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 09:54:34	ga_ls9c_ard_3-2-1_096074_2021-11-03_final.stac-item
2021-11-10 11:20:32	ga_ls9c_ard_3-2-1_110083_2021-11-10_final.stac-item
2021-11-14 10:42:15	ga_ls9c_ard_3-2-1_103081_2021-11-14_final.stac-item
2021-11-17 09:22:52	ga_ls9c_ard_3-2-1_091076_2021-11-16_final.stac-item
2021-12-23 11:34:57	ga_ls9c_ard_3-2-1_112080_2021-12-23_final.stac-item
2022-01-05 11:03:38	ga_ls9c_ard_3-2-1_107079_2022-01-05_final.stac-item
2022-01-12 09:28:06	ga_ls9c_ard_3-2-1_092072_2022-01-11_final.stac-item
2022-01-12 11:10:11	ga_ls9c_ard_3-2-1_108080_2022-01-12_final.stac-item
2022-01-14 09:18:55	ga_ls9c_ard_3-2-1_090080_2022-01-13_final.stac-item
2022-01-17 09:49:27	ga_ls9c_ard_3-2-1_095079_2022-01-17_final.stac-item
2022-01-22 11:46:05	ga_ls9c_ard_3-2-1_114077_2022-01-22_final.stac-item
2022-01-28 11:11:01	ga_ls9c_ard_3-2-1_108082_2022-01-28_final.stac-item
2022-02-02 11:27:09	ga_ls9c_ard_3-2-1_111076_2022-02-02_final.stac-item
2022-02-05 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-02-05_final.stac-item
2022-02-11 11:24:32	ga_ls9c_ard_3-2-1_110085_2022-02-11_final.stac-item
2022-02-25 11:33:57	ga_ls9c_ard_3-2-1_112078_2022-02-25_final.stac-item
2022-03-01 09:30:41	ga_ls9c_ard_3-2-1_092079_2022-03-01_final.stac-item
2022-03-04 09:58:23	ga_ls9c_ard_3-2-1_097071_2022-03-04_final.stac-item
2022-03-29 11:33:48	ga_ls9c_ard_3-2-1_112078_2022-03-29_final.stac-item
2022-04-15 10:36:05	ga_ls9c_ard_3-2-1_103073_2022-04-15_final.stac-item
2022-04-18 09:30:28	ga_ls9c_ard_3-2-1_092079_2022-04-18_final.stac-item
2022-04-25 11:12:17	ga_ls9c_ard_3-2-1_109071_2022-04-25_final.stac-item
2022-04-29 10:47:57	ga_ls9c_ard_3-2-1_105072_2022-04-29_final.stac-item
2022-04-29 10:52:21	ga_ls9c_ard_3-2-1_105083_2022-04-29_final.stac-item
2022-05-02 11:22:26	ga_ls9c_ard_3-2-1_110081_2022-05-02_final.stac-item
2022-05-08 10:40:31	ga_ls9c_ard_3-2-1_104069_2022-05-08_final.stac-item
2022-05-20 11:11:03	ga_ls9c_ard_3-2-1_108084_2022-05-20_final.stac-item
2022-05-23 09:57:52	ga_ls9c_ard_3-2-1_097071_2022-05-23_final.stac-item
2022-05-27 09:34:45	ga_ls9c_ard_3-2-1_093075_2022-05-27_final.stac-item
2022-05-30 10:07:15	ga_ls9c_ard_3-2-1_098079_2022-05-30_final.stac-item
2022-06-03 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-06-03_final.stac-item
2022-06-08 11:39:11	ga_ls9c_ard_3-2-1_113077_2022-06-08_final.stac-item
2022-06-12 09:37:13	ga_ls9c_ard_3-2-1_093081_2022-06-12_final.stac-item
2022-06-17 09:55:49	ga_ls9c_ard_3-2-1_096081_2022-06-17_final.stac-item
2022-06-25 10:40:43	ga_ls9c_ard_3-2-1_104069_2022-06-25_final.stac-item
2022-06-26 09:47:53	ga_ls9c_ard_3-2-1_095076_2022-06-26_final.stac-item
2022-07-01 11:44:54	ga_ls9c_ard_3-2-1_114075_2022-07-01_final.stac-item
2022-07-01 11:45:42	ga_ls9c_ard_3-2-1_114077_2022-07-01_final.stac-item
2022-07-07 11:06:12	ga_ls9c_ard_3-2-1_108071_2022-07-07_final.stac-item
2022-07-08 11:53:03	ga_ls9c_ard_3-2-1_115080_2022-07-08_final.stac-item
2022-07-27 10:45:13	ga_ls9c_ard_3-2-1_104080_2022-07-27_final.stac-item
2022-07-27 10:46:01	ga_ls9c_ard_3-2-1_104082_2022-07-27_final.stac-item
2022-08-04 09:55:05	ga_ls9c_ard_3-2-1_096078_2022-08-04_final.stac-item
2022-08-04 09:55:29	ga_ls9c_ard_3-2-1_096079_2022-08-04_final.stac-item
2022-08-06 11:21:13	ga_ls9c_ard_3-2-1_110077_2022-08-06_final.stac-item
2022-08-06 11:22:49	ga_ls9c_ard_3-2-1_110081_2022-08-06_final.stac-item
2022-08-09 10:12:04	ga_ls9c_ard_3-2-1_099074_2022-08-09_final.stac-item
2022-08-17 09:24:41	ga_ls9c_ard_3-2-1_091079_2022-08-16_final.stac-item
2022-08-24 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-08-24_final.stac-item
2022-08-28 10:41:28	ga_ls9c_ard_3-2-1_104070_2022-08-28_final.stac-item
