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
2021-12-09 11:23:27	ga_ls9c_ard_3-2-1_110082_2021-12-09_final.stac-item
2021-12-11 09:31:47	ga_ls9c_ard_3-2-1_092081_2021-12-11_final.stac-item
2021-12-19 10:17:59	ga_ls9c_ard_3-2-1_100073_2021-12-19_final.stac-item
2021-12-28 10:13:01	ga_ls9c_ard_3-2-1_099076_2021-12-28_final.stac-item
2022-01-05 09:26:21	ga_ls9c_ard_3-2-1_091083_2022-01-04_final.stac-item
2022-01-15 11:41:29	ga_ls9c_ard_3-2-1_113081_2022-01-15_final.stac-item
2022-01-20 10:21:09	ga_ls9c_ard_3-2-1_100081_2022-01-20_final.stac-item
2022-01-23 09:11:59	ga_ls9c_ard_3-2-1_089078_2022-01-22_final.stac-item
2022-01-26 11:20:59	ga_ls9c_ard_3-2-1_110076_2022-01-26_final.stac-item
2022-01-29 10:15:23	ga_ls9c_ard_3-2-1_099082_2022-01-29_final.stac-item
2022-02-09 09:55:37	ga_ls9c_ard_3-2-1_096079_2022-02-09_final.stac-item
2022-02-11 09:45:15	ga_ls9c_ard_3-2-1_094084_2022-02-11_final.stac-item
2022-02-22 11:05:05	ga_ls9c_ard_3-2-1_107083_2022-02-22_final.stac-item
2022-03-19 10:53:35	ga_ls9c_ard_3-2-1_106070_2022-03-19_final.stac-item
2022-03-19 10:54:47	ga_ls9c_ard_3-2-1_106073_2022-03-19_final.stac-item
2022-03-20 10:03:33	ga_ls9c_ard_3-2-1_097084_2022-03-20_final.stac-item
2022-03-25 10:21:39	ga_ls9c_ard_3-2-1_100083_2022-03-25_final.stac-item
2022-03-28 10:51:20	ga_ls9c_ard_3-2-1_105080_2022-03-28_final.stac-item
2022-05-01 10:34:47	ga_ls9c_ard_3-2-1_103070_2022-05-01_final.stac-item
2022-05-04 11:08:04	ga_ls9c_ard_3-2-1_108076_2022-05-04_final.stac-item
2022-05-05 11:52:07	ga_ls9c_ard_3-2-1_115078_2022-05-05_final.stac-item
2022-05-12 10:17:44	ga_ls9c_ard_3-2-1_100074_2022-05-12_final.stac-item
2022-05-13 10:59:47	ga_ls9c_ard_3-2-1_107071_2022-05-13_final.stac-item
2022-05-15 09:11:19	ga_ls9c_ard_3-2-1_089078_2022-05-14_final.stac-item
2022-05-15 09:12:30	ga_ls9c_ard_3-2-1_089081_2022-05-14_final.stac-item
2022-06-07 10:54:43	ga_ls9c_ard_3-2-1_106074_2022-06-07_final.stac-item
2022-06-17 09:52:38	ga_ls9c_ard_3-2-1_096073_2022-06-17_final.stac-item
2022-06-25 09:06:13	ga_ls9c_ard_3-2-1_088080_2022-06-24_final.stac-item
2022-06-25 10:45:06	ga_ls9c_ard_3-2-1_104080_2022-06-25_final.stac-item
2022-06-26 11:25:10	ga_ls9c_ard_3-2-1_111072_2022-06-26_final.stac-item
2022-07-13 10:29:04	ga_ls9c_ard_3-2-1_102071_2022-07-13_final.stac-item
2022-07-21 09:42:08	ga_ls9c_ard_3-2-1_094077_2022-07-21_final.stac-item
2022-07-25 10:53:57	ga_ls9c_ard_3-2-1_106071_2022-07-25_final.stac-item
2022-07-30 11:17:45	ga_ls9c_ard_3-2-1_109084_2022-07-30_final.stac-item
2022-08-31 09:37:52	ga_ls9c_ard_3-2-1_093081_2022-08-31_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-10-18 09:38:05	ga_ls9c_ard_3-2-1_093081_2022-10-18_final.stac-item
2022-10-31 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-10-31_final.stac-item
2022-11-14 09:20:46	ga_ls9c_ard_3-2-1_090084_2022-11-13_final.stac-item
2022-11-17 09:50:52	ga_ls9c_ard_3-2-1_095082_2022-11-17_final.stac-item
2022-11-25 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-11-25_final.stac-item
2022-11-25 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-25_final.stac-item
2022-12-05 09:38:28	ga_ls9c_ard_3-2-1_093082_2022-12-05_final.stac-item
2022-12-12 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-12-12_final.stac-item
2022-12-21 11:15:44	ga_ls9c_ard_3-2-1_109078_2022-12-21_final.stac-item
2022-12-22 10:18:54	ga_ls9c_ard_3-2-1_100075_2022-12-22_final.stac-item
2022-12-30 09:33:29	ga_ls9c_ard_3-2-1_092085_2022-12-30_final.stac-item
2023-01-02 11:42:29	ga_ls9c_ard_3-2-1_113083_2023-01-02_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-08 09:28:55	ga_ls9c_ard_3-2-1_091089_2023-01-07_final.stac-item
