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 09:42:21	ga_ls9c_ard_3-2-1_094078_2021-11-15_final.stac-item
2021-11-17 09:26:04	ga_ls9c_ard_3-2-1_091084_2021-11-16_final.stac-item
2021-12-07 09:54:34	ga_ls9c_ard_3-2-1_096076_2021-12-07_final.stac-item
2021-12-09 09:42:59	ga_ls9c_ard_3-2-1_094078_2021-12-09_final.stac-item
2021-12-30 11:40:44	ga_ls9c_ard_3-2-1_113079_2021-12-30_final.stac-item
2022-01-03 09:38:19	ga_ls9c_ard_3-2-1_093082_2022-01-03_final.stac-item
2022-01-04 10:21:10	ga_ls9c_ard_3-2-1_100081_2022-01-04_final.stac-item
2022-01-12 09:35:17	ga_ls9c_ard_3-2-1_092090_2022-01-12_final.stac-item
2022-01-18 10:33:30	ga_ls9c_ard_3-2-1_102081_2022-01-18_final.stac-item
2022-02-23 10:08:39	ga_ls9c_ard_3-2-1_098081_2022-02-23_final.stac-item
2022-03-05 10:41:15	ga_ls9c_ard_3-2-1_104070_2022-03-05_final.stac-item
2022-03-06 09:48:49	ga_ls9c_ard_3-2-1_095078_2022-03-06_final.stac-item
2022-03-20 10:02:45	ga_ls9c_ard_3-2-1_097082_2022-03-20_final.stac-item
2022-03-27 10:08:52	ga_ls9c_ard_3-2-1_098082_2022-03-27_final.stac-item
2022-04-01 10:22:38	ga_ls9c_ard_3-2-1_101070_2022-04-01_final.stac-item
2022-04-05 10:02:41	ga_ls9c_ard_3-2-1_097082_2022-04-05_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 10:32:23	ga_ls9c_ard_3-2-1_102079_2022-04-08_final.stac-item
2022-04-22 10:41:23	ga_ls9c_ard_3-2-1_104071_2022-04-22_final.stac-item
2022-04-22 10:41:46	ga_ls9c_ard_3-2-1_104072_2022-04-22_final.stac-item
2022-05-08 10:43:42	ga_ls9c_ard_3-2-1_104077_2022-05-08_final.stac-item
2022-06-08 09:59:30	ga_ls9c_ard_3-2-1_097075_2022-06-08_final.stac-item
2022-06-10 09:48:44	ga_ls9c_ard_3-2-1_095079_2022-06-10_final.stac-item
2022-06-24 11:38:43	ga_ls9c_ard_3-2-1_113075_2022-06-24_final.stac-item
2022-07-07 11:08:35	ga_ls9c_ard_3-2-1_108077_2022-07-07_final.stac-item
2022-07-11 10:42:39	ga_ls9c_ard_3-2-1_104074_2022-07-11_final.stac-item
2022-07-25 10:56:45	ga_ls9c_ard_3-2-1_106078_2022-07-25_final.stac-item
2022-08-01 09:24:08	ga_ls9c_ard_3-2-1_091078_2022-07-31_final.stac-item
2022-08-06 09:42:44	ga_ls9c_ard_3-2-1_094078_2022-08-06_final.stac-item
2022-08-27 11:39:53	ga_ls9c_ard_3-2-1_113077_2022-08-27_final.stac-item
2022-09-03 10:08:46	ga_ls9c_ard_3-2-1_098081_2022-09-03_final.stac-item
2022-09-11 10:57:02	ga_ls9c_ard_3-2-1_106078_2022-09-11_final.stac-item
2022-09-21 09:54:55	ga_ls9c_ard_3-2-1_096077_2022-09-21_final.stac-item
2022-09-28 09:59:55	ga_ls9c_ard_3-2-1_097074_2022-09-28_final.stac-item
2022-10-07 11:34:13	ga_ls9c_ard_3-2-1_112078_2022-10-07_final.stac-item
2022-10-14 11:40:52	ga_ls9c_ard_3-2-1_113079_2022-10-14_final.stac-item
2022-10-22 10:51:03	ga_ls9c_ard_3-2-1_105078_2022-10-22_final.stac-item
2022-10-25 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-10-25_final.stac-item
2022-10-31 10:42:03	ga_ls9c_ard_3-2-1_104071_2022-10-31_final.stac-item
2022-11-01 09:49:13	ga_ls9c_ard_3-2-1_095078_2022-11-01_final.stac-item
2022-11-04 11:58:35	ga_ls9c_ard_3-2-1_116077_2022-11-04_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-17 09:52:04	ga_ls9c_ard_3-2-1_095085_2022-11-17_final.stac-item
2022-11-25 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-25_final.stac-item
2022-11-26 09:43:04	ga_ls9c_ard_3-2-1_094078_2022-11-26_final.stac-item
2023-01-15 11:09:32	ga_ls9c_ard_3-2-1_108078_2023-01-15_final.stac-item
2023-01-31 09:30:19	ga_ls9c_ard_3-2-1_092077_2023-01-31_final.stac-item
2023-02-05 09:48:30	ga_ls9c_ard_3-2-1_095076_2023-02-05_final.stac-item
2023-02-06 10:33:22	ga_ls9c_ard_3-2-1_102080_2023-02-06_final.stac-item
2023-02-10 10:09:03	ga_ls9c_ard_3-2-1_098081_2023-02-10_final.stac-item
