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 10:01:58	ga_ls9c_ard_3-2-1_097074_2021-11-18_final.stac-item
2021-11-23 10:02:26	ga_ls9c_ard_3-2-1_098069_2021-11-23_final.stac-item
2021-11-23 10:02:50	ga_ls9c_ard_3-2-1_098070_2021-11-23_final.stac-item
2021-12-14 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-14_final.stac-item
2021-12-25 11:21:24	ga_ls9c_ard_3-2-1_110077_2021-12-25_final.stac-item
2021-12-30 10:01:51	ga_ls9c_ard_3-2-1_097079_2021-12-30_final.stac-item
2022-01-08 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-08_final.stac-item
2022-01-10 11:21:21	ga_ls9c_ard_3-2-1_110077_2022-01-10_final.stac-item
2022-01-12 11:10:35	ga_ls9c_ard_3-2-1_108081_2022-01-12_final.stac-item
2022-01-23 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-23_final.stac-item
2022-02-02 09:51:52	ga_ls9c_ard_3-2-1_095085_2022-02-02_final.stac-item
2022-02-10 10:39:17	ga_ls9c_ard_3-2-1_103080_2022-02-10_final.stac-item
2022-02-22 11:03:53	ga_ls9c_ard_3-2-1_107080_2022-02-22_final.stac-item
2022-03-01 11:10:22	ga_ls9c_ard_3-2-1_108081_2022-03-01_final.stac-item
2022-03-09 10:20:32	ga_ls9c_ard_3-2-1_100080_2022-03-09_final.stac-item
2022-03-09 10:21:19	ga_ls9c_ard_3-2-1_100082_2022-03-09_final.stac-item
2022-03-22 09:51:34	ga_ls9c_ard_3-2-1_095085_2022-03-22_final.stac-item
2022-03-24 09:34:48	ga_ls9c_ard_3-2-1_093074_2022-03-24_final.stac-item
2022-03-25 10:20:27	ga_ls9c_ard_3-2-1_100080_2022-03-25_final.stac-item
2022-04-09 11:13:14	ga_ls9c_ard_3-2-1_109073_2022-04-09_final.stac-item
2022-04-09 11:14:50	ga_ls9c_ard_3-2-1_109077_2022-04-09_final.stac-item
2022-04-23 09:51:21	ga_ls9c_ard_3-2-1_095085_2022-04-23_final.stac-item
2022-05-01 10:39:34	ga_ls9c_ard_3-2-1_103082_2022-05-01_final.stac-item
2022-05-05 11:51:19	ga_ls9c_ard_3-2-1_115076_2022-05-05_final.stac-item
2022-05-08 10:40:07	ga_ls9c_ard_3-2-1_104068_2022-05-08_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-19 10:23:48	ga_ls9c_ard_3-2-1_101074_2022-05-19_final.stac-item
2022-05-25 11:29:11	ga_ls9c_ard_3-2-1_111083_2022-05-25_final.stac-item
2022-05-28 10:20:00	ga_ls9c_ard_3-2-1_100080_2022-05-28_final.stac-item
2022-06-14 11:02:10	ga_ls9c_ard_3-2-1_107077_2022-06-14_final.stac-item
2022-06-23 10:57:49	ga_ls9c_ard_3-2-1_106081_2022-06-23_final.stac-item
2022-07-06 10:24:08	ga_ls9c_ard_3-2-1_101074_2022-07-06_final.stac-item
2022-07-22 10:24:12	ga_ls9c_ard_3-2-1_101074_2022-07-22_final.stac-item
2022-07-26 09:59:09	ga_ls9c_ard_3-2-1_097073_2022-07-26_final.stac-item
2022-07-27 10:46:01	ga_ls9c_ard_3-2-1_104082_2022-07-27_final.stac-item
2022-08-10 10:58:08	ga_ls9c_ard_3-2-1_106081_2022-08-10_final.stac-item
2022-08-15 11:17:07	ga_ls9c_ard_3-2-1_109082_2022-08-15_final.stac-item
2022-08-19 10:48:01	ga_ls9c_ard_3-2-1_105071_2022-08-19_final.stac-item
2022-08-22 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-08-22_final.stac-item
2022-08-23 10:24:31	ga_ls9c_ard_3-2-1_101074_2022-08-23_final.stac-item
2022-09-27 10:59:08	ga_ls9c_ard_3-2-1_106083_2022-09-27_final.stac-item
2022-09-28 10:02:43	ga_ls9c_ard_3-2-1_097081_2022-09-28_final.stac-item
2022-10-06 10:48:57	ga_ls9c_ard_3-2-1_105073_2022-10-06_final.stac-item
2022-10-07 11:35:24	ga_ls9c_ard_3-2-1_112081_2022-10-07_final.stac-item
2022-10-25 09:42:40	ga_ls9c_ard_3-2-1_094077_2022-10-25_final.stac-item
2022-11-02 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-11-02_final.stac-item
2023-02-13 10:39:31	ga_ls9c_ard_3-2-1_103080_2023-02-13_final.stac-item
2023-02-14 09:45:29	ga_ls9c_ard_3-2-1_094084_2023-02-14_final.stac-item
2023-02-16 11:08:47	ga_ls9c_ard_3-2-1_108076_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
