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
2021-11-08 09:59:02	ga_ls9c_ard_3-2-1_097079_2021-11-08_final.stac-item
2021-12-08 10:35:25	ga_ls9c_ard_3-2-1_103070_2021-12-08_final.stac-item
2021-12-19 11:58:52	ga_ls9c_ard_3-2-1_116078_2021-12-19_final.stac-item
2021-12-23 09:58:04	ga_ls9c_ard_3-2-1_096085_2021-12-23_final.stac-item
2021-12-23 11:36:09	ga_ls9c_ard_3-2-1_112083_2021-12-23_final.stac-item
2021-12-30 11:41:32	ga_ls9c_ard_3-2-1_113081_2021-12-30_final.stac-item
2022-01-13 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-01-13_final.stac-item
2022-01-18 10:31:31	ga_ls9c_ard_3-2-1_102076_2022-01-18_final.stac-item
2022-02-10 10:35:41	ga_ls9c_ard_3-2-1_103071_2022-02-10_final.stac-item
2022-02-13 09:32:52	ga_ls9c_ard_3-2-1_092084_2022-02-13_final.stac-item
2022-02-15 10:56:59	ga_ls9c_ard_3-2-1_106078_2022-02-15_final.stac-item
2022-02-26 10:37:55	ga_ls9c_ard_3-2-1_103077_2022-02-26_final.stac-item
2022-03-03 09:18:19	ga_ls9c_ard_3-2-1_090079_2022-03-02_final.stac-item
2022-03-06 11:24:55	ga_ls9c_ard_3-2-1_111071_2022-03-06_final.stac-item
2022-03-19 10:56:47	ga_ls9c_ard_3-2-1_106078_2022-03-19_final.stac-item
2022-04-02 11:05:54	ga_ls9c_ard_3-2-1_108070_2022-04-02_final.stac-item
2022-04-07 09:51:07	ga_ls9c_ard_3-2-1_095084_2022-04-07_final.stac-item
2022-04-16 09:43:39	ga_ls9c_ard_3-2-1_094081_2022-04-16_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-05-14 11:45:26	ga_ls9c_ard_3-2-1_114077_2022-05-14_final.stac-item
2022-05-22 09:20:12	ga_ls9c_ard_3-2-1_090085_2022-05-21_final.stac-item
2022-05-26 10:33:10	ga_ls9c_ard_3-2-1_102082_2022-05-26_final.stac-item
2022-06-08 10:03:05	ga_ls9c_ard_3-2-1_097084_2022-06-08_final.stac-item
2022-06-12 11:16:06	ga_ls9c_ard_3-2-1_109081_2022-06-12_final.stac-item
2022-06-13 10:17:42	ga_ls9c_ard_3-2-1_100074_2022-06-13_final.stac-item
2022-06-15 11:44:39	ga_ls9c_ard_3-2-1_114075_2022-06-15_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-06-28 09:35:07	ga_ls9c_ard_3-2-1_093075_2022-06-28_final.stac-item
2022-06-30 11:02:26	ga_ls9c_ard_3-2-1_107077_2022-06-30_final.stac-item
2022-07-07 11:11:23	ga_ls9c_ard_3-2-1_108084_2022-07-07_final.stac-item
2022-07-10 10:03:23	ga_ls9c_ard_3-2-1_097084_2022-07-10_final.stac-item
2022-07-15 10:18:42	ga_ls9c_ard_3-2-1_100076_2022-07-15_final.stac-item
2022-07-25 10:54:21	ga_ls9c_ard_3-2-1_106072_2022-07-25_final.stac-item
2022-08-02 10:06:13	ga_ls9c_ard_3-2-1_098075_2022-08-02_final.stac-item
2022-08-04 09:51:53	ga_ls9c_ard_3-2-1_096070_2022-08-04_final.stac-item
2022-08-04 09:53:29	ga_ls9c_ard_3-2-1_096074_2022-08-04_final.stac-item
2022-08-19 10:52:01	ga_ls9c_ard_3-2-1_105081_2022-08-19_final.stac-item
2022-08-21 10:40:03	ga_ls9c_ard_3-2-1_103082_2022-08-21_final.stac-item
2022-08-26 09:20:08	ga_ls9c_ard_3-2-1_090083_2022-08-25_final.stac-item
2022-08-31 11:16:45	ga_ls9c_ard_3-2-1_109081_2022-08-31_final.stac-item
2022-09-02 09:27:06	ga_ls9c_ard_3-2-1_091085_2022-09-01_final.stac-item
2022-09-09 09:28:05	ga_ls9c_ard_3-2-1_092072_2022-09-08_final.stac-item
2022-09-09 09:30:29	ga_ls9c_ard_3-2-1_092078_2022-09-09_final.stac-item
2022-09-13 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-09-12_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-10-22 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-10-22_final.stac-item
2022-10-22 10:51:51	ga_ls9c_ard_3-2-1_105080_2022-10-22_final.stac-item
2022-10-25 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-10-25_final.stac-item
2022-11-03 09:40:50	ga_ls9c_ard_3-2-1_093088_2022-11-03_final.stac-item
2022-11-04 11:58:59	ga_ls9c_ard_3-2-1_116078_2022-11-04_final.stac-item
