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
2021-11-02 10:56:03	ga_ls9c_ard_3-2-1_106081_2021-11-02_final.stac-item
2021-11-03 09:53:46	ga_ls9c_ard_3-2-1_096072_2021-11-03_final.stac-item
2021-11-03 09:56:09	ga_ls9c_ard_3-2-1_096078_2021-11-03_final.stac-item
2021-11-05 09:38:13	ga_ls9c_ard_3-2-1_093080_2021-11-05_final.stac-item
2021-11-12 10:59:48	ga_ls9c_ard_3-2-1_106078_2021-11-12_final.stac-item
2021-11-15 09:43:57	ga_ls9c_ard_3-2-1_094082_2021-11-15_final.stac-item
2021-12-09 11:22:39	ga_ls9c_ard_3-2-1_110080_2021-12-09_final.stac-item
2022-01-17 09:49:27	ga_ls9c_ard_3-2-1_095079_2022-01-17_final.stac-item
2022-01-28 09:31:20	ga_ls9c_ard_3-2-1_092080_2022-01-28_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-02-20 11:17:04	ga_ls9c_ard_3-2-1_109082_2022-02-20_final.stac-item
2022-02-24 10:50:18	ga_ls9c_ard_3-2-1_105077_2022-02-24_final.stac-item
2022-02-25 09:52:40	ga_ls9c_ard_3-2-1_096072_2022-02-25_final.stac-item
2022-02-25 09:55:04	ga_ls9c_ard_3-2-1_096078_2022-02-25_final.stac-item
2022-02-26 10:36:19	ga_ls9c_ard_3-2-1_103073_2022-02-26_final.stac-item
2022-03-09 11:58:13	ga_ls9c_ard_3-2-1_116077_2022-03-09_final.stac-item
2022-03-29 09:52:32	ga_ls9c_ard_3-2-1_096072_2022-03-29_final.stac-item
2022-04-12 10:09:13	ga_ls9c_ard_3-2-1_098083_2022-04-12_final.stac-item
2022-04-20 09:18:28	ga_ls9c_ard_3-2-1_090080_2022-04-19_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-04-25 09:39:23	ga_ls9c_ard_3-2-1_093086_2022-04-25_final.stac-item
2022-05-25 09:49:30	ga_ls9c_ard_3-2-1_095081_2022-05-25_final.stac-item
2022-05-30 10:04:52	ga_ls9c_ard_3-2-1_098073_2022-05-30_final.stac-item
2022-06-12 09:40:00	ga_ls9c_ard_3-2-1_093088_2022-06-12_final.stac-item
2022-06-23 09:18:55	ga_ls9c_ard_3-2-1_090081_2022-06-22_final.stac-item
2022-06-28 09:37:31	ga_ls9c_ard_3-2-1_093081_2022-06-28_final.stac-item
2022-07-11 10:44:14	ga_ls9c_ard_3-2-1_104078_2022-07-11_final.stac-item
2022-07-16 11:03:58	ga_ls9c_ard_3-2-1_107081_2022-07-16_final.stac-item
2022-07-17 10:05:59	ga_ls9c_ard_3-2-1_098075_2022-07-17_final.stac-item
2022-07-19 09:54:51	ga_ls9c_ard_3-2-1_096078_2022-07-19_final.stac-item
2022-08-18 10:08:21	ga_ls9c_ard_3-2-1_098080_2022-08-18_final.stac-item
2022-08-23 10:24:55	ga_ls9c_ard_3-2-1_101075_2022-08-23_final.stac-item
2022-08-24 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-08-24_final.stac-item
2022-08-28 10:41:04	ga_ls9c_ard_3-2-1_104069_2022-08-28_final.stac-item
2022-08-29 09:50:14	ga_ls9c_ard_3-2-1_095081_2022-08-29_final.stac-item
2022-09-05 09:52:25	ga_ls9c_ard_3-2-1_096071_2022-09-05_final.stac-item
2022-09-09 09:35:16	ga_ls9c_ard_3-2-1_092090_2022-09-09_final.stac-item
2022-09-30 11:30:26	ga_ls9c_ard_3-2-1_111084_2022-09-30_final.stac-item
2022-10-17 10:30:07	ga_ls9c_ard_3-2-1_102072_2022-10-17_final.stac-item
2022-10-22 10:49:04	ga_ls9c_ard_3-2-1_105073_2022-10-22_final.stac-item
2022-10-24 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-10-24_final.stac-item
2022-11-06 10:06:58	ga_ls9c_ard_3-2-1_098076_2022-11-06_final.stac-item
2022-11-06 10:08:34	ga_ls9c_ard_3-2-1_098080_2022-11-06_final.stac-item
2022-11-08 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-11-08_final.stac-item
2022-11-14 09:18:46	ga_ls9c_ard_3-2-1_090079_2022-11-13_final.stac-item
2022-11-14 10:56:51	ga_ls9c_ard_3-2-1_106077_2022-11-14_final.stac-item
2022-11-18 10:34:08	ga_ls9c_ard_3-2-1_102082_2022-11-18_final.stac-item
2022-11-21 09:24:09	ga_ls9c_ard_3-2-1_091077_2022-11-20_final.stac-item
2022-11-21 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-11-21_final.stac-item
2022-11-24 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-11-24_final.stac-item
