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
2021-11-15 11:17:50	ga_ls9c_ard_3-2-1_110070_2021-11-15_final.stac-item
2021-11-18 10:01:10	ga_ls9c_ard_3-2-1_097072_2021-11-18_final.stac-item
2021-11-22 09:29:38	ga_ls9c_ard_3-2-1_091087_2021-11-21_final.stac-item
2021-12-06 09:10:55	ga_ls9c_ard_3-2-1_089075_2021-12-05_final.stac-item
2021-12-06 09:15:18	ga_ls9c_ard_3-2-1_089086_2021-12-05_final.stac-item
2021-12-06 10:49:00	ga_ls9c_ard_3-2-1_105073_2021-12-06_final.stac-item
2021-12-17 10:30:44	ga_ls9c_ard_3-2-1_102074_2021-12-17_final.stac-item
2021-12-20 09:26:45	ga_ls9c_ard_3-2-1_091084_2021-12-19_final.stac-item
2021-12-23 09:52:28	ga_ls9c_ard_3-2-1_096071_2021-12-23_final.stac-item
2021-12-29 09:18:11	ga_ls9c_ard_3-2-1_090078_2021-12-28_final.stac-item
2021-12-29 10:55:28	ga_ls9c_ard_3-2-1_106074_2021-12-29_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-01-29 10:13:48	ga_ls9c_ard_3-2-1_099078_2022-01-29_final.stac-item
2022-02-08 09:14:22	ga_ls9c_ard_3-2-1_089084_2022-02-07_final.stac-item
2022-02-08 10:49:15	ga_ls9c_ard_3-2-1_105074_2022-02-08_final.stac-item
2022-02-09 11:36:06	ga_ls9c_ard_3-2-1_112083_2022-02-09_final.stac-item
2022-02-13 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-02-13_final.stac-item
2022-03-03 10:54:00	ga_ls9c_ard_3-2-1_106071_2022-03-03_final.stac-item
2022-03-12 10:47:26	ga_ls9c_ard_3-2-1_105070_2022-03-12_final.stac-item
2022-03-26 09:28:49	ga_ls9c_ard_3-2-1_091090_2022-03-25_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-03-31 11:19:27	ga_ls9c_ard_3-2-1_110073_2022-03-31_final.stac-item
2022-04-01 10:22:38	ga_ls9c_ard_3-2-1_101070_2022-04-01_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-13 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-04-13_final.stac-item
2022-04-15 10:35:42	ga_ls9c_ard_3-2-1_103072_2022-04-15_final.stac-item
2022-04-17 10:27:42	ga_ls9c_ard_3-2-1_101083_2022-04-17_final.stac-item
2022-04-18 11:07:21	ga_ls9c_ard_3-2-1_108074_2022-04-18_final.stac-item
2022-04-22 09:06:05	ga_ls9c_ard_3-2-1_088080_2022-04-21_final.stac-item
2022-04-30 09:56:19	ga_ls9c_ard_3-2-1_096082_2022-04-30_final.stac-item
2022-05-02 11:18:03	ga_ls9c_ard_3-2-1_110070_2022-05-02_final.stac-item
2022-05-10 10:28:08	ga_ls9c_ard_3-2-1_102069_2022-05-10_final.stac-item
2022-06-03 11:17:50	ga_ls9c_ard_3-2-1_110070_2022-06-03_final.stac-item
2022-06-19 11:22:48	ga_ls9c_ard_3-2-1_110082_2022-06-19_final.stac-item
2022-07-03 11:36:07	ga_ls9c_ard_3-2-1_112084_2022-07-03_final.stac-item
2022-07-17 10:07:10	ga_ls9c_ard_3-2-1_098078_2022-07-17_final.stac-item
2022-07-17 11:46:28	ga_ls9c_ard_3-2-1_114079_2022-07-17_final.stac-item
2022-07-26 10:03:32	ga_ls9c_ard_3-2-1_097084_2022-07-26_final.stac-item
2022-07-28 09:51:12	ga_ls9c_ard_3-2-1_095084_2022-07-28_final.stac-item
2022-08-09 11:52:57	ga_ls9c_ard_3-2-1_115079_2022-08-09_final.stac-item
2022-08-10 10:58:32	ga_ls9c_ard_3-2-1_106082_2022-08-10_final.stac-item
2022-08-13 09:50:35	ga_ls9c_ard_3-2-1_095082_2022-08-13_final.stac-item
2022-08-16 10:17:06	ga_ls9c_ard_3-2-1_100071_2022-08-16_final.stac-item
2022-08-22 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-08-22_final.stac-item
2022-09-16 09:37:32	ga_ls9c_ard_3-2-1_093080_2022-09-16_final.stac-item
2022-09-18 11:02:29	ga_ls9c_ard_3-2-1_107076_2022-09-18_final.stac-item
2022-09-25 09:32:12	ga_ls9c_ard_3-2-1_092082_2022-09-25_final.stac-item
2022-10-10 10:25:52	ga_ls9c_ard_3-2-1_101077_2022-10-10_final.stac-item
2022-10-14 10:00:47	ga_ls9c_ard_3-2-1_097076_2022-10-14_final.stac-item
