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

79 results

Time (local)	Label
2021-11-20 11:22:41	ga_ls9c_ard_3-2-1_110076_2021-11-20_final.stac-item
2022-01-13 10:15:45	ga_ls9c_ard_3-2-1_099083_2022-01-13_final.stac-item
2022-01-14 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-01-13_final.stac-item
2022-01-14 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-01-14_final.stac-item
2022-01-23 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-22_final.stac-item
2022-02-06 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-02-06_final.stac-item
2022-02-23 11:45:32	ga_ls9c_ard_3-2-1_114076_2022-02-23_final.stac-item
2022-02-26 10:39:54	ga_ls9c_ard_3-2-1_103082_2022-02-26_final.stac-item
2022-03-04 11:42:04	ga_ls9c_ard_3-2-1_113083_2022-03-04_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-03-19 10:55:59	ga_ls9c_ard_3-2-1_106076_2022-03-19_final.stac-item
2022-03-23 10:28:03	ga_ls9c_ard_3-2-1_102068_2022-03-23_final.stac-item
2022-04-07 11:23:37	ga_ls9c_ard_3-2-1_111068_2022-04-07_final.stac-item
2022-07-05 11:20:34	ga_ls9c_ard_3-2-1_110076_2022-07-05_final.stac-item
2022-07-09 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-07-09_final.stac-item
2022-07-16 09:25:05	ga_ls9c_ard_3-2-1_091081_2022-07-15_final.stac-item
2022-07-25 09:20:16	ga_ls9c_ard_3-2-1_090084_2022-07-24_final.stac-item
2022-07-28 11:29:17	ga_ls9c_ard_3-2-1_111082_2022-07-28_final.stac-item
2022-08-06 09:39:57	ga_ls9c_ard_3-2-1_094071_2022-08-06_final.stac-item
2022-09-10 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-09-10_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-09-17 10:17:37	ga_ls9c_ard_3-2-1_100072_2022-09-17_final.stac-item
2022-09-23 09:40:10	ga_ls9c_ard_3-2-1_094071_2022-09-23_final.stac-item
2022-09-30 09:47:10	ga_ls9c_ard_3-2-1_095073_2022-09-30_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
2022-10-28 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-10-28_final.stac-item
2022-10-28 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-10-28_final.stac-item
2022-10-29 10:54:26	ga_ls9c_ard_3-2-1_106071_2022-10-29_final.stac-item
2022-11-06 11:46:39	ga_ls9c_ard_3-2-1_114078_2022-11-06_final.stac-item
2022-11-09 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-09_final.stac-item
2022-11-09 10:38:17	ga_ls9c_ard_3-2-1_103077_2022-11-09_final.stac-item
2022-11-22 10:05:24	ga_ls9c_ard_3-2-1_098072_2022-11-22_final.stac-item
2022-11-30 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-11-30_final.stac-item
2022-12-07 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-12-06_final.stac-item
2022-12-07 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-12-06_nrt.stac-item
2022-12-08 10:05:23	ga_ls9c_ard_3-2-1_098072_2022-12-08_final.stac-item
2022-12-17 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-12-17_final.stac-item
2022-12-19 09:49:14	ga_ls9c_ard_3-2-1_095078_2022-12-19_final.stac-item
2023-01-08 09:23:44	ga_ls9c_ard_3-2-1_091076_2023-01-07_final.stac-item
2023-01-21 10:29:33	ga_ls9c_ard_3-2-1_102071_2023-01-21_final.stac-item
2023-01-25 10:04:31	ga_ls9c_ard_3-2-1_098070_2023-01-25_final.stac-item
2023-02-03 11:38:08	ga_ls9c_ard_3-2-1_113072_2023-02-03_final.stac-item
2023-02-18 10:54:24	ga_ls9c_ard_3-2-1_106071_2023-02-18_final.stac-item
2023-03-09 11:24:14	ga_ls9c_ard_3-2-1_111069_2023-03-09_final.stac-item
2023-03-24 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-03-24_final.stac-item
2023-03-27 09:37:39	ga_ls9c_ard_3-2-1_093081_2023-03-27_final.stac-item
2023-04-03 11:20:16	ga_ls9c_ard_3-2-1_110075_2023-04-03_final.stac-item
2023-04-03 11:23:27	ga_ls9c_ard_3-2-1_110083_2023-04-03_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-05-07 09:28:19	ga_ls9c_ard_3-2-1_092074_2023-05-06_final.stac-item
2023-06-14 10:27:24	ga_ls9c_ard_3-2-1_102068_2023-06-14_final.stac-item
2023-06-15 09:34:10	ga_ls9c_ard_3-2-1_093074_2023-06-15_final.stac-item
2023-06-17 11:04:17	ga_ls9c_ard_3-2-1_107083_2023-06-17_final.stac-item
2023-07-06 11:35:48	ga_ls9c_ard_3-2-1_112084_2023-07-06_final.stac-item
2023-07-19 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-07-18_final.stac-item
2023-07-28 09:16:20	ga_ls9c_ard_3-2-1_090075_2023-07-27_final.stac-item
2023-08-03 10:21:25	ga_ls9c_ard_3-2-1_100083_2023-08-03_final.stac-item
2023-10-02 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-10-02_final.stac-item
2023-10-02 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-10-02_interim.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-10-26 11:32:29	ga_ls9c_ard_3-2-1_112074_2023-10-26_final.stac-item
2023-11-24 11:00:04	ga_ls9c_ard_3-2-1_107070_2023-11-24_final.stac-item
2023-12-03 10:54:40	ga_ls9c_ard_3-2-1_106072_2023-12-03_final.stac-item
2023-12-11 10:04:25	ga_ls9c_ard_3-2-1_098070_2023-12-11_final.stac-item
2023-12-18 10:10:16	ga_ls9c_ard_3-2-1_099069_2023-12-18_final.stac-item
2023-12-19 09:20:14	ga_ls9c_ard_3-2-1_090083_2023-12-18_final.stac-item
2024-01-04 10:55:02	ga_ls9c_ard_3-2-1_106073_2024-01-04_final.stac-item
2024-02-27 11:58:19	ga_ls9c_ard_3-2-1_116077_2024-02-27_final.stac-item
2024-03-06 11:06:56	ga_ls9c_ard_3-2-1_108072_2024-03-06_final.stac-item
2024-03-14 10:17:28	ga_ls9c_ard_3-2-1_100072_2024-03-14_final.stac-item
2024-03-23 11:52:31	ga_ls9c_ard_3-2-1_115078_2024-03-23_final.stac-item
2024-03-25 09:57:16	ga_ls9c_ard_3-2-1_097068_2024-03-25_final.stac-item
2024-03-25 10:04:03	ga_ls9c_ard_3-2-1_097085_2024-03-25_final.stac-item
2024-04-16 09:28:20	ga_ls9c_ard_3-2-1_091089_2024-04-15_final.stac-item
2024-04-17 10:09:11	ga_ls9c_ard_3-2-1_098083_2024-04-17_final.stac-item
2024-04-30 09:38:51	ga_ls9c_ard_3-2-1_093085_2024-04-30_final.stac-item
2024-05-11 09:21:53	ga_ls9c_ard_3-2-1_090089_2024-05-10_final.stac-item
2024-05-15 10:29:35	ga_ls9c_ard_3-2-1_102073_2024-05-15_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years