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
2021-11-09 10:37:48	ga_ls9c_ard_3-2-1_103076_2021-11-09_final.stac-item
2021-12-07 09:55:21	ga_ls9c_ard_3-2-1_096078_2021-12-07_final.stac-item
2022-01-19 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-01-19_final.stac-item
2022-01-26 09:42:53	ga_ls9c_ard_3-2-1_094078_2022-01-26_final.stac-item
2022-02-14 10:14:55	ga_ls9c_ard_3-2-1_099081_2022-02-14_final.stac-item
2022-02-18 09:49:46	ga_ls9c_ard_3-2-1_095080_2022-02-18_final.stac-item
2022-02-27 09:45:28	ga_ls9c_ard_3-2-1_094085_2022-02-27_final.stac-item
2022-03-12 10:51:02	ga_ls9c_ard_3-2-1_105079_2022-03-12_final.stac-item
2022-03-24 09:39:36	ga_ls9c_ard_3-2-1_093086_2022-03-24_final.stac-item
2022-04-12 10:09:13	ga_ls9c_ard_3-2-1_098083_2022-04-12_final.stac-item
2022-04-18 09:30:52	ga_ls9c_ard_3-2-1_092080_2022-04-18_final.stac-item
2022-05-04 09:30:46	ga_ls9c_ard_3-2-1_092080_2022-05-04_final.stac-item
2022-05-18 09:43:21	ga_ls9c_ard_3-2-1_094081_2022-05-18_final.stac-item
2022-05-29 09:25:59	ga_ls9c_ard_3-2-1_091084_2022-05-28_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-06-28 09:36:43	ga_ls9c_ard_3-2-1_093079_2022-06-28_final.stac-item
2022-06-28 09:37:31	ga_ls9c_ard_3-2-1_093081_2022-06-28_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-07-15 10:18:18	ga_ls9c_ard_3-2-1_100075_2022-07-15_final.stac-item
2022-07-17 10:05:59	ga_ls9c_ard_3-2-1_098075_2022-07-17_final.stac-item
2022-07-20 10:38:08	ga_ls9c_ard_3-2-1_103078_2022-07-20_final.stac-item
2022-08-18 10:06:21	ga_ls9c_ard_3-2-1_098075_2022-08-18_final.stac-item
2022-08-31 09:38:40	ga_ls9c_ard_3-2-1_093083_2022-08-31_final.stac-item
2022-09-05 09:53:37	ga_ls9c_ard_3-2-1_096074_2022-09-05_final.stac-item
2022-09-17 10:18:48	ga_ls9c_ard_3-2-1_100075_2022-09-17_final.stac-item
2022-10-10 10:25:04	ga_ls9c_ard_3-2-1_101075_2022-10-10_final.stac-item
2022-10-11 09:30:15	ga_ls9c_ard_3-2-1_092077_2022-10-11_final.stac-item
2022-10-11 11:11:08	ga_ls9c_ard_3-2-1_108082_2022-10-11_final.stac-item
2022-10-12 10:13:08	ga_ls9c_ard_3-2-1_099076_2022-10-12_final.stac-item
2022-10-17 10:30:07	ga_ls9c_ard_3-2-1_102072_2022-10-17_final.stac-item
2022-10-17 10:32:30	ga_ls9c_ard_3-2-1_102078_2022-10-17_final.stac-item
2022-10-21 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-10-21_final.stac-item
2022-10-26 10:25:08	ga_ls9c_ard_3-2-1_101075_2022-10-26_final.stac-item
2022-10-30 11:40:29	ga_ls9c_ard_3-2-1_113078_2022-10-30_final.stac-item
2022-11-02 10:33:16	ga_ls9c_ard_3-2-1_102080_2022-11-02_final.stac-item
2022-11-13 10:15:11	ga_ls9c_ard_3-2-1_099081_2022-11-13_final.stac-item
2022-11-23 10:51:04	ga_ls9c_ard_3-2-1_105078_2022-11-23_final.stac-item
2022-11-26 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-11-26_final.stac-item
2022-11-26 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-26_final.stac-item
2022-12-04 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-04_final.stac-item
2022-12-17 10:03:12	ga_ls9c_ard_3-2-1_097082_2022-12-17_final.stac-item
2022-12-19 09:48:50	ga_ls9c_ard_3-2-1_095077_2022-12-19_final.stac-item
2022-12-21 11:13:44	ga_ls9c_ard_3-2-1_109073_2022-12-21_final.stac-item
2022-12-23 11:03:45	ga_ls9c_ard_3-2-1_107079_2022-12-23_final.stac-item
2023-01-02 11:40:54	ga_ls9c_ard_3-2-1_113079_2023-01-02_final.stac-item
2023-01-08 11:04:12	ga_ls9c_ard_3-2-1_107080_2023-01-08_final.stac-item
2023-01-11 09:56:36	ga_ls9c_ard_3-2-1_096081_2023-01-11_final.stac-item
2023-01-19 10:43:08	ga_ls9c_ard_3-2-1_104074_2023-01-19_final.stac-item
2023-01-29 11:23:08	ga_ls9c_ard_3-2-1_110081_2023-01-29_final.stac-item
2023-01-30 10:24:44	ga_ls9c_ard_3-2-1_101074_2023-01-30_final.stac-item
