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
2021-10-31 11:10:24	ga_ls9c_ard_3-2-1_109070_2021-10-31_final.stac-item
2022-01-08 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-01-08_final.stac-item
2022-01-10 09:45:40	ga_ls9c_ard_3-2-1_094085_2022-01-10_final.stac-item
2022-01-24 09:53:15	ga_ls9c_ard_3-2-1_096073_2022-01-24_final.stac-item
2022-02-16 11:41:26	ga_ls9c_ard_3-2-1_113081_2022-02-16_final.stac-item
2022-02-25 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-02-25_final.stac-item
2022-03-03 09:19:31	ga_ls9c_ard_3-2-1_090082_2022-03-02_final.stac-item
2022-03-25 10:18:04	ga_ls9c_ard_3-2-1_100074_2022-03-25_final.stac-item
2022-03-30 10:37:47	ga_ls9c_ard_3-2-1_103077_2022-03-30_final.stac-item
2022-04-02 09:29:48	ga_ls9c_ard_3-2-1_092077_2022-04-01_final.stac-item
2022-04-11 09:25:58	ga_ls9c_ard_3-2-1_091083_2022-04-10_final.stac-item
2022-04-20 09:18:52	ga_ls9c_ard_3-2-1_090081_2022-04-19_final.stac-item
2022-05-13 11:02:35	ga_ls9c_ard_3-2-1_107078_2022-05-13_final.stac-item
2022-05-28 10:19:12	ga_ls9c_ard_3-2-1_100078_2022-05-28_final.stac-item
2022-06-12 09:35:13	ga_ls9c_ard_3-2-1_093076_2022-06-12_final.stac-item
2022-07-18 10:46:04	ga_ls9c_ard_3-2-1_105067_2022-07-18_final.stac-item
2022-07-26 09:59:33	ga_ls9c_ard_3-2-1_097074_2022-07-26_final.stac-item
2022-08-11 11:41:48	ga_ls9c_ard_3-2-1_113082_2022-08-11_final.stac-item
2022-08-16 10:17:30	ga_ls9c_ard_3-2-1_100072_2022-08-16_final.stac-item
2022-08-31 09:37:04	ga_ls9c_ard_3-2-1_093079_2022-08-31_final.stac-item
2022-09-02 09:23:55	ga_ls9c_ard_3-2-1_091077_2022-09-01_final.stac-item
2022-09-28 10:01:07	ga_ls9c_ard_3-2-1_097077_2022-09-28_final.stac-item
2022-10-09 11:24:40	ga_ls9c_ard_3-2-1_110085_2022-10-09_final.stac-item
2022-10-14 09:59:11	ga_ls9c_ard_3-2-1_097072_2022-10-14_final.stac-item
2022-10-14 11:41:40	ga_ls9c_ard_3-2-1_113081_2022-10-14_final.stac-item
2022-10-14 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-14_final.stac-item
2022-10-18 09:35:17	ga_ls9c_ard_3-2-1_093074_2022-10-18_final.stac-item
2022-10-22 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-10-22_final.stac-item
2022-10-29 09:18:44	ga_ls9c_ard_3-2-1_090079_2022-10-28_final.stac-item
2022-10-31 10:41:16	ga_ls9c_ard_3-2-1_104069_2022-10-31_final.stac-item
2022-11-04 10:18:30	ga_ls9c_ard_3-2-1_100074_2022-11-04_final.stac-item
2022-11-10 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-10_final.stac-item
2022-11-18 10:32:08	ga_ls9c_ard_3-2-1_102077_2022-11-18_final.stac-item
2022-11-19 11:15:47	ga_ls9c_ard_3-2-1_109078_2022-11-19_final.stac-item
2022-11-19 11:17:47	ga_ls9c_ard_3-2-1_109083_2022-11-19_final.stac-item
2022-11-26 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-26_final.stac-item
2022-11-29 10:13:09	ga_ls9c_ard_3-2-1_099076_2022-11-29_final.stac-item
2022-12-03 09:51:12	ga_ls9c_ard_3-2-1_095083_2022-12-03_final.stac-item
2022-12-03 11:27:18	ga_ls9c_ard_3-2-1_111076_2022-12-03_final.stac-item
2022-12-04 10:31:41	ga_ls9c_ard_3-2-1_102076_2022-12-04_final.stac-item
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_final.stac-item
2022-12-07 11:04:36	ga_ls9c_ard_3-2-1_107081_2022-12-07_final.stac-item
2022-12-13 10:24:20	ga_ls9c_ard_3-2-1_101073_2022-12-13_final.stac-item
2022-12-14 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-14_final.stac-item
2022-12-17 10:04:00	ga_ls9c_ard_3-2-1_097084_2022-12-17_final.stac-item
2022-12-19 11:30:06	ga_ls9c_ard_3-2-1_111083_2022-12-19_final.stac-item
2022-12-20 10:32:05	ga_ls9c_ard_3-2-1_102077_2022-12-20_final.stac-item