2022-10-14 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-14_final.stac-item
2022-10-15 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-10-15_final.stac-item
2022-10-21 10:09:47	ga_ls9c_ard_3-2-1_098083_2022-10-21_final.stac-item
2022-10-28 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-10-28_final.stac-item
2022-10-29 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-10-29_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-11-03 09:38:26	ga_ls9c_ard_3-2-1_093082_2022-11-03_final.stac-item
2022-11-05 11:04:34	ga_ls9c_ard_3-2-1_107081_2022-11-05_final.stac-item
2022-11-08 09:58:37	ga_ls9c_ard_3-2-1_096086_2022-11-08_final.stac-item
2022-11-12 11:11:12	ga_ls9c_ard_3-2-1_108082_2022-11-12_final.stac-item
2022-11-16 10:46:29	ga_ls9c_ard_3-2-1_104082_2022-11-16_final.stac-item
2022-11-21 11:05:25	ga_ls9c_ard_3-2-1_107083_2022-11-21_final.stac-item
2022-11-26 09:46:39	ga_ls9c_ard_3-2-1_094087_2022-11-26_final.stac-item
2022-11-30 09:20:18	ga_ls9c_ard_3-2-1_090083_2022-11-29_final.stac-item
2022-11-30 10:53:12	ga_ls9c_ard_3-2-1_106068_2022-11-30_final.stac-item
2022-12-19 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-12-19_final.stac-item
2022-12-23 09:26:28	ga_ls9c_ard_3-2-1_091083_2022-12-22_final.stac-item
2022-12-24 10:10:07	ga_ls9c_ard_3-2-1_098084_2022-12-24_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2022-12-31 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-12-31_final.stac-item
2023-01-02 11:42:29	ga_ls9c_ard_3-2-1_113083_2023-01-02_final.stac-item
2023-01-03 10:41:41	ga_ls9c_ard_3-2-1_104070_2023-01-03_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-15 09:28:15	ga_ls9c_ard_3-2-1_092072_2023-01-14_final.stac-item
2023-01-24 09:26:25	ga_ls9c_ard_3-2-1_091083_2023-01-23_final.stac-item
2023-01-24 09:29:13	ga_ls9c_ard_3-2-1_091090_2023-01-23_final.stac-item
2023-01-27 09:53:23	ga_ls9c_ard_3-2-1_096073_2023-01-27_final.stac-item
2023-01-31 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-01-31_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-03-08 10:41:24	ga_ls9c_ard_3-2-1_104070_2023-03-08_final.stac-item
2023-03-14 10:09:29	ga_ls9c_ard_3-2-1_098083_2023-03-14_final.stac-item
2023-03-16 11:32:01	ga_ls9c_ard_3-2-1_112073_2023-03-16_final.stac-item
2023-03-27 11:16:56	ga_ls9c_ard_3-2-1_109082_2023-03-27_final.stac-item
2023-04-03 11:17:52	ga_ls9c_ard_3-2-1_110069_2023-04-03_final.stac-item
2023-04-10 09:46:19	ga_ls9c_ard_3-2-1_095072_2023-04-10_final.stac-item
2023-04-15 10:03:35	ga_ls9c_ard_3-2-1_098069_2023-04-15_final.stac-item
2023-04-30 11:03:54	ga_ls9c_ard_3-2-1_107081_2023-04-30_final.stac-item
2023-05-19 09:57:20	ga_ls9c_ard_3-2-1_096085_2023-05-19_final.stac-item
2023-05-21 09:44:57	ga_ls9c_ard_3-2-1_094085_2023-05-21_final.stac-item
2023-06-02 10:07:12	ga_ls9c_ard_3-2-1_098079_2023-06-02_final.stac-item
2023-06-04 09:54:26	ga_ls9c_ard_3-2-1_096078_2023-06-04_final.stac-item
2023-06-08 09:32:04	ga_ls9c_ard_3-2-1_092084_2023-06-08_final.stac-item
2023-07-06 09:51:19	ga_ls9c_ard_3-2-1_096070_2023-07-06_final.stac-item
2023-07-19 09:22:05	ga_ls9c_ard_3-2-1_091074_2023-07-18_final.stac-item
2023-07-26 11:09:32	ga_ls9c_ard_3-2-1_108080_2023-07-26_final.stac-item
2023-08-09 11:23:40	ga_ls9c_ard_3-2-1_110084_2023-08-09_final.stac-item
2023-08-10 10:26:51	ga_ls9c_ard_3-2-1_101081_2023-08-10_final.stac-item
2023-08-18 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-08-18_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-11-03 09:06:27	ga_ls9c_ard_3-2-1_088080_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