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

First 100 results (query limit)

Time (local)	Label
2021-11-18 10:06:21	ga_ls9c_ard_3-2-1_097085_2021-11-18_final.stac-item
2021-11-19 10:41:32	ga_ls9c_ard_3-2-1_104073_2021-11-19_final.stac-item
2021-12-04 11:05:22	ga_ls9c_ard_3-2-1_107083_2021-12-04_final.stac-item
2021-12-07 09:53:22	ga_ls9c_ard_3-2-1_096073_2021-12-07_final.stac-item
2021-12-07 09:58:09	ga_ls9c_ard_3-2-1_096085_2021-12-07_final.stac-item
2021-12-12 10:15:02	ga_ls9c_ard_3-2-1_099081_2021-12-12_final.stac-item
2021-12-17 10:31:56	ga_ls9c_ard_3-2-1_102077_2021-12-17_final.stac-item
2021-12-18 09:37:54	ga_ls9c_ard_3-2-1_093081_2021-12-18_final.stac-item
2021-12-22 09:10:24	ga_ls9c_ard_3-2-1_089074_2021-12-21_final.stac-item
2021-12-29 09:18:35	ga_ls9c_ard_3-2-1_090079_2021-12-28_final.stac-item
2021-12-30 10:03:02	ga_ls9c_ard_3-2-1_097082_2021-12-30_final.stac-item
2021-12-31 10:41:07	ga_ls9c_ard_3-2-1_104069_2021-12-31_final.stac-item
2022-01-01 11:23:59	ga_ls9c_ard_3-2-1_111068_2022-01-01_final.stac-item
2022-01-05 11:00:50	ga_ls9c_ard_3-2-1_107072_2022-01-05_final.stac-item
2022-01-14 10:57:01	ga_ls9c_ard_3-2-1_106078_2022-01-14_final.stac-item
2022-01-15 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-01-15_final.stac-item
2022-01-31 11:39:07	ga_ls9c_ard_3-2-1_113075_2022-01-31_final.stac-item
2022-02-11 11:24:08	ga_ls9c_ard_3-2-1_110084_2022-02-11_final.stac-item
2022-02-16 10:02:57	ga_ls9c_ard_3-2-1_097082_2022-02-16_final.stac-item
2022-02-18 11:23:52	ga_ls9c_ard_3-2-1_111068_2022-02-18_final.stac-item
2022-02-20 09:36:11	ga_ls9c_ard_3-2-1_093077_2022-02-20_final.stac-item
2022-02-21 11:58:43	ga_ls9c_ard_3-2-1_116078_2022-02-21_final.stac-item
2022-03-09 10:22:07	ga_ls9c_ard_3-2-1_100084_2022-03-09_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-16 11:22:56	ga_ls9c_ard_3-2-1_110082_2022-04-16_final.stac-item
2022-04-21 09:58:55	ga_ls9c_ard_3-2-1_097073_2022-04-21_final.stac-item
2022-05-01 10:33:59	ga_ls9c_ard_3-2-1_103068_2022-05-01_final.stac-item
2022-05-24 10:39:56	ga_ls9c_ard_3-2-1_104068_2022-05-24_final.stac-item
2022-05-29 09:24:47	ga_ls9c_ard_3-2-1_091081_2022-05-28_final.stac-item
2022-05-29 11:02:52	ga_ls9c_ard_3-2-1_107079_2022-05-29_final.stac-item
2022-05-30 10:04:28	ga_ls9c_ard_3-2-1_098072_2022-05-30_final.stac-item
2022-05-31 09:12:26	ga_ls9c_ard_3-2-1_089081_2022-05-30_final.stac-item
2022-06-01 09:56:30	ga_ls9c_ard_3-2-1_096083_2022-06-01_final.stac-item
2022-06-04 10:24:37	ga_ls9c_ard_3-2-1_101076_2022-06-04_final.stac-item
2022-06-06 10:13:51	ga_ls9c_ard_3-2-1_099080_2022-06-06_final.stac-item
2022-06-17 11:33:54	ga_ls9c_ard_3-2-1_112079_2022-06-17_final.stac-item
2022-06-17 11:35:54	ga_ls9c_ard_3-2-1_112084_2022-06-17_final.stac-item
2022-07-05 09:42:05	ga_ls9c_ard_3-2-1_094077_2022-07-05_final.stac-item
2022-07-07 11:10:11	ga_ls9c_ard_3-2-1_108081_2022-07-07_final.stac-item
2022-07-18 09:11:34	ga_ls9c_ard_3-2-1_089078_2022-07-17_final.stac-item
2022-07-26 09:59:33	ga_ls9c_ard_3-2-1_097074_2022-07-26_final.stac-item
2022-07-31 10:18:33	ga_ls9c_ard_3-2-1_100075_2022-07-31_final.stac-item
2022-08-02 11:45:06	ga_ls9c_ard_3-2-1_114075_2022-08-02_final.stac-item
2022-08-06 09:40:45	ga_ls9c_ard_3-2-1_094073_2022-08-06_final.stac-item
2022-08-10 09:20:27	ga_ls9c_ard_3-2-1_090084_2022-08-09_final.stac-item
2022-08-10 09:20:51	ga_ls9c_ard_3-2-1_090085_2022-08-09_final.stac-item
2022-08-13 11:29:28	ga_ls9c_ard_3-2-1_111082_2022-08-13_final.stac-item
2022-08-22 11:18:08	ga_ls9c_ard_3-2-1_110069_2022-08-22_final.stac-item
2022-08-25 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-08-25_final.stac-item
2022-08-29 11:29:31	ga_ls9c_ard_3-2-1_111082_2022-08-29_final.stac-item
