
2023-06-10 09:16:30	ga_ls9c_ard_3-2-1_090076_2023-06-09_final.stac-item
2023-07-26 09:28:15	ga_ls9c_ard_3-2-1_092074_2023-07-25_final.stac-item
2023-08-12 11:52:11	ga_ls9c_ard_3-2-1_115078_2023-08-12_final.stac-item
2023-08-24 10:39:18	ga_ls9c_ard_3-2-1_103081_2023-08-24_final.stac-item
2023-09-23 10:46:40	ga_ls9c_ard_3-2-1_105068_2023-09-23_final.stac-item
2023-10-17 09:57:01	ga_ls9c_ard_3-2-1_097067_2023-10-17_final.stac-item
2023-10-24 10:09:34	ga_ls9c_ard_3-2-1_098083_2023-10-24_final.stac-item
2023-11-22 11:12:00	ga_ls9c_ard_3-2-1_109069_2023-11-22_final.stac-item
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2023-12-02 10:14:13	ga_ls9c_ard_3-2-1_099079_2023-12-02_final.stac-item
2023-12-24 09:37:11	ga_ls9c_ard_3-2-1_093079_2023-12-24_final.stac-item
2024-01-06 10:40:39	ga_ls9c_ard_3-2-1_104068_2024-01-06_final.stac-item
2024-01-07 09:46:38	ga_ls9c_ard_3-2-1_095072_2024-01-07_final.stac-item
2024-01-31 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-31_final.stac-item
2024-02-04 10:09:26	ga_ls9c_ard_3-2-1_099067_2024-02-04_final.stac-item
2024-02-12 09:23:34	ga_ls9c_ard_3-2-1_091076_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 10:54:54	ga_ls9c_ard_3-2-1_106073_2024-02-21_final.stac-item
2024-03-10 09:07:43	ga_ls9c_ard_3-2-1_088083_2024-03-09_final.stac-item
2024-03-23 10:09:39	ga_ls9c_ard_3-2-1_099068_2024-03-23_final.stac-item
2024-04-18 10:46:50	ga_ls9c_ard_3-2-1_105069_2024-04-18_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