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 11:12:53	ga_ls9c_ard_3-2-1_109070_2021-11-05_final.stac-item
2021-11-12 10:57:25	ga_ls9c_ard_3-2-1_106072_2021-11-12_final.stac-item
2021-11-23 11:43:05	ga_ls9c_ard_3-2-1_114074_2021-11-23_final.stac-item
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-13 10:53:06	ga_ls9c_ard_3-2-1_106068_2021-12-13_final.stac-item
2021-12-18 11:12:00	ga_ls9c_ard_3-2-1_109069_2021-12-18_final.stac-item
2022-01-05 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-04_final.stac-item
2022-01-12 11:07:47	ga_ls9c_ard_3-2-1_108074_2022-01-12_final.stac-item
2022-01-14 09:20:31	ga_ls9c_ard_3-2-1_090084_2022-01-13_final.stac-item
2022-01-23 09:11:35	ga_ls9c_ard_3-2-1_089077_2022-01-22_final.stac-item
2022-01-23 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-23_final.stac-item
2022-02-01 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-01-31_final.stac-item
2022-02-01 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-02-01_final.stac-item
2022-02-19 10:28:14	ga_ls9c_ard_3-2-1_102068_2022-02-19_final.stac-item
2022-03-05 09:06:45	ga_ls9c_ard_3-2-1_088081_2022-03-04_final.stac-item
2022-04-03 11:51:09	ga_ls9c_ard_3-2-1_115075_2022-04-03_final.stac-item
2022-04-04 10:55:55	ga_ls9c_ard_3-2-1_106076_2022-04-04_final.stac-item
2022-04-13 09:11:11	ga_ls9c_ard_3-2-1_089077_2022-04-12_final.stac-item
2022-04-13 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-04-12_final.stac-item
2022-04-18 09:34:27	ga_ls9c_ard_3-2-1_092089_2022-04-18_final.stac-item
2022-04-29 10:51:57	ga_ls9c_ard_3-2-1_105082_2022-04-29_final.stac-item
2022-05-04 11:11:15	ga_ls9c_ard_3-2-1_108084_2022-05-04_final.stac-item
2022-05-20 09:33:45	ga_ls9c_ard_3-2-1_092088_2022-05-20_final.stac-item
2022-05-27 09:39:32	ga_ls9c_ard_3-2-1_093087_2022-05-27_final.stac-item
2022-06-03 11:17:50	ga_ls9c_ard_3-2-1_110070_2022-06-03_final.stac-item
2022-06-14 09:27:16	ga_ls9c_ard_3-2-1_091087_2022-06-13_final.stac-item
2022-06-15 10:08:57	ga_ls9c_ard_3-2-1_098083_2022-06-15_final.stac-item
2022-06-19 11:23:35	ga_ls9c_ard_3-2-1_110084_2022-06-19_final.stac-item
2022-07-05 09:46:04	ga_ls9c_ard_3-2-1_094087_2022-07-05_final.stac-item
2022-07-05 11:19:46	ga_ls9c_ard_3-2-1_110074_2022-07-05_final.stac-item
2022-07-09 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-07-09_final.stac-item
2022-07-26 09:57:09	ga_ls9c_ard_3-2-1_097068_2022-07-26_final.stac-item
2022-07-30 09:40:04	ga_ls9c_ard_3-2-1_093087_2022-07-30_final.stac-item
2022-08-01 09:22:57	ga_ls9c_ard_3-2-1_091075_2022-07-31_final.stac-item
2022-08-08 11:07:41	ga_ls9c_ard_3-2-1_108074_2022-08-08_final.stac-item
2022-08-09 10:10:53	ga_ls9c_ard_3-2-1_099071_2022-08-09_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-08-17 09:28:40	ga_ls9c_ard_3-2-1_091089_2022-08-16_final.stac-item
2022-08-19 10:49:37	ga_ls9c_ard_3-2-1_105075_2022-08-19_final.stac-item
2022-08-24 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-08-24_final.stac-item
2022-08-24 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-08-24_final.stac-item
2022-08-25 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-08-25_final.stac-item
2022-08-28 09:07:46	ga_ls9c_ard_3-2-1_088083_2022-08-27_final.stac-item
2022-10-04 11:00:07	ga_ls9c_ard_3-2-1_107070_2022-10-04_final.stac-item
2022-10-06 09:10:28	ga_ls9c_ard_3-2-1_089074_2022-10-05_final.stac-item
2022-10-06 10:46:57	ga_ls9c_ard_3-2-1_105068_2022-10-06_final.stac-item
2022-10-11 11:07:33	ga_ls9c_ard_3-2-1_108073_2022-10-11_final.stac-item
2022-10-12 10:11:32	ga_ls9c_ard_3-2-1_099072_2022-10-12_final.stac-item
