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

66 results

Time (local)	Label
2021-11-03 11:32:26	ga_ls9c_ard_3-2-1_112072_2021-11-03_final.stac-item
2021-11-20 11:19:54	ga_ls9c_ard_3-2-1_110069_2021-11-20_final.stac-item
2021-12-05 10:09:20	ga_ls9c_ard_3-2-1_098082_2021-12-05_final.stac-item
2021-12-13 10:58:41	ga_ls9c_ard_3-2-1_106082_2021-12-13_final.stac-item
2022-01-28 09:34:07	ga_ls9c_ard_3-2-1_092087_2022-01-28_final.stac-item
2022-02-03 10:29:08	ga_ls9c_ard_3-2-1_102070_2022-02-03_final.stac-item
2022-02-08 09:13:34	ga_ls9c_ard_3-2-1_089082_2022-02-07_final.stac-item
2022-02-24 10:52:18	ga_ls9c_ard_3-2-1_105082_2022-02-24_final.stac-item
2022-02-27 11:23:09	ga_ls9c_ard_3-2-1_110082_2022-02-27_final.stac-item
2022-03-31 11:19:03	ga_ls9c_ard_3-2-1_110072_2022-03-31_final.stac-item
2022-04-19 11:52:36	ga_ls9c_ard_3-2-1_115079_2022-04-19_final.stac-item
2022-04-27 09:27:01	ga_ls9c_ard_3-2-1_091086_2022-04-26_final.stac-item
2022-05-13 09:26:06	ga_ls9c_ard_3-2-1_091084_2022-05-12_final.stac-item
2022-05-18 09:43:45	ga_ls9c_ard_3-2-1_094082_2022-05-18_final.stac-item
2022-06-06 10:09:04	ga_ls9c_ard_3-2-1_099068_2022-06-06_final.stac-item
2022-06-12 09:39:36	ga_ls9c_ard_3-2-1_093087_2022-06-12_final.stac-item
2022-08-06 09:42:20	ga_ls9c_ard_3-2-1_094077_2022-08-06_final.stac-item
2022-08-10 10:58:32	ga_ls9c_ard_3-2-1_106082_2022-08-10_final.stac-item
2022-08-17 09:28:16	ga_ls9c_ard_3-2-1_091088_2022-08-16_final.stac-item
2022-08-17 11:05:34	ga_ls9c_ard_3-2-1_107084_2022-08-17_final.stac-item
2022-08-26 09:20:31	ga_ls9c_ard_3-2-1_090084_2022-08-25_final.stac-item
2022-09-03 10:03:59	ga_ls9c_ard_3-2-1_098069_2022-09-03_final.stac-item
2022-09-05 09:55:12	ga_ls9c_ard_3-2-1_096078_2022-09-05_final.stac-item
2022-09-11 09:21:44	ga_ls9c_ard_3-2-1_090087_2022-09-10_final.stac-item
2022-10-04 09:25:14	ga_ls9c_ard_3-2-1_091080_2022-10-03_final.stac-item
2022-10-17 10:30:31	ga_ls9c_ard_3-2-1_102073_2022-10-17_final.stac-item
2022-10-26 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-10-26_final.stac-item
2022-10-28 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-10-28_final.stac-item
2022-11-19 09:37:42	ga_ls9c_ard_3-2-1_093080_2022-11-19_final.stac-item
2022-11-23 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-11-22_final.stac-item
2022-12-01 11:38:03	ga_ls9c_ard_3-2-1_113072_2022-12-01_final.stac-item
2022-12-07 09:22:55	ga_ls9c_ard_3-2-1_091074_2022-12-06_final.stac-item
2022-12-07 11:00:12	ga_ls9c_ard_3-2-1_107070_2022-12-07_final.stac-item
2023-01-18 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-01-18_final.stac-item
2023-01-24 09:22:50	ga_ls9c_ard_3-2-1_091074_2023-01-23_final.stac-item
2023-02-09 09:26:11	ga_ls9c_ard_3-2-1_091082_2023-02-08_final.stac-item
2023-02-22 10:31:58	ga_ls9c_ard_3-2-1_102077_2023-02-22_final.stac-item
2023-02-25 11:04:25	ga_ls9c_ard_3-2-1_107081_2023-02-25_final.stac-item
2023-03-11 09:39:22	ga_ls9c_ard_3-2-1_093085_2023-03-11_final.stac-item
2023-03-14 11:45:58	ga_ls9c_ard_3-2-1_114077_2023-03-14_final.stac-item
2023-03-24 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-03-23_final.stac-item
2023-03-31 10:48:57	ga_ls9c_ard_3-2-1_105074_2023-03-31_final.stac-item
2023-04-08 09:57:54	ga_ls9c_ard_3-2-1_097070_2023-04-08_final.stac-item
2023-04-08 09:58:42	ga_ls9c_ard_3-2-1_097072_2023-04-08_final.stac-item
2023-05-01 11:44:45	ga_ls9c_ard_3-2-1_114075_2023-05-01_final.stac-item
2023-05-09 10:55:14	ga_ls9c_ard_3-2-1_106075_2023-05-09_final.stac-item
2023-05-16 11:04:57	ga_ls9c_ard_3-2-1_107084_2023-05-16_final.stac-item
2023-05-30 09:33:31	ga_ls9c_ard_3-2-1_093072_2023-05-30_final.stac-item
2023-06-28 10:43:48	ga_ls9c_ard_3-2-1_104078_2023-06-28_final.stac-item
2023-08-07 09:51:33	ga_ls9c_ard_3-2-1_096070_2023-08-07_final.stac-item
2023-08-17 10:28:38	ga_ls9c_ard_3-2-1_102070_2023-08-17_final.stac-item
2023-09-05 09:26:27	ga_ls9c_ard_3-2-1_091084_2023-09-04_final.stac-item
2023-09-14 09:22:22	ga_ls9c_ard_3-2-1_090089_2023-09-13_final.stac-item
2023-10-06 10:19:01	ga_ls9c_ard_3-2-1_100076_2023-10-06_final.stac-item
2023-10-10 09:53:08	ga_ls9c_ard_3-2-1_096073_2023-10-10_final.stac-item
2023-10-10 11:36:01	ga_ls9c_ard_3-2-1_112083_2023-10-10_final.stac-item
2023-11-14 10:26:03	ga_ls9c_ard_3-2-1_101078_2023-11-14_final.stac-item
2023-11-20 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-11-20_final.stac-item
2023-12-04 09:58:38	ga_ls9c_ard_3-2-1_097071_2023-12-04_final.stac-item
2024-01-22 09:07:22	ga_ls9c_ard_3-2-1_088082_2024-01-21_final.stac-item
2024-01-27 11:00:49	ga_ls9c_ard_3-2-1_107072_2024-01-27_final.stac-item
2024-02-07 10:40:45	ga_ls9c_ard_3-2-1_104068_2024-02-07_final.stac-item
2024-04-24 10:14:44	ga_ls9c_ard_3-2-1_099082_2024-04-24_final.stac-item
2024-04-29 10:28:05	ga_ls9c_ard_3-2-1_102069_2024-04-29_final.stac-item
2024-05-07 11:23:30	ga_ls9c_ard_3-2-1_110084_2024-05-07_final.stac-item
2024-05-17 10:17:58	ga_ls9c_ard_3-2-1_100075_2024-05-17_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