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
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-08 09:54:15	ga_ls9c_ard_3-2-1_097067_2021-11-08_final.stac-item
2021-11-08 10:00:37	ga_ls9c_ard_3-2-1_097083_2021-11-08_final.stac-item
2021-11-10 11:16:57	ga_ls9c_ard_3-2-1_110074_2021-11-10_final.stac-item
2021-11-13 09:56:43	ga_ls9c_ard_3-2-1_097067_2021-11-13_final.stac-item
2021-11-15 11:19:25	ga_ls9c_ard_3-2-1_110074_2021-11-15_final.stac-item
2021-11-18 10:05:33	ga_ls9c_ard_3-2-1_097083_2021-11-18_final.stac-item
2021-11-20 11:21:53	ga_ls9c_ard_3-2-1_110074_2021-11-20_final.stac-item
2021-11-25 09:46:04	ga_ls9c_ard_3-2-1_095075_2021-11-25_final.stac-item
2021-12-04 09:28:05	ga_ls9c_ard_3-2-1_091087_2021-12-03_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-14 09:57:04	ga_ls9c_ard_3-2-1_097067_2021-12-14_final.stac-item
2021-12-16 09:47:52	ga_ls9c_ard_3-2-1_095075_2021-12-16_final.stac-item
2021-12-20 11:00:03	ga_ls9c_ard_3-2-1_107070_2021-12-20_final.stac-item
2021-12-27 11:11:50	ga_ls9c_ard_3-2-1_108084_2021-12-27_final.stac-item
2021-12-30 10:03:26	ga_ls9c_ard_3-2-1_097083_2021-12-30_final.stac-item
2022-01-01 09:47:53	ga_ls9c_ard_3-2-1_095075_2022-01-01_final.stac-item
2022-01-05 11:00:02	ga_ls9c_ard_3-2-1_107070_2022-01-05_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-01-14 09:22:31	ga_ls9c_ard_3-2-1_090089_2022-01-13_final.stac-item
2022-01-19 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-01-19_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-01-31 11:41:31	ga_ls9c_ard_3-2-1_113081_2022-01-31_final.stac-item
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final.stac-item
2022-02-13 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-02-13_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-02-14 10:14:08	ga_ls9c_ard_3-2-1_099079_2022-02-14_final.stac-item
2022-02-18 09:47:46	ga_ls9c_ard_3-2-1_095075_2022-02-18_final.stac-item
2022-02-24 10:46:42	ga_ls9c_ard_3-2-1_105068_2022-02-24_final.stac-item
2022-02-27 09:45:52	ga_ls9c_ard_3-2-1_094086_2022-02-27_final.stac-item
2022-03-01 11:11:34	ga_ls9c_ard_3-2-1_108084_2022-03-01_final.stac-item
2022-03-03 09:19:55	ga_ls9c_ard_3-2-1_090083_2022-03-02_final.stac-item
2022-03-03 09:22:18	ga_ls9c_ard_3-2-1_090089_2022-03-02_final.stac-item
2022-03-06 09:47:38	ga_ls9c_ard_3-2-1_095075_2022-03-06_final.stac-item
2022-03-10 09:27:42	ga_ls9c_ard_3-2-1_091087_2022-03-09_final.stac-item
2022-03-12 10:46:38	ga_ls9c_ard_3-2-1_105068_2022-03-12_final.stac-item
2022-03-22 09:47:35	ga_ls9c_ard_3-2-1_095075_2022-03-22_final.stac-item
2022-03-27 10:03:41	ga_ls9c_ard_3-2-1_098069_2022-03-27_final.stac-item
2022-04-02 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-04-02_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-16 11:19:44	ga_ls9c_ard_3-2-1_110074_2022-04-16_final.stac-item
2022-04-18 09:31:40	ga_ls9c_ard_3-2-1_092082_2022-04-18_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 10:54:34	ga_ls9c_ard_3-2-1_106073_2022-04-20_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 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-05-04 09:31:34	ga_ls9c_ard_3-2-1_092082_2022-05-04_final.stac-item
2022-05-09 09:48:28	ga_ls9c_ard_3-2-1_095078_2022-05-09_final.stac-item
2022-05-20 09:28:34	ga_ls9c_ard_3-2-1_092075_2022-05-19_final.stac-item
