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
2021-11-17 09:26:28	ga_ls9c_ard_3-2-1_091085_2021-11-16_final.stac-item
2021-12-07 11:33:27	ga_ls9c_ard_3-2-1_112076_2021-12-07_final.stac-item
2022-01-09 10:40:05	ga_ls9c_ard_3-2-1_103082_2022-01-09_final.stac-item
2022-02-11 09:41:39	ga_ls9c_ard_3-2-1_094075_2022-02-11_final.stac-item
2022-03-06 09:51:37	ga_ls9c_ard_3-2-1_095085_2022-03-06_final.stac-item
2022-03-08 09:38:52	ga_ls9c_ard_3-2-1_093084_2022-03-08_final.stac-item
2022-03-08 09:39:40	ga_ls9c_ard_3-2-1_093086_2022-03-08_final.stac-item
2022-03-09 10:20:32	ga_ls9c_ard_3-2-1_100080_2022-03-09_final.stac-item
2022-03-24 09:36:00	ga_ls9c_ard_3-2-1_093077_2022-03-24_final.stac-item
2022-05-10 10:30:55	ga_ls9c_ard_3-2-1_102076_2022-05-10_final.stac-item
2022-07-01 11:44:54	ga_ls9c_ard_3-2-1_114075_2022-07-01_final.stac-item
2022-07-04 10:38:54	ga_ls9c_ard_3-2-1_103080_2022-07-04_final.stac-item
2022-07-07 09:30:06	ga_ls9c_ard_3-2-1_092078_2022-07-07_final.stac-item
2022-07-12 09:47:49	ga_ls9c_ard_3-2-1_095076_2022-07-12_final.stac-item
2022-07-31 10:20:33	ga_ls9c_ard_3-2-1_100080_2022-07-31_final.stac-item
2022-09-18 11:04:04	ga_ls9c_ard_3-2-1_107080_2022-09-18_final.stac-item
2022-09-24 10:24:38	ga_ls9c_ard_3-2-1_101074_2022-09-24_final.stac-item
2022-09-30 11:27:39	ga_ls9c_ard_3-2-1_111077_2022-09-30_final.stac-item
2022-10-04 11:00:55	ga_ls9c_ard_3-2-1_107072_2022-10-04_final.stac-item
2022-10-24 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-10-24_final.stac-item
2022-10-28 10:15:10	ga_ls9c_ard_3-2-1_099081_2022-10-28_final.stac-item
2022-11-02 10:31:40	ga_ls9c_ard_3-2-1_102076_2022-11-02_final.stac-item
2022-11-06 10:08:58	ga_ls9c_ard_3-2-1_098081_2022-11-06_final.stac-item
2022-11-24 09:56:38	ga_ls9c_ard_3-2-1_096081_2022-11-24_final.stac-item
2023-05-03 09:53:04	ga_ls9c_ard_3-2-1_096074_2023-05-03_final.stac-item
2023-05-03 09:55:51	ga_ls9c_ard_3-2-1_096081_2023-05-03_final.stac-item
2023-05-03 11:34:44	ga_ls9c_ard_3-2-1_112081_2023-05-03_final.stac-item
2023-05-04 10:34:42	ga_ls9c_ard_3-2-1_103070_2023-05-04_final.stac-item
2023-05-04 10:35:54	ga_ls9c_ard_3-2-1_103073_2023-05-04_final.stac-item
2023-05-04 10:36:18	ga_ls9c_ard_3-2-1_103074_2023-05-04_final.stac-item
2023-05-05 09:41:04	ga_ls9c_ard_3-2-1_094075_2023-05-05_final.stac-item
2023-05-05 09:43:28	ga_ls9c_ard_3-2-1_094081_2023-05-05_final.stac-item
2023-05-06 10:24:20	ga_ls9c_ard_3-2-1_101075_2023-05-06_final.stac-item
2023-05-06 10:25:32	ga_ls9c_ard_3-2-1_101078_2023-05-06_final.stac-item
2023-05-07 09:30:42	ga_ls9c_ard_3-2-1_092080_2023-05-07_final.stac-item
2023-05-07 11:09:11	ga_ls9c_ard_3-2-1_108079_2023-05-07_final.stac-item
2023-05-09 09:18:21	ga_ls9c_ard_3-2-1_090080_2023-05-08_final.stac-item
2023-05-09 10:58:02	ga_ls9c_ard_3-2-1_106082_2023-05-09_final.stac-item
2023-05-10 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-05-10_final.stac-item
2023-05-11 10:40:28	ga_ls9c_ard_3-2-1_104069_2023-05-11_final.stac-item
2023-05-11 10:41:40	ga_ls9c_ard_3-2-1_104072_2023-05-11_final.stac-item
2023-05-11 10:42:28	ga_ls9c_ard_3-2-1_104074_2023-05-11_final.stac-item
2023-05-11 10:44:28	ga_ls9c_ard_3-2-1_104079_2023-05-11_final.stac-item
2023-05-13 10:29:18	ga_ls9c_ard_3-2-1_102072_2023-05-13_final.stac-item
2023-05-13 10:32:29	ga_ls9c_ard_3-2-1_102080_2023-05-13_final.stac-item
2023-05-14 09:35:40	ga_ls9c_ard_3-2-1_093077_2023-05-14_final.stac-item
2023-05-14 09:38:03	ga_ls9c_ard_3-2-1_093083_2023-05-14_final.stac-item
2023-05-15 11:58:12	ga_ls9c_ard_3-2-1_116078_2023-05-15_final.stac-item
2023-05-16 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-05-16_final.stac-item
