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
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final.stac-item
2022-01-05 09:26:45	ga_ls9c_ard_3-2-1_091084_2022-01-04_final.stac-item
2022-01-12 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-01-12_final.stac-item
2022-02-09 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-02-09_final.stac-item
2022-03-11 10:03:23	ga_ls9c_ard_3-2-1_098068_2022-03-11_final.stac-item
2022-03-24 09:34:48	ga_ls9c_ard_3-2-1_093074_2022-03-24_final.stac-item
2022-04-06 10:41:57	ga_ls9c_ard_3-2-1_104072_2022-04-06_final.stac-item
2022-04-08 10:29:59	ga_ls9c_ard_3-2-1_102073_2022-04-08_final.stac-item
2022-04-30 09:51:56	ga_ls9c_ard_3-2-1_096071_2022-04-30_final.stac-item
2022-05-23 10:02:40	ga_ls9c_ard_3-2-1_097083_2022-05-23_final.stac-item
2022-05-27 09:34:21	ga_ls9c_ard_3-2-1_093074_2022-05-27_final.stac-item
2022-05-31 10:48:08	ga_ls9c_ard_3-2-1_105073_2022-05-31_final.stac-item
2022-06-05 09:30:35	ga_ls9c_ard_3-2-1_092080_2022-06-05_final.stac-item
2022-06-12 09:34:25	ga_ls9c_ard_3-2-1_093074_2022-06-12_final.stac-item
2022-06-15 10:07:45	ga_ls9c_ard_3-2-1_098080_2022-06-15_final.stac-item
2022-07-14 11:11:56	ga_ls9c_ard_3-2-1_109070_2022-07-14_final.stac-item
2022-07-15 10:21:05	ga_ls9c_ard_3-2-1_100082_2022-07-15_final.stac-item
2022-07-26 09:58:21	ga_ls9c_ard_3-2-1_097071_2022-07-26_final.stac-item
2022-07-26 11:41:37	ga_ls9c_ard_3-2-1_113082_2022-07-26_final.stac-item
2022-08-10 10:54:57	ga_ls9c_ard_3-2-1_106073_2022-08-10_final.stac-item
2022-08-16 10:17:30	ga_ls9c_ard_3-2-1_100072_2022-08-16_final.stac-item
2022-08-24 09:29:41	ga_ls9c_ard_3-2-1_092076_2022-08-23_final.stac-item
2022-09-01 10:18:20	ga_ls9c_ard_3-2-1_100074_2022-09-01_final.stac-item
2022-09-02 11:01:36	ga_ls9c_ard_3-2-1_107074_2022-09-02_final.stac-item
2022-10-04 11:01:43	ga_ls9c_ard_3-2-1_107074_2022-10-04_final.stac-item
2022-10-18 09:35:41	ga_ls9c_ard_3-2-1_093075_2022-10-18_final.stac-item
2022-10-30 11:40:53	ga_ls9c_ard_3-2-1_113079_2022-10-30_final.stac-item
2022-11-01 09:46:26	ga_ls9c_ard_3-2-1_095071_2022-11-01_final.stac-item
2022-11-07 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-11-06_final.stac-item
2022-11-07 10:47:50	ga_ls9c_ard_3-2-1_105070_2022-11-07_final.stac-item
2022-11-12 11:08:01	ga_ls9c_ard_3-2-1_108074_2022-11-12_final.stac-item
2022-11-19 09:36:54	ga_ls9c_ard_3-2-1_093078_2022-11-19_final.stac-item
2022-11-22 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-11-22_final.stac-item
2022-12-01 09:59:58	ga_ls9c_ard_3-2-1_097074_2022-12-01_final.stac-item
2022-12-04 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-04_final.stac-item
2022-12-10 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-12-10_final.stac-item
2022-12-17 09:59:36	ga_ls9c_ard_3-2-1_097073_2022-12-17_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2022-12-23 11:01:21	ga_ls9c_ard_3-2-1_107073_2022-12-23_final.stac-item
2022-12-25 09:13:43	ga_ls9c_ard_3-2-1_089082_2022-12-24_final.stac-item
2023-01-02 11:40:30	ga_ls9c_ard_3-2-1_113078_2023-01-02_final.stac-item
2023-01-08 09:24:32	ga_ls9c_ard_3-2-1_091078_2023-01-07_final.stac-item
2023-01-17 09:18:39	ga_ls9c_ard_3-2-1_090079_2023-01-16_final.stac-item
2023-01-19 10:43:56	ga_ls9c_ard_3-2-1_104076_2023-01-19_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-22 09:33:57	ga_ls9c_ard_3-2-1_093071_2023-01-22_final.stac-item
2023-01-22 09:39:08	ga_ls9c_ard_3-2-1_093084_2023-01-22_final.stac-item
2023-01-29 11:19:32	ga_ls9c_ard_3-2-1_110072_2023-01-29_final.stac-item