2022-12-27 10:38:39	ga_ls9c_ard_3-2-1_103078_2022-12-27_final.stac-item
2022-12-27 10:39:27	ga_ls9c_ard_3-2-1_103080_2022-12-27_final.stac-item
2023-01-08 11:04:36	ga_ls9c_ard_3-2-1_107081_2023-01-08_final.stac-item
2023-01-13 09:46:13	ga_ls9c_ard_3-2-1_094086_2023-01-13_final.stac-item
2023-01-16 10:15:05	ga_ls9c_ard_3-2-1_099081_2023-01-16_final.stac-item
2023-01-19 10:43:32	ga_ls9c_ard_3-2-1_104075_2023-01-19_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-24 11:04:31	ga_ls9c_ard_3-2-1_107081_2023-01-24_final.stac-item
2023-01-31 11:11:12	ga_ls9c_ard_3-2-1_108082_2023-01-31_final.stac-item
2023-02-02 09:19:34	ga_ls9c_ard_3-2-1_090081_2023-02-01_final.stac-item
2023-02-06 10:31:22	ga_ls9c_ard_3-2-1_102075_2023-02-06_final.stac-item
2023-02-07 11:17:02	ga_ls9c_ard_3-2-1_109081_2023-02-07_final.stac-item
2023-02-09 11:04:40	ga_ls9c_ard_3-2-1_107081_2023-02-09_final.stac-item
2023-02-10 10:06:15	ga_ls9c_ard_3-2-1_098074_2023-02-10_final.stac-item
2023-04-04 10:25:02	ga_ls9c_ard_3-2-1_101076_2023-04-04_final.stac-item
2023-04-05 11:05:54	ga_ls9c_ard_3-2-1_108070_2023-04-05_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-28 09:34:37	ga_ls9c_ard_3-2-1_093074_2023-04-28_final.stac-item
2023-04-28 11:12:42	ga_ls9c_ard_3-2-1_109072_2023-04-28_final.stac-item
2023-04-30 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-04-30_final.stac-item
2023-05-04 10:34:18	ga_ls9c_ard_3-2-1_103069_2023-05-04_final.stac-item
2023-05-06 10:23:08	ga_ls9c_ard_3-2-1_101072_2023-05-06_final.stac-item
2023-05-08 11:51:39	ga_ls9c_ard_3-2-1_115077_2023-05-08_final.stac-item
2023-05-09 09:17:33	ga_ls9c_ard_3-2-1_090078_2023-05-08_final.stac-item
2023-05-11 10:42:52	ga_ls9c_ard_3-2-1_104075_2023-05-11_final.stac-item
2023-05-17 10:04:56	ga_ls9c_ard_3-2-1_098073_2023-05-17_final.stac-item
2023-06-20 09:51:31	ga_ls9c_ard_3-2-1_096071_2023-06-20_final.stac-item
2023-06-24 11:08:52	ga_ls9c_ard_3-2-1_108079_2023-06-24_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-06-27 11:40:12	ga_ls9c_ard_3-2-1_113080_2023-06-27_final.stac-item
2023-07-19 09:22:53	ga_ls9c_ard_3-2-1_091076_2023-07-18_final.stac-item
2023-07-19 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-07-18_final.stac-item
2023-07-28 10:53:37	ga_ls9c_ard_3-2-1_106071_2023-07-28_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-08-02 09:37:45	ga_ls9c_ard_3-2-1_093082_2023-08-02_final.stac-item
2023-08-03 10:18:13	ga_ls9c_ard_3-2-1_100075_2023-08-03_final.stac-item
2023-08-08 10:36:00	ga_ls9c_ard_3-2-1_103073_2023-08-08_final.stac-item
2023-10-17 09:59:48	ga_ls9c_ard_3-2-1_097074_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
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-22 10:20:21	ga_ls9c_ard_3-2-1_100079_2023-10-22_final.stac-item
2023-10-24 10:08:22	ga_ls9c_ard_3-2-1_098080_2023-10-24_final.stac-item
2023-10-30 09:30:02	ga_ls9c_ard_3-2-1_092077_2023-10-30_final.stac-item
2023-10-30 11:05:44	ga_ls9c_ard_3-2-1_108069_2023-10-30_final.stac-item
2023-11-01 09:18:27	ga_ls9c_ard_3-2-1_090079_2023-10-31_final.stac-item
2023-11-01 09:18:50	ga_ls9c_ard_3-2-1_090080_2023-10-31_final.stac-item
2023-11-01 10:56:55	ga_ls9c_ard_3-2-1_106078_2023-11-01_final.stac-item
2023-11-02 11:41:22	ga_ls9c_ard_3-2-1_113081_2023-11-02_final.stac-item
2023-11-03 10:43:20	ga_ls9c_ard_3-2-1_104075_2023-11-03_final.stac-item
2023-11-04 11:26:37	ga_ls9c_ard_3-2-1_111075_2023-11-04_final.stac-item
2023-11-14 10:24:51	ga_ls9c_ard_3-2-1_101075_2023-11-14_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