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
2021-10-31 11:10:24	ga_ls9c_ard_3-2-1_109070_2021-10-31_final.stac-item
2021-11-05 09:37:25	ga_ls9c_ard_3-2-1_093078_2021-11-05_final.stac-item
2021-11-15 09:43:57	ga_ls9c_ard_3-2-1_094082_2021-11-15_final.stac-item
2021-11-22 11:02:20	ga_ls9c_ard_3-2-1_107072_2021-11-22_final.stac-item
2021-12-19 10:19:58	ga_ls9c_ard_3-2-1_100078_2021-12-19_final.stac-item
2021-12-19 10:21:34	ga_ls9c_ard_3-2-1_100082_2021-12-19_final.stac-item
2021-12-24 10:38:08	ga_ls9c_ard_3-2-1_103077_2021-12-24_final.stac-item
2022-01-03 09:36:19	ga_ls9c_ard_3-2-1_093077_2022-01-03_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-01-16 10:41:28	ga_ls9c_ard_3-2-1_104070_2022-01-16_final.stac-item
2022-01-28 11:11:49	ga_ls9c_ard_3-2-1_108084_2022-01-28_final.stac-item
2022-02-21 10:18:14	ga_ls9c_ard_3-2-1_100074_2022-02-21_final.stac-item
2022-02-21 10:18:38	ga_ls9c_ard_3-2-1_100075_2022-02-21_final.stac-item
2022-03-25 10:18:04	ga_ls9c_ard_3-2-1_100074_2022-03-25_final.stac-item
2022-04-12 10:09:13	ga_ls9c_ard_3-2-1_098083_2022-04-12_final.stac-item
2022-04-18 09:29:16	ga_ls9c_ard_3-2-1_092076_2022-04-17_final.stac-item
2022-05-06 10:54:29	ga_ls9c_ard_3-2-1_106073_2022-05-06_final.stac-item
2022-05-24 10:44:44	ga_ls9c_ard_3-2-1_104080_2022-05-24_final.stac-item
2022-08-31 09:37:52	ga_ls9c_ard_3-2-1_093081_2022-08-31_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final.stac-item
2022-10-04 11:02:55	ga_ls9c_ard_3-2-1_107077_2022-10-04_final.stac-item
2022-10-14 09:59:11	ga_ls9c_ard_3-2-1_097072_2022-10-14_final.stac-item
2022-10-19 11:59:02	ga_ls9c_ard_3-2-1_116078_2022-10-19_final.stac-item
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final.stac-item
2022-11-04 10:18:30	ga_ls9c_ard_3-2-1_100074_2022-11-04_final.stac-item
2022-11-07 10:47:50	ga_ls9c_ard_3-2-1_105070_2022-11-07_final.stac-item
2022-11-08 11:33:06	ga_ls9c_ard_3-2-1_112075_2022-11-08_final.stac-item
2022-11-10 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-10_final.stac-item
2022-11-12 11:12:00	ga_ls9c_ard_3-2-1_108084_2022-11-12_final.stac-item
2022-11-17 09:51:40	ga_ls9c_ard_3-2-1_095084_2022-11-17_final.stac-item
2022-11-21 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-11-21_final.stac-item
2022-12-04 10:31:41	ga_ls9c_ard_3-2-1_102076_2022-12-04_final.stac-item
2022-12-07 11:01:24	ga_ls9c_ard_3-2-1_107073_2022-12-07_final.stac-item
2022-12-08 10:06:11	ga_ls9c_ard_3-2-1_098074_2022-12-08_final.stac-item
2022-12-15 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-15_final.stac-item
2022-12-19 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-12-19_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2022-12-24 10:05:44	ga_ls9c_ard_3-2-1_098073_2022-12-24_final.stac-item
2022-12-26 09:55:23	ga_ls9c_ard_3-2-1_096078_2022-12-26_final.stac-item
2022-12-30 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-30_final.stac-item
2022-12-30 11:09:59	ga_ls9c_ard_3-2-1_108079_2022-12-30_final.stac-item
2022-12-30 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-30_final.stac-item
2023-01-01 09:19:09	ga_ls9c_ard_3-2-1_090080_2022-12-31_final.stac-item
2023-01-06 09:36:06	ga_ls9c_ard_3-2-1_093076_2023-01-06_final.stac-item
2023-01-06 09:36:53	ga_ls9c_ard_3-2-1_093078_2023-01-06_final.stac-item
2023-01-06 09:39:17	ga_ls9c_ard_3-2-1_093084_2023-01-06_final.stac-item
2023-01-08 11:03:48	ga_ls9c_ard_3-2-1_107079_2023-01-08_final.stac-item
2023-01-10 10:48:15	ga_ls9c_ard_3-2-1_105071_2023-01-10_final.stac-item
2023-01-11 09:55:24	ga_ls9c_ard_3-2-1_096078_2023-01-11_final.stac-item
