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
2021-11-07 09:21:04	ga_ls9c_ard_3-2-1_090084_2021-11-06_final.stac-item
2021-11-19 10:43:07	ga_ls9c_ard_3-2-1_104077_2021-11-19_final.stac-item
2021-12-27 11:10:14	ga_ls9c_ard_3-2-1_108080_2021-12-27_final.stac-item
2022-01-17 09:48:15	ga_ls9c_ard_3-2-1_095076_2022-01-17_final.stac-item
2022-01-21 09:24:20	ga_ls9c_ard_3-2-1_091078_2022-01-20_final.stac-item
2022-02-08 10:51:39	ga_ls9c_ard_3-2-1_105080_2022-02-08_final.stac-item
2022-02-13 09:32:28	ga_ls9c_ard_3-2-1_092083_2022-02-13_final.stac-item
2022-02-17 10:44:36	ga_ls9c_ard_3-2-1_104078_2022-02-17_final.stac-item
2022-02-25 09:53:04	ga_ls9c_ard_3-2-1_096073_2022-02-25_final.stac-item
2022-03-09 11:58:13	ga_ls9c_ard_3-2-1_116077_2022-03-09_final.stac-item
2022-03-23 10:29:38	ga_ls9c_ard_3-2-1_102072_2022-03-23_final.stac-item
2022-03-29 09:53:19	ga_ls9c_ard_3-2-1_096074_2022-03-29_final.stac-item
2022-03-31 09:43:22	ga_ls9c_ard_3-2-1_094080_2022-03-31_final.stac-item
2022-04-02 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-04-02_final.stac-item
2022-04-06 10:44:45	ga_ls9c_ard_3-2-1_104079_2022-04-06_final.stac-item
2022-04-14 09:56:50	ga_ls9c_ard_3-2-1_096083_2022-04-14_final.stac-item
2022-04-28 10:08:41	ga_ls9c_ard_3-2-1_098082_2022-04-28_final.stac-item
2022-05-25 11:26:47	ga_ls9c_ard_3-2-1_111077_2022-05-25_final.stac-item
2022-05-26 10:31:10	ga_ls9c_ard_3-2-1_102077_2022-05-26_final.stac-item
2022-05-27 09:36:44	ga_ls9c_ard_3-2-1_093080_2022-05-27_final.stac-item
2022-05-31 10:50:31	ga_ls9c_ard_3-2-1_105079_2022-05-31_final.stac-item
2022-06-01 11:33:47	ga_ls9c_ard_3-2-1_112079_2022-06-01_final.stac-item
2022-06-03 09:41:21	ga_ls9c_ard_3-2-1_094076_2022-06-03_final.stac-item
2022-06-21 11:09:42	ga_ls9c_ard_3-2-1_108080_2022-06-21_final.stac-item
2022-06-25 10:44:42	ga_ls9c_ard_3-2-1_104079_2022-06-25_final.stac-item
2022-07-13 10:32:40	ga_ls9c_ard_3-2-1_102080_2022-07-13_final.stac-item
2022-07-23 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-07-23_final.stac-item
2022-07-28 09:50:00	ga_ls9c_ard_3-2-1_095081_2022-07-28_final.stac-item
2022-08-02 10:06:37	ga_ls9c_ard_3-2-1_098076_2022-08-02_final.stac-item
2022-08-05 10:35:33	ga_ls9c_ard_3-2-1_103071_2022-08-05_final.stac-item
2022-08-05 10:39:09	ga_ls9c_ard_3-2-1_103080_2022-08-05_final.stac-item
2022-08-06 11:21:37	ga_ls9c_ard_3-2-1_110078_2022-08-06_final.stac-item
2022-08-14 10:29:51	ga_ls9c_ard_3-2-1_102072_2022-08-14_final.stac-item
2022-08-16 10:18:42	ga_ls9c_ard_3-2-1_100075_2022-08-16_final.stac-item
2022-08-24 09:32:29	ga_ls9c_ard_3-2-1_092083_2022-08-24_final.stac-item
2022-09-09 09:30:05	ga_ls9c_ard_3-2-1_092077_2022-09-09_final.stac-item
2022-09-16 11:16:25	ga_ls9c_ard_3-2-1_109080_2022-09-16_final.stac-item
2022-09-25 09:31:00	ga_ls9c_ard_3-2-1_092079_2022-09-25_final.stac-item
2022-09-30 09:49:57	ga_ls9c_ard_3-2-1_095080_2022-09-30_final.stac-item
2022-10-04 09:24:26	ga_ls9c_ard_3-2-1_091078_2022-10-03_final.stac-item
2022-10-08 10:37:24	ga_ls9c_ard_3-2-1_103075_2022-10-08_final.stac-item
2022-10-18 09:34:06	ga_ls9c_ard_3-2-1_093071_2022-10-18_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-21 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-10-21_final.stac-item
2022-10-23 11:33:07	ga_ls9c_ard_3-2-1_112075_2022-10-23_final.stac-item
2022-10-24 10:38:42	ga_ls9c_ard_3-2-1_103078_2022-10-24_final.stac-item
2022-10-26 10:24:44	ga_ls9c_ard_3-2-1_101074_2022-10-26_final.stac-item
2022-10-28 10:12:22	ga_ls9c_ard_3-2-1_099074_2022-10-28_final.stac-item
2022-10-29 09:20:20	ga_ls9c_ard_3-2-1_090083_2022-10-28_final.stac-item
2022-11-05 09:24:53	ga_ls9c_ard_3-2-1_091079_2022-11-04_final.stac-item
