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
2022-02-23 10:07:27	ga_ls9c_ard_3-2-1_098078_2022-02-23_final.stac-item
2022-03-28 10:50:56	ga_ls9c_ard_3-2-1_105079_2022-03-28_final.stac-item
2022-06-14 11:02:34	ga_ls9c_ard_3-2-1_107078_2022-06-14_final.stac-item
2022-06-28 11:11:37	ga_ls9c_ard_3-2-1_109069_2022-06-28_final.stac-item
2022-07-09 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-07-09_final.stac-item
2022-07-25 10:57:09	ga_ls9c_ard_3-2-1_106079_2022-07-25_final.stac-item
2022-08-03 09:13:48	ga_ls9c_ard_3-2-1_089083_2022-08-02_final.stac-item
2022-08-06 09:44:44	ga_ls9c_ard_3-2-1_094083_2022-08-06_final.stac-item
2022-08-12 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-08-12_final.stac-item
2022-09-13 10:43:53	ga_ls9c_ard_3-2-1_104076_2022-09-13_final.stac-item
2022-09-22 10:38:35	ga_ls9c_ard_3-2-1_103078_2022-09-22_final.stac-item
2022-09-27 10:57:32	ga_ls9c_ard_3-2-1_106079_2022-09-27_final.stac-item
2022-10-06 10:51:21	ga_ls9c_ard_3-2-1_105079_2022-10-06_final.stac-item
2022-10-31 10:44:51	ga_ls9c_ard_3-2-1_104078_2022-10-31_final.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-24 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-24_final.stac-item
2022-12-03 11:24:30	ga_ls9c_ard_3-2-1_111069_2022-12-03_final.stac-item
2022-12-17 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-12-17_final.stac-item
2023-01-01 10:57:38	ga_ls9c_ard_3-2-1_106079_2023-01-01_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-19 10:45:32	ga_ls9c_ard_3-2-1_104080_2023-01-19_final.stac-item
2023-01-24 11:00:55	ga_ls9c_ard_3-2-1_107072_2023-01-24_final.stac-item
2023-01-27 09:56:35	ga_ls9c_ard_3-2-1_096081_2023-01-27_final.stac-item
2023-01-27 11:33:52	ga_ls9c_ard_3-2-1_112077_2023-01-27_final.stac-item
2023-01-30 10:24:44	ga_ls9c_ard_3-2-1_101074_2023-01-30_final.stac-item
2023-02-03 10:01:15	ga_ls9c_ard_3-2-1_097077_2023-02-03_final.stac-item
2023-02-03 10:04:02	ga_ls9c_ard_3-2-1_097084_2023-02-03_final.stac-item
2023-02-04 10:44:07	ga_ls9c_ard_3-2-1_104076_2023-02-04_final.stac-item
2023-02-05 09:49:42	ga_ls9c_ard_3-2-1_095079_2023-02-05_final.stac-item
2023-02-08 10:18:13	ga_ls9c_ard_3-2-1_100073_2023-02-08_final.stac-item
2023-02-09 11:03:52	ga_ls9c_ard_3-2-1_107079_2023-02-09_final.stac-item
2023-02-09 11:04:16	ga_ls9c_ard_3-2-1_107080_2023-02-09_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_2023-02-10_final.stac-item
2023-02-14 09:42:18	ga_ls9c_ard_3-2-1_094076_2023-02-14_final.stac-item
2023-04-22 10:14:10	ga_ls9c_ard_3-2-1_099080_2023-04-22_final.stac-item
2023-04-23 09:17:20	ga_ls9c_ard_3-2-1_090077_2023-04-22_final.stac-item
2023-04-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2023-04-23_final.stac-item
2023-04-25 10:45:26	ga_ls9c_ard_3-2-1_104081_2023-04-25_final.stac-item
2023-04-26 09:48:36	ga_ls9c_ard_3-2-1_095078_2023-04-26_final.stac-item
2023-04-26 09:49:00	ga_ls9c_ard_3-2-1_095079_2023-04-26_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 11:15:06	ga_ls9c_ard_3-2-1_109078_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
2023-04-28 11:17:05	ga_ls9c_ard_3-2-1_109083_2023-04-28_final.stac-item
2023-04-30 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-04-30_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-04-30 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-04-30_final.stac-item
2023-05-28 09:47:52	ga_ls9c_ard_3-2-1_095077_2023-05-28_final.stac-item
