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
2021-11-03 09:56:09	ga_ls9c_ard_3-2-1_096078_2021-11-03_final.stac-item
2021-11-03 09:58:56	ga_ls9c_ard_3-2-1_096085_2021-11-03_final.stac-item
2021-11-05 09:40:36	ga_ls9c_ard_3-2-1_093086_2021-11-05_final.stac-item
2021-11-07 10:58:32	ga_ls9c_ard_3-2-1_106081_2021-11-07_final.stac-item
2021-11-08 09:55:51	ga_ls9c_ard_3-2-1_097071_2021-11-08_final.stac-item
2021-11-10 11:15:46	ga_ls9c_ard_3-2-1_110071_2021-11-10_final.stac-item
2021-11-12 09:23:56	ga_ls9c_ard_3-2-1_091085_2021-11-11_final.stac-item
2021-11-17 09:26:28	ga_ls9c_ard_3-2-1_091085_2021-11-16_final.stac-item
2021-11-18 11:40:14	ga_ls9c_ard_3-2-1_113073_2021-11-18_final.stac-item
2021-11-22 09:28:51	ga_ls9c_ard_3-2-1_091085_2021-11-21_final.stac-item
2021-11-24 10:44:46	ga_ls9c_ard_3-2-1_104075_2021-11-24_final.stac-item
2021-12-07 09:52:58	ga_ls9c_ard_3-2-1_096072_2021-12-07_final.stac-item
2021-12-07 11:31:51	ga_ls9c_ard_3-2-1_112072_2021-12-07_final.stac-item
2021-12-10 10:25:26	ga_ls9c_ard_3-2-1_101076_2021-12-10_final.stac-item
2021-12-12 10:09:51	ga_ls9c_ard_3-2-1_099068_2021-12-12_final.stac-item
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-18 09:34:43	ga_ls9c_ard_3-2-1_093073_2021-12-18_final.stac-item
2021-12-26 10:25:22	ga_ls9c_ard_3-2-1_101076_2021-12-26_final.stac-item
2021-12-29 09:21:23	ga_ls9c_ard_3-2-1_090086_2021-12-28_final.stac-item
2021-12-30 11:38:20	ga_ls9c_ard_3-2-1_113073_2021-12-30_final.stac-item
2022-01-03 09:34:43	ga_ls9c_ard_3-2-1_093073_2022-01-03_final.stac-item
2022-01-11 10:25:19	ga_ls9c_ard_3-2-1_101076_2022-01-11_final.stac-item
2022-01-13 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-01-13_final.stac-item
2022-01-14 09:18:31	ga_ls9c_ard_3-2-1_090079_2022-01-13_final.stac-item
2022-01-15 11:38:17	ga_ls9c_ard_3-2-1_113073_2022-01-15_final.stac-item
2022-01-17 09:46:39	ga_ls9c_ard_3-2-1_095072_2022-01-17_final.stac-item
2022-01-19 09:34:42	ga_ls9c_ard_3-2-1_093073_2022-01-19_final.stac-item
2022-01-26 11:19:47	ga_ls9c_ard_3-2-1_110073_2022-01-26_final.stac-item
2022-01-30 09:18:34	ga_ls9c_ard_3-2-1_090079_2022-01-29_final.stac-item
2022-02-02 09:49:04	ga_ls9c_ard_3-2-1_095078_2022-02-02_final.stac-item
2022-02-04 09:33:55	ga_ls9c_ard_3-2-1_093071_2022-02-04_final.stac-item
2022-02-09 11:34:06	ga_ls9c_ard_3-2-1_112078_2022-02-09_final.stac-item
2022-02-11 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-02-11_final.stac-item
2022-02-12 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-02-12_final.stac-item
2022-02-14 10:14:08	ga_ls9c_ard_3-2-1_099079_2022-02-14_final.stac-item
2022-02-15 10:55:23	ga_ls9c_ard_3-2-1_106074_2022-02-15_final.stac-item
2022-02-20 09:33:48	ga_ls9c_ard_3-2-1_093071_2022-02-20_final.stac-item
2022-02-20 09:34:35	ga_ls9c_ard_3-2-1_093073_2022-02-20_final.stac-item
2022-02-25 11:33:57	ga_ls9c_ard_3-2-1_112078_2022-02-25_final.stac-item
2022-02-27 09:45:52	ga_ls9c_ard_3-2-1_094086_2022-02-27_final.stac-item
2022-03-07 10:33:17	ga_ls9c_ard_3-2-1_102081_2022-03-07_final.stac-item
2022-03-09 10:20:32	ga_ls9c_ard_3-2-1_100080_2022-03-09_final.stac-item
2022-03-10 09:27:42	ga_ls9c_ard_3-2-1_091087_2022-03-09_final.stac-item
2022-03-21 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-03-21_final.stac-item
2022-03-25 10:20:27	ga_ls9c_ard_3-2-1_100080_2022-03-25_final.stac-item
2022-03-25 10:21:15	ga_ls9c_ard_3-2-1_100082_2022-03-25_final.stac-item
2022-03-27 11:46:34	ga_ls9c_ard_3-2-1_114079_2022-03-27_final.stac-item
2022-03-30 10:36:59	ga_ls9c_ard_3-2-1_103075_2022-03-30_final.stac-item