2023-02-17 11:52:02	ga_ls9c_ard_3-2-1_115076_2023-02-17_final.stac-item
2023-02-20 10:43:11	ga_ls9c_ard_3-2-1_104074_2023-02-20_final.stac-item
2023-02-23 09:37:55	ga_ls9c_ard_3-2-1_093081_2023-02-23_final.stac-item
2023-03-09 11:29:49	ga_ls9c_ard_3-2-1_111083_2023-03-09_final.stac-item
2023-03-14 11:45:11	ga_ls9c_ard_3-2-1_114075_2023-03-14_final.stac-item
2023-03-15 10:48:45	ga_ls9c_ard_3-2-1_105073_2023-03-15_final.stac-item
2023-03-18 11:23:14	ga_ls9c_ard_3-2-1_110082_2023-03-18_final.stac-item
2023-03-20 09:30:47	ga_ls9c_ard_3-2-1_092079_2023-03-20_final.stac-item
2023-03-26 10:32:53	ga_ls9c_ard_3-2-1_102080_2023-03-26_final.stac-item
2023-04-04 10:25:50	ga_ls9c_ard_3-2-1_101078_2023-04-04_final.stac-item
2023-04-17 09:52:26	ga_ls9c_ard_3-2-1_096072_2023-04-17_final.stac-item
2023-04-17 09:53:14	ga_ls9c_ard_3-2-1_096074_2023-04-17_final.stac-item
2023-04-19 09:43:40	ga_ls9c_ard_3-2-1_094081_2023-04-19_final.stac-item
2023-04-20 10:23:44	ga_ls9c_ard_3-2-1_101073_2023-04-20_final.stac-item
2023-04-29 10:17:28	ga_ls9c_ard_3-2-1_100073_2023-04-29_final.stac-item
2023-05-02 10:51:06	ga_ls9c_ard_3-2-1_105080_2023-05-02_final.stac-item
2023-05-04 10:35:54	ga_ls9c_ard_3-2-1_103073_2023-05-04_final.stac-item
2023-05-05 11:22:21	ga_ls9c_ard_3-2-1_110081_2023-05-05_final.stac-item
2023-05-06 10:23:08	ga_ls9c_ard_3-2-1_101072_2023-05-06_final.stac-item
2023-05-07 09:31:30	ga_ls9c_ard_3-2-1_092082_2023-05-07_final.stac-item
2023-05-09 10:56:50	ga_ls9c_ard_3-2-1_106079_2023-05-09_final.stac-item
2023-05-09 10:57:38	ga_ls9c_ard_3-2-1_106081_2023-05-09_final.stac-item
2023-05-10 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-05-10_final.stac-item
2023-05-15 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-05-15_final.stac-item
2023-05-15 10:20:55	ga_ls9c_ard_3-2-1_100082_2023-05-15_final.stac-item
2023-05-15 11:58:12	ga_ls9c_ard_3-2-1_116078_2023-05-15_final.stac-item
2023-05-17 10:05:20	ga_ls9c_ard_3-2-1_098074_2023-05-17_final.stac-item
2023-05-20 10:35:48	ga_ls9c_ard_3-2-1_103073_2023-05-20_final.stac-item
2023-05-21 09:43:21	ga_ls9c_ard_3-2-1_094081_2023-05-21_final.stac-item
2023-07-11 11:51:11	ga_ls9c_ard_3-2-1_115076_2023-07-11_final.stac-item
2023-09-04 10:17:40	ga_ls9c_ard_3-2-1_100073_2023-09-04_final.stac-item
2023-09-05 09:24:51	ga_ls9c_ard_3-2-1_091080_2023-09-04_final.stac-item
2023-09-05 11:04:32	ga_ls9c_ard_3-2-1_107082_2023-09-05_final.stac-item
2023-09-07 09:14:31	ga_ls9c_ard_3-2-1_089085_2023-09-06_final.stac-item
2023-09-12 11:08:24	ga_ls9c_ard_3-2-1_108076_2023-09-12_final.stac-item
2023-09-16 10:42:06	ga_ls9c_ard_3-2-1_104072_2023-09-16_final.stac-item
2023-09-21 09:24:57	ga_ls9c_ard_3-2-1_091080_2023-09-20_final.stac-item
2023-09-21 11:04:14	ga_ls9c_ard_3-2-1_107081_2023-09-21_final.stac-item
2023-09-25 10:35:05	ga_ls9c_ard_3-2-1_103070_2023-09-25_final.stac-item
2023-09-25 10:36:40	ga_ls9c_ard_3-2-1_103074_2023-09-25_final.stac-item
2023-09-28 09:31:03	ga_ls9c_ard_3-2-1_092080_2023-09-28_final.stac-item
2023-09-30 09:20:19	ga_ls9c_ard_3-2-1_090084_2023-09-29_final.stac-item
2023-10-05 09:38:32	ga_ls9c_ard_3-2-1_093083_2023-10-05_final.stac-item
2023-10-07 09:28:35	ga_ls9c_ard_3-2-1_091089_2023-10-06_final.stac-item
2023-10-08 10:04:16	ga_ls9c_ard_3-2-1_098070_2023-10-08_final.stac-item
2023-10-10 09:51:57	ga_ls9c_ard_3-2-1_096070_2023-10-10_final.stac-item
2023-10-10 11:35:13	ga_ls9c_ard_3-2-1_112081_2023-10-10_final.stac-item
2023-10-11 10:35:37	ga_ls9c_ard_3-2-1_103071_2023-10-11_final.stac-item
2023-10-12 09:44:00	ga_ls9c_ard_3-2-1_094081_2023-10-12_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_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