2022-11-11 10:24:21	ga_ls9c_ard_3-2-1_101073_2022-11-11_final.stac-item
2022-11-17 09:48:28	ga_ls9c_ard_3-2-1_095076_2022-11-17_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-11-21 11:03:50	ga_ls9c_ard_3-2-1_107079_2022-11-21_final.stac-item
2022-11-24 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-11-24_final.stac-item
2022-11-29 11:52:02	ga_ls9c_ard_3-2-1_115076_2022-11-29_final.stac-item
2022-12-10 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-12-10_final.stac-item
2022-12-12 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-12-12_final.stac-item
2023-01-06 11:15:23	ga_ls9c_ard_3-2-1_109077_2023-01-06_final.stac-item
2023-01-10 09:11:45	ga_ls9c_ard_3-2-1_089077_2023-01-09_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-25 10:08:30	ga_ls9c_ard_3-2-1_098080_2023-01-25_final.stac-item
2023-01-26 09:16:54	ga_ls9c_ard_3-2-1_089090_2023-01-25_final.stac-item
2023-01-27 09:53:23	ga_ls9c_ard_3-2-1_096073_2023-01-27_final.stac-item
2023-01-27 09:58:10	ga_ls9c_ard_3-2-1_096085_2023-01-27_final.stac-item
2023-01-29 09:43:03	ga_ls9c_ard_3-2-1_094078_2023-01-29_final.stac-item
2023-02-05 09:50:30	ga_ls9c_ard_3-2-1_095081_2023-02-05_final.stac-item
2023-02-09 11:03:04	ga_ls9c_ard_3-2-1_107077_2023-02-09_final.stac-item
2023-02-11 09:15:01	ga_ls9c_ard_3-2-1_089085_2023-02-10_final.stac-item
2023-02-16 09:31:06	ga_ls9c_ard_3-2-1_092079_2023-02-16_final.stac-item
2023-02-25 09:28:20	ga_ls9c_ard_3-2-1_091088_2023-02-24_final.stac-item
2023-02-25 11:00:50	ga_ls9c_ard_3-2-1_107072_2023-02-25_final.stac-item
2023-05-04 10:35:54	ga_ls9c_ard_3-2-1_103073_2023-05-04_final.stac-item
2023-05-05 09:45:51	ga_ls9c_ard_3-2-1_094087_2023-05-05_final.stac-item
2023-05-13 10:28:54	ga_ls9c_ard_3-2-1_102071_2023-05-13_final.stac-item
2023-05-31 10:17:11	ga_ls9c_ard_3-2-1_100073_2023-05-31_final.stac-item
2023-05-31 11:58:03	ga_ls9c_ard_3-2-1_116078_2023-05-31_final.stac-item
2023-06-01 09:24:21	ga_ls9c_ard_3-2-1_091080_2023-05-31_final.stac-item
2023-06-02 10:03:13	ga_ls9c_ard_3-2-1_098069_2023-06-02_final.stac-item
2023-06-02 11:44:53	ga_ls9c_ard_3-2-1_114076_2023-06-02_final.stac-item
2023-06-04 09:51:15	ga_ls9c_ard_3-2-1_096070_2023-06-04_final.stac-item
2023-06-13 09:49:21	ga_ls9c_ard_3-2-1_095081_2023-06-13_final.stac-item
2023-06-21 10:35:58	ga_ls9c_ard_3-2-1_103074_2023-06-21_final.stac-item
2023-06-22 11:20:02	ga_ls9c_ard_3-2-1_110076_2023-06-22_final.stac-item
2023-06-24 09:28:23	ga_ls9c_ard_3-2-1_092075_2023-06-23_final.stac-item
2023-07-05 09:13:14	ga_ls9c_ard_3-2-1_089083_2023-07-04_final.stac-item
2023-07-13 10:03:09	ga_ls9c_ard_3-2-1_097084_2023-07-13_final.stac-item
2023-07-15 11:29:17	ga_ls9c_ard_3-2-1_111083_2023-07-15_final.stac-item
2023-07-20 11:44:14	ga_ls9c_ard_3-2-1_114074_2023-07-20_final.stac-item
2023-08-02 09:37:21	ga_ls9c_ard_3-2-1_093081_2023-08-02_final.stac-item
2023-08-05 11:45:10	ga_ls9c_ard_3-2-1_114076_2023-08-05_final.stac-item
2023-08-10 10:22:27	ga_ls9c_ard_3-2-1_101070_2023-08-10_final.stac-item
2023-08-12 10:14:53	ga_ls9c_ard_3-2-1_099082_2023-08-12_final.stac-item
2023-08-14 10:01:20	ga_ls9c_ard_3-2-1_097079_2023-08-14_final.stac-item
2023-08-18 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-08-18_final.stac-item
2023-10-19 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-10-19_final.stac-item
2023-10-19 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-10-19_final.stac-item
2023-10-24 11:46:52	ga_ls9c_ard_3-2-1_114079_2023-10-24_final.stac-item
2023-10-25 09:14:21	ga_ls9c_ard_3-2-1_089084_2023-10-24_final.stac-item
2023-11-01 10:54:32	ga_ls9c_ard_3-2-1_106072_2023-11-01_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