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
2023-07-15 09:46:00	ga_ls9c_ard_3-2-1_095072_2023-07-15_final.stac-item
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-07-15 09:48:24	ga_ls9c_ard_3-2-1_095078_2023-07-15_final.stac-item
2023-07-15 09:49:12	ga_ls9c_ard_3-2-1_095080_2023-07-15_final.stac-item
2023-07-15 09:50:48	ga_ls9c_ard_3-2-1_095084_2023-07-15_final.stac-item
2023-07-15 09:51:36	ga_ls9c_ard_3-2-1_095086_2023-07-15_final.stac-item
2023-07-15 11:24:06	ga_ls9c_ard_3-2-1_111070_2023-07-15_final.stac-item
2023-07-15 11:24:30	ga_ls9c_ard_3-2-1_111071_2023-07-15_final.stac-item
2023-07-15 11:24:53	ga_ls9c_ard_3-2-1_111072_2023-07-15_final.stac-item
2023-07-15 11:25:41	ga_ls9c_ard_3-2-1_111074_2023-07-15_final.stac-item
2023-07-15 11:26:29	ga_ls9c_ard_3-2-1_111076_2023-07-15_final.stac-item
2023-07-15 11:27:41	ga_ls9c_ard_3-2-1_111079_2023-07-15_final.stac-item
2023-07-15 11:28:05	ga_ls9c_ard_3-2-1_111080_2023-07-15_final.stac-item
2023-07-16 10:28:28	ga_ls9c_ard_3-2-1_102070_2023-07-16_final.stac-item
2023-07-16 10:29:16	ga_ls9c_ard_3-2-1_102072_2023-07-16_final.stac-item
2023-07-16 10:30:04	ga_ls9c_ard_3-2-1_102074_2023-07-16_final.stac-item
2023-07-16 10:30:28	ga_ls9c_ard_3-2-1_102075_2023-07-16_final.stac-item
2023-07-16 10:32:04	ga_ls9c_ard_3-2-1_102079_2023-07-16_final.stac-item
2023-07-16 10:32:52	ga_ls9c_ard_3-2-1_102081_2023-07-16_final.stac-item
2023-07-17 09:34:03	ga_ls9c_ard_3-2-1_093073_2023-07-17_final.stac-item
2023-07-17 09:35:15	ga_ls9c_ard_3-2-1_093076_2023-07-17_final.stac-item
2023-07-17 09:35:39	ga_ls9c_ard_3-2-1_093077_2023-07-17_final.stac-item
2023-07-17 09:36:03	ga_ls9c_ard_3-2-1_093078_2023-07-17_final.stac-item
2023-07-17 09:37:14	ga_ls9c_ard_3-2-1_093081_2023-07-17_final.stac-item
2023-07-17 09:37:38	ga_ls9c_ard_3-2-1_093082_2023-07-17_final.stac-item
2023-07-17 11:11:44	ga_ls9c_ard_3-2-1_109070_2023-07-17_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-17 11:13:20	ga_ls9c_ard_3-2-1_109074_2023-07-17_final.stac-item
2023-07-17 11:14:32	ga_ls9c_ard_3-2-1_109077_2023-07-17_final.stac-item
2023-07-17 11:14:56	ga_ls9c_ard_3-2-1_109078_2023-07-17_final.stac-item
2023-07-17 11:15:20	ga_ls9c_ard_3-2-1_109079_2023-07-17_final.stac-item
2023-07-17 11:15:44	ga_ls9c_ard_3-2-1_109080_2023-07-17_final.stac-item
2023-07-17 11:16:55	ga_ls9c_ard_3-2-1_109083_2023-07-17_final.stac-item
2023-07-18 10:17:19	ga_ls9c_ard_3-2-1_100073_2023-07-18_final.stac-item
2023-07-18 10:18:30	ga_ls9c_ard_3-2-1_100076_2023-07-18_final.stac-item
2023-07-18 10:19:18	ga_ls9c_ard_3-2-1_100078_2023-07-18_final.stac-item
2023-07-18 10:19:42	ga_ls9c_ard_3-2-1_100079_2023-07-18_final.stac-item
2023-07-18 10:20:06	ga_ls9c_ard_3-2-1_100080_2023-07-18_final.stac-item
2023-07-18 10:20:30	ga_ls9c_ard_3-2-1_100081_2023-07-18_final.stac-item
2023-07-18 10:20:54	ga_ls9c_ard_3-2-1_100082_2023-07-18_final.stac-item
2023-07-18 10:21:18	ga_ls9c_ard_3-2-1_100083_2023-07-18_final.stac-item
2023-07-18 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-07-18_final.stac-item
2023-07-18 11:58:11	ga_ls9c_ard_3-2-1_116078_2023-07-18_final.stac-item
2023-07-19 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-07-18_final.stac-item
2023-07-19 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-07-18_final.stac-item
2023-07-19 09:22:05	ga_ls9c_ard_3-2-1_091074_2023-07-18_final.stac-item
2023-07-19 09:22:29	ga_ls9c_ard_3-2-1_091075_2023-07-18_final.stac-item
2023-07-19 09:22:53	ga_ls9c_ard_3-2-1_091076_2023-07-18_final.stac-item
2023-07-19 09:24:53	ga_ls9c_ard_3-2-1_091081_2023-07-18_final.stac-item
