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

64 results

Time (local)	Label
2021-11-11 10:20:39	ga_ls9c_ard_3-2-1_100080_2021-11-11_final.stac-item
2021-11-20 11:22:17	ga_ls9c_ard_3-2-1_110075_2021-11-20_final.stac-item
2021-12-18 11:12:48	ga_ls9c_ard_3-2-1_109071_2021-12-18_final.stac-item
2021-12-27 09:31:21	ga_ls9c_ard_3-2-1_092080_2021-12-27_final.stac-item
2022-01-01 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-01-01_final.stac-item
2022-01-14 09:19:19	ga_ls9c_ard_3-2-1_090081_2022-01-13_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-03-04 09:57:11	ga_ls9c_ard_3-2-1_097068_2022-03-04_final.stac-item
2022-03-08 09:39:40	ga_ls9c_ard_3-2-1_093086_2022-03-08_final.stac-item
2022-03-19 10:54:23	ga_ls9c_ard_3-2-1_106072_2022-03-19_final.stac-item
2022-03-26 09:27:37	ga_ls9c_ard_3-2-1_091087_2022-03-25_final.stac-item
2022-04-04 10:53:32	ga_ls9c_ard_3-2-1_106070_2022-04-04_final.stac-item
2022-05-01 10:39:34	ga_ls9c_ard_3-2-1_103082_2022-05-01_final.stac-item
2022-05-05 10:15:13	ga_ls9c_ard_3-2-1_099083_2022-05-05_final.stac-item
2022-05-07 10:00:51	ga_ls9c_ard_3-2-1_097078_2022-05-07_final.stac-item
2022-05-14 11:46:14	ga_ls9c_ard_3-2-1_114079_2022-05-14_final.stac-item
2022-05-29 11:03:40	ga_ls9c_ard_3-2-1_107081_2022-05-29_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-06-15 10:04:10	ga_ls9c_ard_3-2-1_098071_2022-06-15_final.stac-item
2022-06-26 11:26:46	ga_ls9c_ard_3-2-1_111076_2022-06-26_final.stac-item
2022-07-21 09:41:20	ga_ls9c_ard_3-2-1_094075_2022-07-21_final.stac-item
2022-08-13 09:46:35	ga_ls9c_ard_3-2-1_095072_2022-08-13_final.stac-item
2022-09-14 11:29:10	ga_ls9c_ard_3-2-1_111081_2022-09-14_final.stac-item
2022-10-14 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-14_final.stac-item
2022-10-14 10:01:59	ga_ls9c_ard_3-2-1_097079_2022-10-14_final.stac-item
2022-11-06 11:45:03	ga_ls9c_ard_3-2-1_114074_2022-11-06_final.stac-item
2022-11-13 10:10:48	ga_ls9c_ard_3-2-1_099070_2022-11-13_final.stac-item
2022-11-15 10:02:50	ga_ls9c_ard_3-2-1_097081_2022-11-15_final.stac-item
2022-11-22 10:04:37	ga_ls9c_ard_3-2-1_098070_2022-11-22_final.stac-item
2023-01-02 10:02:01	ga_ls9c_ard_3-2-1_097079_2023-01-02_final.stac-item
2023-01-05 10:32:07	ga_ls9c_ard_3-2-1_102077_2023-01-05_final.stac-item
2023-01-11 11:36:41	ga_ls9c_ard_3-2-1_112084_2023-01-11_final.stac-item
2023-02-02 10:54:52	ga_ls9c_ard_3-2-1_106072_2023-02-02_final.stac-item
2023-02-09 09:27:47	ga_ls9c_ard_3-2-1_091086_2023-02-08_final.stac-item
2023-02-25 09:29:08	ga_ls9c_ard_3-2-1_091090_2023-02-24_final.stac-item
2023-03-08 09:04:54	ga_ls9c_ard_3-2-1_088076_2023-03-07_interim.stac-item
2023-04-07 10:55:07	ga_ls9c_ard_3-2-1_106074_2023-04-07_final.stac-item
2023-04-28 09:39:48	ga_ls9c_ard_3-2-1_093087_2023-04-28_final.stac-item
2023-05-01 10:05:04	ga_ls9c_ard_3-2-1_098073_2023-05-01_final.stac-item
2023-05-16 09:22:53	ga_ls9c_ard_3-2-1_091076_2023-05-15_final.stac-item
2023-05-28 09:51:04	ga_ls9c_ard_3-2-1_095085_2023-05-28_final.stac-item
2023-06-09 11:50:37	ga_ls9c_ard_3-2-1_115075_2023-06-09_final.stac-item
2023-07-12 09:20:41	ga_ls9c_ard_3-2-1_090086_2023-07-11_final.stac-item
2023-07-19 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-07-19_final.stac-item
2023-07-28 10:57:13	ga_ls9c_ard_3-2-1_106080_2023-07-28_final.stac-item
2023-08-12 11:51:47	ga_ls9c_ard_3-2-1_115077_2023-08-12_final.stac-item
2023-08-22 09:13:33	ga_ls9c_ard_3-2-1_089083_2023-08-21_final.stac-item
2023-09-03 09:39:11	ga_ls9c_ard_3-2-1_093085_2023-09-03_final.stac-item
2023-09-11 10:27:56	ga_ls9c_ard_3-2-1_101083_2023-09-11_final.stac-item
2023-09-13 10:15:35	ga_ls9c_ard_3-2-1_099083_2023-09-13_final.stac-item
2023-09-21 11:01:26	ga_ls9c_ard_3-2-1_107074_2023-09-21_final.stac-item
2023-09-30 10:53:37	ga_ls9c_ard_3-2-1_106070_2023-09-30_final.stac-item
2023-10-01 10:02:24	ga_ls9c_ard_3-2-1_097081_2023-10-01_final.stac-item
2023-10-07 09:27:00	ga_ls9c_ard_3-2-1_091085_2023-10-06_final.stac-item
2023-10-16 09:16:56	ga_ls9c_ard_3-2-1_090075_2023-10-15_final.stac-item
2023-11-06 09:40:35	ga_ls9c_ard_3-2-1_093088_2023-11-06_final.stac-item
2023-11-18 10:04:10	ga_ls9c_ard_3-2-1_097085_2023-11-18_final.stac-item
2023-12-13 09:58:04	ga_ls9c_ard_3-2-1_096085_2023-12-13_final.stac-item
2023-12-28 09:16:50	ga_ls9c_ard_3-2-1_089090_2023-12-27_final.stac-item
2024-01-18 09:28:56	ga_ls9c_ard_3-2-1_092074_2024-01-17_final.stac-item
2024-01-21 11:42:17	ga_ls9c_ard_3-2-1_113083_2024-01-21_final.stac-item
2024-02-05 09:18:13	ga_ls9c_ard_3-2-1_090078_2024-02-04_final.stac-item
2024-02-15 09:58:01	ga_ls9c_ard_3-2-1_096085_2024-02-15_final.stac-item
2024-03-31 11:04:58	ga_ls9c_ard_3-2-1_107083_2024-03-31_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