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
2021-11-20 09:45:36	ga_ls9c_ard_3-2-1_094080_2021-11-20_final.stac-item
2021-12-11 09:31:47	ga_ls9c_ard_3-2-1_092081_2021-12-11_final.stac-item
2021-12-12 10:16:38	ga_ls9c_ard_3-2-1_099085_2021-12-12_final.stac-item
2021-12-14 10:01:51	ga_ls9c_ard_3-2-1_097079_2021-12-14_final.stac-item
2021-12-20 11:00:51	ga_ls9c_ard_3-2-1_107072_2021-12-20_final.stac-item
2021-12-24 10:38:32	ga_ls9c_ard_3-2-1_103078_2021-12-24_final.stac-item
2021-12-25 11:24:35	ga_ls9c_ard_3-2-1_110085_2021-12-25_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-20 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-01-20_final.stac-item
2022-01-21 09:27:08	ga_ls9c_ard_3-2-1_091085_2022-01-20_final.stac-item
2022-02-03 10:31:08	ga_ls9c_ard_3-2-1_102075_2022-02-03_final.stac-item
2022-02-08 09:12:46	ga_ls9c_ard_3-2-1_089080_2022-02-07_final.stac-item
2022-02-15 09:19:42	ga_ls9c_ard_3-2-1_090082_2022-02-14_final.stac-item
2022-02-18 09:50:58	ga_ls9c_ard_3-2-1_095083_2022-02-18_final.stac-item
2022-02-25 09:57:51	ga_ls9c_ard_3-2-1_096085_2022-02-25_final.stac-item
2022-03-05 10:44:03	ga_ls9c_ard_3-2-1_104077_2022-03-05_final.stac-item
2022-03-23 10:30:50	ga_ls9c_ard_3-2-1_102075_2022-03-23_final.stac-item
2022-03-29 11:32:36	ga_ls9c_ard_3-2-1_112075_2022-03-29_final.stac-item
2022-04-21 11:38:12	ga_ls9c_ard_3-2-1_113074_2022-04-21_final.stac-item
2022-05-07 09:58:27	ga_ls9c_ard_3-2-1_097072_2022-05-07_final.stac-item
2022-05-15 09:12:54	ga_ls9c_ard_3-2-1_089082_2022-05-14_final.stac-item
2022-05-18 09:45:45	ga_ls9c_ard_3-2-1_094087_2022-05-18_final.stac-item
2022-05-21 11:51:31	ga_ls9c_ard_3-2-1_115077_2022-05-21_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-05-29 11:04:52	ga_ls9c_ard_3-2-1_107084_2022-05-29_final.stac-item
2022-06-09 09:07:04	ga_ls9c_ard_3-2-1_088083_2022-06-08_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-06-24 11:40:42	ga_ls9c_ard_3-2-1_113080_2022-06-24_final.stac-item
2022-07-01 11:46:30	ga_ls9c_ard_3-2-1_114079_2022-07-01_final.stac-item
2022-07-09 09:20:08	ga_ls9c_ard_3-2-1_090084_2022-07-08_final.stac-item
2022-07-10 11:41:28	ga_ls9c_ard_3-2-1_113082_2022-07-10_final.stac-item
2022-07-21 11:20:13	ga_ls9c_ard_3-2-1_110075_2022-07-21_final.stac-item
2022-08-24 09:31:41	ga_ls9c_ard_3-2-1_092081_2022-08-24_final.stac-item
2022-08-25 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-08-25_final.stac-item
2022-08-25 10:15:45	ga_ls9c_ard_3-2-1_099083_2022-08-25_final.stac-item
2022-09-03 10:10:22	ga_ls9c_ard_3-2-1_098085_2022-09-03_final.stac-item
2022-09-07 11:20:08	ga_ls9c_ard_3-2-1_110074_2022-09-07_final.stac-item
2022-09-11 10:54:14	ga_ls9c_ard_3-2-1_106071_2022-09-11_final.stac-item
2022-09-20 10:46:32	ga_ls9c_ard_3-2-1_105067_2022-09-20_final.stac-item
2022-09-27 09:23:03	ga_ls9c_ard_3-2-1_090090_2022-09-26_final.stac-item
2022-10-05 11:46:34	ga_ls9c_ard_3-2-1_114078_2022-10-05_final.stac-item
2022-10-30 09:57:12	ga_ls9c_ard_3-2-1_097067_2022-10-30_final.stac-item
2022-11-02 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-11-02_final.stac-item
2022-11-10 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-11-10_final.stac-item
2022-12-02 10:40:50	ga_ls9c_ard_3-2-1_104068_2022-12-02_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-17 11:41:41	ga_ls9c_ard_3-2-1_113081_2022-12-17_final.stac-item
2022-12-20 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-20_final.stac-item
2022-12-23 09:26:04	ga_ls9c_ard_3-2-1_091082_2022-12-22_final.stac-item
2022-12-26 09:55:23	ga_ls9c_ard_3-2-1_096078_2022-12-26_final.stac-item
