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 10:55:39	ga_ls9c_ard_3-2-1_106080_2021-11-02_final.stac-item
2021-11-08 09:55:27	ga_ls9c_ard_3-2-1_097070_2021-11-08_final.stac-item
2021-11-18 10:03:57	ga_ls9c_ard_3-2-1_097079_2021-11-18_final.stac-item
2021-11-20 09:42:01	ga_ls9c_ard_3-2-1_094071_2021-11-20_final.stac-item
2021-11-22 09:25:16	ga_ls9c_ard_3-2-1_091076_2021-11-21_final.stac-item
2021-12-04 09:28:05	ga_ls9c_ard_3-2-1_091087_2021-12-03_final.stac-item
2021-12-18 11:12:00	ga_ls9c_ard_3-2-1_109069_2021-12-18_final.stac-item
2021-12-22 09:13:36	ga_ls9c_ard_3-2-1_089082_2021-12-21_final.stac-item
2022-01-05 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-05_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-02-08 10:52:51	ga_ls9c_ard_3-2-1_105083_2022-02-08_final.stac-item
2022-02-10 10:39:41	ga_ls9c_ard_3-2-1_103081_2022-02-10_final.stac-item
2022-03-12 09:12:09	ga_ls9c_ard_3-2-1_089079_2022-03-11_final.stac-item
2022-03-20 09:57:58	ga_ls9c_ard_3-2-1_097070_2022-03-20_final.stac-item
2022-03-30 10:35:47	ga_ls9c_ard_3-2-1_103072_2022-03-30_final.stac-item
2022-04-01 10:27:25	ga_ls9c_ard_3-2-1_101082_2022-04-01_final.stac-item
2022-04-10 11:58:29	ga_ls9c_ard_3-2-1_116078_2022-04-10_final.stac-item
2022-04-27 11:03:31	ga_ls9c_ard_3-2-1_107080_2022-04-27_final.stac-item
2022-04-29 10:51:57	ga_ls9c_ard_3-2-1_105082_2022-04-29_final.stac-item
2022-05-02 09:40:21	ga_ls9c_ard_3-2-1_094073_2022-05-02_final.stac-item
2022-05-05 10:12:50	ga_ls9c_ard_3-2-1_099077_2022-05-05_final.stac-item
2022-05-07 09:57:39	ga_ls9c_ard_3-2-1_097070_2022-05-07_final.stac-item
2022-05-15 09:13:18	ga_ls9c_ard_3-2-1_089083_2022-05-14_final.stac-item
2022-05-15 10:46:12	ga_ls9c_ard_3-2-1_105068_2022-05-15_final.stac-item
2022-05-20 09:32:57	ga_ls9c_ard_3-2-1_092086_2022-05-20_final.stac-item
2022-05-20 11:05:27	ga_ls9c_ard_3-2-1_108070_2022-05-20_final.stac-item
2022-05-31 09:11:14	ga_ls9c_ard_3-2-1_089078_2022-05-30_final.stac-item
2022-06-09 09:06:40	ga_ls9c_ard_3-2-1_088082_2022-06-08_final.stac-item
2022-06-14 10:59:22	ga_ls9c_ard_3-2-1_107070_2022-06-14_final.stac-item
2022-06-15 10:02:58	ga_ls9c_ard_3-2-1_098068_2022-06-15_final.stac-item
2022-07-02 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-07-02_final.stac-item
2022-07-17 10:06:46	ga_ls9c_ard_3-2-1_098077_2022-07-17_final.stac-item
2022-07-20 10:35:44	ga_ls9c_ard_3-2-1_103072_2022-07-20_final.stac-item
2022-07-25 10:52:46	ga_ls9c_ard_3-2-1_106068_2022-07-25_final.stac-item
2022-07-25 10:53:10	ga_ls9c_ard_3-2-1_106069_2022-07-25_final.stac-item
2022-08-19 10:46:50	ga_ls9c_ard_3-2-1_105068_2022-08-19_final.stac-item
2022-08-21 10:36:04	ga_ls9c_ard_3-2-1_103072_2022-08-21_final.stac-item
2022-08-22 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-08-22_final.stac-item
2022-08-25 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-08-25_final.stac-item
2022-09-02 09:26:18	ga_ls9c_ard_3-2-1_091083_2022-09-01_final.stac-item
2022-09-10 10:09:46	ga_ls9c_ard_3-2-1_099068_2022-09-10_final.stac-item
2022-09-13 09:06:36	ga_ls9c_ard_3-2-1_088080_2022-09-12_final.stac-item
2022-09-19 10:03:40	ga_ls9c_ard_3-2-1_098068_2022-09-19_final.stac-item
2022-10-05 10:04:06	ga_ls9c_ard_3-2-1_098069_2022-10-05_final.stac-item
2022-10-15 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-14_final.stac-item
2022-10-18 09:35:41	ga_ls9c_ard_3-2-1_093075_2022-10-18_final.stac-item
2022-10-19 10:20:33	ga_ls9c_ard_3-2-1_100079_2022-10-19_final.stac-item
2022-11-04 10:17:18	ga_ls9c_ard_3-2-1_100071_2022-11-04_final.stac-item
2022-11-12 09:33:55	ga_ls9c_ard_3-2-1_092086_2022-11-12_final.stac-item
