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
2021-11-20 09:45:12	ga_ls9c_ard_3-2-1_094079_2021-11-20_final.stac-item
2021-12-09 11:23:51	ga_ls9c_ard_3-2-1_110083_2021-12-09_final.stac-item
2021-12-25 09:43:18	ga_ls9c_ard_3-2-1_094079_2021-12-25_final.stac-item
2021-12-27 11:11:50	ga_ls9c_ard_3-2-1_108084_2021-12-27_final.stac-item
2022-01-08 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-01-08_final.stac-item
2022-02-23 10:09:03	ga_ls9c_ard_3-2-1_098082_2022-02-23_final.stac-item
2022-02-24 10:51:06	ga_ls9c_ard_3-2-1_105079_2022-02-24_final.stac-item
2022-03-31 09:43:46	ga_ls9c_ard_3-2-1_094081_2022-03-31_final.stac-item
2022-04-03 10:14:39	ga_ls9c_ard_3-2-1_099081_2022-04-03_final.stac-item
2022-04-07 09:49:31	ga_ls9c_ard_3-2-1_095080_2022-04-07_final.stac-item
2022-04-23 09:49:21	ga_ls9c_ard_3-2-1_095080_2022-04-23_final.stac-item
2022-06-09 10:44:45	ga_ls9c_ard_3-2-1_104080_2022-06-09_final.stac-item
2022-07-09 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-07-09_final.stac-item
2022-07-19 09:55:39	ga_ls9c_ard_3-2-1_096080_2022-07-19_final.stac-item
2022-07-25 10:57:09	ga_ls9c_ard_3-2-1_106079_2022-07-25_final.stac-item
2022-07-27 10:43:37	ga_ls9c_ard_3-2-1_104076_2022-07-27_final.stac-item
2022-08-04 09:53:53	ga_ls9c_ard_3-2-1_096075_2022-08-04_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-08-22 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-08-22_final.stac-item
2022-08-26 10:57:25	ga_ls9c_ard_3-2-1_106079_2022-08-26_final.stac-item
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final.stac-item
2022-10-10 10:27:28	ga_ls9c_ard_3-2-1_101081_2022-10-10_final.stac-item
2022-10-19 11:58:38	ga_ls9c_ard_3-2-1_116077_2022-10-19_final.stac-item
2022-10-25 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-10-25_final.stac-item
2022-10-29 10:58:25	ga_ls9c_ard_3-2-1_106081_2022-10-29_final.stac-item
2022-11-17 09:50:04	ga_ls9c_ard_3-2-1_095080_2022-11-17_final.stac-item
2022-11-20 10:20:58	ga_ls9c_ard_3-2-1_100080_2022-11-20_final.stac-item
2022-12-06 10:21:20	ga_ls9c_ard_3-2-1_100081_2022-12-06_final.stac-item
2022-12-25 10:51:00	ga_ls9c_ard_3-2-1_105078_2022-12-25_final.stac-item
2023-01-10 10:51:02	ga_ls9c_ard_3-2-1_105078_2023-01-10_final.stac-item
2023-01-15 09:30:39	ga_ls9c_ard_3-2-1_092078_2023-01-15_final.stac-item
2023-01-20 09:49:53	ga_ls9c_ard_3-2-1_095080_2023-01-20_final.stac-item
2023-01-27 09:55:23	ga_ls9c_ard_3-2-1_096078_2023-01-27_final.stac-item
2023-01-27 09:56:11	ga_ls9c_ard_3-2-1_096080_2023-01-27_final.stac-item
2023-01-29 09:43:27	ga_ls9c_ard_3-2-1_094079_2023-01-29_final.stac-item
2023-02-04 10:45:19	ga_ls9c_ard_3-2-1_104079_2023-02-04_final.stac-item
2023-02-05 09:48:30	ga_ls9c_ard_3-2-1_095076_2023-02-05_final.stac-item
2023-02-05 11:28:35	ga_ls9c_ard_3-2-1_111079_2023-02-05_final.stac-item
2023-02-08 10:21:00	ga_ls9c_ard_3-2-1_100080_2023-02-08_final.stac-item
2023-02-08 10:21:24	ga_ls9c_ard_3-2-1_100081_2023-02-08_final.stac-item
2023-02-16 09:31:30	ga_ls9c_ard_3-2-1_092080_2023-02-16_final.stac-item
2023-04-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2023-04-23_final.stac-item
2023-04-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2023-04-23_final.stac-item
2023-04-24 10:00:11	ga_ls9c_ard_3-2-1_097076_2023-04-24_final.stac-item
2023-04-25 10:43:26	ga_ls9c_ard_3-2-1_104076_2023-04-25_final.stac-item
2023-04-26 09:49:48	ga_ls9c_ard_3-2-1_095081_2023-04-26_final.stac-item
2023-04-26 11:27:29	ga_ls9c_ard_3-2-1_111078_2023-04-26_final.stac-item
