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
2021-11-05 09:37:25	ga_ls9c_ard_3-2-1_093078_2021-11-05_final.stac-item
2021-12-08 10:38:13	ga_ls9c_ard_3-2-1_103077_2021-12-08_final.stac-item
2021-12-11 09:32:11	ga_ls9c_ard_3-2-1_092082_2021-12-11_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-06-05 11:05:05	ga_ls9c_ard_3-2-1_108069_2022-06-05_final.stac-item
2022-06-23 09:18:55	ga_ls9c_ard_3-2-1_090081_2022-06-22_final.stac-item
2022-06-30 11:04:02	ga_ls9c_ard_3-2-1_107081_2022-06-30_final.stac-item
2022-07-09 10:53:25	ga_ls9c_ard_3-2-1_106070_2022-07-09_final.stac-item
2022-07-16 09:25:53	ga_ls9c_ard_3-2-1_091083_2022-07-15_final.stac-item
2022-07-30 09:34:53	ga_ls9c_ard_3-2-1_093074_2022-07-30_final.stac-item
2022-08-03 09:14:12	ga_ls9c_ard_3-2-1_089084_2022-08-02_final.stac-item
2022-08-29 09:49:50	ga_ls9c_ard_3-2-1_095080_2022-08-29_final.stac-item
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-24 10:23:50	ga_ls9c_ard_3-2-1_101072_2022-09-24_final.stac-item
2022-09-27 09:19:27	ga_ls9c_ard_3-2-1_090081_2022-09-26_final.stac-item
2022-10-04 11:02:55	ga_ls9c_ard_3-2-1_107077_2022-10-04_final.stac-item
2022-10-10 10:26:16	ga_ls9c_ard_3-2-1_101078_2022-10-10_final.stac-item
2022-10-12 11:52:01	ga_ls9c_ard_3-2-1_115076_2022-10-12_final.stac-item
2022-10-17 10:32:06	ga_ls9c_ard_3-2-1_102077_2022-10-17_final.stac-item
2022-10-20 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-10-20_final.stac-item
2022-10-25 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-10-25_final.stac-item
2022-10-31 10:41:39	ga_ls9c_ard_3-2-1_104070_2022-10-31_final.stac-item
2022-11-03 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-11-03_final.stac-item
2022-11-06 11:47:27	ga_ls9c_ard_3-2-1_114080_2022-11-06_final.stac-item
2022-11-13 10:11:59	ga_ls9c_ard_3-2-1_099073_2022-11-13_final.stac-item
2022-11-17 09:51:16	ga_ls9c_ard_3-2-1_095083_2022-11-17_final.stac-item
2022-11-17 09:51:40	ga_ls9c_ard_3-2-1_095084_2022-11-17_final.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-11-21 09:24:57	ga_ls9c_ard_3-2-1_091079_2022-11-20_final.stac-item
2022-12-05 11:12:33	ga_ls9c_ard_3-2-1_109070_2022-12-05_final.stac-item
2022-12-08 10:06:59	ga_ls9c_ard_3-2-1_098076_2022-12-08_final.stac-item
2022-12-08 10:07:23	ga_ls9c_ard_3-2-1_098077_2022-12-08_final.stac-item
2022-12-09 10:47:27	ga_ls9c_ard_3-2-1_105069_2022-12-09_final.stac-item
2022-12-10 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-12-10_final.stac-item
2022-12-14 11:07:12	ga_ls9c_ard_3-2-1_108072_2022-12-14_final.stac-item
2022-12-15 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-15_final.stac-item
2022-12-15 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-12-15_final.stac-item
2022-12-18 10:41:16	ga_ls9c_ard_3-2-1_104069_2022-12-18_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 09:36:51	ga_ls9c_ard_3-2-1_093078_2022-12-21_final.stac-item
2022-12-30 11:11:35	ga_ls9c_ard_3-2-1_108083_2022-12-30_final.stac-item
2023-01-13 09:45:25	ga_ls9c_ard_3-2-1_094084_2023-01-13_final.stac-item
2023-01-13 09:45:49	ga_ls9c_ard_3-2-1_094085_2023-01-13_final.stac-item
2023-01-17 09:18:39	ga_ls9c_ard_3-2-1_090079_2023-01-16_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-20 09:51:53	ga_ls9c_ard_3-2-1_095085_2023-01-20_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-22 11:14:50	ga_ls9c_ard_3-2-1_109076_2023-01-22_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-01-25 11:47:00	ga_ls9c_ard_3-2-1_114079_2023-01-25_final.stac-item