2023-05-18 10:46:59	ga_ls9c_ard_3-2-1_105070_2023-05-18_final.stac-item
2023-05-18 10:47:23	ga_ls9c_ard_3-2-1_105071_2023-05-18_final.stac-item
2023-05-20 10:35:00	ga_ls9c_ard_3-2-1_103071_2023-05-20_final.stac-item
2023-05-21 09:43:21	ga_ls9c_ard_3-2-1_094081_2023-05-21_final.stac-item
2023-05-21 11:22:14	ga_ls9c_ard_3-2-1_110081_2023-05-21_final.stac-item
2023-09-06 10:08:32	ga_ls9c_ard_3-2-1_098081_2023-09-06_final.stac-item
2023-09-08 09:56:36	ga_ls9c_ard_3-2-1_096082_2023-09-08_final.stac-item
2023-09-10 09:41:52	ga_ls9c_ard_3-2-1_094076_2023-09-10_final.stac-item
2023-09-10 09:43:52	ga_ls9c_ard_3-2-1_094081_2023-09-10_final.stac-item
2023-09-12 11:06:49	ga_ls9c_ard_3-2-1_108072_2023-09-12_final.stac-item
2023-09-14 09:18:46	ga_ls9c_ard_3-2-1_090080_2023-09-13_final.stac-item
2023-09-14 10:56:51	ga_ls9c_ard_3-2-1_106078_2023-09-14_final.stac-item
2023-09-14 10:57:15	ga_ls9c_ard_3-2-1_106079_2023-09-14_final.stac-item
2023-09-15 10:00:26	ga_ls9c_ard_3-2-1_097076_2023-09-15_final.stac-item
2023-09-15 10:02:50	ga_ls9c_ard_3-2-1_097082_2023-09-15_final.stac-item
2023-09-15 11:40:31	ga_ls9c_ard_3-2-1_113079_2023-09-15_final.stac-item
2023-09-16 10:44:30	ga_ls9c_ard_3-2-1_104078_2023-09-16_final.stac-item
2023-09-17 09:51:16	ga_ls9c_ard_3-2-1_095084_2023-09-17_final.stac-item
2023-09-17 11:26:34	ga_ls9c_ard_3-2-1_111075_2023-09-17_final.stac-item
2023-09-17 11:28:58	ga_ls9c_ard_3-2-1_111081_2023-09-17_final.stac-item
2023-09-19 09:35:43	ga_ls9c_ard_3-2-1_093076_2023-09-19_final.stac-item
2023-09-19 09:36:07	ga_ls9c_ard_3-2-1_093077_2023-09-19_final.stac-item
2023-09-19 11:15:00	ga_ls9c_ard_3-2-1_109077_2023-09-19_final.stac-item
2023-09-21 09:24:33	ga_ls9c_ard_3-2-1_091079_2023-09-20_final.stac-item
2023-09-21 11:03:26	ga_ls9c_ard_3-2-1_107079_2023-09-21_final.stac-item
2023-09-24 09:56:13	ga_ls9c_ard_3-2-1_096081_2023-09-24_final.stac-item
2023-09-24 09:56:37	ga_ls9c_ard_3-2-1_096082_2023-09-24_final.stac-item
2023-09-25 10:37:28	ga_ls9c_ard_3-2-1_103076_2023-09-25_final.stac-item
2023-09-25 10:38:16	ga_ls9c_ard_3-2-1_103078_2023-09-25_final.stac-item
2023-09-25 10:38:40	ga_ls9c_ard_3-2-1_103079_2023-09-25_final.stac-item
2023-09-25 10:39:04	ga_ls9c_ard_3-2-1_103080_2023-09-25_final.stac-item
2023-09-26 09:41:26	ga_ls9c_ard_3-2-1_094075_2023-09-26_final.stac-item
2023-09-26 09:43:50	ga_ls9c_ard_3-2-1_094081_2023-09-26_final.stac-item
2023-09-28 11:10:44	ga_ls9c_ard_3-2-1_108082_2023-09-28_final.stac-item
2023-09-30 09:18:44	ga_ls9c_ard_3-2-1_090080_2023-09-29_final.stac-item
2023-09-30 09:19:55	ga_ls9c_ard_3-2-1_090083_2023-09-29_final.stac-item
2023-10-01 10:00:25	ga_ls9c_ard_3-2-1_097076_2023-10-01_final.stac-item
2023-10-01 10:02:24	ga_ls9c_ard_3-2-1_097081_2023-10-01_final.stac-item
2023-10-01 11:39:42	ga_ls9c_ard_3-2-1_113077_2023-10-01_final.stac-item
2023-10-02 10:43:17	ga_ls9c_ard_3-2-1_104075_2023-10-02_final.stac-item
2023-10-02 10:43:41	ga_ls9c_ard_3-2-1_104076_2023-10-02_final.stac-item
2023-10-02 10:44:05	ga_ls9c_ard_3-2-1_104077_2023-10-02_final.stac-item
2023-10-04 10:33:45	ga_ls9c_ard_3-2-1_102082_2023-10-04_final.stac-item
2023-10-05 09:36:33	ga_ls9c_ard_3-2-1_093078_2023-10-05_final.stac-item
2023-10-09 10:50:20	ga_ls9c_ard_3-2-1_105077_2023-10-09_final.stac-item
2023-10-09 10:51:32	ga_ls9c_ard_3-2-1_105080_2023-10-09_final.stac-item
2023-10-10 11:34:01	ga_ls9c_ard_3-2-1_112078_2023-10-10_final.stac-item
2023-10-11 10:38:25	ga_ls9c_ard_3-2-1_103078_2023-10-11_final.stac-item
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_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