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
2021-11-13 09:59:30	ga_ls9c_ard_3-2-1_097074_2021-11-13_final.stac-item
2021-11-20 09:43:13	ga_ls9c_ard_3-2-1_094074_2021-11-20_final.stac-item
2021-11-23 10:02:26	ga_ls9c_ard_3-2-1_098069_2021-11-23_final.stac-item
2021-12-06 09:12:54	ga_ls9c_ard_3-2-1_089080_2021-12-05_final.stac-item
2021-12-18 09:38:42	ga_ls9c_ard_3-2-1_093083_2021-12-18_final.stac-item
2021-12-18 11:13:36	ga_ls9c_ard_3-2-1_109073_2021-12-18_final.stac-item
2021-12-19 10:22:22	ga_ls9c_ard_3-2-1_100084_2021-12-19_final.stac-item
2021-12-21 11:47:18	ga_ls9c_ard_3-2-1_114080_2021-12-21_final.stac-item
2021-12-29 10:55:28	ga_ls9c_ard_3-2-1_106074_2021-12-29_final.stac-item
2022-01-10 11:18:57	ga_ls9c_ard_3-2-1_110071_2022-01-10_final.stac-item
2022-01-14 09:18:08	ga_ls9c_ard_3-2-1_090078_2022-01-13_final.stac-item
2022-01-22 11:45:17	ga_ls9c_ard_3-2-1_114075_2022-01-22_final.stac-item
2022-01-22 11:47:17	ga_ls9c_ard_3-2-1_114080_2022-01-22_final.stac-item
2022-01-26 11:20:59	ga_ls9c_ard_3-2-1_110076_2022-01-26_final.stac-item
2022-02-02 09:47:28	ga_ls9c_ard_3-2-1_095074_2022-02-02_final.stac-item
2022-02-07 11:47:17	ga_ls9c_ard_3-2-1_114080_2022-02-07_final.stac-item
2022-02-12 10:26:06	ga_ls9c_ard_3-2-1_101078_2022-02-12_final.stac-item
2022-02-20 09:39:47	ga_ls9c_ard_3-2-1_093086_2022-02-20_final.stac-item
2022-02-23 10:07:27	ga_ls9c_ard_3-2-1_098078_2022-02-23_final.stac-item
2022-02-23 11:44:44	ga_ls9c_ard_3-2-1_114074_2022-02-23_final.stac-item
2022-03-10 09:24:54	ga_ls9c_ard_3-2-1_091080_2022-03-09_final.stac-item
2022-03-11 11:45:51	ga_ls9c_ard_3-2-1_114077_2022-03-11_final.stac-item
2022-03-19 10:53:59	ga_ls9c_ard_3-2-1_106071_2022-03-19_final.stac-item
2022-03-19 10:54:23	ga_ls9c_ard_3-2-1_106072_2022-03-19_final.stac-item
2022-03-23 10:30:02	ga_ls9c_ard_3-2-1_102073_2022-03-23_final.stac-item
2022-03-24 11:17:17	ga_ls9c_ard_3-2-1_109083_2022-03-24_final.stac-item
2022-04-08 10:29:59	ga_ls9c_ard_3-2-1_102073_2022-04-08_final.stac-item
2022-04-09 11:12:26	ga_ls9c_ard_3-2-1_109071_2022-04-09_final.stac-item
2022-04-19 11:52:12	ga_ls9c_ard_3-2-1_115078_2022-04-19_final.stac-item
2022-05-07 10:00:51	ga_ls9c_ard_3-2-1_097078_2022-05-07_final.stac-item
2022-05-13 11:00:59	ga_ls9c_ard_3-2-1_107074_2022-05-13_final.stac-item
2022-05-18 09:44:33	ga_ls9c_ard_3-2-1_094084_2022-05-18_final.stac-item
2022-05-22 09:20:36	ga_ls9c_ard_3-2-1_090086_2022-05-21_final.stac-item
2022-05-23 11:39:57	ga_ls9c_ard_3-2-1_113079_2022-05-23_final.stac-item
2022-06-05 11:05:29	ga_ls9c_ard_3-2-1_108070_2022-06-05_final.stac-item
2022-06-07 09:20:14	ga_ls9c_ard_3-2-1_090085_2022-06-06_final.stac-item
2022-06-17 11:35:30	ga_ls9c_ard_3-2-1_112083_2022-06-17_final.stac-item
2022-06-22 10:16:07	ga_ls9c_ard_3-2-1_099085_2022-06-22_final.stac-item
2022-06-22 11:51:48	ga_ls9c_ard_3-2-1_115077_2022-06-22_final.stac-item
2022-06-28 09:34:43	ga_ls9c_ard_3-2-1_093074_2022-06-28_final.stac-item
2022-07-04 10:34:07	ga_ls9c_ard_3-2-1_103068_2022-07-04_final.stac-item
2022-07-07 11:05:48	ga_ls9c_ard_3-2-1_108070_2022-07-07_final.stac-item
2022-07-08 10:09:22	ga_ls9c_ard_3-2-1_099068_2022-07-08_final.stac-item
2022-08-03 09:16:36	ga_ls9c_ard_3-2-1_089090_2022-08-02_final.stac-item
2022-08-10 10:58:32	ga_ls9c_ard_3-2-1_106082_2022-08-10_final.stac-item
2022-08-24 11:11:22	ga_ls9c_ard_3-2-1_108083_2022-08-24_final.stac-item
2022-09-19 11:44:57	ga_ls9c_ard_3-2-1_114074_2022-09-19_final.stac-item
2022-09-28 10:00:43	ga_ls9c_ard_3-2-1_097076_2022-09-28_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-20 11:01:25	ga_ls9c_ard_3-2-1_107073_2022-10-20_final.stac-item
2022-10-27 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-10-26_final.stac-item