2023-01-27 11:34:40	ga_ls9c_ard_3-2-1_112079_2023-01-27_final.stac-item
2023-02-02 09:20:46	ga_ls9c_ard_3-2-1_090084_2023-02-01_final.stac-item
2023-02-03 11:42:07	ga_ls9c_ard_3-2-1_113082_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
2023-02-08 10:21:48	ga_ls9c_ard_3-2-1_100082_2023-02-08_final.stac-item
2023-02-10 10:08:15	ga_ls9c_ard_3-2-1_098079_2023-02-10_final.stac-item
2023-02-11 09:14:37	ga_ls9c_ard_3-2-1_089084_2023-02-10_final.stac-item
2023-02-11 10:50:42	ga_ls9c_ard_3-2-1_105077_2023-02-11_final.stac-item
2023-02-22 10:33:58	ga_ls9c_ard_3-2-1_102082_2023-02-22_final.stac-item
2023-03-02 11:20:57	ga_ls9c_ard_3-2-1_110076_2023-03-02_final.stac-item
2023-03-03 10:25:20	ga_ls9c_ard_3-2-1_101076_2023-03-03_final.stac-item
2023-03-11 09:35:23	ga_ls9c_ard_3-2-1_093075_2023-03-11_final.stac-item
2023-04-03 11:22:39	ga_ls9c_ard_3-2-1_110081_2023-04-03_final.stac-item
2023-04-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2023-04-22_final.stac-item
2023-04-28 09:37:24	ga_ls9c_ard_3-2-1_093081_2023-04-28_final.stac-item
2023-04-30 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-04-30_final.stac-item
2023-05-02 10:45:55	ga_ls9c_ard_3-2-1_105067_2023-05-02_final.stac-item
2023-05-07 09:31:30	ga_ls9c_ard_3-2-1_092082_2023-05-07_final.stac-item
2023-05-16 10:59:22	ga_ls9c_ard_3-2-1_107070_2023-05-16_final.stac-item
2023-06-24 09:30:22	ga_ls9c_ard_3-2-1_092080_2023-06-24_final.stac-item
2023-06-27 09:58:31	ga_ls9c_ard_3-2-1_097073_2023-06-27_final.stac-item
2023-07-03 09:24:22	ga_ls9c_ard_3-2-1_091080_2023-07-02_final.stac-item
2023-07-05 10:45:44	ga_ls9c_ard_3-2-1_105067_2023-07-05_final.stac-item
2023-07-15 09:50:24	ga_ls9c_ard_3-2-1_095083_2023-07-15_final.stac-item
2023-07-19 11:03:46	ga_ls9c_ard_3-2-1_107081_2023-07-19_final.stac-item
2023-07-21 09:12:31	ga_ls9c_ard_3-2-1_089081_2023-07-20_final.stac-item
2023-07-29 11:40:54	ga_ls9c_ard_3-2-1_113081_2023-07-29_final.stac-item
2023-08-02 11:11:50	ga_ls9c_ard_3-2-1_109070_2023-08-02_final.stac-item
2023-10-15 10:11:45	ga_ls9c_ard_3-2-1_099073_2023-10-15_final.stac-item
2023-10-16 09:19:20	ga_ls9c_ard_3-2-1_090081_2023-10-15_final.stac-item
2023-10-25 09:15:09	ga_ls9c_ard_3-2-1_089086_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 09:52:48	ga_ls9c_ard_3-2-1_096072_2023-10-26_final.stac-item
2023-10-27 10:34:52	ga_ls9c_ard_3-2-1_103069_2023-10-27_final.stac-item
2023-11-01 09:21:14	ga_ls9c_ard_3-2-1_090086_2023-10-31_final.stac-item
2023-11-02 09:58:53	ga_ls9c_ard_3-2-1_097072_2023-11-02_final.stac-item
2023-11-02 11:40:58	ga_ls9c_ard_3-2-1_113080_2023-11-02_final.stac-item
2023-11-15 11:05:43	ga_ls9c_ard_3-2-1_108069_2023-11-15_final.stac-item
2023-11-15 11:10:54	ga_ls9c_ard_3-2-1_108082_2023-11-15_final.stac-item
2023-11-18 10:03:22	ga_ls9c_ard_3-2-1_097083_2023-11-18_final.stac-item
2023-11-19 10:41:27	ga_ls9c_ard_3-2-1_104070_2023-11-19_final.stac-item
2023-11-19 10:43:51	ga_ls9c_ard_3-2-1_104076_2023-11-19_final.stac-item
2023-11-22 11:12:48	ga_ls9c_ard_3-2-1_109071_2023-11-22_final.stac-item
2023-11-23 10:18:23	ga_ls9c_ard_3-2-1_100074_2023-11-23_final.stac-item
2023-11-23 11:58:52	ga_ls9c_ard_3-2-1_116078_2023-11-23_final.stac-item
2023-11-25 10:06:27	ga_ls9c_ard_3-2-1_098075_2023-11-25_final.stac-item
2023-11-25 11:47:19	ga_ls9c_ard_3-2-1_114080_2023-11-25_final.stac-item
2023-11-25 11:47:43	ga_ls9c_ard_3-2-1_114081_2023-11-25_final.stac-item
2023-11-29 11:23:01	ga_ls9c_ard_3-2-1_110081_2023-11-29_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