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
2021-11-10 11:16:34	ga_ls9c_ard_3-2-1_110073_2021-11-10_final.stac-item
2021-11-23 10:03:38	ga_ls9c_ard_3-2-1_098072_2021-11-23_final.stac-item
2021-12-07 09:52:58	ga_ls9c_ard_3-2-1_096072_2021-12-07_final.stac-item
2021-12-20 11:03:38	ga_ls9c_ard_3-2-1_107079_2021-12-20_final.stac-item
2022-01-03 09:40:42	ga_ls9c_ard_3-2-1_093088_2022-01-03_final.stac-item
2022-01-08 11:34:07	ga_ls9c_ard_3-2-1_112078_2022-01-08_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-01-24 11:34:08	ga_ls9c_ard_3-2-1_112078_2022-01-24_final.stac-item
2022-02-05 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-02-05_final.stac-item
2022-02-09 11:34:06	ga_ls9c_ard_3-2-1_112078_2022-02-09_final.stac-item
2022-02-15 09:20:29	ga_ls9c_ard_3-2-1_090084_2022-02-14_final.stac-item
2022-03-04 10:01:35	ga_ls9c_ard_3-2-1_097079_2022-03-04_final.stac-item
2022-03-24 09:34:01	ga_ls9c_ard_3-2-1_093072_2022-03-24_final.stac-item
2022-03-24 09:36:00	ga_ls9c_ard_3-2-1_093077_2022-03-24_final.stac-item
2022-03-24 09:38:24	ga_ls9c_ard_3-2-1_093083_2022-03-24_final.stac-item
2022-03-25 10:21:15	ga_ls9c_ard_3-2-1_100082_2022-03-25_final.stac-item
2022-04-21 09:58:55	ga_ls9c_ard_3-2-1_097073_2022-04-21_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-06-07 09:18:14	ga_ls9c_ard_3-2-1_090080_2022-06-06_final.stac-item
2022-06-09 10:41:10	ga_ls9c_ard_3-2-1_104071_2022-06-09_final.stac-item
2022-06-19 09:41:07	ga_ls9c_ard_3-2-1_094075_2022-06-19_final.stac-item
2022-07-12 09:47:49	ga_ls9c_ard_3-2-1_095076_2022-07-12_final.stac-item
2022-08-17 09:27:05	ga_ls9c_ard_3-2-1_091085_2022-08-16_final.stac-item
2022-08-31 11:17:09	ga_ls9c_ard_3-2-1_109082_2022-08-31_final.stac-item
2022-09-04 10:48:26	ga_ls9c_ard_3-2-1_105072_2022-09-04_final.stac-item
2022-09-19 11:45:21	ga_ls9c_ard_3-2-1_114075_2022-09-19_final.stac-item
2022-09-28 10:01:55	ga_ls9c_ard_3-2-1_097079_2022-09-28_final.stac-item
2022-10-01 10:29:14	ga_ls9c_ard_3-2-1_102070_2022-10-01_final.stac-item
2022-10-01 10:33:13	ga_ls9c_ard_3-2-1_102080_2022-10-01_final.stac-item
2022-10-16 11:25:44	ga_ls9c_ard_3-2-1_111072_2022-10-16_final.stac-item
2022-10-16 11:29:19	ga_ls9c_ard_3-2-1_111081_2022-10-16_final.stac-item
2022-11-23 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-11-22_final.stac-item
2023-05-02 10:47:06	ga_ls9c_ard_3-2-1_105070_2023-05-02_final.stac-item
2023-05-02 10:47:30	ga_ls9c_ard_3-2-1_105071_2023-05-02_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 11:35:56	ga_ls9c_ard_3-2-1_112084_2023-05-03_final.stac-item
2023-05-04 10:39:29	ga_ls9c_ard_3-2-1_103082_2023-05-04_final.stac-item
2023-05-05 11:19:33	ga_ls9c_ard_3-2-1_110074_2023-05-05_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 10:54:02	ga_ls9c_ard_3-2-1_106072_2023-05-09_final.stac-item
2023-05-12 11:29:19	ga_ls9c_ard_3-2-1_111083_2023-05-12_final.stac-item
2023-05-12 11:29:43	ga_ls9c_ard_3-2-1_111084_2023-05-12_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
2023-05-16 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-05-15_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-05-17 10:07:44	ga_ls9c_ard_3-2-1_098080_2023-05-17_final.stac-item
2023-05-18 09:13:18	ga_ls9c_ard_3-2-1_089083_2023-05-17_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