2022-08-30 10:31:54	ga_ls9c_ard_3-2-1_102077_2022-08-30_final.stac-item
2022-08-31 11:17:09	ga_ls9c_ard_3-2-1_109082_2022-08-31_final.stac-item
2022-09-02 11:04:47	ga_ls9c_ard_3-2-1_107082_2022-09-02_final.stac-item
2022-09-06 10:37:40	ga_ls9c_ard_3-2-1_103076_2022-09-06_final.stac-item
2022-09-11 09:18:56	ga_ls9c_ard_3-2-1_090080_2022-09-10_final.stac-item
2022-09-12 09:59:49	ga_ls9c_ard_3-2-1_097074_2022-09-12_final.stac-item
2022-09-26 11:52:22	ga_ls9c_ard_3-2-1_115077_2022-09-26_final.stac-item
2022-10-01 10:31:37	ga_ls9c_ard_3-2-1_102076_2022-10-01_final.stac-item
2022-10-02 09:39:35	ga_ls9c_ard_3-2-1_093085_2022-10-02_final.stac-item
2022-10-04 11:03:19	ga_ls9c_ard_3-2-1_107078_2022-10-04_final.stac-item
2022-10-23 11:35:07	ga_ls9c_ard_3-2-1_112080_2022-10-23_final.stac-item
2022-10-24 10:38:18	ga_ls9c_ard_3-2-1_103077_2022-10-24_final.stac-item
2022-10-30 11:40:53	ga_ls9c_ard_3-2-1_113079_2022-10-30_final.stac-item
2022-11-04 10:20:54	ga_ls9c_ard_3-2-1_100080_2022-11-04_final.stac-item
2022-11-22 10:09:24	ga_ls9c_ard_3-2-1_098082_2022-11-22_final.stac-item
2022-11-25 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-11-25_final.stac-item
2022-11-30 10:58:00	ga_ls9c_ard_3-2-1_106080_2022-11-30_final.stac-item
2022-12-01 10:02:46	ga_ls9c_ard_3-2-1_097081_2022-12-01_final.stac-item
2022-12-11 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-12-11_final.stac-item
2022-12-24 11:45:49	ga_ls9c_ard_3-2-1_114076_2022-12-24_final.stac-item
2023-01-04 09:48:27	ga_ls9c_ard_3-2-1_095076_2023-01-04_final.stac-item
2023-01-16 10:15:29	ga_ls9c_ard_3-2-1_099082_2023-01-16_final.stac-item
2023-01-23 11:58:07	ga_ls9c_ard_3-2-1_116076_2023-01-23_final.stac-item
2023-01-29 09:42:15	ga_ls9c_ard_3-2-1_094076_2023-01-29_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_2023-02-10_final.stac-item
2023-02-18 09:19:54	ga_ls9c_ard_3-2-1_090082_2023-02-17_final.stac-item
2023-02-19 10:02:20	ga_ls9c_ard_3-2-1_097080_2023-02-19_final.stac-item
2023-02-26 10:06:48	ga_ls9c_ard_3-2-1_098076_2023-02-26_final.stac-item
2023-03-02 11:21:21	ga_ls9c_ard_3-2-1_110077_2023-03-02_final.stac-item
2023-03-26 10:30:54	ga_ls9c_ard_3-2-1_102075_2023-03-26_final.stac-item
2023-03-27 09:36:27	ga_ls9c_ard_3-2-1_093078_2023-03-27_final.stac-item
2023-05-07 11:06:00	ga_ls9c_ard_3-2-1_108071_2023-05-07_final.stac-item
2023-05-16 11:03:22	ga_ls9c_ard_3-2-1_107080_2023-05-16_final.stac-item
2023-05-30 09:37:07	ga_ls9c_ard_3-2-1_093081_2023-05-30_final.stac-item
2023-06-13 09:50:09	ga_ls9c_ard_3-2-1_095083_2023-06-13_final.stac-item
2023-06-16 10:20:37	ga_ls9c_ard_3-2-1_100082_2023-06-16_final.stac-item
2023-06-16 10:21:24	ga_ls9c_ard_3-2-1_100084_2023-06-16_final.stac-item
2023-06-19 09:11:50	ga_ls9c_ard_3-2-1_089080_2023-06-18_final.stac-item
2023-06-24 11:04:52	ga_ls9c_ard_3-2-1_108069_2023-06-24_final.stac-item
2023-07-10 11:11:07	ga_ls9c_ard_3-2-1_108084_2023-07-10_final.stac-item
2023-07-12 09:18:41	ga_ls9c_ard_3-2-1_090081_2023-07-11_final.stac-item
2023-09-09 10:34:41	ga_ls9c_ard_3-2-1_103069_2023-09-09_final.stac-item
2023-09-11 10:27:08	ga_ls9c_ard_3-2-1_101081_2023-09-11_final.stac-item
2023-09-19 09:38:55	ga_ls9c_ard_3-2-1_093084_2023-09-19_final.stac-item
2023-09-23 09:14:34	ga_ls9c_ard_3-2-1_089085_2023-09-22_final.stac-item
2023-09-28 11:06:44	ga_ls9c_ard_3-2-1_108072_2023-09-28_final.stac-item
2023-09-29 10:11:56	ga_ls9c_ard_3-2-1_099074_2023-09-29_final.stac-item
2023-10-04 10:30:58	ga_ls9c_ard_3-2-1_102075_2023-10-04_final.stac-item
2023-10-05 11:12:14	ga_ls9c_ard_3-2-1_109070_2023-10-05_final.stac-item
2023-10-08 11:46:45	ga_ls9c_ard_3-2-1_114079_2023-10-08_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