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
2021-11-12 10:59:01	ga_ls9c_ard_3-2-1_106076_2021-11-12_final.stac-item
2021-12-09 09:41:47	ga_ls9c_ard_3-2-1_094075_2021-12-09_final.stac-item
2021-12-18 09:39:54	ga_ls9c_ard_3-2-1_093086_2021-12-18_final.stac-item
2021-12-18 11:15:12	ga_ls9c_ard_3-2-1_109077_2021-12-18_final.stac-item
2021-12-23 11:33:21	ga_ls9c_ard_3-2-1_112076_2021-12-23_final.stac-item
2021-12-25 09:44:06	ga_ls9c_ard_3-2-1_094081_2021-12-25_final.stac-item
2022-01-03 11:15:12	ga_ls9c_ard_3-2-1_109077_2022-01-03_final.stac-item
2022-01-04 10:18:47	ga_ls9c_ard_3-2-1_100075_2022-01-04_final.stac-item
2022-01-31 11:39:31	ga_ls9c_ard_3-2-1_113076_2022-01-31_final.stac-item
2022-02-11 09:44:03	ga_ls9c_ard_3-2-1_094081_2022-02-11_final.stac-item
2022-02-22 11:03:53	ga_ls9c_ard_3-2-1_107080_2022-02-22_final.stac-item
2022-03-08 09:38:52	ga_ls9c_ard_3-2-1_093084_2022-03-08_final.stac-item
2022-03-25 10:21:15	ga_ls9c_ard_3-2-1_100082_2022-03-25_final.stac-item
2022-04-04 09:18:14	ga_ls9c_ard_3-2-1_090079_2022-04-03_final.stac-item
2022-04-05 11:40:23	ga_ls9c_ard_3-2-1_113079_2022-04-05_final.stac-item
2022-04-13 10:47:41	ga_ls9c_ard_3-2-1_105071_2022-04-13_final.stac-item
2022-05-01 10:39:34	ga_ls9c_ard_3-2-1_103082_2022-05-01_final.stac-item
2022-05-03 10:26:48	ga_ls9c_ard_3-2-1_101081_2022-05-03_final.stac-item
2022-05-16 09:54:09	ga_ls9c_ard_3-2-1_096077_2022-05-16_final.stac-item
2022-05-17 10:37:24	ga_ls9c_ard_3-2-1_103077_2022-05-17_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-21 10:11:02	ga_ls9c_ard_3-2-1_099073_2022-05-21_final.stac-item
2022-06-19 09:43:30	ga_ls9c_ard_3-2-1_094081_2022-06-19_final.stac-item
2022-07-01 11:44:54	ga_ls9c_ard_3-2-1_114075_2022-07-01_final.stac-item
2022-07-04 10:38:54	ga_ls9c_ard_3-2-1_103080_2022-07-04_final.stac-item
2022-07-06 10:24:56	ga_ls9c_ard_3-2-1_101076_2022-07-06_final.stac-item
2022-07-14 11:14:43	ga_ls9c_ard_3-2-1_109077_2022-07-14_final.stac-item
2022-07-15 10:20:18	ga_ls9c_ard_3-2-1_100080_2022-07-15_final.stac-item
2022-07-18 10:47:40	ga_ls9c_ard_3-2-1_105071_2022-07-18_final.stac-item
2022-07-27 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-07-27_final.stac-item
2022-08-01 09:26:56	ga_ls9c_ard_3-2-1_091085_2022-07-31_final.stac-item
2022-08-07 10:25:13	ga_ls9c_ard_3-2-1_101076_2022-08-07_final.stac-item
2022-08-10 09:18:27	ga_ls9c_ard_3-2-1_090079_2022-08-09_final.stac-item
2022-08-11 09:59:20	ga_ls9c_ard_3-2-1_097073_2022-08-11_final.stac-item
2022-08-23 10:25:18	ga_ls9c_ard_3-2-1_101076_2022-08-23_final.stac-item
2022-08-31 11:17:09	ga_ls9c_ard_3-2-1_109082_2022-08-31_final.stac-item
2022-09-01 10:20:44	ga_ls9c_ard_3-2-1_100080_2022-09-01_final.stac-item
2022-09-18 11:04:52	ga_ls9c_ard_3-2-1_107082_2022-09-18_final.stac-item
2022-09-19 11:45:45	ga_ls9c_ard_3-2-1_114076_2022-09-19_final.stac-item
2022-09-24 10:25:26	ga_ls9c_ard_3-2-1_101076_2022-09-24_final.stac-item
2022-10-07 11:35:24	ga_ls9c_ard_3-2-1_112081_2022-10-07_final.stac-item
2022-10-25 09:42:40	ga_ls9c_ard_3-2-1_094077_2022-10-25_final.stac-item
2023-02-18 09:19:06	ga_ls9c_ard_3-2-1_090080_2023-02-17_final.stac-item
2023-02-20 10:45:35	ga_ls9c_ard_3-2-1_104080_2023-02-20_final.stac-item
2023-02-21 09:50:20	ga_ls9c_ard_3-2-1_095081_2023-02-21_final.stac-item
2023-02-25 11:03:38	ga_ls9c_ard_3-2-1_107079_2023-02-25_final.stac-item
2023-03-09 11:29:49	ga_ls9c_ard_3-2-1_111083_2023-03-09_final.stac-item
2023-03-20 09:30:47	ga_ls9c_ard_3-2-1_092079_2023-03-20_final.stac-item
2023-03-20 11:06:28	ga_ls9c_ard_3-2-1_108071_2023-03-20_final.stac-item