2023-07-19 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-07-18_final.stac-item
2023-07-19 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-07-18_final.stac-item
2023-07-19 09:26:29	ga_ls9c_ard_3-2-1_091085_2023-07-18_final.stac-item
2023-07-19 09:26:52	ga_ls9c_ard_3-2-1_091086_2023-07-18_final.stac-item
2023-07-19 11:00:10	ga_ls9c_ard_3-2-1_107072_2023-07-19_final.stac-item
2023-07-19 11:00:58	ga_ls9c_ard_3-2-1_107074_2023-07-19_final.stac-item
2023-07-19 11:03:22	ga_ls9c_ard_3-2-1_107080_2023-07-19_final.stac-item
2023-07-19 11:03:46	ga_ls9c_ard_3-2-1_107081_2023-07-19_final.stac-item
2023-07-19 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-07-19_final.stac-item
2023-07-19 11:04:58	ga_ls9c_ard_3-2-1_107084_2023-07-19_final.stac-item
2023-07-20 10:03:21	ga_ls9c_ard_3-2-1_098069_2023-07-20_final.stac-item
2023-07-20 10:05:21	ga_ls9c_ard_3-2-1_098074_2023-07-20_final.stac-item
2023-07-20 10:08:08	ga_ls9c_ard_3-2-1_098081_2023-07-20_final.stac-item
2023-07-20 10:08:32	ga_ls9c_ard_3-2-1_098082_2023-07-20_final.stac-item
2023-07-20 10:08:56	ga_ls9c_ard_3-2-1_098083_2023-07-20_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-20 11:46:37	ga_ls9c_ard_3-2-1_114080_2023-07-20_final.stac-item
2023-07-20 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-07-20_final.stac-item
2023-07-21 09:10:07	ga_ls9c_ard_3-2-1_089075_2023-07-20_final.stac-item
2023-07-21 09:10:31	ga_ls9c_ard_3-2-1_089076_2023-07-20_final.stac-item
2023-07-21 09:10:55	ga_ls9c_ard_3-2-1_089077_2023-07-20_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-07-21 09:12:31	ga_ls9c_ard_3-2-1_089081_2023-07-20_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-07-21 09:13:43	ga_ls9c_ard_3-2-1_089084_2023-07-20_final.stac-item
2023-07-21 09:14:07	ga_ls9c_ard_3-2-1_089085_2023-07-20_final.stac-item
2023-07-21 09:16:06	ga_ls9c_ard_3-2-1_089090_2023-07-20_final.stac-item
2023-07-21 10:47:00	ga_ls9c_ard_3-2-1_105070_2023-07-21_final.stac-item
2023-07-21 10:47:24	ga_ls9c_ard_3-2-1_105071_2023-07-21_final.stac-item
2023-07-21 10:47:48	ga_ls9c_ard_3-2-1_105072_2023-07-21_final.stac-item
2023-07-21 10:48:12	ga_ls9c_ard_3-2-1_105073_2023-07-21_final.stac-item
2023-07-21 10:48:36	ga_ls9c_ard_3-2-1_105074_2023-07-21_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-07-22 09:51:23	ga_ls9c_ard_3-2-1_096070_2023-07-22_final.stac-item
2023-07-22 09:52:11	ga_ls9c_ard_3-2-1_096072_2023-07-22_final.stac-item
2023-07-22 09:54:34	ga_ls9c_ard_3-2-1_096078_2023-07-22_final.stac-item
2023-07-22 09:54:58	ga_ls9c_ard_3-2-1_096079_2023-07-22_final.stac-item
2023-07-22 09:55:22	ga_ls9c_ard_3-2-1_096080_2023-07-22_final.stac-item
2023-07-22 09:56:10	ga_ls9c_ard_3-2-1_096082_2023-07-22_final.stac-item
2023-07-22 09:56:58	ga_ls9c_ard_3-2-1_096084_2023-07-22_final.stac-item
2023-07-22 09:57:46	ga_ls9c_ard_3-2-1_096086_2023-07-22_final.stac-item
2023-07-22 11:31:04	ga_ls9c_ard_3-2-1_112072_2023-07-22_final.stac-item
2023-07-22 11:31:52	ga_ls9c_ard_3-2-1_112074_2023-07-22_final.stac-item
2023-07-22 11:32:15	ga_ls9c_ard_3-2-1_112075_2023-07-22_final.stac-item
2023-07-22 11:32:39	ga_ls9c_ard_3-2-1_112076_2023-07-22_final.stac-item
2023-07-22 11:33:51	ga_ls9c_ard_3-2-1_112079_2023-07-22_final.stac-item
2023-07-22 11:34:39	ga_ls9c_ard_3-2-1_112081_2023-07-22_final.stac-item
2023-07-23 10:33:50	ga_ls9c_ard_3-2-1_103068_2023-07-23_final.stac-item
2023-07-23 10:35:26	ga_ls9c_ard_3-2-1_103072_2023-07-23_final.stac-item
2023-07-23 10:37:26	ga_ls9c_ard_3-2-1_103077_2023-07-23_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