2023-02-22 10:33:10	ga_ls9c_ard_3-2-1_102080_2023-02-22_final.stac-item
2023-03-02 11:21:45	ga_ls9c_ard_3-2-1_110078_2023-03-02_final.stac-item
2023-03-08 10:45:47	ga_ls9c_ard_3-2-1_104081_2023-03-08_final.stac-item
2023-03-09 09:47:21	ga_ls9c_ard_3-2-1_095074_2023-03-09_final.stac-item
2023-03-16 09:56:43	ga_ls9c_ard_3-2-1_096082_2023-03-16_final.stac-item
2023-03-25 09:48:03	ga_ls9c_ard_3-2-1_095076_2023-03-25_final.stac-item
2023-04-01 09:54:32	ga_ls9c_ard_3-2-1_096077_2023-04-01_final.stac-item
2023-04-03 09:43:22	ga_ls9c_ard_3-2-1_094080_2023-04-03_final.stac-item
2023-04-25 10:43:50	ga_ls9c_ard_3-2-1_104077_2023-04-25_final.stac-item
2023-04-26 09:47:48	ga_ls9c_ard_3-2-1_095076_2023-04-26_final.stac-item
2023-05-03 11:34:20	ga_ls9c_ard_3-2-1_112080_2023-05-03_final.stac-item
2023-05-05 09:41:52	ga_ls9c_ard_3-2-1_094077_2023-05-05_final.stac-item
2023-05-05 11:17:57	ga_ls9c_ard_3-2-1_110070_2023-05-05_final.stac-item
2023-05-10 10:00:00	ga_ls9c_ard_3-2-1_097076_2023-05-10_final.stac-item
2023-05-12 09:47:38	ga_ls9c_ard_3-2-1_095076_2023-05-12_final.stac-item
2023-05-16 11:02:34	ga_ls9c_ard_3-2-1_107078_2023-05-16_final.stac-item
2023-05-17 10:08:08	ga_ls9c_ard_3-2-1_098081_2023-05-17_final.stac-item
2023-05-19 11:34:14	ga_ls9c_ard_3-2-1_112080_2023-05-19_final.stac-item
2023-05-28 09:47:29	ga_ls9c_ard_3-2-1_095076_2023-05-28_final.stac-item
2023-05-28 11:27:57	ga_ls9c_ard_3-2-1_111080_2023-05-28_final.stac-item
2023-05-29 10:31:32	ga_ls9c_ard_3-2-1_102078_2023-05-29_final.stac-item
2023-06-21 10:34:46	ga_ls9c_ard_3-2-1_103071_2023-06-21_final.stac-item
2023-06-22 09:41:33	ga_ls9c_ard_3-2-1_094077_2023-06-22_final.stac-item
2023-06-27 09:59:19	ga_ls9c_ard_3-2-1_097075_2023-06-27_final.stac-item
2023-06-27 09:59:43	ga_ls9c_ard_3-2-1_097076_2023-06-27_final.stac-item
2023-07-06 09:53:19	ga_ls9c_ard_3-2-1_096075_2023-07-06_final.stac-item
2023-07-15 11:28:05	ga_ls9c_ard_3-2-1_111080_2023-07-15_final.stac-item
2023-07-22 11:32:15	ga_ls9c_ard_3-2-1_112075_2023-07-22_final.stac-item
2023-07-25 10:25:51	ga_ls9c_ard_3-2-1_101079_2023-07-25_final.stac-item
2023-07-26 09:31:51	ga_ls9c_ard_3-2-1_092083_2023-07-26_final.stac-item
2023-07-28 09:19:08	ga_ls9c_ard_3-2-1_090082_2023-07-27_final.stac-item
2023-07-29 09:59:37	ga_ls9c_ard_3-2-1_097075_2023-07-29_final.stac-item
2023-07-31 11:26:10	ga_ls9c_ard_3-2-1_111075_2023-07-31_final.stac-item
2023-08-02 11:11:27	ga_ls9c_ard_3-2-1_109069_2023-08-02_final.stac-item
2023-08-09 09:41:11	ga_ls9c_ard_3-2-1_094075_2023-08-09_final.stac-item
2023-08-09 09:42:47	ga_ls9c_ard_3-2-1_094079_2023-08-09_final.stac-item
2023-08-10 10:26:27	ga_ls9c_ard_3-2-1_101080_2023-08-10_final.stac-item
2023-08-11 09:32:01	ga_ls9c_ard_3-2-1_092083_2023-08-11_final.stac-item
2023-08-15 10:43:23	ga_ls9c_ard_3-2-1_104076_2023-08-15_final.stac-item
2023-08-15 10:44:59	ga_ls9c_ard_3-2-1_104080_2023-08-15_final.stac-item
2023-10-13 10:22:54	ga_ls9c_ard_3-2-1_101070_2023-10-13_final.stac-item
2023-10-17 11:40:41	ga_ls9c_ard_3-2-1_113079_2023-10-17_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-28 09:44:49	ga_ls9c_ard_3-2-1_094083_2023-10-28_final.stac-item
2023-10-29 10:22:53	ga_ls9c_ard_3-2-1_101070_2023-10-29_final.stac-item
2023-11-02 10:00:29	ga_ls9c_ard_3-2-1_097076_2023-11-02_final.stac-item
2023-11-02 11:40:34	ga_ls9c_ard_3-2-1_113079_2023-11-02_final.stac-item
2023-11-04 09:48:32	ga_ls9c_ard_3-2-1_095077_2023-11-04_final.stac-item
2023-11-19 10:41:51	ga_ls9c_ard_3-2-1_104071_2023-11-19_final.stac-item
2023-11-26 10:50:54	ga_ls9c_ard_3-2-1_105078_2023-11-26_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