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
2021-12-14 10:03:27	ga_ls9c_ard_3-2-1_097083_2021-12-14_final.stac-item
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2021-12-22 10:51:17	ga_ls9c_ard_3-2-1_105079_2021-12-22_final.stac-item
2022-02-20 11:15:28	ga_ls9c_ard_3-2-1_109078_2022-02-20_final.stac-item
2022-03-08 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-03-08_final.stac-item
2022-04-04 09:19:50	ga_ls9c_ard_3-2-1_090083_2022-04-03_final.stac-item
2022-05-06 09:19:36	ga_ls9c_ard_3-2-1_090083_2022-05-05_final.stac-item
2022-05-30 10:04:52	ga_ls9c_ard_3-2-1_098073_2022-05-30_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-08-26 10:57:25	ga_ls9c_ard_3-2-1_106079_2022-08-26_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-23 11:23:03	ga_ls9c_ard_3-2-1_110081_2022-09-23_final.stac-item
2022-09-27 09:19:27	ga_ls9c_ard_3-2-1_090081_2022-09-26_final.stac-item
2022-12-24 10:09:19	ga_ls9c_ard_3-2-1_098082_2022-12-24_final.stac-item
2023-01-02 10:03:36	ga_ls9c_ard_3-2-1_097083_2023-01-02_final.stac-item
2023-01-19 10:45:32	ga_ls9c_ard_3-2-1_104080_2023-01-19_final.stac-item
2023-01-28 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-28_final.stac-item
2023-02-02 10:56:51	ga_ls9c_ard_3-2-1_106077_2023-02-02_final.stac-item
2023-02-05 11:26:59	ga_ls9c_ard_3-2-1_111075_2023-02-05_final.stac-item
2023-02-05 11:27:23	ga_ls9c_ard_3-2-1_111076_2023-02-05_final.stac-item
2023-02-07 09:40:08	ga_ls9c_ard_3-2-1_093086_2023-02-07_final.stac-item
2023-02-10 11:46:20	ga_ls9c_ard_3-2-1_114077_2023-02-10_final.stac-item
2023-02-14 09:44:17	ga_ls9c_ard_3-2-1_094081_2023-02-14_final.stac-item
2023-04-22 10:14:57	ga_ls9c_ard_3-2-1_099082_2023-04-22_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2023-04-22_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-04-24 09:59:47	ga_ls9c_ard_3-2-1_097075_2023-04-24_final.stac-item
2023-04-24 10:00:59	ga_ls9c_ard_3-2-1_097078_2023-04-24_final.stac-item
2023-04-24 10:02:11	ga_ls9c_ard_3-2-1_097081_2023-04-24_final.stac-item
2023-04-24 10:02:59	ga_ls9c_ard_3-2-1_097083_2023-04-24_final.stac-item
2023-04-24 11:38:40	ga_ls9c_ard_3-2-1_113075_2023-04-24_final.stac-item
2023-04-26 09:49:48	ga_ls9c_ard_3-2-1_095081_2023-04-26_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-28 09:35:49	ga_ls9c_ard_3-2-1_093077_2023-04-28_final.stac-item
2023-04-28 09:36:13	ga_ls9c_ard_3-2-1_093078_2023-04-28_final.stac-item
2023-04-28 09:38:36	ga_ls9c_ard_3-2-1_093084_2023-04-28_final.stac-item
2023-04-28 11:12:18	ga_ls9c_ard_3-2-1_109071_2023-04-28_final.stac-item
2023-04-28 11:14:42	ga_ls9c_ard_3-2-1_109077_2023-04-28_final.stac-item
2023-04-28 11:15:53	ga_ls9c_ard_3-2-1_109080_2023-04-28_final.stac-item
2023-04-29 10:20:39	ga_ls9c_ard_3-2-1_100081_2023-04-29_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-04-30 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-04-30_final.stac-item
2023-05-28 11:26:22	ga_ls9c_ard_3-2-1_111076_2023-05-28_final.stac-item
2023-07-29 09:59:37	ga_ls9c_ard_3-2-1_097075_2023-07-29_final.stac-item
2023-07-29 10:00:01	ga_ls9c_ard_3-2-1_097076_2023-07-29_final.stac-item
2023-07-29 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-07-29_final.stac-item
2023-08-02 11:11:50	ga_ls9c_ard_3-2-1_109070_2023-08-02_final.stac-item
2023-08-02 11:12:38	ga_ls9c_ard_3-2-1_109072_2023-08-02_final.stac-item
2023-08-05 10:05:05	ga_ls9c_ard_3-2-1_098073_2023-08-05_final.stac-item
2023-08-05 10:05:53	ga_ls9c_ard_3-2-1_098075_2023-08-05_final.stac-item