2023-01-17 10:57:08	ga_ls9c_ard_3-2-1_106078_2023-01-17_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-18 10:02:41	ga_ls9c_ard_3-2-1_097081_2023-01-18_final.stac-item
2023-01-19 10:43:32	ga_ls9c_ard_3-2-1_104075_2023-01-19_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-28 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-28_final.stac-item
2023-01-31 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-01-31_final.stac-item
2023-02-03 11:39:20	ga_ls9c_ard_3-2-1_113075_2023-02-03_final.stac-item
2023-02-04 10:44:07	ga_ls9c_ard_3-2-1_104076_2023-02-04_final.stac-item
2023-02-06 10:30:10	ga_ls9c_ard_3-2-1_102072_2023-02-06_final.stac-item
2023-02-07 11:17:26	ga_ls9c_ard_3-2-1_109082_2023-02-07_final.stac-item
2023-02-10 11:47:08	ga_ls9c_ard_3-2-1_114079_2023-02-10_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2023-04-22_final.stac-item
2023-04-24 09:58:59	ga_ls9c_ard_3-2-1_097073_2023-04-24_final.stac-item
2023-05-02 09:14:13	ga_ls9c_ard_3-2-1_089085_2023-05-01_final.stac-item
2023-05-02 10:52:18	ga_ls9c_ard_3-2-1_105083_2023-05-02_final.stac-item
2023-05-07 11:06:00	ga_ls9c_ard_3-2-1_108071_2023-05-07_final.stac-item
2023-05-08 10:12:22	ga_ls9c_ard_3-2-1_099076_2023-05-08_final.stac-item
2023-05-08 11:50:27	ga_ls9c_ard_3-2-1_115074_2023-05-08_final.stac-item
2023-06-22 11:20:02	ga_ls9c_ard_3-2-1_110076_2023-06-22_final.stac-item
2023-06-27 09:58:31	ga_ls9c_ard_3-2-1_097073_2023-06-27_final.stac-item
2023-06-29 09:50:13	ga_ls9c_ard_3-2-1_095083_2023-06-29_final.stac-item
2023-07-15 09:46:48	ga_ls9c_ard_3-2-1_095074_2023-07-15_final.stac-item
2023-07-15 09:51:12	ga_ls9c_ard_3-2-1_095085_2023-07-15_final.stac-item
2023-07-17 11:11:44	ga_ls9c_ard_3-2-1_109070_2023-07-17_final.stac-item
2023-07-19 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-07-18_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-23 10:37:26	ga_ls9c_ard_3-2-1_103077_2023-07-23_final.stac-item
2023-07-28 10:53:13	ga_ls9c_ard_3-2-1_106070_2023-07-28_final.stac-item
2023-08-03 10:21:01	ga_ls9c_ard_3-2-1_100082_2023-08-03_final.stac-item
2023-08-03 10:21:49	ga_ls9c_ard_3-2-1_100084_2023-08-03_final.stac-item
2023-08-04 09:25:48	ga_ls9c_ard_3-2-1_091083_2023-08-03_final.stac-item
2023-08-05 11:45:10	ga_ls9c_ard_3-2-1_114076_2023-08-05_final.stac-item
2023-10-13 10:23:41	ga_ls9c_ard_3-2-1_101072_2023-10-13_final.stac-item
2023-10-13 10:24:29	ga_ls9c_ard_3-2-1_101074_2023-10-13_final.stac-item
2023-10-14 09:32:28	ga_ls9c_ard_3-2-1_092083_2023-10-14_final.stac-item
2023-10-14 11:05:46	ga_ls9c_ard_3-2-1_108069_2023-10-14_final.stac-item
2023-10-16 09:19:20	ga_ls9c_ard_3-2-1_090081_2023-10-15_final.stac-item
2023-10-17 10:02:12	ga_ls9c_ard_3-2-1_097080_2023-10-17_final.stac-item
2023-10-19 09:50:39	ga_ls9c_ard_3-2-1_095082_2023-10-19_final.stac-item
2023-10-20 10:32:19	ga_ls9c_ard_3-2-1_102078_2023-10-20_final.stac-item
2023-10-22 11:58:26	ga_ls9c_ard_3-2-1_116077_2023-10-22_final.stac-item
2023-10-24 11:45:40	ga_ls9c_ard_3-2-1_114076_2023-10-24_final.stac-item
2023-10-25 10:50:26	ga_ls9c_ard_3-2-1_105077_2023-10-25_final.stac-item
2023-10-26 09:53:36	ga_ls9c_ard_3-2-1_096074_2023-10-26_final.stac-item
2023-10-27 10:38:03	ga_ls9c_ard_3-2-1_103077_2023-10-27_final.stac-item
2023-11-14 10:24:51	ga_ls9c_ard_3-2-1_101075_2023-11-14_final.stac-item
2023-11-15 11:10:30	ga_ls9c_ard_3-2-1_108081_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
2023-11-21 10:31:31	ga_ls9c_ard_3-2-1_102076_2023-11-21_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