2023-01-31 09:35:06	ga_ls9c_ard_3-2-1_092089_2023-01-31_final.stac-item
2023-02-02 10:58:27	ga_ls9c_ard_3-2-1_106081_2023-02-02_final.stac-item
2023-02-03 10:02:50	ga_ls9c_ard_3-2-1_097081_2023-02-03_final.stac-item
2023-02-03 11:40:08	ga_ls9c_ard_3-2-1_113077_2023-02-03_final.stac-item
2023-02-05 09:50:30	ga_ls9c_ard_3-2-1_095081_2023-02-05_final.stac-item
2023-02-05 11:27:23	ga_ls9c_ard_3-2-1_111076_2023-02-05_final.stac-item
2023-02-05 11:28:59	ga_ls9c_ard_3-2-1_111080_2023-02-05_final.stac-item
2023-02-06 10:33:22	ga_ls9c_ard_3-2-1_102080_2023-02-06_final.stac-item
2023-02-14 09:42:42	ga_ls9c_ard_3-2-1_094077_2023-02-14_final.stac-item
2023-03-02 09:46:04	ga_ls9c_ard_3-2-1_094086_2023-03-02_final.stac-item
2023-04-25 10:41:27	ga_ls9c_ard_3-2-1_104071_2023-04-25_final.stac-item
2023-04-25 10:45:26	ga_ls9c_ard_3-2-1_104081_2023-04-25_final.stac-item
2023-04-28 09:35:25	ga_ls9c_ard_3-2-1_093076_2023-04-28_final.stac-item
2023-04-29 10:19:51	ga_ls9c_ard_3-2-1_100079_2023-04-29_final.stac-item
2023-05-01 10:05:28	ga_ls9c_ard_3-2-1_098074_2023-05-01_final.stac-item
2023-05-01 11:45:56	ga_ls9c_ard_3-2-1_114078_2023-05-01_final.stac-item
2023-05-04 10:37:30	ga_ls9c_ard_3-2-1_103077_2023-05-04_final.stac-item
2023-05-06 10:24:20	ga_ls9c_ard_3-2-1_101075_2023-05-06_final.stac-item
2023-05-07 09:29:30	ga_ls9c_ard_3-2-1_092077_2023-05-06_final.stac-item
2023-05-07 11:09:59	ga_ls9c_ard_3-2-1_108081_2023-05-07_final.stac-item
2023-05-09 10:56:50	ga_ls9c_ard_3-2-1_106079_2023-05-09_final.stac-item
2023-05-09 10:57:38	ga_ls9c_ard_3-2-1_106081_2023-05-09_final.stac-item
2023-06-19 10:47:32	ga_ls9c_ard_3-2-1_105072_2023-06-19_final.stac-item
2023-06-20 09:52:42	ga_ls9c_ard_3-2-1_096074_2023-06-20_final.stac-item
2023-06-22 11:20:02	ga_ls9c_ard_3-2-1_110076_2023-06-22_final.stac-item
2023-06-29 11:26:18	ga_ls9c_ard_3-2-1_111076_2023-06-29_final.stac-item
2023-06-29 11:28:18	ga_ls9c_ard_3-2-1_111081_2023-06-29_final.stac-item
2023-07-01 11:15:59	ga_ls9c_ard_3-2-1_109081_2023-07-01_final.stac-item
2023-07-19 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-07-18_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-22 11:35:27	ga_ls9c_ard_3-2-1_112083_2023-07-22_final.stac-item
2023-07-23 10:34:14	ga_ls9c_ard_3-2-1_103069_2023-07-23_final.stac-item
2023-07-26 09:30:39	ga_ls9c_ard_3-2-1_092080_2023-07-26_final.stac-item
2023-08-05 11:45:58	ga_ls9c_ard_3-2-1_114078_2023-08-05_final.stac-item
2023-10-16 10:57:25	ga_ls9c_ard_3-2-1_106079_2023-10-16_final.stac-item
2023-10-17 09:59:24	ga_ls9c_ard_3-2-1_097073_2023-10-17_final.stac-item
2023-10-18 10:44:40	ga_ls9c_ard_3-2-1_104078_2023-10-18_final.stac-item
2023-10-22 10:18:21	ga_ls9c_ard_3-2-1_100074_2023-10-22_final.stac-item
2023-10-24 10:06:23	ga_ls9c_ard_3-2-1_098075_2023-10-24_final.stac-item
2023-10-25 10:47:38	ga_ls9c_ard_3-2-1_105070_2023-10-25_final.stac-item
2023-10-28 11:18:31	ga_ls9c_ard_3-2-1_110070_2023-10-28_final.stac-item
2023-10-28 11:22:54	ga_ls9c_ard_3-2-1_110081_2023-10-28_final.stac-item
2023-10-29 10:22:53	ga_ls9c_ard_3-2-1_101070_2023-10-29_final.stac-item
2023-11-02 10:01:17	ga_ls9c_ard_3-2-1_097078_2023-11-02_final.stac-item
2023-11-03 10:44:32	ga_ls9c_ard_3-2-1_104078_2023-11-03_final.stac-item
2023-11-03 10:45:20	ga_ls9c_ard_3-2-1_104080_2023-11-03_final.stac-item
2023-11-05 10:31:24	ga_ls9c_ard_3-2-1_102076_2023-11-05_final.stac-item
2023-11-05 10:32:12	ga_ls9c_ard_3-2-1_102078_2023-11-05_final.stac-item
2023-11-14 10:27:15	ga_ls9c_ard_3-2-1_101081_2023-11-14_final.stac-item
2023-11-22 09:36:18	ga_ls9c_ard_3-2-1_093077_2023-11-22_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