2023-03-26 10:32:53	ga_ls9c_ard_3-2-1_102080_2023-03-26_final.stac-item
2023-04-13 10:17:34	ga_ls9c_ard_3-2-1_100073_2023-04-13_final.stac-item
2023-04-14 11:00:49	ga_ls9c_ard_3-2-1_107073_2023-04-14_final.stac-item
2023-04-15 10:05:11	ga_ls9c_ard_3-2-1_098073_2023-04-15_final.stac-item
2023-04-15 11:45:40	ga_ls9c_ard_3-2-1_114077_2023-04-15_final.stac-item
2023-04-17 11:34:55	ga_ls9c_ard_3-2-1_112081_2023-04-17_final.stac-item
2023-04-19 11:18:10	ga_ls9c_ard_3-2-1_110070_2023-04-19_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 10:03:47	ga_ls9c_ard_3-2-1_097085_2023-04-24_final.stac-item
2023-04-29 10:17:28	ga_ls9c_ard_3-2-1_100073_2023-04-29_final.stac-item
2023-04-29 10:20:39	ga_ls9c_ard_3-2-1_100081_2023-04-29_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-05-01 11:45:09	ga_ls9c_ard_3-2-1_114076_2023-05-01_final.stac-item
2023-05-01 11:45:56	ga_ls9c_ard_3-2-1_114078_2023-05-01_final.stac-item
2023-05-02 09:13:49	ga_ls9c_ard_3-2-1_089084_2023-05-01_final.stac-item
2023-05-04 10:37:30	ga_ls9c_ard_3-2-1_103077_2023-05-04_final.stac-item
2023-05-07 09:30:42	ga_ls9c_ard_3-2-1_092080_2023-05-07_final.stac-item
2023-05-11 10:40:52	ga_ls9c_ard_3-2-1_104070_2023-05-11_final.stac-item
2023-05-11 10:41:16	ga_ls9c_ard_3-2-1_104071_2023-05-11_final.stac-item
2023-05-17 10:05:20	ga_ls9c_ard_3-2-1_098074_2023-05-17_final.stac-item
2023-05-17 11:44:13	ga_ls9c_ard_3-2-1_114074_2023-05-17_final.stac-item
2023-05-17 11:45:25	ga_ls9c_ard_3-2-1_114077_2023-05-17_final.stac-item
2023-05-20 10:35:48	ga_ls9c_ard_3-2-1_103073_2023-05-20_final.stac-item
2023-06-03 10:46:52	ga_ls9c_ard_3-2-1_105070_2023-06-03_final.stac-item
2023-06-21 10:35:34	ga_ls9c_ard_3-2-1_103073_2023-06-21_final.stac-item
2023-06-28 10:41:25	ga_ls9c_ard_3-2-1_104072_2023-06-28_final.stac-item
2023-07-06 09:52:31	ga_ls9c_ard_3-2-1_096073_2023-07-06_final.stac-item
2023-07-09 10:25:03	ga_ls9c_ard_3-2-1_101077_2023-07-09_final.stac-item
2023-07-10 09:31:26	ga_ls9c_ard_3-2-1_092082_2023-07-10_final.stac-item
2023-09-08 09:57:00	ga_ls9c_ard_3-2-1_096083_2023-09-08_final.stac-item
2023-09-09 10:37:53	ga_ls9c_ard_3-2-1_103077_2023-09-09_final.stac-item
2023-09-11 10:23:32	ga_ls9c_ard_3-2-1_101072_2023-09-11_final.stac-item
2023-09-12 09:31:55	ga_ls9c_ard_3-2-1_092082_2023-09-12_final.stac-item
2023-09-13 10:15:11	ga_ls9c_ard_3-2-1_099082_2023-09-13_final.stac-item
2023-09-14 09:19:34	ga_ls9c_ard_3-2-1_090082_2023-09-13_final.stac-item
2023-09-15 11:41:19	ga_ls9c_ard_3-2-1_113081_2023-09-15_final.stac-item
2023-09-18 10:29:21	ga_ls9c_ard_3-2-1_102071_2023-09-18_final.stac-item
2023-09-19 09:38:31	ga_ls9c_ard_3-2-1_093083_2023-09-19_final.stac-item
2023-09-19 09:38:55	ga_ls9c_ard_3-2-1_093084_2023-09-19_final.stac-item
2023-09-19 11:13:00	ga_ls9c_ard_3-2-1_109072_2023-09-19_final.stac-item
2023-09-24 09:53:25	ga_ls9c_ard_3-2-1_096074_2023-09-24_final.stac-item
2023-09-27 10:23:29	ga_ls9c_ard_3-2-1_101072_2023-09-27_final.stac-item
2023-09-28 11:10:44	ga_ls9c_ard_3-2-1_108082_2023-09-28_final.stac-item
2023-10-02 10:44:53	ga_ls9c_ard_3-2-1_104079_2023-10-02_final.stac-item
2023-10-03 09:47:41	ga_ls9c_ard_3-2-1_095075_2023-10-03_final.stac-item
2023-10-04 10:29:46	ga_ls9c_ard_3-2-1_102072_2023-10-04_final.stac-item
2023-10-10 09:53:32	ga_ls9c_ard_3-2-1_096074_2023-10-10_final.stac-item
2023-10-10 09:56:20	ga_ls9c_ard_3-2-1_096081_2023-10-10_final.stac-item
2023-10-14 09:32:04	ga_ls9c_ard_3-2-1_092082_2023-10-14_final.stac-item
2023-10-14 11:10:33	ga_ls9c_ard_3-2-1_108081_2023-10-14_final.stac-item
2023-10-14 11:10:57	ga_ls9c_ard_3-2-1_108082_2023-10-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years