2022-12-31 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-31_final.stac-item
2023-01-10 09:13:45	ga_ls9c_ard_3-2-1_089082_2023-01-09_final.stac-item
2023-01-15 09:34:38	ga_ls9c_ard_3-2-1_092088_2023-01-15_final.stac-item
2023-01-15 11:11:31	ga_ls9c_ard_3-2-1_108083_2023-01-15_final.stac-item
2023-01-19 10:43:32	ga_ls9c_ard_3-2-1_104075_2023-01-19_final.stac-item
2023-02-06 10:34:10	ga_ls9c_ard_3-2-1_102082_2023-02-06_final.stac-item
2023-02-18 10:59:11	ga_ls9c_ard_3-2-1_106083_2023-02-18_final.stac-item
2023-02-23 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-02-23_final.stac-item
2023-02-25 11:02:02	ga_ls9c_ard_3-2-1_107075_2023-02-25_final.stac-item
2023-03-04 11:06:59	ga_ls9c_ard_3-2-1_108072_2023-03-04_final.stac-item
2023-03-07 11:41:26	ga_ls9c_ard_3-2-1_113081_2023-03-07_final.stac-item
2023-03-15 09:11:28	ga_ls9c_ard_3-2-1_089077_2023-03-14_final.stac-item
2023-03-18 11:19:39	ga_ls9c_ard_3-2-1_110073_2023-03-18_final.stac-item
2023-04-03 09:41:23	ga_ls9c_ard_3-2-1_094075_2023-04-03_final.stac-item
2023-04-12 09:34:20	ga_ls9c_ard_3-2-1_093073_2023-04-12_final.stac-item
2023-04-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2023-04-23_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-05-02 10:46:19	ga_ls9c_ard_3-2-1_105068_2023-05-02_final.stac-item
2023-05-05 11:18:45	ga_ls9c_ard_3-2-1_110072_2023-05-05_final.stac-item
2023-05-09 10:52:50	ga_ls9c_ard_3-2-1_106069_2023-05-09_final.stac-item
2023-05-09 10:53:38	ga_ls9c_ard_3-2-1_106071_2023-05-09_final.stac-item
2023-05-23 11:05:27	ga_ls9c_ard_3-2-1_108070_2023-05-23_final.stac-item
2023-05-25 09:20:10	ga_ls9c_ard_3-2-1_090085_2023-05-24_final.stac-item
2023-06-17 09:22:12	ga_ls9c_ard_3-2-1_091075_2023-06-16_final.stac-item
2023-06-19 09:13:26	ga_ls9c_ard_3-2-1_089084_2023-06-18_final.stac-item
2023-07-05 09:13:14	ga_ls9c_ard_3-2-1_089083_2023-07-04_final.stac-item
2023-07-10 09:28:38	ga_ls9c_ard_3-2-1_092075_2023-07-09_final.stac-item
2023-07-13 09:59:09	ga_ls9c_ard_3-2-1_097074_2023-07-13_final.stac-item
2023-07-13 10:01:33	ga_ls9c_ard_3-2-1_097080_2023-07-13_final.stac-item
2023-07-13 11:37:15	ga_ls9c_ard_3-2-1_113072_2023-07-13_final.stac-item
2023-07-17 09:36:03	ga_ls9c_ard_3-2-1_093078_2023-07-17_final.stac-item
2023-07-19 09:26:29	ga_ls9c_ard_3-2-1_091085_2023-07-18_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-07-26 09:28:39	ga_ls9c_ard_3-2-1_092075_2023-07-25_final.stac-item
2023-08-15 10:45:47	ga_ls9c_ard_3-2-1_104082_2023-08-15_final.stac-item
2023-09-05 09:24:28	ga_ls9c_ard_3-2-1_091079_2023-09-04_final.stac-item
2023-09-05 09:26:51	ga_ls9c_ard_3-2-1_091085_2023-09-04_final.stac-item
2023-09-09 10:38:16	ga_ls9c_ard_3-2-1_103078_2023-09-09_final.stac-item
2023-09-14 10:55:15	ga_ls9c_ard_3-2-1_106074_2023-09-14_final.stac-item
2023-09-21 10:59:50	ga_ls9c_ard_3-2-1_107070_2023-09-21_final.stac-item
2023-09-30 09:20:43	ga_ls9c_ard_3-2-1_090085_2023-09-29_final.stac-item
2023-10-17 10:04:12	ga_ls9c_ard_3-2-1_097085_2023-10-17_final.stac-item
2023-10-19 09:47:51	ga_ls9c_ard_3-2-1_095075_2023-10-19_final.stac-item
2023-10-21 11:17:10	ga_ls9c_ard_3-2-1_109082_2023-10-21_final.stac-item
2023-10-27 10:34:28	ga_ls9c_ard_3-2-1_103068_2023-10-27_final.stac-item
2023-11-21 10:29:07	ga_ls9c_ard_3-2-1_102070_2023-11-21_final.stac-item
2023-11-22 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-11-22_final.stac-item
2023-11-25 11:46:08	ga_ls9c_ard_3-2-1_114077_2023-11-25_final.stac-item
2023-12-06 11:23:56	ga_ls9c_ard_3-2-1_111068_2023-12-06_final.stac-item
2023-12-06 11:27:55	ga_ls9c_ard_3-2-1_111078_2023-12-06_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