2022-11-30 10:56:48	ga_ls9c_ard_3-2-1_106077_2022-11-30_final.stac-item
2022-12-03 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-12-03_final.stac-item
2022-12-20 10:32:53	ga_ls9c_ard_3-2-1_102079_2022-12-20_final.stac-item
2022-12-21 11:13:44	ga_ls9c_ard_3-2-1_109073_2022-12-21_final.stac-item
2022-12-26 11:35:28	ga_ls9c_ard_3-2-1_112081_2022-12-26_final.stac-item
2022-12-28 11:21:56	ga_ls9c_ard_3-2-1_110078_2022-12-28_final.stac-item
2023-01-06 09:36:06	ga_ls9c_ard_3-2-1_093076_2023-01-06_final.stac-item
2023-01-10 10:51:02	ga_ls9c_ard_3-2-1_105078_2023-01-10_final.stac-item
2023-01-11 11:35:53	ga_ls9c_ard_3-2-1_112082_2023-01-11_final.stac-item
2023-01-18 11:40:46	ga_ls9c_ard_3-2-1_113079_2023-01-18_final.stac-item
2023-01-24 09:24:26	ga_ls9c_ard_3-2-1_091078_2023-01-23_final.stac-item
2023-01-24 11:01:19	ga_ls9c_ard_3-2-1_107073_2023-01-24_final.stac-item
2023-01-24 11:03:43	ga_ls9c_ard_3-2-1_107079_2023-01-24_final.stac-item
2023-01-24 11:04:31	ga_ls9c_ard_3-2-1_107081_2023-01-24_final.stac-item
2023-01-28 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-28_final.stac-item
2023-01-31 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-01-31_final.stac-item
2023-02-02 10:56:51	ga_ls9c_ard_3-2-1_106077_2023-02-02_final.stac-item
2023-02-08 10:21:00	ga_ls9c_ard_3-2-1_100080_2023-02-08_final.stac-item
2023-02-09 11:04:40	ga_ls9c_ard_3-2-1_107081_2023-02-09_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_2023-02-10_final.stac-item
2023-03-02 11:22:33	ga_ls9c_ard_3-2-1_110080_2023-03-02_final.stac-item
2023-03-08 10:42:11	ga_ls9c_ard_3-2-1_104072_2023-03-08_final.stac-item
2023-04-04 10:23:26	ga_ls9c_ard_3-2-1_101072_2023-04-04_final.stac-item
2023-04-21 09:32:30	ga_ls9c_ard_3-2-1_092084_2023-04-21_final.stac-item
2023-04-24 11:39:04	ga_ls9c_ard_3-2-1_113076_2023-04-24_final.stac-item
2023-04-30 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-04-30_final.stac-item
2023-04-30 11:03:54	ga_ls9c_ard_3-2-1_107081_2023-04-30_final.stac-item
2023-05-08 10:15:58	ga_ls9c_ard_3-2-1_099085_2023-05-08_final.stac-item
2023-05-09 10:57:14	ga_ls9c_ard_3-2-1_106080_2023-05-09_final.stac-item
2023-05-11 10:40:52	ga_ls9c_ard_3-2-1_104070_2023-05-11_final.stac-item
2023-05-18 10:52:10	ga_ls9c_ard_3-2-1_105083_2023-05-18_final.stac-item
2023-05-21 09:45:45	ga_ls9c_ard_3-2-1_094087_2023-05-21_final.stac-item
2023-05-28 11:28:45	ga_ls9c_ard_3-2-1_111082_2023-05-28_final.stac-item
2023-05-30 11:14:48	ga_ls9c_ard_3-2-1_109078_2023-05-30_final.stac-item
2023-06-02 10:06:00	ga_ls9c_ard_3-2-1_098076_2023-06-02_final.stac-item
2023-06-23 10:26:00	ga_ls9c_ard_3-2-1_101080_2023-06-23_final.stac-item
2023-06-24 11:04:52	ga_ls9c_ard_3-2-1_108069_2023-06-24_final.stac-item
2023-07-01 09:34:43	ga_ls9c_ard_3-2-1_093075_2023-07-01_final.stac-item
2023-07-18 10:20:54	ga_ls9c_ard_3-2-1_100082_2023-07-18_final.stac-item
2023-07-28 09:18:44	ga_ls9c_ard_3-2-1_090081_2023-07-27_final.stac-item
2023-07-28 10:54:01	ga_ls9c_ard_3-2-1_106072_2023-07-28_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-07-30 10:41:18	ga_ls9c_ard_3-2-1_104071_2023-07-30_final.stac-item
2023-08-04 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-08-04_final.stac-item
2023-08-10 10:22:27	ga_ls9c_ard_3-2-1_101070_2023-08-10_final.stac-item
2023-10-14 09:32:28	ga_ls9c_ard_3-2-1_092083_2023-10-14_final.stac-item
2023-10-30 09:31:38	ga_ls9c_ard_3-2-1_092081_2023-10-30_final.stac-item
2023-11-05 10:29:49	ga_ls9c_ard_3-2-1_102072_2023-11-05_final.stac-item
2023-11-05 10:31:00	ga_ls9c_ard_3-2-1_102075_2023-11-05_final.stac-item
2023-11-29 11:23:01	ga_ls9c_ard_3-2-1_110081_2023-11-29_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