2023-02-05 11:29:23	ga_ls9c_ard_3-2-1_111081_2023-02-05_final.stac-item
2023-02-07 09:36:09	ga_ls9c_ard_3-2-1_093076_2023-02-07_final.stac-item
2023-02-07 09:40:08	ga_ls9c_ard_3-2-1_093086_2023-02-07_final.stac-item
2023-02-10 10:07:27	ga_ls9c_ard_3-2-1_098077_2023-02-10_final.stac-item
2023-02-10 10:08:15	ga_ls9c_ard_3-2-1_098079_2023-02-10_final.stac-item
2023-02-10 11:45:56	ga_ls9c_ard_3-2-1_114076_2023-02-10_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-05-01 10:06:16	ga_ls9c_ard_3-2-1_098076_2023-05-01_final.stac-item
2023-05-02 09:13:25	ga_ls9c_ard_3-2-1_089083_2023-05-01_final.stac-item
2023-05-06 10:25:08	ga_ls9c_ard_3-2-1_101077_2023-05-06_final.stac-item
2023-05-07 11:06:00	ga_ls9c_ard_3-2-1_108071_2023-05-07_final.stac-item
2023-05-08 10:11:10	ga_ls9c_ard_3-2-1_099073_2023-05-08_final.stac-item
2023-05-09 10:53:38	ga_ls9c_ard_3-2-1_106071_2023-05-09_final.stac-item
2023-05-11 10:42:52	ga_ls9c_ard_3-2-1_104075_2023-05-11_final.stac-item
2023-05-13 10:28:06	ga_ls9c_ard_3-2-1_102069_2023-05-13_final.stac-item
2023-06-26 09:20:49	ga_ls9c_ard_3-2-1_090087_2023-06-25_final.stac-item
2023-06-26 10:53:19	ga_ls9c_ard_3-2-1_106071_2023-06-26_final.stac-item
2023-06-27 09:58:07	ga_ls9c_ard_3-2-1_097072_2023-06-27_final.stac-item
2023-06-27 11:37:48	ga_ls9c_ard_3-2-1_113074_2023-06-27_final.stac-item
2023-06-28 10:41:25	ga_ls9c_ard_3-2-1_104072_2023-06-28_final.stac-item
2023-06-29 09:49:25	ga_ls9c_ard_3-2-1_095081_2023-06-29_final.stac-item
2023-06-29 09:50:13	ga_ls9c_ard_3-2-1_095083_2023-06-29_final.stac-item
2023-07-01 09:37:30	ga_ls9c_ard_3-2-1_093082_2023-07-01_final.stac-item
2023-07-17 11:16:31	ga_ls9c_ard_3-2-1_109082_2023-07-17_final.stac-item
2023-07-25 10:25:03	ga_ls9c_ard_3-2-1_101077_2023-07-25_final.stac-item
2023-07-28 09:18:44	ga_ls9c_ard_3-2-1_090081_2023-07-27_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-07-29 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-07-29_final.stac-item
2023-07-29 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-07-29_final.stac-item
2023-08-02 11:12:14	ga_ls9c_ard_3-2-1_109071_2023-08-02_final.stac-item
2023-08-05 10:06:17	ga_ls9c_ard_3-2-1_098076_2023-08-05_final.stac-item
2023-10-16 09:18:08	ga_ls9c_ard_3-2-1_090078_2023-10-15_final.stac-item
2023-10-16 10:58:37	ga_ls9c_ard_3-2-1_106082_2023-10-16_final.stac-item
2023-10-22 10:17:33	ga_ls9c_ard_3-2-1_100072_2023-10-22_final.stac-item
2023-10-22 10:22:20	ga_ls9c_ard_3-2-1_100084_2023-10-22_final.stac-item
2023-10-23 11:01:36	ga_ls9c_ard_3-2-1_107074_2023-10-23_final.stac-item
2023-10-24 10:07:59	ga_ls9c_ard_3-2-1_098079_2023-10-24_final.stac-item
2023-10-24 11:46:04	ga_ls9c_ard_3-2-1_114077_2023-10-24_final.stac-item
2023-10-28 09:40:50	ga_ls9c_ard_3-2-1_094073_2023-10-28_final.stac-item
2023-10-31 11:52:58	ga_ls9c_ard_3-2-1_115079_2023-10-31_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-02 11:39:46	ga_ls9c_ard_3-2-1_113077_2023-11-02_final.stac-item
2023-11-03 10:42:08	ga_ls9c_ard_3-2-1_104072_2023-11-03_final.stac-item
2023-11-17 09:20:29	ga_ls9c_ard_3-2-1_090084_2023-11-16_final.stac-item
2023-11-18 09:58:34	ga_ls9c_ard_3-2-1_097071_2023-11-18_final.stac-item
2023-11-18 09:58:58	ga_ls9c_ard_3-2-1_097072_2023-11-18_final.stac-item
2023-11-18 09:59:22	ga_ls9c_ard_3-2-1_097073_2023-11-18_final.stac-item
2023-11-18 10:02:34	ga_ls9c_ard_3-2-1_097081_2023-11-18_final.stac-item
2023-11-18 11:39:51	ga_ls9c_ard_3-2-1_113077_2023-11-18_final.stac-item
2023-11-18 11:42:15	ga_ls9c_ard_3-2-1_113083_2023-11-18_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