2022-04-03 10:09:28	ga_ls9c_ard_3-2-1_099068_2022-04-03_final.stac-item
2022-04-09 09:33:33	ga_ls9c_ard_3-2-1_093071_2022-04-09_final.stac-item
2022-04-15 10:36:53	ga_ls9c_ard_3-2-1_103075_2022-04-15_final.stac-item
2022-04-20 09:18:04	ga_ls9c_ard_3-2-1_090079_2022-04-19_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-04-25 09:39:23	ga_ls9c_ard_3-2-1_093086_2022-04-25_final.stac-item
2022-04-25 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-05-04 11:07:16	ga_ls9c_ard_3-2-1_108074_2022-05-04_final.stac-item
2022-05-08 10:43:42	ga_ls9c_ard_3-2-1_104077_2022-05-08_final.stac-item
2022-05-11 09:39:17	ga_ls9c_ard_3-2-1_093086_2022-05-11_final.stac-item
2022-05-15 09:10:07	ga_ls9c_ard_3-2-1_089075_2022-05-14_final.stac-item
2022-05-18 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-05-18_final.stac-item
2022-05-20 11:07:03	ga_ls9c_ard_3-2-1_108074_2022-05-20_final.stac-item
2022-05-23 10:01:04	ga_ls9c_ard_3-2-1_097079_2022-05-23_final.stac-item
2022-05-24 09:06:15	ga_ls9c_ard_3-2-1_088081_2022-05-23_final.stac-item
2022-05-25 09:45:55	ga_ls9c_ard_3-2-1_095072_2022-05-25_final.stac-item
2022-05-30 10:03:16	ga_ls9c_ard_3-2-1_098069_2022-05-30_final.stac-item
2022-06-02 10:38:34	ga_ls9c_ard_3-2-1_103080_2022-06-02_final.stac-item
2022-06-03 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-06-03_final.stac-item
2022-06-05 11:10:40	ga_ls9c_ard_3-2-1_108083_2022-06-05_final.stac-item
2022-06-10 09:45:57	ga_ls9c_ard_3-2-1_095072_2022-06-10_final.stac-item
2022-06-17 09:57:25	ga_ls9c_ard_3-2-1_096085_2022-06-17_final.stac-item
2022-06-18 10:39:30	ga_ls9c_ard_3-2-1_103082_2022-06-18_final.stac-item
2022-06-19 09:45:30	ga_ls9c_ard_3-2-1_094086_2022-06-19_final.stac-item
2022-06-21 09:30:01	ga_ls9c_ard_3-2-1_092078_2022-06-21_final.stac-item
2022-07-02 09:10:23	ga_ls9c_ard_3-2-1_089075_2022-07-01_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-08 10:13:46	ga_ls9c_ard_3-2-1_099079_2022-07-08_final.stac-item
2022-07-11 09:06:33	ga_ls9c_ard_3-2-1_088081_2022-07-10_final.stac-item
2022-07-16 09:27:29	ga_ls9c_ard_3-2-1_091087_2022-07-15_final.stac-item
2022-07-18 09:10:22	ga_ls9c_ard_3-2-1_089075_2022-07-17_final.stac-item
2022-07-20 10:36:56	ga_ls9c_ard_3-2-1_103075_2022-07-20_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-26 09:59:09	ga_ls9c_ard_3-2-1_097073_2022-07-26_final.stac-item
2022-07-28 09:52:24	ga_ls9c_ard_3-2-1_095087_2022-07-28_final.stac-item
2022-07-30 09:34:29	ga_ls9c_ard_3-2-1_093073_2022-07-30_final.stac-item
2022-08-02 10:03:49	ga_ls9c_ard_3-2-1_098069_2022-08-02_final.stac-item
2022-08-06 09:45:08	ga_ls9c_ard_3-2-1_094084_2022-08-06_final.stac-item
2022-08-06 09:45:56	ga_ls9c_ard_3-2-1_094086_2022-08-06_final.stac-item
2022-08-08 11:07:41	ga_ls9c_ard_3-2-1_108074_2022-08-08_final.stac-item
2022-08-13 09:48:59	ga_ls9c_ard_3-2-1_095078_2022-08-13_final.stac-item
2022-08-15 11:17:07	ga_ls9c_ard_3-2-1_109082_2022-08-15_final.stac-item
2022-08-17 11:04:46	ga_ls9c_ard_3-2-1_107082_2022-08-17_final.stac-item
2022-08-26 09:20:31	ga_ls9c_ard_3-2-1_090084_2022-08-25_final.stac-item
2022-08-29 09:49:02	ga_ls9c_ard_3-2-1_095078_2022-08-29_final.stac-item
2022-08-31 09:39:52	ga_ls9c_ard_3-2-1_093086_2022-08-31_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
2022-09-13 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-09-12_final.stac-item
2022-09-16 11:16:25	ga_ls9c_ard_3-2-1_109080_2022-09-16_final.stac-item
2022-09-20 10:46:32	ga_ls9c_ard_3-2-1_105067_2022-09-20_final.stac-item
2022-09-27 10:58:20	ga_ls9c_ard_3-2-1_106081_2022-09-27_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