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
2021-11-12 09:22:44	ga_ls9c_ard_3-2-1_091082_2021-11-11_final.stac-item
2021-12-20 09:26:45	ga_ls9c_ard_3-2-1_091084_2021-12-19_final.stac-item
2021-12-24 10:40:07	ga_ls9c_ard_3-2-1_103082_2021-12-24_final.stac-item
2022-01-03 09:33:55	ga_ls9c_ard_3-2-1_093071_2022-01-03_final.stac-item
2022-01-05 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-05_final.stac-item
2022-01-29 10:13:24	ga_ls9c_ard_3-2-1_099077_2022-01-29_final.stac-item
2022-02-07 10:08:00	ga_ls9c_ard_3-2-1_098079_2022-02-07_final.stac-item
2022-03-26 09:24:25	ga_ls9c_ard_3-2-1_091079_2022-03-25_final.stac-item
2022-06-05 09:28:12	ga_ls9c_ard_3-2-1_092074_2022-06-04_final.stac-item
2022-07-02 10:49:16	ga_ls9c_ard_3-2-1_105075_2022-07-02_final.stac-item
2022-07-19 11:31:21	ga_ls9c_ard_3-2-1_112072_2022-07-19_final.stac-item
2022-07-24 10:09:29	ga_ls9c_ard_3-2-1_099068_2022-07-24_final.stac-item
2022-07-24 10:11:05	ga_ls9c_ard_3-2-1_099072_2022-07-24_final.stac-item
2022-08-04 11:35:57	ga_ls9c_ard_3-2-1_112083_2022-08-04_final.stac-item
2022-08-24 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-08-23_final.stac-item
2022-09-09 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-09-09_final.stac-item
2022-09-17 10:21:36	ga_ls9c_ard_3-2-1_100082_2022-09-17_final.stac-item
2022-09-18 11:05:16	ga_ls9c_ard_3-2-1_107083_2022-09-18_final.stac-item
2022-09-19 10:10:03	ga_ls9c_ard_3-2-1_098084_2022-09-19_final.stac-item
2022-09-22 10:34:35	ga_ls9c_ard_3-2-1_103068_2022-09-22_final.stac-item
2022-09-24 10:26:38	ga_ls9c_ard_3-2-1_101079_2022-09-24_final.stac-item
2022-10-09 09:41:24	ga_ls9c_ard_3-2-1_094074_2022-10-09_final.stac-item
2022-10-10 10:26:16	ga_ls9c_ard_3-2-1_101078_2022-10-10_final.stac-item
2022-12-03 09:46:49	ga_ls9c_ard_3-2-1_095072_2022-12-03_final.stac-item
2022-12-03 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-12-03_final.stac-item
2023-01-10 09:10:57	ga_ls9c_ard_3-2-1_089075_2023-01-09_final.stac-item
2023-01-15 09:33:26	ga_ls9c_ard_3-2-1_092085_2023-01-15_final.stac-item
2023-01-22 11:16:50	ga_ls9c_ard_3-2-1_109081_2023-01-22_final.stac-item
2023-02-11 09:11:49	ga_ls9c_ard_3-2-1_089077_2023-02-10_final.stac-item
2023-03-09 09:46:33	ga_ls9c_ard_3-2-1_095072_2023-03-09_final.stac-item
2023-03-15 10:49:57	ga_ls9c_ard_3-2-1_105076_2023-03-15_final.stac-item
2023-03-27 09:34:51	ga_ls9c_ard_3-2-1_093074_2023-03-27_final.stac-item
2023-03-29 09:26:26	ga_ls9c_ard_3-2-1_091084_2023-03-28_final.stac-item
2023-04-08 09:57:54	ga_ls9c_ard_3-2-1_097070_2023-04-08_final.stac-item
2023-05-03 11:31:57	ga_ls9c_ard_3-2-1_112074_2023-05-03_final.stac-item
2023-05-31 10:19:34	ga_ls9c_ard_3-2-1_100079_2023-05-31_final.stac-item
2023-06-03 09:12:46	ga_ls9c_ard_3-2-1_089082_2023-06-02_final.stac-item
2023-06-10 10:55:23	ga_ls9c_ard_3-2-1_106076_2023-06-10_final.stac-item
2023-06-13 09:50:57	ga_ls9c_ard_3-2-1_095085_2023-06-13_final.stac-item
2023-07-10 11:05:55	ga_ls9c_ard_3-2-1_108071_2023-07-10_final.stac-item
2023-08-28 11:51:07	ga_ls9c_ard_3-2-1_115075_2023-08-28_final.stac-item
2023-08-31 09:06:16	ga_ls9c_ard_3-2-1_088080_2023-08-30_final.stac-item
2023-10-07 09:26:36	ga_ls9c_ard_3-2-1_091084_2023-10-06_final.stac-item
2023-11-01 10:56:08	ga_ls9c_ard_3-2-1_106076_2023-11-01_final.stac-item
2023-11-06 09:34:12	ga_ls9c_ard_3-2-1_093072_2023-11-06_final.stac-item
2023-11-09 10:04:43	ga_ls9c_ard_3-2-1_098071_2023-11-09_final.stac-item
2023-12-26 09:23:13	ga_ls9c_ard_3-2-1_091075_2023-12-25_final.stac-item
2024-01-27 11:00:01	ga_ls9c_ard_3-2-1_107070_2024-01-27_final.stac-item
2024-02-04 11:51:31	ga_ls9c_ard_3-2-1_115075_2024-02-04_final.stac-item
2024-02-09 10:30:22	ga_ls9c_ard_3-2-1_102073_2024-02-09_final.stac-item
2024-02-15 09:57:37	ga_ls9c_ard_3-2-1_096084_2024-02-15_final.stac-item
2024-02-21 09:22:24	ga_ls9c_ard_3-2-1_090089_2024-02-20_final.stac-item
2024-02-23 09:06:48	ga_ls9c_ard_3-2-1_088081_2024-02-22_final.stac-item
2024-02-23 09:07:36	ga_ls9c_ard_3-2-1_088083_2024-02-22_final.stac-item
2024-03-15 09:23:02	ga_ls9c_ard_3-2-1_091075_2024-03-14_final.stac-item
2024-03-15 09:26:14	ga_ls9c_ard_3-2-1_091083_2024-03-14_final.stac-item
2024-03-24 09:17:12	ga_ls9c_ard_3-2-1_090076_2024-03-23_final.stac-item
2024-04-08 11:51:59	ga_ls9c_ard_3-2-1_115077_2024-04-08_final.stac-item
2024-04-08 11:53:11	ga_ls9c_ard_3-2-1_115080_2024-04-08_final.stac-item
2024-04-13 10:28:47	ga_ls9c_ard_3-2-1_102070_2024-04-13_final.stac-item
2024-05-04 09:14:30	ga_ls9c_ard_3-2-1_089086_2024-05-03_interim.stac-item
2024-05-11 10:55:11	ga_ls9c_ard_3-2-1_106075_2024-05-11_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