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

61 results

Time (local)	Label
2021-11-24 10:41:59	ga_ls9c_ard_3-2-1_104068_2021-11-24_final.stac-item
2021-12-05 10:04:57	ga_ls9c_ard_3-2-1_098071_2021-12-05_final.stac-item
2022-01-04 10:19:34	ga_ls9c_ard_3-2-1_100077_2022-01-04_final.stac-item
2022-01-23 09:12:23	ga_ls9c_ard_3-2-1_089079_2022-01-22_final.stac-item
2022-01-29 10:15:47	ga_ls9c_ard_3-2-1_099083_2022-01-29_final.stac-item
2022-02-05 10:19:58	ga_ls9c_ard_3-2-1_100078_2022-02-05_final.stac-item
2022-02-11 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-02-11_final.stac-item
2022-02-15 09:22:53	ga_ls9c_ard_3-2-1_090090_2022-02-14_final.stac-item
2022-04-03 10:09:28	ga_ls9c_ard_3-2-1_099068_2022-04-03_final.stac-item
2022-04-03 10:09:52	ga_ls9c_ard_3-2-1_099069_2022-04-03_final.stac-item
2022-04-07 11:24:25	ga_ls9c_ard_3-2-1_111070_2022-04-07_final.stac-item
2022-05-10 10:27:44	ga_ls9c_ard_3-2-1_102068_2022-05-10_final.stac-item
2022-05-13 09:22:30	ga_ls9c_ard_3-2-1_091075_2022-05-12_final.stac-item
2022-05-17 10:33:49	ga_ls9c_ard_3-2-1_103068_2022-05-17_final.stac-item
2022-05-21 10:10:14	ga_ls9c_ard_3-2-1_099071_2022-05-21_final.stac-item
2022-06-14 11:04:58	ga_ls9c_ard_3-2-1_107084_2022-06-14_final.stac-item
2022-06-20 10:27:36	ga_ls9c_ard_3-2-1_101083_2022-06-20_final.stac-item
2022-06-25 09:07:25	ga_ls9c_ard_3-2-1_088083_2022-06-24_final.stac-item
2022-06-30 09:27:33	ga_ls9c_ard_3-2-1_091087_2022-06-29_final.stac-item
2022-07-11 09:06:33	ga_ls9c_ard_3-2-1_088081_2022-07-10_final.stac-item
2022-08-01 11:01:50	ga_ls9c_ard_3-2-1_107075_2022-08-01_final.stac-item
2022-08-08 09:33:11	ga_ls9c_ard_3-2-1_092085_2022-08-08_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-08-30 10:29:06	ga_ls9c_ard_3-2-1_102070_2022-08-30_final.stac-item
2022-08-31 09:39:04	ga_ls9c_ard_3-2-1_093084_2022-08-31_final.stac-item
2022-09-23 11:23:03	ga_ls9c_ard_3-2-1_110081_2022-09-23_final.stac-item
2022-10-06 10:47:21	ga_ls9c_ard_3-2-1_105069_2022-10-06_final.stac-item
2022-10-19 10:17:45	ga_ls9c_ard_3-2-1_100072_2022-10-19_final.stac-item
2022-11-01 11:26:06	ga_ls9c_ard_3-2-1_111073_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
2022-11-16 09:07:36	ga_ls9c_ard_3-2-1_088082_2022-11-15_final.stac-item
2022-11-19 11:14:12	ga_ls9c_ard_3-2-1_109074_2022-11-19_final.stac-item
2022-12-10 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-12-10_final.stac-item
2022-12-18 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-12-18_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-29 11:19:32	ga_ls9c_ard_3-2-1_110072_2023-01-29_final.stac-item
2023-03-21 10:10:50	ga_ls9c_ard_3-2-1_099071_2023-03-21_final.stac-item
2023-04-05 09:27:49	ga_ls9c_ard_3-2-1_092072_2023-04-04_final.stac-item
2023-04-30 09:27:24	ga_ls9c_ard_3-2-1_091087_2023-04-29_final.stac-item
2023-07-03 09:26:46	ga_ls9c_ard_3-2-1_091086_2023-07-02_final.stac-item
2023-07-12 09:21:53	ga_ls9c_ard_3-2-1_090089_2023-07-11_final.stac-item
2023-07-20 10:09:44	ga_ls9c_ard_3-2-1_098085_2023-07-20_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-08-12 10:10:30	ga_ls9c_ard_3-2-1_099071_2023-08-12_final.stac-item
2023-08-17 10:33:25	ga_ls9c_ard_3-2-1_102082_2023-08-17_final.stac-item
2023-09-01 09:46:45	ga_ls9c_ard_3-2-1_095073_2023-09-01_final.stac-item
2023-10-10 11:34:01	ga_ls9c_ard_3-2-1_112078_2023-10-10_final.stac-item
2023-10-21 09:35:29	ga_ls9c_ard_3-2-1_093075_2023-10-21_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-11-18 11:42:15	ga_ls9c_ard_3-2-1_113083_2023-11-18_final.stac-item
2023-12-31 11:21:24	ga_ls9c_ard_3-2-1_110077_2023-12-31_final.stac-item
2024-01-01 10:23:23	ga_ls9c_ard_3-2-1_101071_2024-01-01_final.stac-item
2024-01-21 11:38:41	ga_ls9c_ard_3-2-1_113074_2024-01-21_final.stac-item
2024-02-13 11:46:54	ga_ls9c_ard_3-2-1_114079_2024-02-13_final.stac-item
2024-02-17 11:20:31	ga_ls9c_ard_3-2-1_110075_2024-02-17_final.stac-item
2024-03-03 10:35:37	ga_ls9c_ard_3-2-1_103071_2024-03-03_final.stac-item
2024-03-24 09:21:36	ga_ls9c_ard_3-2-1_090087_2024-03-23_final.stac-item
2024-03-31 09:22:06	ga_ls9c_ard_3-2-1_091073_2024-03-30_final.stac-item
2024-04-08 10:15:30	ga_ls9c_ard_3-2-1_099083_2024-04-08_final.stac-item
2024-04-21 11:17:38	ga_ls9c_ard_3-2-1_110069_2024-04-21_final.stac-item
2024-04-21 11:19:38	ga_ls9c_ard_3-2-1_110074_2024-04-21_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years