Search ga_ls9c_ard_3 whole collection

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

62 results

Time (local)	Label
2021-11-15 11:18:38	ga_ls9c_ard_3-2-1_110072_2021-11-15_final.stac-item
2021-12-05 10:04:09	ga_ls9c_ard_3-2-1_098069_2021-12-05_final.stac-item
2021-12-14 11:42:20	ga_ls9c_ard_3-2-1_113083_2021-12-14_final.stac-item
2021-12-29 10:57:04	ga_ls9c_ard_3-2-1_106078_2021-12-29_final.stac-item
2022-01-01 11:29:10	ga_ls9c_ard_3-2-1_111081_2022-01-01_final.stac-item
2022-01-02 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-01-02_final.stac-item
2022-01-04 10:18:47	ga_ls9c_ard_3-2-1_100075_2022-01-04_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-02-07 11:45:17	ga_ls9c_ard_3-2-1_114075_2022-02-07_final.stac-item
2022-02-13 09:28:05	ga_ls9c_ard_3-2-1_092072_2022-02-12_final.stac-item
2022-04-05 11:41:10	ga_ls9c_ard_3-2-1_113081_2022-04-05_final.stac-item
2022-05-13 11:00:59	ga_ls9c_ard_3-2-1_107074_2022-05-13_final.stac-item
2022-05-27 11:14:49	ga_ls9c_ard_3-2-1_109078_2022-05-27_final.stac-item
2022-06-03 11:20:14	ga_ls9c_ard_3-2-1_110076_2022-06-03_final.stac-item
2022-06-16 10:50:14	ga_ls9c_ard_3-2-1_105078_2022-06-16_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-09-11 10:55:02	ga_ls9c_ard_3-2-1_106073_2022-09-11_final.stac-item
2022-09-16 09:40:20	ga_ls9c_ard_3-2-1_093087_2022-09-16_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-16 11:24:08	ga_ls9c_ard_3-2-1_111068_2022-10-16_final.stac-item
2022-11-15 10:04:01	ga_ls9c_ard_3-2-1_097084_2022-11-15_final.stac-item
2022-12-19 09:50:49	ga_ls9c_ard_3-2-1_095082_2022-12-19_final.stac-item
2022-12-26 11:36:16	ga_ls9c_ard_3-2-1_112083_2022-12-26_final.stac-item
2022-12-30 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-12-30_final.stac-item
2023-01-27 09:57:47	ga_ls9c_ard_3-2-1_096084_2023-01-27_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-12 09:58:16	ga_ls9c_ard_3-2-1_096085_2023-02-12_final.stac-item
2023-03-02 11:23:45	ga_ls9c_ard_3-2-1_110083_2023-03-02_final.stac-item
2023-03-28 10:20:53	ga_ls9c_ard_3-2-1_100081_2023-03-28_final.stac-item
2023-04-05 09:28:37	ga_ls9c_ard_3-2-1_092074_2023-04-04_final.stac-item
2023-04-27 10:28:15	ga_ls9c_ard_3-2-1_102069_2023-04-27_final.stac-item
2023-05-10 11:40:53	ga_ls9c_ard_3-2-1_113081_2023-05-10_final.stac-item
2023-05-21 11:19:50	ga_ls9c_ard_3-2-1_110075_2023-05-21_final.stac-item
2023-06-17 10:59:29	ga_ls9c_ard_3-2-1_107071_2023-06-17_final.stac-item
2023-07-05 09:14:26	ga_ls9c_ard_3-2-1_089086_2023-07-04_final.stac-item
2023-07-08 09:43:46	ga_ls9c_ard_3-2-1_094082_2023-07-08_final.stac-item
2023-07-09 10:22:15	ga_ls9c_ard_3-2-1_101070_2023-07-09_final.stac-item
2023-07-16 10:28:52	ga_ls9c_ard_3-2-1_102071_2023-07-16_final.stac-item
2023-08-07 09:57:32	ga_ls9c_ard_3-2-1_096085_2023-08-07_final.stac-item
2023-08-12 10:14:05	ga_ls9c_ard_3-2-1_099080_2023-08-12_final.stac-item
2023-08-16 11:24:39	ga_ls9c_ard_3-2-1_111071_2023-08-16_final.stac-item
2023-08-21 10:04:46	ga_ls9c_ard_3-2-1_098072_2023-08-21_final.stac-item
2023-08-22 09:13:33	ga_ls9c_ard_3-2-1_089083_2023-08-21_final.stac-item
2023-09-16 09:06:49	ga_ls9c_ard_3-2-1_088081_2023-09-15_final.stac-item
2023-09-30 10:54:01	ga_ls9c_ard_3-2-1_106071_2023-09-30_final.stac-item
2023-11-18 09:56:59	ga_ls9c_ard_3-2-1_097067_2023-11-18_final.stac-item
2023-11-23 10:19:11	ga_ls9c_ard_3-2-1_100076_2023-11-23_final.stac-item
2023-12-04 11:37:55	ga_ls9c_ard_3-2-1_113072_2023-12-04_final.stac-item
2023-12-23 10:33:12	ga_ls9c_ard_3-2-1_102080_2023-12-23_final.stac-item
2023-12-25 11:58:56	ga_ls9c_ard_3-2-1_116078_2023-12-25_final.stac-item
2023-12-30 10:34:58	ga_ls9c_ard_3-2-1_103069_2023-12-30_final.stac-item
2024-01-19 10:09:24	ga_ls9c_ard_3-2-1_099067_2024-01-19_final.stac-item
2024-02-12 09:27:09	ga_ls9c_ard_3-2-1_091085_2024-02-11_final.stac-item
2024-02-25 10:29:22	ga_ls9c_ard_3-2-1_102071_2024-02-25_final.stac-item
2024-03-07 11:51:23	ga_ls9c_ard_3-2-1_115075_2024-03-07_final.stac-item
2024-03-11 11:29:27	ga_ls9c_ard_3-2-1_111082_2024-03-11_final.stac-item
2024-03-31 11:02:10	ga_ls9c_ard_3-2-1_107076_2024-03-31_final.stac-item
2024-04-30 11:16:32	ga_ls9c_ard_3-2-1_109082_2024-04-30_final.stac-item
2024-05-01 10:21:18	ga_ls9c_ard_3-2-1_100083_2024-05-01_final.stac-item
2024-05-09 11:06:45	ga_ls9c_ard_3-2-1_108073_2024-05-09_final.stac-item
2024-05-21 11:35:19	ga_ls9c_ard_3-2-1_112083_2024-05-21_final.stac-item
2024-06-04 10:04:19	ga_ls9c_ard_3-2-1_098072_2024-06-04_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