2022-10-18 11:12:11	ga_ls9c_ard_3-2-1_109069_2022-10-18_final.stac-item
2022-10-18 11:14:10	ga_ls9c_ard_3-2-1_109074_2022-10-18_final.stac-item
2022-10-22 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-10-21_final.stac-item
2022-11-05 09:29:17	ga_ls9c_ard_3-2-1_091090_2022-11-04_final.stac-item
2022-11-06 11:47:51	ga_ls9c_ard_3-2-1_114081_2022-11-06_final.stac-item
2022-11-07 09:13:21	ga_ls9c_ard_3-2-1_089081_2022-11-06_final.stac-item
2022-11-07 10:52:14	ga_ls9c_ard_3-2-1_105081_2022-11-07_final.stac-item
2022-11-17 11:26:10	ga_ls9c_ard_3-2-1_111073_2022-11-17_final.stac-item
2022-11-20 10:19:46	ga_ls9c_ard_3-2-1_100077_2022-11-20_final.stac-item
2022-11-22 10:05:01	ga_ls9c_ard_3-2-1_098071_2022-11-22_final.stac-item
2022-11-29 11:52:50	ga_ls9c_ard_3-2-1_115078_2022-11-29_final.stac-item
2022-11-30 09:22:18	ga_ls9c_ard_3-2-1_090088_2022-11-29_final.stac-item
2022-12-08 10:03:24	ga_ls9c_ard_3-2-1_098067_2022-12-08_final.stac-item
2022-12-08 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-12-08_final.stac-item
2022-12-16 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-12-15_final.stac-item
2022-12-24 10:04:56	ga_ls9c_ard_3-2-1_098071_2022-12-24_final.stac-item
2023-01-16 11:53:10	ga_ls9c_ard_3-2-1_115079_2023-01-16_final.stac-item
2023-01-21 10:33:56	ga_ls9c_ard_3-2-1_102082_2023-01-21_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-01-26 10:49:47	ga_ls9c_ard_3-2-1_105075_2023-01-26_final.stac-item
2023-02-01 10:13:59	ga_ls9c_ard_3-2-1_099078_2023-02-01_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-02-20 10:40:47	ga_ls9c_ard_3-2-1_104068_2023-02-20_final.stac-item
2023-02-23 11:14:00	ga_ls9c_ard_3-2-1_109074_2023-02-23_final.stac-item
2023-03-20 11:08:04	ga_ls9c_ard_3-2-1_108075_2023-03-20_final.stac-item
2023-03-23 11:38:32	ga_ls9c_ard_3-2-1_113074_2023-03-23_final.stac-item
2023-04-10 11:23:36	ga_ls9c_ard_3-2-1_111068_2023-04-10_final.stac-item
2023-04-16 10:46:51	ga_ls9c_ard_3-2-1_105069_2023-04-16_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-26 09:46:12	ga_ls9c_ard_3-2-1_095072_2023-04-26_final.stac-item
2023-04-26 09:51:48	ga_ls9c_ard_3-2-1_095086_2023-04-26_final.stac-item
2023-04-26 11:24:18	ga_ls9c_ard_3-2-1_111070_2023-04-26_final.stac-item
2023-04-29 10:21:27	ga_ls9c_ard_3-2-1_100083_2023-04-29_final.stac-item
2023-05-07 09:28:43	ga_ls9c_ard_3-2-1_092075_2023-05-06_final.stac-item
2023-05-08 10:12:46	ga_ls9c_ard_3-2-1_099077_2023-05-08_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-18 10:48:59	ga_ls9c_ard_3-2-1_105075_2023-05-18_final.stac-item
2023-05-27 09:06:36	ga_ls9c_ard_3-2-1_088082_2023-05-26_final.stac-item
2023-06-17 09:26:35	ga_ls9c_ard_3-2-1_091086_2023-06-16_final.stac-item
2023-06-17 11:01:05	ga_ls9c_ard_3-2-1_107075_2023-06-17_final.stac-item
2023-06-19 10:48:20	ga_ls9c_ard_3-2-1_105074_2023-06-19_final.stac-item
2023-06-22 09:45:32	ga_ls9c_ard_3-2-1_094087_2023-06-22_final.stac-item
2023-06-25 10:10:02	ga_ls9c_ard_3-2-1_099071_2023-06-25_final.stac-item
2023-06-29 09:51:48	ga_ls9c_ard_3-2-1_095087_2023-06-29_final.stac-item
2023-07-01 09:39:30	ga_ls9c_ard_3-2-1_093087_2023-07-01_final.stac-item
2023-07-07 10:38:59	ga_ls9c_ard_3-2-1_103081_2023-07-07_final.stac-item
2023-07-11 10:08:43	ga_ls9c_ard_3-2-1_099067_2023-07-11_final.stac-item
2023-09-12 11:08:00	ga_ls9c_ard_3-2-1_108075_2023-09-12_final.stac-item
2023-09-17 11:26:10	ga_ls9c_ard_3-2-1_111074_2023-09-17_final.stac-item
2023-09-19 09:40:30	ga_ls9c_ard_3-2-1_093088_2023-09-19_final.stac-item
2023-10-12 09:40:49	ga_ls9c_ard_3-2-1_094073_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