2023-07-05 10:52:07	ga_ls9c_ard_3-2-1_105083_2023-07-05_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-07-24 11:18:17	ga_ls9c_ard_3-2-1_110071_2023-07-24_final.stac-item
2023-07-25 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-25_final.stac-item
2023-07-28 09:17:56	ga_ls9c_ard_3-2-1_090079_2023-07-27_final.stac-item
2023-07-29 10:00:25	ga_ls9c_ard_3-2-1_097077_2023-07-29_final.stac-item
2023-08-02 09:35:45	ga_ls9c_ard_3-2-1_093077_2023-08-02_final.stac-item
2023-08-02 09:38:33	ga_ls9c_ard_3-2-1_093084_2023-08-02_final.stac-item
2023-08-04 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-08-04_final.stac-item
2023-08-05 10:07:29	ga_ls9c_ard_3-2-1_098079_2023-08-05_final.stac-item
2023-08-05 11:45:10	ga_ls9c_ard_3-2-1_114076_2023-08-05_final.stac-item
2023-08-06 09:12:16	ga_ls9c_ard_3-2-1_089080_2023-08-05_final.stac-item
2023-10-14 09:30:05	ga_ls9c_ard_3-2-1_092077_2023-10-14_final.stac-item
2023-10-15 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-10-15_final.stac-item
2023-10-15 10:12:57	ga_ls9c_ard_3-2-1_099076_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
2023-10-17 10:02:12	ga_ls9c_ard_3-2-1_097080_2023-10-17_final.stac-item
2023-10-17 11:40:17	ga_ls9c_ard_3-2-1_113078_2023-10-17_final.stac-item
2023-10-19 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_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 10:17:09	ga_ls9c_ard_3-2-1_100071_2023-10-22_final.stac-item
2023-10-22 10:19:09	ga_ls9c_ard_3-2-1_100076_2023-10-22_final.stac-item
2023-10-23 11:03:12	ga_ls9c_ard_3-2-1_107078_2023-10-23_final.stac-item
2023-10-24 10:05:11	ga_ls9c_ard_3-2-1_098072_2023-10-24_final.stac-item
2023-10-26 09:54:24	ga_ls9c_ard_3-2-1_096076_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
2023-10-28 11:19:19	ga_ls9c_ard_3-2-1_110072_2023-10-28_final.stac-item
2023-10-29 10:26:04	ga_ls9c_ard_3-2-1_101078_2023-10-29_final.stac-item
2023-11-02 11:40:34	ga_ls9c_ard_3-2-1_113079_2023-11-02_final.stac-item
2023-11-03 10:40:32	ga_ls9c_ard_3-2-1_104068_2023-11-03_final.stac-item
2023-11-03 10:44:08	ga_ls9c_ard_3-2-1_104077_2023-11-03_final.stac-item
2023-11-04 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-11-04_final.stac-item
2023-11-05 10:29:49	ga_ls9c_ard_3-2-1_102072_2023-11-05_final.stac-item
2023-11-05 10:31:48	ga_ls9c_ard_3-2-1_102077_2023-11-05_final.stac-item
2023-11-15 11:09:18	ga_ls9c_ard_3-2-1_108078_2023-11-15_final.stac-item
2023-11-15 11:09:42	ga_ls9c_ard_3-2-1_108079_2023-11-15_final.stac-item
2023-11-16 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-11-16_final.stac-item
2023-11-17 09:18:53	ga_ls9c_ard_3-2-1_090080_2023-11-16_final.stac-item
2023-11-18 09:59:46	ga_ls9c_ard_3-2-1_097074_2023-11-18_final.stac-item
2023-11-18 11:40:39	ga_ls9c_ard_3-2-1_113079_2023-11-18_final.stac-item
2023-11-20 09:50:38	ga_ls9c_ard_3-2-1_095082_2023-11-20_final.stac-item
2023-11-20 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-11-20_final.stac-item
2023-11-20 11:25:56	ga_ls9c_ard_3-2-1_111073_2023-11-20_final.stac-item
2023-11-22 11:12:48	ga_ls9c_ard_3-2-1_109071_2023-11-22_final.stac-item
2023-11-22 11:13:12	ga_ls9c_ard_3-2-1_109072_2023-11-22_final.stac-item
2023-11-22 11:16:23	ga_ls9c_ard_3-2-1_109080_2023-11-22_final.stac-item
2023-11-24 09:28:46	ga_ls9c_ard_3-2-1_091089_2023-11-23_final.stac-item
2023-11-24 11:03:39	ga_ls9c_ard_3-2-1_107079_2023-11-24_final.stac-item
2023-11-24 11:05:39	ga_ls9c_ard_3-2-1_107084_2023-11-24_final.stac-item
2023-11-26 09:14:25	ga_ls9c_ard_3-2-1_089084_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