2023-04-28 09:37:48	ga_ls9c_ard_3-2-1_093082_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
2023-05-28 11:25:58	ga_ls9c_ard_3-2-1_111075_2023-05-28_final.stac-item
2023-07-15 09:49:12	ga_ls9c_ard_3-2-1_095080_2023-07-15_final.stac-item
2023-07-15 09:49:36	ga_ls9c_ard_3-2-1_095081_2023-07-15_final.stac-item
2023-07-15 11:26:29	ga_ls9c_ard_3-2-1_111076_2023-07-15_final.stac-item
2023-07-15 11:27:17	ga_ls9c_ard_3-2-1_111078_2023-07-15_final.stac-item
2023-07-20 10:08:32	ga_ls9c_ard_3-2-1_098082_2023-07-20_final.stac-item
2023-07-21 10:51:00	ga_ls9c_ard_3-2-1_105080_2023-07-21_final.stac-item
2023-07-22 09:53:22	ga_ls9c_ard_3-2-1_096075_2023-07-22_final.stac-item
2023-07-22 09:55:22	ga_ls9c_ard_3-2-1_096080_2023-07-22_final.stac-item
2023-07-23 10:36:14	ga_ls9c_ard_3-2-1_103074_2023-07-23_final.stac-item
2023-07-23 10:37:02	ga_ls9c_ard_3-2-1_103076_2023-07-23_final.stac-item
2023-07-24 09:41:24	ga_ls9c_ard_3-2-1_094076_2023-07-24_final.stac-item
2023-07-24 09:41:48	ga_ls9c_ard_3-2-1_094077_2023-07-24_final.stac-item
2023-07-24 11:21:53	ga_ls9c_ard_3-2-1_110080_2023-07-24_final.stac-item
2023-07-26 09:30:15	ga_ls9c_ard_3-2-1_092079_2023-07-26_final.stac-item
2023-07-26 09:31:03	ga_ls9c_ard_3-2-1_092081_2023-07-26_final.stac-item
2023-07-28 10:56:49	ga_ls9c_ard_3-2-1_106079_2023-07-28_final.stac-item
2023-07-29 10:00:01	ga_ls9c_ard_3-2-1_097076_2023-07-29_final.stac-item
2023-08-02 09:36:09	ga_ls9c_ard_3-2-1_093078_2023-08-02_final.stac-item
2023-08-02 11:15:50	ga_ls9c_ard_3-2-1_109080_2023-08-02_final.stac-item
2023-08-04 11:04:17	ga_ls9c_ard_3-2-1_107082_2023-08-04_final.stac-item
2023-08-08 10:36:24	ga_ls9c_ard_3-2-1_103074_2023-08-08_final.stac-item
2023-10-14 11:10:09	ga_ls9c_ard_3-2-1_108080_2023-10-14_final.stac-item
2023-10-17 10:00:36	ga_ls9c_ard_3-2-1_097076_2023-10-17_final.stac-item
2023-10-17 10:01:00	ga_ls9c_ard_3-2-1_097077_2023-10-17_final.stac-item
2023-10-19 09:48:15	ga_ls9c_ard_3-2-1_095076_2023-10-19_final.stac-item
2023-10-19 11:27:56	ga_ls9c_ard_3-2-1_111078_2023-10-19_final.stac-item
2023-10-20 10:33:06	ga_ls9c_ard_3-2-1_102080_2023-10-20_final.stac-item
2023-10-21 11:15:34	ga_ls9c_ard_3-2-1_109078_2023-10-21_final.stac-item
2023-10-21 11:15:58	ga_ls9c_ard_3-2-1_109079_2023-10-21_final.stac-item
2023-10-21 11:16:22	ga_ls9c_ard_3-2-1_109080_2023-10-21_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 10:08:46	ga_ls9c_ard_3-2-1_098081_2023-10-24_final.stac-item
2023-10-25 10:51:14	ga_ls9c_ard_3-2-1_105079_2023-10-25_final.stac-item
2023-10-26 09:54:00	ga_ls9c_ard_3-2-1_096075_2023-10-26_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 09:56:48	ga_ls9c_ard_3-2-1_096082_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
2023-10-28 09:43:13	ga_ls9c_ard_3-2-1_094079_2023-10-28_final.stac-item
2023-10-30 09:30:26	ga_ls9c_ard_3-2-1_092078_2023-10-30_final.stac-item
2023-10-30 11:09:19	ga_ls9c_ard_3-2-1_108078_2023-10-30_final.stac-item
2023-11-02 10:00:05	ga_ls9c_ard_3-2-1_097075_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
2023-11-04 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-11-04_final.stac-item
2023-11-14 10:26:51	ga_ls9c_ard_3-2-1_101080_2023-11-14_final.stac-item
2023-11-15 09:30:25	ga_ls9c_ard_3-2-1_092078_2023-11-15_final.stac-item
2023-11-21 10:33:07	ga_ls9c_ard_3-2-1_102080_2023-11-21_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
2023-11-24 11:03:15	ga_ls9c_ard_3-2-1_107078_2023-11-24_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