2022-11-14 10:54:04	ga_ls9c_ard_3-2-1_106070_2022-11-14_final.stac-item
2022-11-15 10:02:02	ga_ls9c_ard_3-2-1_097079_2022-11-15_final.stac-item
2022-11-20 10:19:22	ga_ls9c_ard_3-2-1_100076_2022-11-20_final.stac-item
2022-12-07 09:23:43	ga_ls9c_ard_3-2-1_091076_2022-12-06_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2022-12-08 10:04:59	ga_ls9c_ard_3-2-1_098071_2022-12-08_final.stac-item
2022-12-09 10:49:27	ga_ls9c_ard_3-2-1_105074_2022-12-09_final.stac-item
2022-12-19 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-12-19_final.stac-item
2022-12-21 11:13:20	ga_ls9c_ard_3-2-1_109072_2022-12-21_final.stac-item
2022-12-23 11:00:10	ga_ls9c_ard_3-2-1_107070_2022-12-23_final.stac-item
2022-12-25 09:16:30	ga_ls9c_ard_3-2-1_089089_2022-12-24_final.stac-item
2023-01-10 09:10:33	ga_ls9c_ard_3-2-1_089074_2023-01-09_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-10 10:52:38	ga_ls9c_ard_3-2-1_105082_2023-01-10_final.stac-item
2023-01-18 09:57:06	ga_ls9c_ard_3-2-1_097067_2023-01-18_final.stac-item
2023-01-22 09:35:33	ga_ls9c_ard_3-2-1_093075_2023-01-22_final.stac-item
2023-01-22 09:39:32	ga_ls9c_ard_3-2-1_093085_2023-01-22_final.stac-item
2023-01-28 10:35:04	ga_ls9c_ard_3-2-1_103069_2023-01-28_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-09 09:26:59	ga_ls9c_ard_3-2-1_091084_2023-02-08_final.stac-item
2023-02-12 09:52:41	ga_ls9c_ard_3-2-1_096071_2023-02-12_final.stac-item
2023-02-12 11:32:46	ga_ls9c_ard_3-2-1_112074_2023-02-12_final.stac-item
2023-02-13 10:36:20	ga_ls9c_ard_3-2-1_103072_2023-02-13_final.stac-item
2023-03-22 09:22:47	ga_ls9c_ard_3-2-1_090090_2023-03-21_final.stac-item
2023-04-08 09:58:18	ga_ls9c_ard_3-2-1_097071_2023-04-08_final.stac-item
2023-04-11 10:28:46	ga_ls9c_ard_3-2-1_102070_2023-04-11_final.stac-item
2023-04-14 09:28:43	ga_ls9c_ard_3-2-1_091090_2023-04-13_final.stac-item
2023-04-16 10:49:39	ga_ls9c_ard_3-2-1_105076_2023-04-16_final.stac-item
2023-04-26 09:46:36	ga_ls9c_ard_3-2-1_095073_2023-04-26_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_2023-04-29_final.stac-item
2023-05-10 10:03:36	ga_ls9c_ard_3-2-1_097085_2023-05-10_final.stac-item
2023-05-12 09:46:26	ga_ls9c_ard_3-2-1_095073_2023-05-12_final.stac-item
2023-06-08 09:32:04	ga_ls9c_ard_3-2-1_092084_2023-06-08_final.stac-item
2023-06-16 10:16:13	ga_ls9c_ard_3-2-1_100071_2023-06-16_final.stac-item
2023-06-17 11:01:05	ga_ls9c_ard_3-2-1_107075_2023-06-17_final.stac-item
2023-06-18 10:02:40	ga_ls9c_ard_3-2-1_098068_2023-06-18_final.stac-item
2023-06-18 10:08:39	ga_ls9c_ard_3-2-1_098083_2023-06-18_final.stac-item
2023-06-19 09:11:26	ga_ls9c_ard_3-2-1_089079_2023-06-18_final.stac-item
2023-06-20 09:56:42	ga_ls9c_ard_3-2-1_096084_2023-06-20_final.stac-item
2023-06-22 11:18:26	ga_ls9c_ard_3-2-1_110072_2023-06-22_final.stac-item
2023-06-24 09:32:22	ga_ls9c_ard_3-2-1_092085_2023-06-24_final.stac-item
2023-06-25 10:14:50	ga_ls9c_ard_3-2-1_099083_2023-06-25_final.stac-item
2023-07-02 10:21:11	ga_ls9c_ard_3-2-1_100083_2023-07-02_final.stac-item
2023-07-03 09:25:58	ga_ls9c_ard_3-2-1_091084_2023-07-02_final.stac-item
2023-07-03 10:59:16	ga_ls9c_ard_3-2-1_107070_2023-07-03_final.stac-item
2023-07-04 10:04:04	ga_ls9c_ard_3-2-1_098071_2023-07-04_final.stac-item
2023-09-05 09:28:51	ga_ls9c_ard_3-2-1_091090_2023-09-04_final.stac-item
2023-09-06 10:03:21	ga_ls9c_ard_3-2-1_098068_2023-09-06_final.stac-item
2023-10-03 11:25:46	ga_ls9c_ard_3-2-1_111073_2023-10-03_final.stac-item
2023-10-06 10:22:13	ga_ls9c_ard_3-2-1_100084_2023-10-06_final.stac-item
2023-10-08 10:03:53	ga_ls9c_ard_3-2-1_098069_2023-10-08_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