2022-11-05 11:02:58	ga_ls9c_ard_3-2-1_107077_2022-11-05_final.stac-item
2022-11-06 10:05:46	ga_ls9c_ard_3-2-1_098073_2022-11-06_final.stac-item
2022-11-12 11:10:24	ga_ls9c_ard_3-2-1_108080_2022-11-12_final.stac-item
2022-11-19 09:36:54	ga_ls9c_ard_3-2-1_093078_2022-11-19_final.stac-item
2022-11-24 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-11-24_final.stac-item
2022-11-26 09:41:52	ga_ls9c_ard_3-2-1_094075_2022-11-26_final.stac-item
2022-12-07 11:05:00	ga_ls9c_ard_3-2-1_107082_2022-12-07_final.stac-item
2023-01-03 10:41:17	ga_ls9c_ard_3-2-1_104069_2023-01-03_final.stac-item
2023-01-09 10:06:35	ga_ls9c_ard_3-2-1_098075_2023-01-09_final.stac-item
2023-01-20 09:47:53	ga_ls9c_ard_3-2-1_095075_2023-01-20_final.stac-item
2023-01-20 09:48:17	ga_ls9c_ard_3-2-1_095076_2023-01-20_final.stac-item
2023-02-03 09:58:51	ga_ls9c_ard_3-2-1_097071_2023-02-03_final.stac-item
2023-02-04 10:44:31	ga_ls9c_ard_3-2-1_104077_2023-02-04_final.stac-item
2023-03-09 11:29:49	ga_ls9c_ard_3-2-1_111083_2023-03-09_final.stac-item
2023-03-13 09:25:49	ga_ls9c_ard_3-2-1_091082_2023-03-12_final.stac-item
2023-03-26 10:32:29	ga_ls9c_ard_3-2-1_102079_2023-03-26_final.stac-item
2023-04-06 11:50:45	ga_ls9c_ard_3-2-1_115074_2023-04-06_final.stac-item
2023-04-11 10:32:45	ga_ls9c_ard_3-2-1_102080_2023-04-11_final.stac-item
2023-04-15 10:05:35	ga_ls9c_ard_3-2-1_098074_2023-04-15_final.stac-item
2023-04-22 11:50:39	ga_ls9c_ard_3-2-1_115074_2023-04-22_final.stac-item
2023-05-01 11:47:08	ga_ls9c_ard_3-2-1_114081_2023-05-01_final.stac-item
2023-05-03 11:34:44	ga_ls9c_ard_3-2-1_112081_2023-05-03_final.stac-item
2023-05-06 10:25:56	ga_ls9c_ard_3-2-1_101079_2023-05-06_final.stac-item
2023-05-19 09:54:57	ga_ls9c_ard_3-2-1_096079_2023-05-19_final.stac-item
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final.stac-item
2023-07-05 10:50:08	ga_ls9c_ard_3-2-1_105078_2023-07-05_final.stac-item
2023-07-05 10:52:07	ga_ls9c_ard_3-2-1_105083_2023-07-05_final.stac-item
2023-07-17 09:37:14	ga_ls9c_ard_3-2-1_093081_2023-07-17_final.stac-item
2023-07-21 10:49:48	ga_ls9c_ard_3-2-1_105077_2023-07-21_final.stac-item
2023-07-21 10:52:12	ga_ls9c_ard_3-2-1_105083_2023-07-21_final.stac-item
2023-07-24 09:42:12	ga_ls9c_ard_3-2-1_094078_2023-07-24_final.stac-item
2023-07-27 10:11:56	ga_ls9c_ard_3-2-1_099075_2023-07-27_final.stac-item
2023-07-28 09:19:32	ga_ls9c_ard_3-2-1_090083_2023-07-27_final.stac-item
2023-07-28 10:56:25	ga_ls9c_ard_3-2-1_106078_2023-07-28_final.stac-item
2023-08-04 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-08-03_final.stac-item
2023-08-09 11:21:16	ga_ls9c_ard_3-2-1_110078_2023-08-09_final.stac-item
2023-08-11 11:08:31	ga_ls9c_ard_3-2-1_108077_2023-08-11_final.stac-item
2023-08-16 11:28:15	ga_ls9c_ard_3-2-1_111080_2023-08-16_final.stac-item
2023-08-17 10:29:26	ga_ls9c_ard_3-2-1_102072_2023-08-17_final.stac-item
2023-08-18 11:14:41	ga_ls9c_ard_3-2-1_109077_2023-08-18_final.stac-item
2023-08-18 11:15:53	ga_ls9c_ard_3-2-1_109080_2023-08-18_final.stac-item
2023-10-17 10:00:36	ga_ls9c_ard_3-2-1_097076_2023-10-17_final.stac-item
2023-10-19 11:28:44	ga_ls9c_ard_3-2-1_111080_2023-10-19_final.stac-item
2023-10-26 11:32:53	ga_ls9c_ard_3-2-1_112075_2023-10-26_final.stac-item
2023-10-31 10:14:53	ga_ls9c_ard_3-2-1_099081_2023-10-31_final.stac-item
2023-11-14 10:27:15	ga_ls9c_ard_3-2-1_101081_2023-11-14_final.stac-item
2023-11-15 11:10:06	ga_ls9c_ard_3-2-1_108080_2023-11-15_final.stac-item
2023-11-16 10:11:42	ga_ls9c_ard_3-2-1_099073_2023-11-16_final.stac-item
2023-11-16 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-11-16_final.stac-item
2023-11-16 10:14:53	ga_ls9c_ard_3-2-1_099081_2023-11-16_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