2022-05-23 10:01:04	ga_ls9c_ard_3-2-1_097079_2022-05-23_final.stac-item
2022-05-23 11:40:45	ga_ls9c_ard_3-2-1_113081_2022-05-23_final.stac-item
2022-05-27 09:35:09	ga_ls9c_ard_3-2-1_093076_2022-05-27_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-06-03 11:19:02	ga_ls9c_ard_3-2-1_110073_2022-06-03_final.stac-item
2022-06-05 09:28:36	ga_ls9c_ard_3-2-1_092075_2022-06-04_final.stac-item
2022-06-05 11:10:40	ga_ls9c_ard_3-2-1_108083_2022-06-05_final.stac-item
2022-06-06 10:08:40	ga_ls9c_ard_3-2-1_099067_2022-06-06_final.stac-item
2022-06-07 10:54:19	ga_ls9c_ard_3-2-1_106073_2022-06-07_final.stac-item
2022-06-17 09:57:25	ga_ls9c_ard_3-2-1_096085_2022-06-17_final.stac-item
2022-06-17 11:31:07	ga_ls9c_ard_3-2-1_112072_2022-06-17_final.stac-item
2022-06-22 10:08:56	ga_ls9c_ard_3-2-1_099067_2022-06-22_final.stac-item
2022-06-23 09:19:43	ga_ls9c_ard_3-2-1_090083_2022-06-22_final.stac-item
2022-06-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2022-06-23_final.stac-item
2022-07-01 10:06:49	ga_ls9c_ard_3-2-1_098077_2022-07-01_final.stac-item
2022-07-06 10:26:08	ga_ls9c_ard_3-2-1_101079_2022-07-06_final.stac-item
2022-07-07 09:34:06	ga_ls9c_ard_3-2-1_092088_2022-07-07_final.stac-item
2022-07-09 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-07-09_final.stac-item
2022-07-10 09:59:23	ga_ls9c_ard_3-2-1_097074_2022-07-10_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-07-14 11:11:32	ga_ls9c_ard_3-2-1_109069_2022-07-14_final.stac-item
2022-07-17 10:06:46	ga_ls9c_ard_3-2-1_098077_2022-07-17_final.stac-item
2022-07-21 11:19:49	ga_ls9c_ard_3-2-1_110074_2022-07-21_final.stac-item
2022-07-22 10:26:12	ga_ls9c_ard_3-2-1_101079_2022-07-22_final.stac-item
2022-07-23 09:29:00	ga_ls9c_ard_3-2-1_092075_2022-07-22_final.stac-item
2022-07-23 09:34:11	ga_ls9c_ard_3-2-1_092088_2022-07-23_final.stac-item
2022-07-25 10:54:45	ga_ls9c_ard_3-2-1_106073_2022-07-25_final.stac-item
2022-07-25 10:57:09	ga_ls9c_ard_3-2-1_106079_2022-07-25_final.stac-item
2022-07-26 09:59:09	ga_ls9c_ard_3-2-1_097073_2022-07-26_final.stac-item
2022-07-26 09:59:33	ga_ls9c_ard_3-2-1_097074_2022-07-26_final.stac-item
2022-08-02 10:07:01	ga_ls9c_ard_3-2-1_098077_2022-08-02_final.stac-item
2022-08-08 09:34:23	ga_ls9c_ard_3-2-1_092088_2022-08-08_final.stac-item
2022-08-08 11:11:41	ga_ls9c_ard_3-2-1_108084_2022-08-08_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-08-11 09:59:44	ga_ls9c_ard_3-2-1_097074_2022-08-11_final.stac-item
2022-08-13 09:47:47	ga_ls9c_ard_3-2-1_095075_2022-08-13_final.stac-item
2022-08-13 09:50:35	ga_ls9c_ard_3-2-1_095082_2022-08-13_final.stac-item
2022-08-24 09:34:29	ga_ls9c_ard_3-2-1_092088_2022-08-24_final.stac-item
2022-08-24 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-08-24_final.stac-item
2022-08-26 10:55:01	ga_ls9c_ard_3-2-1_106073_2022-08-26_final.stac-item
2022-08-26 10:57:25	ga_ls9c_ard_3-2-1_106079_2022-08-26_final.stac-item
2022-08-27 09:59:48	ga_ls9c_ard_3-2-1_097074_2022-08-27_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-02 11:00:00	ga_ls9c_ard_3-2-1_107070_2022-09-02_final.stac-item
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-09-19 10:07:16	ga_ls9c_ard_3-2-1_098077_2022-09-19_final.stac-item
2022-09-27 10:57:32	ga_ls9c_ard_3-2-1_106079_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years