2022-08-31 09:40:40	ga_ls9c_ard_3-2-1_093088_2022-08-31_final.stac-item
2022-09-07 09:42:26	ga_ls9c_ard_3-2-1_094077_2022-09-07_final.stac-item
2022-09-16 11:12:50	ga_ls9c_ard_3-2-1_109071_2022-09-16_final.stac-item
2022-09-27 09:19:51	ga_ls9c_ard_3-2-1_090082_2022-09-26_final.stac-item
2022-09-28 09:58:20	ga_ls9c_ard_3-2-1_097070_2022-09-28_final.stac-item
2022-10-03 10:18:28	ga_ls9c_ard_3-2-1_100074_2022-10-03_final.stac-item
2022-10-09 09:40:36	ga_ls9c_ard_3-2-1_094072_2022-10-09_final.stac-item
2022-10-21 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-10-21_final.stac-item
2022-10-22 09:14:34	ga_ls9c_ard_3-2-1_089084_2022-10-21_final.stac-item
2022-11-15 09:58:02	ga_ls9c_ard_3-2-1_097069_2022-11-15_final.stac-item
2022-11-15 11:42:31	ga_ls9c_ard_3-2-1_113083_2022-11-15_final.stac-item
2022-11-18 10:30:08	ga_ls9c_ard_3-2-1_102072_2022-11-18_final.stac-item
2022-11-23 09:13:22	ga_ls9c_ard_3-2-1_089081_2022-11-22_final.stac-item
2022-12-02 10:44:02	ga_ls9c_ard_3-2-1_104076_2022-12-02_final.stac-item
2023-01-02 11:40:54	ga_ls9c_ard_3-2-1_113079_2023-01-02_final.stac-item
2023-01-06 09:38:53	ga_ls9c_ard_3-2-1_093083_2023-01-06_final.stac-item
2023-01-10 10:48:39	ga_ls9c_ard_3-2-1_105072_2023-01-10_final.stac-item
2023-01-26 09:15:18	ga_ls9c_ard_3-2-1_089086_2023-01-25_final.stac-item
2023-02-16 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-02-16_final.stac-item
2023-02-16 11:10:47	ga_ls9c_ard_3-2-1_108081_2023-02-16_final.stac-item
2023-02-16 11:11:59	ga_ls9c_ard_3-2-1_108084_2023-02-16_final.stac-item
2023-03-16 09:53:08	ga_ls9c_ard_3-2-1_096073_2023-03-16_final.stac-item
2023-03-29 09:28:02	ga_ls9c_ard_3-2-1_091088_2023-03-28_final.stac-item
2023-04-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2023-04-23_final.stac-item
2023-04-26 09:49:48	ga_ls9c_ard_3-2-1_095081_2023-04-26_final.stac-item
2023-04-26 09:50:36	ga_ls9c_ard_3-2-1_095083_2023-04-26_final.stac-item
2023-05-07 11:10:47	ga_ls9c_ard_3-2-1_108083_2023-05-07_final.stac-item
2023-05-08 10:13:58	ga_ls9c_ard_3-2-1_099080_2023-05-08_final.stac-item
2023-05-10 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-05-10_final.stac-item
2023-05-12 09:50:26	ga_ls9c_ard_3-2-1_095083_2023-05-12_final.stac-item
2023-05-16 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-05-16_final.stac-item
2023-05-28 11:28:45	ga_ls9c_ard_3-2-1_111082_2023-05-28_final.stac-item
2023-05-29 10:28:21	ga_ls9c_ard_3-2-1_102070_2023-05-29_final.stac-item
2023-06-19 10:45:56	ga_ls9c_ard_3-2-1_105068_2023-06-19_final.stac-item
2023-06-20 11:35:11	ga_ls9c_ard_3-2-1_112083_2023-06-20_final.stac-item
2023-06-23 10:24:24	ga_ls9c_ard_3-2-1_101076_2023-06-23_final.stac-item
2023-07-16 10:30:28	ga_ls9c_ard_3-2-1_102075_2023-07-16_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-23 10:35:50	ga_ls9c_ard_3-2-1_103073_2023-07-23_final.stac-item
2023-07-23 10:36:14	ga_ls9c_ard_3-2-1_103074_2023-07-23_final.stac-item
2023-07-26 09:33:03	ga_ls9c_ard_3-2-1_092086_2023-07-26_final.stac-item
2023-08-04 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-08-04_final.stac-item
2023-08-16 09:47:22	ga_ls9c_ard_3-2-1_095075_2023-08-16_final.stac-item
2023-08-16 09:48:58	ga_ls9c_ard_3-2-1_095079_2023-08-16_final.stac-item
2023-08-16 09:49:46	ga_ls9c_ard_3-2-1_095081_2023-08-16_final.stac-item
2023-10-26 11:36:05	ga_ls9c_ard_3-2-1_112083_2023-10-26_final.stac-item
2023-10-27 10:36:52	ga_ls9c_ard_3-2-1_103074_2023-10-27_final.stac-item
2023-10-30 11:09:19	ga_ls9c_ard_3-2-1_108078_2023-10-30_final.stac-item
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final.stac-item
2023-11-02 10:02:05	ga_ls9c_ard_3-2-1_097080_2023-11-02_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