2022-10-29 09:20:44	ga_ls9c_ard_3-2-1_090084_2022-10-28_final.stac-item
2022-11-03 09:34:03	ga_ls9c_ard_3-2-1_093071_2022-11-03_final.stac-item
2022-11-03 11:17:43	ga_ls9c_ard_3-2-1_109083_2022-11-03_final.stac-item
2022-11-14 10:55:15	ga_ls9c_ard_3-2-1_106073_2022-11-14_final.stac-item
2022-11-17 11:26:57	ga_ls9c_ard_3-2-1_111075_2022-11-17_final.stac-item
2022-11-30 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-11-30_final.stac-item
2022-12-04 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-12-04_final.stac-item
2022-12-08 11:45:28	ga_ls9c_ard_3-2-1_114075_2022-12-08_final.stac-item
2022-12-09 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-12-09_final.stac-item
2022-12-12 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-12-12_final.stac-item
2022-12-19 11:25:43	ga_ls9c_ard_3-2-1_111072_2022-12-19_final.stac-item
2022-12-24 11:45:01	ga_ls9c_ard_3-2-1_114074_2022-12-24_final.stac-item
2022-12-26 09:57:47	ga_ls9c_ard_3-2-1_096084_2022-12-26_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2022-12-30 11:07:11	ga_ls9c_ard_3-2-1_108072_2022-12-30_final.stac-item
2022-12-31 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-12-31_final.stac-item
2023-01-08 11:02:13	ga_ls9c_ard_3-2-1_107075_2023-01-08_final.stac-item
2023-01-13 11:24:42	ga_ls9c_ard_3-2-1_110085_2023-01-13_final.stac-item
2023-01-14 10:25:53	ga_ls9c_ard_3-2-1_101077_2023-01-14_final.stac-item
2023-01-14 10:28:16	ga_ls9c_ard_3-2-1_101083_2023-01-14_final.stac-item
2023-01-20 09:47:29	ga_ls9c_ard_3-2-1_095074_2023-01-20_final.stac-item
2023-01-22 11:13:38	ga_ls9c_ard_3-2-1_109073_2023-01-22_final.stac-item
2023-01-31 11:06:24	ga_ls9c_ard_3-2-1_108070_2023-01-31_final.stac-item
2023-02-22 10:33:58	ga_ls9c_ard_3-2-1_102082_2023-02-22_final.stac-item
2023-03-03 10:28:07	ga_ls9c_ard_3-2-1_101083_2023-03-03_final.stac-item
2023-03-11 11:12:40	ga_ls9c_ard_3-2-1_109071_2023-03-11_final.stac-item
2023-04-04 10:22:39	ga_ls9c_ard_3-2-1_101070_2023-04-04_final.stac-item
2023-05-14 11:12:57	ga_ls9c_ard_3-2-1_109073_2023-05-14_final.stac-item
2023-06-29 09:49:25	ga_ls9c_ard_3-2-1_095081_2023-06-29_final.stac-item
2023-07-05 09:13:14	ga_ls9c_ard_3-2-1_089083_2023-07-04_final.stac-item
2023-07-06 11:34:36	ga_ls9c_ard_3-2-1_112081_2023-07-06_final.stac-item
2023-07-17 09:38:50	ga_ls9c_ard_3-2-1_093085_2023-07-17_final.stac-item
2023-07-18 11:57:23	ga_ls9c_ard_3-2-1_116076_2023-07-18_final.stac-item
2023-07-19 10:59:46	ga_ls9c_ard_3-2-1_107071_2023-07-19_final.stac-item
2023-07-21 09:10:55	ga_ls9c_ard_3-2-1_089077_2023-07-20_final.stac-item
2023-07-21 10:51:24	ga_ls9c_ard_3-2-1_105081_2023-07-21_final.stac-item
2023-07-24 09:44:36	ga_ls9c_ard_3-2-1_094084_2023-07-24_final.stac-item
2023-07-26 11:06:21	ga_ls9c_ard_3-2-1_108072_2023-07-26_final.stac-item
2023-07-29 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-07-29_final.stac-item
2023-08-02 09:34:33	ga_ls9c_ard_3-2-1_093074_2023-08-02_final.stac-item
2023-08-09 09:40:23	ga_ls9c_ard_3-2-1_094073_2023-08-09_final.stac-item
2023-08-11 09:28:50	ga_ls9c_ard_3-2-1_092075_2023-08-10_final.stac-item
2023-08-11 11:06:07	ga_ls9c_ard_3-2-1_108071_2023-08-11_final.stac-item
2023-08-14 09:57:44	ga_ls9c_ard_3-2-1_097070_2023-08-14_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_final.stac-item
2023-10-17 09:58:12	ga_ls9c_ard_3-2-1_097070_2023-10-17_final.stac-item
2023-10-31 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-10-31_final.stac-item
2023-11-22 11:13:36	ga_ls9c_ard_3-2-1_109073_2023-11-22_final.stac-item
2023-11-23 11:58:04	ga_ls9c_ard_3-2-1_116076_2023-11-23_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