2023-08-05 11:46:46	ga_ls9c_ard_3-2-1_114080_2023-08-05_final.stac-item
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_final.stac-item
2023-10-13 10:26:05	ga_ls9c_ard_3-2-1_101078_2023-10-13_final.stac-item
2023-10-14 09:30:52	ga_ls9c_ard_3-2-1_092079_2023-10-14_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-14 11:10:09	ga_ls9c_ard_3-2-1_108080_2023-10-14_final.stac-item
2023-10-15 10:14:57	ga_ls9c_ard_3-2-1_099081_2023-10-15_final.stac-item
2023-10-15 11:53:02	ga_ls9c_ard_3-2-1_115079_2023-10-15_final.stac-item
2023-10-16 09:18:56	ga_ls9c_ard_3-2-1_090080_2023-10-15_final.stac-item
2023-10-17 10:00:36	ga_ls9c_ard_3-2-1_097076_2023-10-17_final.stac-item
2023-10-18 10:43:28	ga_ls9c_ard_3-2-1_104075_2023-10-18_final.stac-item
2023-10-18 10:45:28	ga_ls9c_ard_3-2-1_104080_2023-10-18_final.stac-item
2023-10-20 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-10-20_final.stac-item
2023-10-20 10:32:19	ga_ls9c_ard_3-2-1_102078_2023-10-20_final.stac-item
2023-10-21 09:36:41	ga_ls9c_ard_3-2-1_093078_2023-10-21_final.stac-item
2023-10-22 10:18:21	ga_ls9c_ard_3-2-1_100074_2023-10-22_final.stac-item
2023-10-22 10:18:45	ga_ls9c_ard_3-2-1_100075_2023-10-22_final.stac-item
2023-10-23 09:24:19	ga_ls9c_ard_3-2-1_091078_2023-10-22_final.stac-item
2023-10-24 11:46:04	ga_ls9c_ard_3-2-1_114077_2023-10-24_final.stac-item
2023-10-26 09:54:48	ga_ls9c_ard_3-2-1_096077_2023-10-26_final.stac-item
2023-10-26 09:55:36	ga_ls9c_ard_3-2-1_096079_2023-10-26_final.stac-item
2023-10-26 11:34:53	ga_ls9c_ard_3-2-1_112080_2023-10-26_final.stac-item
2023-10-27 10:38:27	ga_ls9c_ard_3-2-1_103078_2023-10-27_final.stac-item
2023-10-28 09:41:38	ga_ls9c_ard_3-2-1_094075_2023-10-28_final.stac-item
2023-10-29 10:25:40	ga_ls9c_ard_3-2-1_101077_2023-10-29_final.stac-item
2023-10-29 10:27:16	ga_ls9c_ard_3-2-1_101081_2023-10-29_final.stac-item
2023-10-30 11:10:55	ga_ls9c_ard_3-2-1_108082_2023-10-30_final.stac-item
2023-10-31 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-10-31_final.stac-item
2023-10-31 11:50:58	ga_ls9c_ard_3-2-1_115074_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
2023-11-03 10:43:44	ga_ls9c_ard_3-2-1_104076_2023-11-03_final.stac-item
2023-11-03 10:44:32	ga_ls9c_ard_3-2-1_104078_2023-11-03_final.stac-item
2023-11-03 10:45:20	ga_ls9c_ard_3-2-1_104080_2023-11-03_final.stac-item
2023-11-04 09:49:43	ga_ls9c_ard_3-2-1_095080_2023-11-04_final.stac-item
2023-11-04 09:50:07	ga_ls9c_ard_3-2-1_095081_2023-11-04_final.stac-item
2023-11-04 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-11-04_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-11-15 09:30:49	ga_ls9c_ard_3-2-1_092079_2023-11-15_final.stac-item
2023-11-15 09:31:37	ga_ls9c_ard_3-2-1_092081_2023-11-15_final.stac-item
2023-11-15 11:08:31	ga_ls9c_ard_3-2-1_108076_2023-11-15_final.stac-item
2023-11-16 10:11:42	ga_ls9c_ard_3-2-1_099073_2023-11-16_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_2023-11-20_final.stac-item
2023-11-22 09:37:54	ga_ls9c_ard_3-2-1_093081_2023-11-22_final.stac-item
2023-11-22 09:38:18	ga_ls9c_ard_3-2-1_093082_2023-11-22_final.stac-item
2023-11-23 10:20:47	ga_ls9c_ard_3-2-1_100080_2023-11-23_final.stac-item
2023-11-24 11:04:03	ga_ls9c_ard_3-2-1_107080_2023-11-24_final.stac-item
2023-11-24 11:04:51	ga_ls9c_ard_3-2-1_107082_2023-11-24_final.stac-item
2023-11-25 11:44:56	ga_ls9c_ard_3-2-1_114074_2023-11-25_final.stac-item
2023-11-25 11:46:31	ga_ls9c_ard_3-2-1_114078_2023-11-25_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