2023-01-18 09:59:54	ga_ls9c_ard_3-2-1_097074_2023-01-18_final.stac-item
2023-02-03 10:01:39	ga_ls9c_ard_3-2-1_097078_2023-02-03_final.stac-item
2023-02-07 11:17:02	ga_ls9c_ard_3-2-1_109081_2023-02-07_final.stac-item
2023-02-13 10:40:19	ga_ls9c_ard_3-2-1_103082_2023-02-13_final.stac-item
2023-03-17 10:36:23	ga_ls9c_ard_3-2-1_103073_2023-03-17_final.stac-item
2023-03-18 11:23:38	ga_ls9c_ard_3-2-1_110083_2023-03-18_final.stac-item
2023-04-03 11:22:39	ga_ls9c_ard_3-2-1_110081_2023-04-03_final.stac-item
2023-04-07 10:54:43	ga_ls9c_ard_3-2-1_106073_2023-04-07_final.stac-item
2023-04-16 09:11:58	ga_ls9c_ard_3-2-1_089079_2023-04-15_final.stac-item
2023-04-16 10:51:39	ga_ls9c_ard_3-2-1_105081_2023-04-16_final.stac-item
2023-04-22 11:51:03	ga_ls9c_ard_3-2-1_115075_2023-04-22_final.stac-item
2023-05-02 09:12:13	ga_ls9c_ard_3-2-1_089080_2023-05-01_final.stac-item
2023-05-05 11:22:21	ga_ls9c_ard_3-2-1_110081_2023-05-05_final.stac-item
2023-05-18 10:51:23	ga_ls9c_ard_3-2-1_105081_2023-05-18_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 11:20:14	ga_ls9c_ard_3-2-1_110076_2023-05-21_final.stac-item
2023-06-12 10:43:23	ga_ls9c_ard_3-2-1_104077_2023-06-12_final.stac-item
2023-06-17 09:21:00	ga_ls9c_ard_3-2-1_091072_2023-06-16_final.stac-item
2023-07-04 10:07:15	ga_ls9c_ard_3-2-1_098079_2023-07-04_final.stac-item
2023-07-07 10:33:48	ga_ls9c_ard_3-2-1_103068_2023-07-07_final.stac-item
2023-07-08 11:22:15	ga_ls9c_ard_3-2-1_110081_2023-07-08_final.stac-item
2023-07-10 11:07:55	ga_ls9c_ard_3-2-1_108076_2023-07-10_final.stac-item
2023-07-11 11:51:35	ga_ls9c_ard_3-2-1_115077_2023-07-11_final.stac-item
2023-07-15 09:50:48	ga_ls9c_ard_3-2-1_095084_2023-07-15_final.stac-item
2023-07-19 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-07-18_final.stac-item
2023-07-26 11:07:56	ga_ls9c_ard_3-2-1_108076_2023-07-26_final.stac-item
2023-07-28 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-07-27_final.stac-item
2023-08-16 09:46:10	ga_ls9c_ard_3-2-1_095072_2023-08-16_final.stac-item
2023-08-18 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-08-18_final.stac-item
2023-08-24 10:36:07	ga_ls9c_ard_3-2-1_103073_2023-08-24_final.stac-item
2023-08-28 10:09:26	ga_ls9c_ard_3-2-1_099068_2023-08-28_final.stac-item
2023-09-06 10:08:08	ga_ls9c_ard_3-2-1_098080_2023-09-06_final.stac-item
2023-09-10 09:45:03	ga_ls9c_ard_3-2-1_094084_2023-09-10_final.stac-item
2023-09-13 11:52:04	ga_ls9c_ard_3-2-1_115077_2023-09-13_final.stac-item
2023-09-20 10:21:22	ga_ls9c_ard_3-2-1_100082_2023-09-20_final.stac-item
2023-09-21 09:21:45	ga_ls9c_ard_3-2-1_091072_2023-09-20_final.stac-item
2023-10-05 09:39:20	ga_ls9c_ard_3-2-1_093085_2023-10-05_final.stac-item
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final.stac-item
2023-11-07 10:22:16	ga_ls9c_ard_3-2-1_100084_2023-11-07_final.stac-item
2023-11-09 11:46:00	ga_ls9c_ard_3-2-1_114077_2023-11-09_final.stac-item
2023-11-15 09:32:25	ga_ls9c_ard_3-2-1_092083_2023-11-15_final.stac-item
2023-11-19 09:06:57	ga_ls9c_ard_3-2-1_088081_2023-11-18_final.stac-item
2023-11-23 11:58:52	ga_ls9c_ard_3-2-1_116078_2023-11-23_final.stac-item
2023-12-13 09:57:40	ga_ls9c_ard_3-2-1_096084_2023-12-13_final.stac-item
2023-12-15 11:18:37	ga_ls9c_ard_3-2-1_110070_2023-12-15_final.stac-item
2023-12-21 10:42:46	ga_ls9c_ard_3-2-1_104073_2023-12-21_final.stac-item
2023-12-22 11:30:01	ga_ls9c_ard_3-2-1_111083_2023-12-22_final.stac-item
2023-12-23 10:29:37	ga_ls9c_ard_3-2-1_102071_2023-12-23_final.stac-item
2023-12-24 11:12:05	ga_ls9c_ard_3-2-1_109069_2023-12-24_final.stac-item
2024-01-04 09:19:44	ga_ls9c_ard_3-2-1_090082_2024-01-03_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