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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

68 results

Time (local)	Label
2021-11-17 09:26:04	ga_ls9c_ard_3-2-1_091084_2021-11-16_final.stac-item
2021-12-09 09:41:23	ga_ls9c_ard_3-2-1_094074_2021-12-09_final.stac-item
2021-12-22 10:52:05	ga_ls9c_ard_3-2-1_105081_2021-12-22_final.stac-item
2021-12-25 11:21:00	ga_ls9c_ard_3-2-1_110076_2021-12-25_final.stac-item
2022-01-01 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-01-01_final.stac-item
2022-01-01 11:25:58	ga_ls9c_ard_3-2-1_111073_2022-01-01_final.stac-item
2022-01-05 09:23:09	ga_ls9c_ard_3-2-1_091075_2022-01-04_final.stac-item
2022-01-17 11:29:08	ga_ls9c_ard_3-2-1_111081_2022-01-17_final.stac-item
2022-01-23 09:16:23	ga_ls9c_ard_3-2-1_089089_2022-01-22_final.stac-item
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-09 11:32:31	ga_ls9c_ard_3-2-1_112074_2022-02-09_final.stac-item
2022-02-14 10:13:44	ga_ls9c_ard_3-2-1_099078_2022-02-14_final.stac-item
2022-02-15 09:22:53	ga_ls9c_ard_3-2-1_090090_2022-02-14_final.stac-item
2022-04-29 09:11:52	ga_ls9c_ard_3-2-1_089079_2022-04-28_final.stac-item
2022-05-06 10:52:53	ga_ls9c_ard_3-2-1_106069_2022-05-06_final.stac-item
2022-05-21 10:09:02	ga_ls9c_ard_3-2-1_099068_2022-05-21_final.stac-item
2022-06-14 09:22:53	ga_ls9c_ard_3-2-1_091076_2022-06-13_final.stac-item
2022-06-15 10:02:58	ga_ls9c_ard_3-2-1_098068_2022-06-15_final.stac-item
2022-06-22 10:10:31	ga_ls9c_ard_3-2-1_099071_2022-06-22_final.stac-item
2022-07-10 11:40:16	ga_ls9c_ard_3-2-1_113079_2022-07-10_final.stac-item
2022-07-23 09:32:36	ga_ls9c_ard_3-2-1_092084_2022-07-23_final.stac-item
2022-07-24 11:52:22	ga_ls9c_ard_3-2-1_115078_2022-07-24_final.stac-item
2022-07-25 09:21:28	ga_ls9c_ard_3-2-1_090087_2022-07-24_final.stac-item
2022-08-25 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-08-25_final.stac-item
2022-09-17 11:58:53	ga_ls9c_ard_3-2-1_116078_2022-09-17_final.stac-item
2022-09-29 10:40:47	ga_ls9c_ard_3-2-1_104068_2022-09-29_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-29 09:22:20	ga_ls9c_ard_3-2-1_090088_2022-10-28_final.stac-item
2022-11-06 11:46:39	ga_ls9c_ard_3-2-1_114078_2022-11-06_final.stac-item
2022-11-07 09:11:45	ga_ls9c_ard_3-2-1_089077_2022-11-06_final.stac-item
2022-11-14 09:17:58	ga_ls9c_ard_3-2-1_090077_2022-11-13_final.stac-item
2022-11-22 10:08:12	ga_ls9c_ard_3-2-1_098079_2022-11-22_final.stac-item
2022-12-07 09:27:43	ga_ls9c_ard_3-2-1_091086_2022-12-06_nrt.stac-item
2022-12-14 11:07:36	ga_ls9c_ard_3-2-1_108073_2022-12-14_final.stac-item
2022-12-15 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-12-15_final.stac-item
2022-12-29 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-12-29_final.stac-item
2023-01-26 10:47:24	ga_ls9c_ard_3-2-1_105069_2023-01-26_final.stac-item
2023-02-14 11:20:47	ga_ls9c_ard_3-2-1_110075_2023-02-14_final.stac-item
2023-02-19 09:58:45	ga_ls9c_ard_3-2-1_097071_2023-02-19_final.stac-item
2023-02-20 10:46:23	ga_ls9c_ard_3-2-1_104082_2023-02-20_final.stac-item
2023-03-12 11:58:44	ga_ls9c_ard_3-2-1_116078_2023-03-12_final.stac-item
2023-04-15 10:02:24	ga_ls9c_ard_3-2-1_098066_2023-04-15_final.stac-item
2023-05-02 09:14:37	ga_ls9c_ard_3-2-1_089086_2023-05-01_final.stac-item
2023-05-25 10:52:16	ga_ls9c_ard_3-2-1_106068_2023-05-25_final.stac-item
2023-05-28 11:23:58	ga_ls9c_ard_3-2-1_111070_2023-05-28_final.stac-item
2023-06-01 11:03:38	ga_ls9c_ard_3-2-1_107081_2023-06-01_final.stac-item
2023-06-04 09:57:38	ga_ls9c_ard_3-2-1_096086_2023-06-04_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-09 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-09_final.stac-item
2023-08-02 11:17:02	ga_ls9c_ard_3-2-1_109083_2023-08-02_final.stac-item
2023-09-22 11:45:53	ga_ls9c_ard_3-2-1_114077_2023-09-22_final.stac-item
2023-10-16 10:53:02	ga_ls9c_ard_3-2-1_106068_2023-10-16_final.stac-item
2023-11-22 11:14:24	ga_ls9c_ard_3-2-1_109075_2023-11-22_final.stac-item
2024-01-08 10:28:43	ga_ls9c_ard_3-2-1_102069_2024-01-08_final.stac-item
2024-01-09 11:14:47	ga_ls9c_ard_3-2-1_109076_2024-01-09_final.stac-item
2024-01-25 11:14:44	ga_ls9c_ard_3-2-1_109076_2024-01-25_final.stac-item
2024-01-25 11:14:44	ga_ls9c_ard_3-2-1_109076_2024-01-25_nrt.stac-item
2024-01-27 09:23:31	ga_ls9c_ard_3-2-1_091076_2024-01-26_final.stac-item
2024-01-30 09:52:04	ga_ls9c_ard_3-2-1_096070_2024-01-30_final.stac-item
2024-03-08 09:17:17	ga_ls9c_ard_3-2-1_090076_2024-03-07_final.stac-item
2024-03-14 11:57:56	ga_ls9c_ard_3-2-1_116076_2024-03-14_final.stac-item
2024-03-18 09:51:56	ga_ls9c_ard_3-2-1_096070_2024-03-18_final.stac-item
2024-03-31 09:28:05	ga_ls9c_ard_3-2-1_091088_2024-03-30_final.stac-item
2024-04-11 10:42:22	ga_ls9c_ard_3-2-1_104073_2024-04-11_final.stac-item
2024-04-11 10:45:58	ga_ls9c_ard_3-2-1_104082_2024-04-11_final.stac-item
2024-04-23 11:10:47	ga_ls9c_ard_3-2-1_108083_2024-04-23_final.stac-item
2024-04-25 09:17:07	ga_ls9c_ard_3-2-1_090077_2024-04-24_final.stac-item
2024-04-28 11:25:43	ga_ls9c_ard_3-2-1_111074_2024-04-28_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