2023-05-19 11:35:01	ga_ls9c_ard_3-2-1_112082_2023-05-19_final.stac-item
2023-05-21 09:40:33	ga_ls9c_ard_3-2-1_094074_2023-05-21_final.stac-item
2023-05-21 11:18:39	ga_ls9c_ard_3-2-1_110072_2023-05-21_final.stac-item
2023-05-21 11:21:50	ga_ls9c_ard_3-2-1_110080_2023-05-21_final.stac-item
2023-05-22 10:26:12	ga_ls9c_ard_3-2-1_101080_2023-05-22_final.stac-item
2023-09-04 10:17:40	ga_ls9c_ard_3-2-1_100073_2023-09-04_final.stac-item
2023-09-05 09:24:04	ga_ls9c_ard_3-2-1_091078_2023-09-04_final.stac-item
2023-09-05 09:25:15	ga_ls9c_ard_3-2-1_091081_2023-09-04_final.stac-item
2023-09-05 09:27:15	ga_ls9c_ard_3-2-1_091086_2023-09-04_final.stac-item
2023-09-06 10:05:44	ga_ls9c_ard_3-2-1_098074_2023-09-06_final.stac-item
2023-09-06 10:08:08	ga_ls9c_ard_3-2-1_098080_2023-09-06_final.stac-item
2023-09-09 10:38:40	ga_ls9c_ard_3-2-1_103079_2023-09-09_final.stac-item
2023-09-09 10:39:52	ga_ls9c_ard_3-2-1_103082_2023-09-09_final.stac-item
2023-09-10 09:43:28	ga_ls9c_ard_3-2-1_094080_2023-09-10_final.stac-item
2023-09-10 11:19:33	ga_ls9c_ard_3-2-1_110073_2023-09-10_final.stac-item
2023-09-13 10:14:23	ga_ls9c_ard_3-2-1_099080_2023-09-13_final.stac-item
2023-09-13 10:15:35	ga_ls9c_ard_3-2-1_099083_2023-09-13_final.stac-item
2023-09-14 10:57:39	ga_ls9c_ard_3-2-1_106080_2023-09-14_final.stac-item
2023-09-15 09:59:38	ga_ls9c_ard_3-2-1_097074_2023-09-15_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 11:39:19	ga_ls9c_ard_3-2-1_113076_2023-09-15_final.stac-item
2023-09-16 10:43:42	ga_ls9c_ard_3-2-1_104076_2023-09-16_final.stac-item
2023-09-17 09:48:05	ga_ls9c_ard_3-2-1_095076_2023-09-17_final.stac-item
2023-09-18 10:31:21	ga_ls9c_ard_3-2-1_102076_2023-09-18_final.stac-item
2023-09-20 10:21:46	ga_ls9c_ard_3-2-1_100083_2023-09-20_final.stac-item
2023-09-21 09:25:45	ga_ls9c_ard_3-2-1_091082_2023-09-20_final.stac-item
2023-09-21 11:00:38	ga_ls9c_ard_3-2-1_107072_2023-09-21_final.stac-item
2023-09-21 11:01:50	ga_ls9c_ard_3-2-1_107075_2023-09-21_final.stac-item
2023-09-22 10:06:12	ga_ls9c_ard_3-2-1_098075_2023-09-22_final.stac-item
2023-09-22 11:45:05	ga_ls9c_ard_3-2-1_114075_2023-09-22_final.stac-item
2023-09-23 10:48:15	ga_ls9c_ard_3-2-1_105072_2023-09-23_final.stac-item
2023-09-25 10:37:52	ga_ls9c_ard_3-2-1_103077_2023-09-25_final.stac-item
2023-09-26 09:43:26	ga_ls9c_ard_3-2-1_094080_2023-09-26_final.stac-item
2023-09-26 11:22:19	ga_ls9c_ard_3-2-1_110080_2023-09-26_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 11:50:49	ga_ls9c_ard_3-2-1_115074_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
2023-10-03 09:47:41	ga_ls9c_ard_3-2-1_095075_2023-10-03_final.stac-item
2023-10-03 11:26:34	ga_ls9c_ard_3-2-1_111075_2023-10-03_final.stac-item
2023-10-06 10:21:25	ga_ls9c_ard_3-2-1_100082_2023-10-06_final.stac-item
2023-10-07 11:00:17	ga_ls9c_ard_3-2-1_107071_2023-10-07_final.stac-item
2023-10-08 10:03:29	ga_ls9c_ard_3-2-1_098068_2023-10-08_final.stac-item
2023-10-09 09:13:27	ga_ls9c_ard_3-2-1_089082_2023-10-08_final.stac-item
2023-10-09 10:49:32	ga_ls9c_ard_3-2-1_105075_2023-10-09_final.stac-item
2023-10-09 10:51:56	ga_ls9c_ard_3-2-1_105081_2023-10-09_final.stac-item
2023-10-10 11:35:37	ga_ls9c_ard_3-2-1_112082_2023-10-10_final.stac-item
2023-10-12 09:43:36	ga_ls9c_ard_3-2-1_094080_2023-10-12_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